Zoltan Istvan’s The Transhumanist Wager is an epic story of radical libertarian ideas, their enemies, and the violent global conflict that ensues, painted in strong saturated colors with little room for intermediate shades and character development.

After reading cover to cover, and then reading it more carefully, I have mixed love/hate feelings about this novel.

It’s a page turner. Istvan — a former journalist for the National Geographic Channel and The New York Times, whose award-winning coverage of the war in Kashmir gained worldwide attention — knows how to tell a compelling story.

There are strong parallels with Atlas Shrugged. Jethro Knights, the main character of The Transhumanist Wager, is a modern John Galt — a transhumanist and even-more -radical version of Ayn Rand’s hero.

Jethro is obsessed with and focused on attaining personal immortality via biological life extension and especially mind uploading and eternal cybernetic life.

America is in a deep economic recession, with rising unemployment and domestic terrorism. Transhumanist ideas are in the limelight, violently opposed by a “politically correct” establishment, inept politicians, and a domineering, violent religious right movement, led by arch-villain Reverend Belinas.

In the first third of the book, partly autobiographic, we follow Jethro in his solo circumnavigation of the world in a sailboat that he built himself, working as a travel and war journalist on the side. On his boat, Jethro meditates on the big questions and issues. And when he returns to New York five years later, he is ready to fight Belinas and take over the world. And yes, there is a love story. It begins in a Kashmir war zone, and continues after Jethro’s return.

Militant libertarianism

Jethro’s philosophy is an extreme, militant version of the radically libertarian formulation of transhumanism championed by the Extropy Institute in the 90s. Attaining immortality is a prerequisite for becoming all-powerful “Omnipotenders” and moving on to dominate the universe. So life extension must have the highest priority, without letting unnecessary distractions like empathy, compassion, or love stand in the way.

Jethro is a two-dimensional icon in an epic story. From the (few) attempts to give him depth, we can see that there is probably a nice person at his core, but he is a fundamentalist like Reverend Belinas where his goals and philosophical outlook are concerned. In the final confrontation with Belinas, Jethro kills his enemy after a powerful clash of ideas, but not without Belinas scoring some points. Yes, Jethro would commit atrocities in pursuit of his objectives, and even kill the persons he loves most.

I’m a radical transhumanist, but I find Jethro’s approach alienating. I can find worthy elements in different worldviews, but I don’t think any worldview has all the answers. I think militant fundamentalism — the certainty of having all the answers, and the will to crush the unbelievers — is at the root of most evils. Religion can be good, but the Inquisition was an atrocity. Atheism can be good, but oppressive, authoritarian, militant atheism is not. Libertarianism is good, but indifference to the pain of others is not. Transhumanism is good, but I hope it will prevail without the violence described in the novel.

Toward the end of the book, Jethro’s missiles destroy the Vatican, killing the Pope and hundreds of believers in prayer in St. Peter’s square. Jethro would answer that violent acts of war were initiated by others (first the U.S. government, then an international coalition), and the transhumanists retaliated in self-defense, after warning the population to leave the targeted areas, to minimize collateral damage. But what I find much more difficult to accept is that Jethro considers other persons as expendable, and would not stop even at large-scale genocidal mass murder.

In contrast, transhumanist leader Preston Langmore is a nice soft-spoken guy, a visionary humanist who is happy enough thinking that perhaps his grandchildren will be immortal, without really hoping to see immortality in his lifetime. But he doesn’t have what it takes to defend transhumanists from more and more violent attacks. After a leading transhumanist scientist working on alternative substrates for mind uploading is savagely murdered and beheaded by Belinas’ thugs, with the silent complicity of the government, it’s Jethro who must take the lead.

Transhumania — the ultimate Galt’s Gulch

Jethro’s more and more popular Transhumanist Citizens movement trumps and exposes a terrorist attack against a cryonics facility. But Belinas’ religious right — this time with the full and open support of the government — in a now-dystopian police-state America, threatens massive violent repression against transhumanists.

Jethro escapes and creates the ultimate Galt’s Gulch: Transhumania, a high-tech floating seasteading community populated by the world’s best and brightest. The citizens of Transhumania develop amazingly advanced science and technology — and powerful weapons for the final confrontation that they know will come soon.

Of course the good guys win … but are they still good guys? They impose a strict “transhumanian” rule over the rest of the planet, with many good things like scientific education and opportunity for all. But also some fascist measures that don’t seem libertarian to me, not at all.

In The Artilect War, Hugo de Garis says that the transhumanist drive to develop technologies to transcend the human condition, in particular more-than-human artificial intelligences, is on an inescapable collision course with traditional morality, religion, and social organization. He believes a massive conflict with billions of deaths is bound to happen someday, perhaps in this century. The Transhumanist Wager is probably the first novel to address de Garis’ doomsday scenario (Jethro would annihilate the rest of humanity if he had to.)

I really hope Istvan’s fiction will remain fiction, but it seems disturbingly plausible. If transhumanists will need to defend themselves, a Jethro will probably emerge.

Quantum Zen

My favorite character is the delicious Zoe Bach, Jethro’s one and only love. With a mixed Western and Eastern heritage, Zoe is a spiritual transhumanist who shares Jethro’s enthusiasm for becoming immortal and transcending the human condition by means of advanced technology. But at the same time, she remains open to the more spiritual forms of transcendence found in Eastern mysticism.

In her “Quantum Zen” outlook, Zoe is not so focused on immortality: she imagines that future super-science will be able to resurrect the dead. Jethro agrees, but he considers far-future speculations as a distraction from his overpowering drive to launch his transhumanist revolution and attain immortality here and now. The tension between Jethro’s and Zoe’s philosophies is, for me, the most interesting aspect of the novel.

Pitching transhumanism

Zoltan told me that “the main goal with book was to create a powerful artistic statement for the current and younger generation of thinkers and readers, to pull young people away from fantasy genres into transhumanism. My novel is trying to tell them that transhumanism is every bit as exciting and rewarding as anything commercial Hollywood puts out there for them.

“I’m hoping that a young person who is in college or high school might read my book and decide that they would rather pursue a career in science and technology than, let’s say business, law, or advertising. If my novel will convince people to pursue science and reason in their daily lives instead of fantasy and commercialism, then I will be a happy, fulfilled person.”

I think The Transhumanist Wager is a very powerful artistic statement indeed, but one that promotes an interpretation of transhumanism that I find far too militant and devoid of compassion.

At the same time, while Zoltan and Jethro don’t have all the answers, they do ask important questions, and offer some valid answers. I find their libertarianism too militant and uncompromising, but at the same time, I think it’s important to affirm libertarian ideas loud and clear in today’s dull, politically correct, anti-libertarian cultural climate.

I don’t think science will advance as fast as Zoltan hopes, not even in a real-world Transhumania, but I think it’s important to offer younger generations compelling artistic visions of a solar, positive future powered by transhumanist science.

Zoltan’s book has the potential to become a cult book. I hope it will be widely read and discussed.

credit: Baris Simsek

This is a really interesting article about body and mind which I recently read. I wanted to share it with my readers:

The New York Times | “I am not this body”

Here is a compelling excerpt: “I do not identify with my body. I have a body but I am a mind.

“My body and I have an intimate but awkward relationship, like foreign roommates who share a bedroom but not a language.

“As the thinker of the pair, I contemplate my body with curiosity, as a scientist might observe a primitive species. Though I identify with mind, the mind itself is matter.

“My relation to my body resembles a privy council’s relation to an adolescent king. I am thoughtful and wise and know best what to do, but my capricious body possesses the power and final authority, and I must tiptoe round its whims.”

Best,
Ray Kurzweil

Artist’s impression of TF-X future flying car in flight (credit: Terrafugia Inc.)

“Where’s my flying car?”

Skeptics have trashed predictions of flying cars with this annoying question ever since the Jetsons.

But now Terrafugia Inc. has announced feasibility studies of a four-seat, vertical takeoff and landing (VTOL) [similar to a helicopter] plug-in hybrid-electric flying car, the TF-X.

Just tell it where to go. It flies (and lands) for you — no runway needed — and then transforms into a car, says Terrafugia. It can even take off on roads.

So how real is it?

Well, Terrafugia already has some street (literally) cred with its Transition flying car, a two-place, street-legal airplane that has been heralded as the “first practical flying car,” the company claims. It’s designed to fit in a single-car garage, be safely driven on the highway, and be flown (conventionally) in and out of general aviation airports. It runs on premium unleaded automotive gasoline, and the same engine powers the propeller in flight or the rear wheels on the ground.

The company has not yet announced FAA certification or delivery dates, but it says it has more than 100 customers committed. Meanwhile, DrivenToFly.com has produced this cool video showing a lustworthy test version in action:

The Defense Advanced Research Projects Agency’s Transformer (TX) solicitaton (announced April 12, 2010) is another reality check. It proposes to combine the advantages of ground vehicles and helicopters, with vertical take-off and landing, four-person payload, able to safely travel on roads for 250 nautical miles (288 conventional miles) on one tank of fuel, and be operated by a typical soldier.

Transformer (TX) concept (credit: DARPA)

So what would a TF-X autonomous flying car look like? Here’s how Terrafugia envisons it:

As YouTube commenter Glowitzer put it: “Shut up and take my money!!”

The Skycar

Meanwhile, Moller International says it has developed “the first and only feasible, personally affordable, personal vertical takeoff and landing (VTOL) vehicle” — the Skycar 400. “Skycar can cruise comfortably at 275 MPH (maximum speed of 375 MPH) and achieve up to 20 miles per gallon on clean-burning, ethanol fuel.”

Skycar 400 (credit: Moller International)

It won’t be an actual roadworthy car, and not autonomous, but close. Like the TF-X, the aircraft has an automated “fly by wire” system: the pilot initially provides inputs for direction, speed, and altitude, and on-board systems interpret these inputs to do the actual flying. “Operating a Skycar … could be done by someone with little training or flight experience, but will, at least initially, require a private pilot’s license until the ease of operation and safety are thoroughly demonstrated,” the company claims.

The company also says it has done an unmanned hover demonstration flight with a prototype unit.

Moller International announced May 8 that it’s in a joint-venture discussion with Athena Technologies to produce and distribute Moller’s Skycar and Neuera “volantors,” to be partly made in China.

PAL-V ONE

And there’s PAL-V ONE, a two-seat hybrid car/gyroplane introduced in April 2012 by the Dutch company PAL-V Europe NV. On the road, it drives like a sports car and banks like a motorcycle. “For take-off, a strip of 165 meters (540 feet) is enough and it can be either paved or grass,” the company says. [H/T: Dan]

Hmmm, what happens if Google teams up with one of these companies….?

Famous flying cars

The Gyrocopter, 1935 (credit: Modern Mechanix & Inventions)

ConvairCar, 1947 (credit: Convair)

Suburban copter, 1951 (credit: Popular Mechanics)

The Jetsons animated sitcom, 1962 (credit: Hanna-Barbera)

Hiller’s Aerial Sedan, 1967 (credit: Popular Mechanics)

“Roads? Where we’re going, we don’t need roads.” — Doc in Back to the Future, 1985 (credit: Universal Pictures)

Moller M200X, 1989 (credit: Moller International)

The Fifth Element, 1997 (credit: Columbia Pictures)

(Credit: Google)

“Google’s self-driving car gathers 750 megabytes of sensor data per SECOND! That is just mind-boggling to me. Here is a picture of what the car ‘sees’ while it is driving and about to make a left turn. It is capturing every single thing that it sees moving — cars, trucks, birds, rolling balls, dropped cigarette butts, and fusing all that together to make its decisions while driving. If it sees a cigarette butt, it knows a person might be creeping out from between cars. If it sees a rolling ball it knows a child might run out from a driveway. I am truly stunned by how impressive an achievement this is.”— IdeaLab founder/CEO Bill Gross.

Add to that: real-time data from street view, GPS, and Google maps — as shown below from a recent Google patent award — and you’ve got one humungous graphics processing system on board.

Now what if some elements of all this data could also be projected on a special windshield display or on Google Glass for driver override, when needed? Add to that: weather and traffic reports ahead, police-scanner data (to avoid a road chase in progress, let’s say), news reports mentioning local events, oh, and Yelp reports, and Find My Friends or Latitude popup pics, and throw in a live HD action cam (I’m experimenting with a Contour+2 with live HDMI streaming — I need one more for rear-view pics — more on that later) and what about a panorama cam and …. OK, you get the idea. (Would adding an Oculus Rift be over the top?)

(Credit: Google)

credit: stock image

Mr. Kurzweil,

I’m currently in the middle of How to Create a Mind. I’m struggling with this one a bit more than you’re other books, but it’s very enjoyable and elucidating.

You have for some time predicted human level machine intelligence arriving by 2029.

However, in Mind you estimate the speed of a computer necessary to simulate the brain at 100 trillion cps, and state that the latest supercomputers achieve this speed.

Which means that very soon we will have a machine with twice the necessary power, then quadruple, and so on.

If four or five years from now we have a computer of ten times the necessary power AND there emerges a well-funded, collaborative effort to simulate a brain on such a machine, would you amend your prediction of the emergence of strong AI?

I guess what I mean to ask is, what developments would you look for to determine that strong AI is only a few years away?

Regards,
Sean

Sean,

I’ve always expected to have the hardware sooner. By 2020, the requisite hardware will be very inexpensive. The software is the gating item.

Developments such as Watson should give us confidence that we are on track.

Best,
Ray Kurzweil

credit: stock image

Dr. Kurzweil,

My name is Stanley. I too was born and bred in Queens, New York. I am also an Alcor member since 1992. I was part of the New York stabilization team and was part many cryonic cases.

I I am currently experiencing an extreme case of death terror.

I am 45 years old and am desperate not to require cryopreservation, and live to be uploaded.

I so want to live forever, though as a human I can’t conceive of eternity.

I never want to lose my stream of identity and prefer an uploading scenerio which involves replacing my neurons with chips, rather than uploading into cyberspace, in which case the uploaded me would think it’s me, but the me that is writing to you today would die as my brain dies of hypoxia.

Dr. Kurzweil, can you please write to me, and calm this horrid, Emily-Dickinson-like anxiety.

— Stanley

Stanley,

I discuss the issue you raise –– which is called the “identity issue” in the chapter “Thought Experiments on the Mind” in my latest book How to Create a Mind.  I can send you a complimentary signed copy if you send me a land address.

My vision of the future is that we will start to augment our brains with nonbiological intelligence starting in the 2030s. We are already doing that with devices and cloud computing outside of our bodies.

Some people such as Parkinson’s patients already have computers connected into their brains that have wireless communication allowing new software to be downloaded from outside the patient.

In the 2030s, nanobots will travel into the brain noninvasively (no surgery required) and connect our neurons directly to the cloud. In the book I describe how our neocortex (the region of the brain where we do our thinking) has about 300 million modules each of which can recognize, remember, and transmit a pattern and can also connect itself to other modules to create new patterns.

We will be able to expand that number (300 million) by creating synthetic neocortical modules in the cloud. Our biological thinking is more or less fixed in capacity whereas the cloud being pure information technology approximately doubles in capacity each year.

So as we get to the 2040s our nonbiological intelligence will predominate.  That portion of our thinking — which will become essentially all of it — will be backed up.

In the book I argue that our identity is preserved if there is continuity in our pattern which the above scenario maintains.  So we can gradually transform into a nonbiological intelligence that will be backed up.  That is the scenario that avoids cryopreservation and the path I am seeking to follow.

Best,
Ray Kurzweil

(Credit: NASA)

This is part two of a two-part series on the limits of human economic growth on planet Earth.  Part one details some of the environmental and natural resource challenges we’re up against. Part two, here, looks at the ultimate size of the resource pool and solutions to our problems.  Both parts are based on Ramez Naam’s new book, The Infinite Resource: The Power of Ideas on a Finite Planet

The Solution: Growing the Pie

As part one of this series showed, we are up against incredible challenges: feeding a world with a rapidly growing appetite, the continuing loss of the world’s precious forests, the ongoing collapse of fish species in the oceans, the rapid depletion of our fresh water resources, and the over-arching threat of climate change, which makes all others far worse.

Ending growth isn’t a realistic option. Billions of people in the developing world want access to more resources,deserve those resources as much as those of us in the rich world do, and need them in order to rise out of poverty. Growth won’t end without a struggle. And that struggle could turn violent, as it has in the past.

There’s only one acceptable way out of our current predicament. And that is to grow the total pie of resources available to the world’s inhabitants. And a close look at the numbers and at the human history of innovation suggests this is possible.

Food

No resource has driven more discussion of impending limits to growth than food. Malthus — the original proponent of a near term limit to growth — wrote in the late 18^th century that population would always grow exponentially, while food production could at best grow linearly. Thus, humanity was doomed to remain in what we now refer to as the Malthusian Trap.

More recently, in 1968, environmentalist Paul Ehrlich opened his best seller The Population Bomb with the lines. “The battle to feed humanity is over. In the 1970s the world will undergo famines — hundreds of millions of people are going to starve to death in spite of any crash programs embarked upon now. At this late date, nothing can prevent a substantial increase in the world death rate.”

Both Malthus and Ehrlich were wrong. Population did expand, but so did food production. Since Ehrlich wrote The Population Bomb, the population has doubled and death rates have declined. Food yields — the amount grown per acre — have nearly tripled. That increase in food yields has been driven by new seeds, better farming methods, and increased availability of fertilizer and pesticides.

But increasing yields aren’t anything new.  The yield growth since the 1960s has been dramatic, but it’s part of a process that’s been going on for more than 10,000 years.  In pre-historic times, it took perhaps 3,000 acres of land to feed one hunter gatherer.  Today it takes about 1/3 of one acre to feed the average person on earth.  We’ve increased the amount of food grown per acre by a factor of 10,000 in 10,000 years.

Since pre-history, humans have increased the food output of an acre of land by a factor of 10,000. See The Infinite Resource: Power of Ideas on a Finite Planet for full data sources involved in this graph.

Even with this tremendous surge in food yields, we know that there’s headroom. Current farms convert less than 0.1% of the solar energy that strikes them into calories consumable by humans. The theoretical limit of photosynthesis is around 13% conversion of sunlight into calories. We may never reach that theoretical limit, but even if we could reach, say, 3% conversion, we would be growing thirty times as much food per acre as we are now, enough to feed a population far larger than humanity is ever projected to reach.

Closer to the present, there are more practical and specific reasons to believe that feeding the world is possible. Today, global grain yields average around 3.5 tons per hectare. In the US, they average around 7 tons per hectare. That difference in yield primarily reflects more access to capital and energy. US farmers (and farmers in other rich countries) can afford fertilizer, mechanized farm equipment, irrigation systems, pesticides, and other tools that boost agricultural yields. Bringing developing world farmers access to the same tools would boost yields as well, potentially doubling them, which is more than the 70% increase the FAO believes is required by 2050.  Indeed, the best farms in the US routinely get double the US average yield, so even this level is far from the maximum achievable.

Food yields in the US and other developed nations are twice those of the world as a whole. If the world as a whole had food yields similar to those of the US, we would already have sufficient food production to meet the demand expected by 2050. Source: FAO

There may be other, less capital-and energy intensive routes as well. The yield gains over the last half century have come primarily from better seeds. And we know that further gains by seed improvements are possible. One intriguing possibility is to upgrade the photosynthesis pathways in wheat, rice, and millet. Those staple crops use C3 photosynthesis.  Corn and sugarcane, on the other hand, use a newer photosynthetic pathway called C4. And as a result, Corn yields about 70% more grain per acre than wheat or rice. The Gates Foundation and other non-profits are working on ways to integrate C4 genes into rice and wheat now.

What of fertilizer? Nitrogen fertilizer is made from natural gas today, in a process that gives off greenhouse gases. Multiple groups, however, have shown that fertilizer can be synthesized from wind power and nitrogen in the air (where it makes up 78% of the atmosphere). An even more radical approach would be to borrow a trick from legumes. Soy and other legumes fertilize themselves (with help from symbiotic bacteria) by pulling nitrogen from the atmosphere themselves. Early stage projects funded by the Gates Foundation and elsewhere are evaluating whether wheat, corn, rice, and other cereals could be engineered to fertilize themselves from the air in the same way, reducing both the need to apply artificial fertilizer, and the nitrogen runoff that results from it.

Advances in how we produce food could also have a substantial impact on our overfishing of the seas. Wild fish are under threat of extinction because they’re hunted to feed us. Yet land animals that we farm are under no threat of extinction. Shifting from hunting fish to farming fish — where the farmers have the incentive to keep their stocks healthy — could do a tremendous amount of good for wild fish. Over the last few decades, the tonnage of fish farmed has soared, even as the tonnage of fish caught from the wild has stayed stagnant.

Advances in sustainable fish farming could take this even further, creating fish farms that are cleaner and better for the oceans around them, while able to produce protein far more efficiently than land animals, and removing the threat of extinction from wild fish.

Wild fish catch has stagnated since the 1990s, as declining wild fish populations have made it harder and harder to bring fish in. Meanwhile, aquaculture (farmed fish) has boomed to take up the slack. Source: FAO

In short, the planet’s ultimate limit on food production is many times higher than our projected needs.

That, in turn, leads to an even more intriguing possibility. If we could raise food yields faster than demand, could we shrink the amount of land we use to farm? For instance, between now and 2100, total food demand may roughly double (driven more by increasing meat consumption than by population). If, in that timeframe, we could triple farm yields, then we could, potentially, grow all the food necessary to meet demand only two thirds of the land area used today.

That, in turn, would free up roughly 10% of the world’s land area, which could be returned to wilderness, to managed forest, or some other use. Whether or not we’d do this depends on an enormous number of factors.  Humanity may or may not decide to reforest the planet or return land to wilderness. But if we innovate fast enough in lifting crop yields, we would have the option.

Water

We live on a water world.  70% of the world’s surface is covered in water. Yet the vast majority of that water — around 97% of it — is salt water. Another 2% is locked up in ice caps and glaciers. Only around 1% of the world’s water is fresh, and of that, humanity can only easily access about a tenth, or 0.1%.

Humans access only a tiny fraction of the Earth’s available water. Most of the rest is salt water. Source: USGS.

If we could efficiently convert salt water to fresh, we’d have access to a vast supply of water to use in growing crops and sustaining human civilization. For decades, desalination has been considered a deeply anti-environmental process, though. It’s energy intensive. As a result, it releases huge amounts of greenhouse gases. Any attempt to increase fresh water access through desalination would have environmental consequences too dire to make the process worthwhile.

That view is out of date. From the time of the ancient Greeks through the late 1960s, desalination technology barely changed at all: boil water, capture steam, let the steam condense into fresh water. That process is incredibly energy intensive.

In the late 60s, however, two scientists at UCLA set out to see if they could mimic a feature of the biological membranes around cells. Cell membranes are selectively permeable. They can allow water and some molecules to pass through them while blocking out others. The resulting discoveries by Stanley Loeb and Srinivasa Sourirajan set off a long sequence of innovations in desalination using semi-permeable membranes. As a result, the energy needed to desalinate a gallon of water has fallen by a nearly factor of 10 since 1970.

The amount of energy required to desalinate water has dropped by nearly a factor of 10 since 1970. Source: Menachem and Elimelech, “The Future of Seawater Desalination,” Science (2011)

The process is sufficiently cheap now that modern plants sell desalinated water at around 5 gallons per penny, or 500 gallons per US dollar. That is still too expensive for bulk use in agriculture, but it’s approaching the price where large scale desalination becomes truly feasible.

Of course, many dry areas are also inland, but the same technologies that can desalinate water cheaply can also help filter and recycle dirty water cheaply, allowing communities to re-use wastewater.

Ultimately, with sufficient energy and with continued improvement in desalination technology, we can have access to water supplies many times larger than any projected human need. Those are two big ifs, but they’re far from inconceivable.

Energy

Finally, let’s come to energy, and with it, climate change. Most human energy use today is from fossil fuels, and this directly leads to the CO2 emissions that are warming the planet. Over the coming years we need to reduce our greenhouse gas emissions by at least 80% (and possibly more). At the same time, the demands of the rising poor are going to push us to consume nearly twice as much energy as we do now by 2050.

Fortunately, the physical resources of the planet are more than up to the task. As I’ve written before in Scientific American, the sun strikes the Earth with roughly 5,000 times as much energy as we consume from all sources combined. Some of that energy differentially heats the atmosphere, driving wind. Some of it evaporates water, which later comes down as rain or snow, creating hydro power. And the largest share of it directly strikes the surface of the Earth as photons.

That energy is so vast that solar panels on less than 0.3% of the Earth’s land area would supply many times more energy than humanity needs for the next few decades.

Only 0.3% of the Earth’s land area would be required to meet human energy needs with current efficiency solar panels. Image courtesy of landartgenerator.org

0.3% of the Earth’s land area is nothing to sneeze at. At the same time, it’s roughly 1/100^th of the area that we use to grow crops and graze livestock. And it’s 1/60^th of the area covered by the world’s deserts. With a small fraction of the planet’s deserts we could capture abundant energy to power the world.

The problems with renewable energy today have primarily been twofold: Cost and storage. Renewables have been far more expensive than fossil fuels. And they are intermittent, not always available when you need them (at night, for instance, or when the wind isn’t blowing). But both problems are solvable.

On the cost front, solar power is now approaching the price of grid electricity in the sunny parts of the world. It’s done this by plunging in cost over the last 30 years. A watt of solar power today costs just 1/20^th of what it did in 1980, a staggering decline.

The cost of solar power has dropped by a factor of 20 over the last 33 years. Within the next 15 years, on current path, it will be cheaper than both coal and natural gas across most of the planet. Source: NREL Background Image: Ramez Naam

On current pace, by 2020 to 2025, solar power will be cheaper than electricity from coal or natural gas across the large majority of the planet, including China, India, and most of the developing world, where energy use is rising fastest.

Of course, past trends aren’t guarantees of future performance. To continue the cost plunge, we’ll need to innovate in the design and construction of solar modules, in new ways to deploy large solar arrays that cut deployment costs, in the cost of invertors (which convert DC solar electricity to AC grid electricity) and other equipment that must come with the core solar modules. Those advances are neither trivial nor guaranteed. They require a continued investment in R&D to achieve.

Nevertheless, there seem to be good odds that, within the next few decades, if not the next one decade, solar power will be capable of providing cheap, abundant, carbon-free electricity in a way that can be scaled around the world.

The second problem with renewables is storage. We use energy when the sun isn’t shining and when the wind isn’t blowing.  Germany has demonstrated that renewables can provide up to about 40% of the electricity used in a power grid on their own. Beyond that, we need a large scale way to store the energy, and to keep the overall cost of renewables down, we need to store it cheaply. We also use energy in our vehicles, for which we need a way to store it densely — more stored energy in less mass. There’s a case to be made that today, storage is a bigger challenge than energy collection itself.

Fortunately, human ingenuity is dropping the price of batteries, as well, and increasing the amount of power that can be stored. Between 1991 and 2005, the price of storing a watt-hour of electricity in a lithium ion battery dropped by a factor of around 10, from $3.20 per watt hour to just over $0.30 per watt hour. In the same timeframe, the amount of energy that could be stored in lithium ion batteries of a given weight (their energy density) more than doubled, from under 90 watt hours per kilogram to more than 200 watt hours per kilogram.

That pace of improvement of both price and density is faster than the corresponding pace of improvement of solar and wind. In a typical 15- year period, the price of solar cells falls by around a factor of three, while the prices of batteries have fallen by around a factor of 10. If the learning curve of battery technologies can be maintained, the ability to store energy will advance faster than the ability to collect it, and overall prices will keep falling.

Between 1991 and 2005, the price of laptop batteries dropped by nearly 10x, and the amount of energy stored per weight more than doubled. Source: David Anderson and Dalia Patino-Echeverri, “An Evaluation of Current and Future Costs for Lithium-Ion Batteries for Use in Electrified Vehicle Powertrains.”

On the horizon are new battery technologies:  solid state batteries (made like transistors) and metal-air batteries. At the upper end, metal-air batteriescould storemore than ten times the amount of energy that lithium-ion batteries do, and correspondingly drop the cost. That would give batteries an energy density similar to that of fossil fuels, meaning that electric vehicles (or even electric aircraft) with ranges similar to — or perhaps greater than — fossil fueled vehicles would be possible.

To be clear, there are substantial technical hurdles here too — metal-air batteries aren’t yet to the point that they can be charged and discharged the many thousands of times that a grid-scale or electric vehicle battery needs to be. But the basic physics and chemistry tell us that much higher energy densities than we see today are possible, and the long history of driving down the price of energy storage gives us reason to believe that it’s possible to keep doing so.

Energy, in short, is abundant. Carbon-free energy, the sort that would allow us to keep growing energy use while freeing ourselves from fossil fuels, is abundant. The problem isn’t solved, to be clear. Far from it.  Huge challenges remain in innovating to bring the cost of renewables and storage down. Even then, deployment will be a gigantic undertaking. But the limiting factor on our use of clean energy – for the next few centuries, at least — isn’t the available resource. It’s our cleverness and ingenuity in learning to harness it cheaply and efficiently.

Growth Without Growth

I’ve focused the last few sections how large our ultimate physical resource base is. The ultimate supplies of energy, of potential food, and of potentially drinkable water for the planet are all hundreds of times greater than we can see humanity needing for the next century.

Yet if physical resource growth continues unabated, it will eventually consume any resource base, no matter how large. Could it be, though, that we can grow our economy and our well-being without growing our consumption of physical resources? There are reasons to think so.

Population:

Let’s start with population. Malthus thought of population growth as an exponential process, doomed to consume all available resources. And for quite some time, human population did grow exponentially. But those days appear to be over.

In Brazil, two generations ago, the average woman had 6 children over the course of her lifetime. Now, the average woman in Brazil has just 1.8 children over her lifetime.  That number isn’t enough to even maintain the population. If fertility doesn’t rise, Brazil’s population will shrink over time.

Brazil is just one example. Everywhere that incomes rise, that education rises, and that women gain more opportunity outside of the home, fertility rates drop. European women now have around 1.5 children on average over the course of their lifetimes. Russian women are similar. South Korean women have only 1.3 children, on average, over the course of their lives.

Around the world as a whole, the average number of children a woman will have in her lifetime has dropped in half over the last 50-odd years, from 4.9 children per woman in 1960 to 2.5 children per woman around the world in 2011. When fertility drops below 2.1, population stops growing.

Around the world, the number of children born per woman over her lifetime has dropped from 5 in 1950 to less than 2.5 today. When the number drops near 2 in the coming decades, population will plateau. Source: World Bank. Background Image: Alejandra Quintero Sinisterra

As a result, between 2050 and 2100, something almost unprecedented in the history of the world is likely to occur.  The world’s population is likely to plateau between 9 and 10 billion people. And after that, so long as wealth and education continue to rise, the world’s population is likely to drop.

The Great Decoupling

So population will reach a maximum. What of resource consumption per person? There, too, we see signs of a slowdown of growth, or in some cases, a complete halt to growth, or even a reduction in consumption.

Consider US oil consumption. While the average American consumed more than 30 barrels of oil a year in 1972, today he or she consumes only around 19 barrels of oil a year, and still dropping.

The average American uses a third less oil than in 1972. The International Energy Agency forecasts even further declines to come. Source: IEA.

Some of this is a shift away from oil and to other sources of energy. But summing up all energy sources combined, the average American uses slightly less energy than in the 1970s, even as per capita GDP has doubled, living area per person has nearly doubled, and life expectancy has risen by more than 8 years.

In fact, if we plot US GDP per person vs. US energy per person and US CO2 emissions per person, we see GDP (economic activity) pulling away from our use of energy and our CO2 emissions.

US GDP Per Capita has roughly doubled since 1970, while energy use and CO2 emissions per capita have dropped slightly. More wealth does not have to mean more consumption or more pollution. Source: World Bank.

Some will argue that this is a result of the US having outsourced energy US and CO2 emissions to other parts of the world (e.g., China).  And that is partially true. Yet a look at the same numbers globally shows a similar pattern. CO2 emissions and energy use per capita are rising, but not nearly as quickly as GDP per capita.

On a global scale, GDP is decoupling from energy use and CO2 emissions as well. Since 1970, GDP has grown at twice the rate of CO2 emissions, and 1.5x the rate of energy use. Source: World Bank.

Let’s be clear. This decoupling isn’t enough yet. Any rise in CO2 emissions per capita is problematic. We need a steep decrease in CO2 emissions.  The above isn’t intended as a case that we’re on the right track yet — we’re not. It’s meant to illustrate something different: In principle, it’s possible to grow wealth and well-being without using more of a physical resource. The two can be decoupled. Now we need to accelerate the pace of that decoupling.

Turning the Corner

In some cases, we’ve actually gone beyond leaving consumption or pollution at a flatline, and have turned a corner. While growing an economy, we’ve shrunk the use of some resources, and the amounts of many types of pollution released.

Consider water use. In the United States, per capita water withdrawals rose from 1900 until the 1970s. But since then, they’ve dropped by more than a third:

Water use per person in the United States peaked in the late 1970s and has declined ever since, largely due to more efficient agriculture. Source: Pacific Institute. Background image: José Manuel Suárez

That drop in water use has happened even as the US economy has roughly doubled in size and as US food production (the primary use of water) has also doubled. How?  More efficient technology. We’ve increased crop yields by designing seeds that make better use of water and nutrients. We’ve shifted farm irrigation towards more and more efficient drip irrigation. We’ve increased the use of no-till farming, that dries out the soil less, conserving more of the water that’s there.

Again, this change isn’t yet enough. But it’s an indicator that we can grow wealth and grow output while shrinking consumption.

The same is even more true in pollution.

Emissions of sulfur dioxide, the chemical that causes acid rain, are less than half of what they were in 1970, and are down to levels not seen in the United States since 1910. Carbon monoxide emissions are down to half of what they were in 1970.

Mercury emissions have dropped by half since 1990. Lead concentrations in the atmosphere are just one tenth of what they were in 1980, and new emissions of lead have dropped to near zero. Emissions of particulates, PCBs, and nitrogen oxide are all down by roughly half.  Worldwide emissions of ozone-destroying CFCs, once used as refrigerants, have plummeted to nearly zero. The Antarctic ozone hole is now recovering, ahead of schedule.

The world has driven the production of ozone-destroying CFCs down nearly to zero.Source: World Bank. Background Image: NASA.

The Limits to Growth model predicted that pollution would keep increasing so long as the world economy grew. The only way to reduce pollution was to reduce economic activity. But that isn’t what happened.  Our cars and trucks haven’t stopped running. Their engines haven’t seized up. Our power plants have kept producing valuable electricity. And our refrigerators haven’t stopped working. In every case we’ve found a way to reduce the amount of a pollutant we emit, or to replace the substance with something more benign, without stopping industry or growth. Innovation has driven down pollution while our economy has grown.

That hasn’t happened on its own. The market has played a key role in each of those reductions of pollution, but it hasn’t been the driver. The driver has been our decision, collectively, to put restrictions on pollution levels. The US created laws to phase our lead and benzene, to reduce the emissions of acid-rain producing sulfur dioxide, and to control other pollutants. The world as a whole signed the Montreal Protocol to phase out CFCs and other compounds that were destroying the planet’s ozone layer.

Environmental concern is a phenomenon that tends to rise in a nation after a certain level of wealth. Still developing nations like China haven’t reached that point yet. Until recently, the environment has been a low priority. But with pollution there approaching levels nearly as bad as the US saw in the 70s, we can see the beginnings of a Chinese environmental movement that will likewise press for reduced pollution.

We still have miles to go in driving pollution lower, but the successes of the last decades demonstrate that pollution isn’t an inevitable side effect of economic growth. We can have more, while polluting less, and while consuming less.

Winning the Race

So we’re at a crucial point in human history — a race between destruction and creation. On the one side, we have the pace at which we’re consuming finite resources and warming and polluting the planet — a trend with disastrous consequences should it continue unchecked. On the other side, we have our vigorous progress in innovating to tap more efficiently and cleanly into a truly enormous supply of fundamental natural resources the planet provides.

Are we on track to win this race?

That’s not at all clear. Consider, for a moment, climate and energy. Multiple groups have proposed plans by which the world could be powered almost entirely by renewable energy by 2050, or, in the most ambitions plans, by 2030.

Yet even as those plans are articulated, worldwide CO2 emissions are rising, not falling. In 2012, the planet as a whole emitted a record-breaking 35.6 billion tons of CO2 into the atmosphere. And the concentration of greenhouse gases in the atmosphere is surging along with our annual emissions. In 2012, atmospheric CO2 concentrations rose by the largest amount in 15 years to a new level of 395 ppm, most of the way to the 450ppm that climate scientists have articulated as the threshold for dangerous warming.

The fundamental driver here is economics. Consumers, businesses, and industry want energy. They need energy. That’s true everywhere in the world. And they will buy whatever sort of energy is cheapest. Indeed, if a new source of energy is sufficiently cheaper than the old, consumers will switch their energy consumption from the old to the new.

If we want to win the race against climate change, one thing matters more than all others:  make renewable energy (including storage) cheap. Dirt cheap. And do it fast.

How do we do that? Fundamentally, we need to increase the pace of innovation. And there are two clear strategies to do so.

The first is to invest more in clean energy R&D.  In 2012, the US suffered $100 billion in damage from the climate-linked disasters of Hurricane Sandy and the still-ongoing drought. Yet we spent only $5 billion on clean energy R&D, an amount that’s roughly half of what we spent in the 1980s.

It’s also a small fraction of the $30 billion the US spends each year on medical research and the $80 billion the US spends each year on defense R&D. Yet in a very real sense, clean energy R&D is an investment in both future health and in national security. Bill Gates proposed last year that this amount should be roughly tripled to $16 billion. That’s a fine start.

The second is to be more inclusive in our cost accounting. The market is a brilliant algorithm that does a masterful job of allocating resources and driving incentives — so long as costs are fully transparent to it. But sometimes, a cost is completely missing from the books — missing in such a way that the market can’t see it.

Fossil fuels have substantial side effects that those who burn them aren’t charged for. The damage done to the environment — and thus, to others — is a cost that society pays, which isn’t passed on to the polluter. That cost is high. Peer-reviewed research suggests that every ton of CO2 emitted inflicts somewhere between $55 and $250 of damage on the environment and others.

Because that cost isn’t passed on as part of the price of fossil fuel use, the market misbehaves. The overall cost of coal, natural gas, and oil is higher than the price paid at the pump or on the power bill. But the part that’s missing is being inflicted on others, spread out over billions of people on the planet, and smeared out over years to come.

Those sorts of costs that are handed off to third parties are called externalities. They’re external to the transaction happening between between buyer and seller. Because the market doesn’t see those costs, it can’t work to minimize them on its own. The whole history of environmental regulation is one of controlling such externalities. We’ve done that by imposing hard limits on the amount of pollution that can be produced.

We’ve also done it by charging a price for pollution — attempting to insert that externality cost back into the transaction. That technique — a price for polluting — was a key part of both the reduction in acid-rain producing sulfur dioxide in the United States, and also in the efforts that drove down CFC emissions around the world and prevented further damage to the ozone layer.

A price on greenhouse emissions — a carbon price, if you will — would spur both conservation and innovation. Because fossil fuel use would be higher, consumers and businesses would be incented to use less fossil fuels, to opt for higher efficiency, and to switch to lower carbon sources of energy.

But even more importantly, a carbon price would accelerate innovation in renewable energy and energy storage. How? More customers purchasing wind or solar power and the batteries that will go with them means more dollars going into the industry. That allows renewable energy manufacturers to build larger factories, which get better economies of scale in producing solar panels and wind turbines.

It also provides those companies with more dollars to invest into research and development of their own. And it makes the industry more attractive for early stage investors looking to back revolutionary new ideas in renewable energy.

By driving the cost of renewable energy down, a carbon price has a global effect — those cheaper renewable energy sources become more attractive to consumers around the world, whether their own country has a carbon price or not.

I’ve focused here primarily on climate, because it’s the threat that touches all others. But similar approaches apply to food, to water, and to fish in the ocean. In all of those cases, there’s room for substantially higher federal R&D — to invest in crops that have higher yields, particularly for the developing world; to develop new low-cost ways to cut water usage in farming; and to put more sensible prices and restrictions on the over-fishing of deep ocean fish, and thus accelerate the shift to sustainable fish farming.

Easy Way or Hard Way?

Ultimately, there are two paths forward for us, the easy way and the hard way.

In the easy way, we acknowledge the evidence that we are causing real harm to our planet, leaving it worse off for future generations, and flirting with the possibility of sudden and dramatic consequences.  We retain our optimism, that we can both address these problems and be far richer in the future than we are today. We take our wildly successful economic system and we fix it so that it recognizes the value of our shared resources and encourages their protection, restoration, and careful, efficient, sustainable use. We invest in action to reduce the risk of even worse future disasters caused by our unwise past. Nothing is certain in life. But on that path, the most likely outcome is that we’ll solve the problems that plague us and grow progressively richer even as we reduce and eventually reverse our negative impact on the planet.

On this path, there’s no sign that economic growth needs to end. There’s no sign that we’re anywhere near the wealth limit of this planet. We have sufficient energy, sufficient water, and the capacity to grow sufficient food to provide 9 or 10 billion people with a level of affluence far beyond what even the richest in the world enjoy today.

The other path, the hard way, isn’t so pleasant. On that path, we continue to deny the damage we’re doing, the very real consequences, and the risk of much worse if we continue along this path. We keep on acting in the way we have, pumping carbon into the atmosphere, warming the planet, acidifying the oceans, hunting fish towards the brink of extinction, depleting the last fossil water buried under our lands. On that path, we’ll eventually come to realize that we’ve made a mistake. When the rivers and wells run dry, when we can no longer find the type of fish we used to eat, when the corals we used to admire have all bleached, when droughts and floods and storms wreck our cities and fields, then we’ll realize that we’ve taken the wrong path.

And then we’ll respond.

I’m an optimist. I believe in humanity’s ingenuity. Even on the path of the hard way, I think we’ll prevail. We’ll scramble and find solutions. Yet the cost will be far higher a decade or two from now than it would be if we started today. And the scars will run deeper, in species lost, in acidified seas, in forests chopped or burned down, in climate-created famines and pestilence, in wars and conflicts born of resource scarcity.

Or perhaps I’m wrong, and on that hard path we simply won’t respond in time, in the way that other cultures of the past failed to respond to the disasters that ultimately led to their collapse. It’s not a chance any of us should be eager to take.

Easy way or hard way. The choice is ours.

For more elaboration on the argument above, see The Infinite Resource: The Power of Ideas on a Finite Planet.

References and Further Reading

A long list of citations for both parts of this series is available in the references to book, from which the series is adapted.

Many of the references listed in Part One are just as relevant for understanding the solutions to our problems as the problems themselves.

To these, some good additions are below:

On the potential of renewable energy (including solar) to power the world, see:

- IPCC, Special Report on Renewable Energy Sources and Climate Change Mitigation

- National Renewable Energy Laboratory, Renewable Electricity Futures Report

- National Renewable Energy Laboratory, Transportation Energy Futures

On desalination technology past and future trends, an excellent summary is found in Menachem and Elimelech, “The Future of Seawater Desalination”, Science (2011)

On fresh water depletion: Pacific Institute, The Worlds Water, Vol. 7

On climate change: Intergovernmental Panel on Climate Change, IPCC Fourth Assessment Report: Climate Change 2007 (AR4)

On feeding the world and the ultimate limits of global food yields, see:

- Food and Agriculture Organization of the UN, How to Feed the World in 2050

- International Food Research Institute, Biophysical Limits to Global Food Production

Data on population growth rates and on GDP, energy use, and CO2 emissions per capita are all drawn from the World Bank, Data Bank of Development Indicators

Much more is found within the book.

Originally posted at Scientific American.

(Credit: NASA)

This is part one of a two-part series on the limits of human economic growth on planet Earth. Part one details some of the environmental and natural resource challenges we’re up against. Part two, on the ultimate size of the resource pool and solutions to our problems, will be published tomorrow and linked here. Both parts are based on Ramez Naam’s new book, The Infinite Resource: The Power of Ideas on a Finite Planet

The world is facing incredibly serious natural resource and environmental challenges: Climate change, fresh water depletion, ocean over-fishing, deforestation, air and water pollution, the struggle to feed a planet of billions.

All of these challenges are exacerbated by ever rising demand — over the next 40 years estimates are that demand for fresh water will rise 50%, demand for food will rise 70%, and demand for energy will nearly double — all in the same period that we need to tackle climate change, depletion of rivers and aquifers, and deforestation.

One view of these looming threats is that we’ve exhausted planet’s resources. We’ve overshot the planet’s carrying capacity. Economic growth — the root problem driving our growing consumption and pollution — has to end. Indeed, the global economy may even need to shrink to avoid complete ecological disaster. That’s the thesis of a long line of environmental books, from The Limits to Growth to Peak Everything.

The problems

Looking at this large array of problems, it would be easy to agree with the Limits to Growththesis — we are simply consuming too much and polluting too much. The underlying driver  — economic growth — can’t keep going without sending us over a precipice.

In my own new book, The Infinite Resource: The Power of Ideas on a Finite Planet, I challenge this view. The problem isn’t economic growth, per se. Nor is the problem that our natural resources are too small.

While finite, the natural resources the planet supplies are vast and far larger than humanity needs in order to continue to thrive and grow prosperity for centuries to come. The problem, rather, is the types of resources we access, and the manner and efficiency with which we use them.

And the ultimate solution to those problems is innovation — innovation in the science and technology that we use to tap into physical resources, and innovation in the economic system that steers our consumption.

The situation we’re in isn’t a looming wall that we’re doomed to crash into. It’s a race — a race between depletion and pollution of natural resources on one side, and our pace of innovation on the other.

I’m not claiming here that we’re assured of victory. Rather, I’m claiming that winning — greatly expanding the global economy while at the same time shrinking or even reversing our impact on the planet — is possible. Whether or not we achieve that depends in very large part on the choices we make.

So with that, let’s take a closer look at the problems, at why ending growth isn’t a viable solution, at the true resources of the planet, and at what we need to do to win this most important race.

Feeding the World:

Humanity has converted roughly a third of the Earth’s land area to the production of food — by far the largest environmental impact we’ve had. Image: Wikipedia

Food production has affected the environment more than any other activity humans have engaged in. Humanity devotes more land to food production than anything else — roughly a third of the surface area of the earth, much of which was once forest but has been converted by humans into farms or grazing lands. Agriculture also contributes to a host of other environmental and resource challenges.

Nitrogen runoff from fertilizer used on US farms in the Midwest has created an 8,000 square mile dead zone in the Gulf of Mexico, an area roughly the size of New Jersey. Runoffs of pesticides are the number one source of pollution in US lakes and rivers. Farm irrigation uses 70% of the world’s fresh water, a resource increasingly under pressure.

Despite that heavy investment of resources and the significant negative side-effects of agriculture, food production is falling behind demand. Between 2002 and 2008, worldwide food prices soared, as demand — particularly from Asia — spiked, while production rose only modestly. Prices today remain more than double their levels of a decade ago. Prices dropped a bit as the recession of 2009 slowed demand, but are now back at record highs. Those high prices, in turn, have stalled progress in reducing global hunger rates. They may also have contributed to the unrest of the Arab Spring.

Food prices spiked at more than twice their historic levels in 2008 and again in 2011. They remain well above their long term averages now. Source: FAO

Worse may be yet to come. Even as food prices hover near record highs, demand is rising. The Food and Agriculture Organization of the United Nations estimates that, by 2050, we will need to grow 70% more food than we do today to feed the world.

If food production doesn’t rise by that amount, prices will rise further. Hunger — something we’ve made steady progress against for 40 years — may rise once more. Political unrest and global instability may follow.

Deforestation

More than half of the prehistoric forest of the Earth has been cleared by humans, primarily to grow food. Image: FAO.

The most obvious way to grow more food is to turn more land over to the task. But that runs hard into another ecological problem: Deforestation.

In prehistoric times, roughly half of the earth’s land surface was forested. Today only half of that forest area remains, the rest having been converted into farm land and grazing land by human hands. And every year, the planet loses roughly another 50,000 square miles, an area roughly the size of Louisiana. Much of that is in the tropics. Since 1950, a full 60% of the world’s tropical rainforests have been destroyed.

Nevertheless, those forests are the most obvious place to expand farming into. The rest of the land on the surface of the planet is either already farmed; is covered in desert, mountain, or swamps; or is used up by cities and towns. And indeed, in the tropics, agriculture is the #1 contributor to deforestation, accounting for an estimated 80% of the forest chopped down.

The planet’s forests are, as The Economist called them, the world’s lungs. They consume CO2 from the atmosphere, converting it into wood and leaf. The world’s forests contain around one trillion tons of carbon (or 3.7 trillion tons of CO2) — equivalent to nearly a century of human emissions. They emit a quarter of the oxygen that feeds all other animal life on earth, including humans. They provide a safe haven for millions of species found nowhere else.

The rain forests alone are estimated to contain 75% of the biodiversity found on land. Forests keep topsoil in place that would otherwise fly away. (Sadly, when topsoil that was once forest blows away, forests suffer, as bordering farmers chop more of it down to acquire more land to make up for the drop in productivity of their current lands.) And, through a process called evapotranspiration, forests bring rain to areas downwind of them. Tropical rainforests alone produce around 20% of the world’s oxygen and 30% of the world’s fresh water. Human activity that damages them has wide reaching effects.

Feeding the growing appetite of humanity by simply farming more land simply isn’t an option — unless we want to accept the release of hundreds of billions of tons of CO2, the disruption of local precipitation patterns, and the extinction of hundreds of thousands of species as an acceptable loss.

To preserve our remaining forests, we’re going to need to grow more food without farming more land.

Fresh Water

Farming (and to a lesser extent, other human activities) are also placing a huge stress on fresh water supplies. Water is life. Agriculture depends upon it. Nearly 70% of the water humanity uses is for irrigation. Growing food for an average human diet requires an estimated 320 gallons of water a day. For an average American diet the number is closer to 900 gallons of water a day. To produce that water, we’re drawing down rivers, lakes, and fossil water aquifers at an unsustainable rate.

The Aral Sea, once the fourth largest fresh water body on Earth, before and after. The sea has been almost completely drained for agriculture. Image: NASA

Beneath the American high plains of Nebraska, Kansas, northern Texas, and five other states lies the Ogallala Aquifer, a giant underground reservoir of fresh water that farms and people in the region depend on. Ogallala is full of ‘fossil water’ — the remnants of the glaciers and ice sheets that retreated from this area more than 10,000 years ago, melting and filling underwater basins as they went. That fossil water is used to irrigate 27% of the farmland in the United States.

Ogallala’s water level is dropping, in some places as fast as three feet per year. In two months the water we withdraw from Ogallala is enough to fill a cube a mile on a side, enough to cover every inch of the island of Manhattan in more than 200 feet of standing water.

Water is abundant on our planet. Oceans cover 70% of the Earth’s surface. Their combined volume is huge. Even freshwater is vast in quantity. It literally falls from the sky.

Yet the rate at which we consume water — particularly for agriculture — exceeds the rate at which we can capture it from rain or from sustainable withdrawals from rivers. To feed our planet, we’ve turned to more extreme methods, draining some rivers dry, and pumping water out of aquifers that will take thousands of years — if not longer — to refill once we’re done with them.

The Indus River Valley aquifer under India’s breadbasket is being drained at a rate of 20 cubic kilometers a year. Water tables in Gujarat province are falling by as much as 20 feet a year. The giant North China Plain aquifer, which provides irrigation for fields that feed hundreds of millions, has been found to drop as much as 10 feet in a single year. A World Bank report cautions that in some places in northern China, wells have to be drilled nearly half a mile deep to find fresh water. Hebeiprovince, one of five atop the aquifer, has seen more than 900 of its 1,052 lakes dry up and disappear due to dropping water tables. In Mexico’s agricultural state of Guanajuato, the water table is dropping by 6 feet a year. In north eastern Iran, it’s dropping by as much as 10 feet a year.

Water is being withdrawn from rivers as well.  Seasonal water levels are dropping on China’s Yellow River, on the Nile in Egypt, on the Indus as far north as Pakistan, and on the Rio Grande in the US. Parts of the Colorado River are a stunning 130 feet below their historic levels. The river no longer reaches the sea. Nor does the Yellow River or dozens of others around the world that have been tapped for irrigation. The rivers that flow through Central Asia have been so massively drained for agriculture that the vast Aral Sea they once fed, once the fourth largest freshwater lake in the world, is now little more than a dry, salty lakebed, its former shore dotted with abandoned fishing villages and the bones of beached boats.

On current course and speed, the Ogallala aquifer will run dry before this century is over, and possibly much sooner. The North China Plain aquifer will run dry. The Indus River Valley aquifer will run dry. And when they do, the cost to agriculture — and thus to human life — will be enormous.

Ocean Overfishing

In the oceans, the situation is nearly as dire. Fish are an essential human food source. Worldwide, they provide 16% of the protein humans consume. In Africa, they provide 21%. In Asia, a whopping 28%. In some individual countries, fish are even more vital. Fish provide 65% of the protein available in Ghana, 58% of the protein available in Indonesia, and 50% of the protein available in Bangladesh. Worldwide, a billion people rely on fish as their primary protein source.

Fish are, in principle, a renewable resource. They breed to create more fish, turning nutrients in the oceaninto forms that humans and other animals can readily consume.

Yet even renewable resources have their limits. When hunted too rapidly, fish populations can collapse. The number of adult breeders that remain can be too low to rebuild the population as they deal with predators, with competitor species, and with the continued pressure of human fishing. That sort of collapse has happened again and again in recent years, with disastrous impacts for both fish species and humans.

More than a third of all ocean fish species have seen their populations crash. Virtually all others are overexploited or being exploited to the maximum possible already. Image: SALIP

Today, the Food and Agriculture Organization of the UN estimates that a third of fish species have either crashed already or are overexploited and pushed to the edge. Another half of all fish species are fully exploited, with no room to grow production. If the demand for fish continues to grow at or near past rates, the FAO believes global fisheries could completely collapse by 2050.

If we want to keep eating fish for the rest of this century, we need to find a better way to acquire them.

Climate Change

Then there is the problem that exacerbates all others.

Our planet is warming. CO2 and other greenhouse gases released by our relentless burning of fossil fuels, our deforestation of the planet, and our livestock are accumulating in the atmosphere. Those gases, in turn, are trapping more heat that would otherwise have escaped into space.

The evidence is all around us. In 1850, Glacier National Park was home to 150 active glaciers. Today it has 25. By 2030 they could all be gone. Mt. Kilimanjaro, the highest peak in Africa, was covered a century ago by twenty square kilometers of glacier. Today it’s covered by less than three.  Permafrost in the northenlattitudes is melting so badly that residents of at least four Alaskan villages are trying to relocate their entire towns to firmer ground.

And perhaps most dramatically, the Arctic ice cap is melting rapidly. In 1980, the smallest area covered by Arctic ice in summer was 8 million square kilometers. In September 2012 it was down to 3.4 million square kilometers. With the ice half as thick as it once was, the ice cap’s volume is barely a quarter of what it was thirty years ago.

As recently as 2007, the IPCC predicted that ice-free Arctic summer days wouldn’t arrive until the middle of the 22^nd century, more than 130 years in the future. Now there’s the very real risk that we’ll see those first ice-free summer days by the end of this decade — more than a hundred years ahead of schedule.

The volume of sea ice in September has dropped to less than a quarter of its levels in 1980. At this rate, the first ice-free September day could occur before the end of the decade, and the Arctic could be free of ice at the end of June by 2030. Source: NSIDC

The most commonly discussed impact of climate change is rising sea levels. And indeed, climate change is expected to raise global sea levels by 3 to 6 feet by the end of the century, not enough to drown the Statue of Liberty, but enough to put dozens of coastal cities and island nations at risk.

Yet there are other risks not so far in the future. Indeed, they’re here now.

In 2003, Europe went through its hottest summer on record since at least 1540. An estimated 70,000 people died from the heat wave. Fires destroyed 10% of the forests of Portugal. France lost 20% of its wheat harvest. Ukraine lost a whopping 75%.

Since then, record droughts hit China in 2009 and 2010, wiping out nearly half the winter wheat harvest, leaving 20 million people without adequate drinking water, and drying up wells that had provided water since 1517.

Climate change causes drought by increasing the moisture demand of the atmosphere. Every degree Celsius of warming increases the amount of water the air can hold by around 7%. But that moisture isn’t distributed evenly. Warmer air can whisk huge volumes of water away from one place, and bring it down in a sudden deluge in another.

And so, in May 2010, China also saw epic floods that killed more than 3,000 people, destroyed 1 million homes, and forced the evacuation of 15 million more.

In August of 2010, another heat wave struck Russia, setting record highs of 111 degrees Fahrenheit and killing 55,000 people across the country in just two months. In Moscow alone, 11,000 people died as a result of the heat.

And the US hasn’t been immune to the effects either. In 2012, the combination of Hurricane Sandy and devastating drought across the American South and Midwest inflicted a combined $100 billion in damage to the US. The drought alone wiped out a quarter of the US corn crop. And that drought, which began in 2011, shows no signs of abetting. Conditions this year, in the spring of 2013, are drier than they were in the spring of 2012.

It’s impossible to attribute a single, specific extreme weather event to climate change. Even if CO2 levels had never risen on Earth, some extreme weather events would occur. But it’s clear that extreme weather is becoming more common as the planet warms, just as models predict.

Heat waves are the clearest example. Record highs are now twice as common as record lows. But both record highs and record lows are now more common, as a warmer, more energetic atmosphere can move masses of air around more rapidly. And peer-reviewed studies have now shown that the deadly heat waves and droughts I’ve just mentioned — Europe in 2003, Russia in 2010, the US South and Midwest since 2011 — were all made many times more likely by climate change.

What will happen if the planet warms as expected on the business-as-usual path?  Climate simulations show decade long dustbowls in the US, Africa, China, and parts of Europe, combined with torrential rains and monsoons in other areas, stronger and more frequent hurricanes in the Atlantic, and incredible periodic heat waves over much of the world.

Climate models predict severe droughts across much of the world by the end of this century. For comparison, the US dust bowl was a -3 on this scale. Image courtesy of NCAR.

Climate change makes every other environmental problem worse. Drought has already taken its toll on the Amazon and other tropical forests. Heat and drought accelerate fresh water loss. Heat, drought, and extreme weather have decimated crops and threaten to do much worse in the future, making it that much harder to feed the population. And the other big effect of CO2 emissions release, ocean acidification, threatens the corals that are essential to the ocean food web — a food web already under pressure from human overfishing.

The Tipping Points

Climate change comes with an added risk — the changes we make to the planet may themselves accelerate warming. Consider the Arctic sea ice. Bright white ice absorbs only about 10% of the solar energy that strikes it, and reflects the rest back into space. But when Arctic sea ice melts, it exposes dark ocean waters beneath it. That dark water absorbs 90% of the solar energy that strikes it. That contributes to the melt of the rest of the ice, as the waters near the Arctic warm more quickly as they’re absorbed. It’s also significant on a planetary scale. If the entire Arctic were ice-free throughout the whole of summer, the added heat captured would roughly equal the total amount of heat captured from all human CO2 emissions to date.

Let me say that again — if the Arctic were ice free throughout the sunniest months of summer (something that could happen within 20 years at the current pace), then even if we ended all human CO2 emissions, the planet would keep warming at a pace similar to the one that it’s on now. And of course, if we don’t end human CO2 emissions, the increasing energy absorption of a dark Arctic will accelerate the pace of warming.

As the Arctic sea ice melts, it exposes darker waters below that capture far more of the sun’s energy, speeding warming of both the region and the planet. Image: NASA

Nor do the feedback loops stop there. As the Arctic melts, the permafrost in Siberia, Canada, and Alaska is melting with it. Below that permafrost is another trillion tons or so of carbon. As the permafrost melts, some of that carbon will emerge into the atmosphere. And a fraction of it will emerge in the form of methane, a gas that is 25-30 times more powerful in its greenhouse effect than CO2. How much warming that’s likely to contribute is still a topic of much debate, but at the upper end, it could also equal human emissions.

In short, we’re on the verge of setting off chain reactions that will keep the planet warming — and accelerate the pace — even after we cease our burning of fossil fuels.

The End of Growth?

The situation we’re in is dire. We’re doing damage to the very systems that we depend upon for survival. What’s the cure?

One refrain is that the core problem is economic growth. The Limits to Growth, the best-selling environmental book of all time, used computer models to demonstrate that unchecked economic growth would eventually lead to overconsumption, over-pollution, or both, sending us off a precipice that would lead to a collapse of human populations and well-being.

Bill McKibben, author of half a dozen environmental books and a leading activist for a low-carbon world, someone for whom I have a tremendous amount of respect, calls economic growth “the one big habit we finally must break.”

Paul Gilding, former head of Greenpeace International, titled his most recent book The Great Disruption: Why the Climate Crisis Will Bring on the End of Shopping and the Birth of a New World. He writes, “The Earth is full. In fact our human society and economy is now so large that we have passed the limits of our planet’s capacity to support us and it is overflowing. Our current model of economic growth is driving this system, the one we rely upon for our present and future prosperity, over the cliff.”

Richard Heinberg of the Post-Carbon Institute, author of Peak Everything, named his latest book The End of Growth: Adapting to Our New Economic Reality. He opens his book with his thesis:  “Economic growth as we have known it is over and done with. The ‘growth’ that we are talking about consists of the overall size of the economy and of the quantities of energy and material goods flowing through it. […] The general trend-line of the economy (measured in terms of production and consumption of real goods) will be level or downward rather than upward from now on.”

There are reasons both to hope and to believe that all of these statements are incorrect.

We must hope that economic growth isn’t over on two separate grounds:

The first is the moral ground. Roughly one billion people alive today on the planet have access to automobiles, air conditioners, and central heat. The other six billion do not. Two billion lack access to a toilet. One billion lack access to electricity. The bulk of the growth to come over the next few decades — in global GDP, in energy consumption, in CO2 emissions, in food consumption, in water use — will all come from the developing world. That growth isn’t trivial. It isn’t about building McMansions or driving SUVs. It is, by and large, growth that reflects the aspirations of billions of people around the world to rise to a level of comfort that nearly everyone in the rich world — even those we consider poor — enjoy. A path forward that doesn’t allow room for billions to rise out of poverty and to at least this modicum of comfort is not a very appealing one.

The second is the practical grounds. What power do we have to stop those in the developing world — where almost all the real growth is to come — from consuming more?  Very little. Perhaps it is resource scarcity itself that will halt the growth of consumption. But if so, that won’t happen easily or peacefully. As demand for energy, food, and water all rise, if supplies remain stagnant (or even drop) prices will rise, unrest will kick in, and violent conflict is a very real possibility. Already we’ve seen that drought helped start the civil war in Sudan’s Darfur region that took hundreds of thousands of lives, and that China, India, and Pakistan — three nuclear armed powers — have exchanged sharp barbs over scarce water resources in the region where the three countries meet.

A world where growth is over is not a world we’re very likely to enjoy.

We are in short, up against immense resource problems at the same time that we’re facing incredible growth in demand. We’re between a rock and a hard place.

Is there a way out of this mess?  Can we grow wealth for billions while solving the environmental challenges facing us?  I think we can, if we make smart choices, and fast. For that, read Part Two, tomorrow.

References and Further Reading

A long list of citations for this piece is available in the references to The Infinite Resource, from which its adapted.

For good starting places and comprehensive reports on these topics, see the following:

On feeding the planet:  FAO, The State of Food and Agriculture – 2012

On ocean overfishing: FAO, The State of World Fisheries and Agriculture – 2012

On fresh water depletion: Pacific Institute, The Worlds Water, Vol. 7

On climate change: Intergovernmental Panel on Climate Change, IPCC Fourth Assessment Report: Climate Change 2007 (AR4)

On growth in energy demand: International Energy Agency, World Energy Outlook 2012

Originally posted at Scientific American.

(credit: stock image)

Dear Professor Kurzweil,

I was hoping for your views on the potential elitization of Singularity that could lead to exacerbation of class/opportunity/economic division.

The ongoing quest for extending human life and artificially enhancing its quality testifies to our instincts for permanence and survival at all cost.

Technologically acquired supremacy breaks the well accepted paradigm that improved life span, physical and cognitive performance is possible only with practice, studious effort and a healthy lifestyle.

Enhancement made accessible to all holds potential to eliminate interpersonal rivalry, covetousness and even war, by equalizing life span and quality. All of us would be “first (beings) among equals.”

However, the more likely scenario is trenchantly divisive, with those who cannot afford such impressive enhancements being at risk of being outdone, outlived, if not exploited, by enhanced beings. A brave new world where talent and effort becomes obsolete and perfection is for sale is morally transgressive.

— Joseph

Joseph,

There is an approximately 50% deflation rate for all information technology. That is why mobile phones were only affordable by the wealthy 15 years ago and now are dramatically better yet very inexpensive, so much so that there are approximately six billion cell phones in the world and about a billion smart phones.

Technology starts out affordable only by the rich at a point where it does not work very well. By the time a technology is perfected it is almost free. Even physical devices will become almost free with the advent of 3D printing.

Best,
Ray Kurzweil

related:
National Nanotechnology Initiative | “Ethical, legal and societal issues”

Grid structure of cerebral pathways (credit: Science)

As a biomedical research scientist I am concerned about President Obama’s broad new research initiative ”to map the human brain.”

The BRAIN ((Brain Research through Advancing Innovative Neurotechnologies) initiative is a very ambitious, and perhaps even noble, effort, and I am most definitely not against imaging or nanotechnology as tools for research.

But, without specific goals, hypotheses or endpoints, the research effort becomes a fishing expedition. That is, if we throw enough technology at the project and get enough people involved, something is sure to come of it — maybe.

I am also not against Big Science projects, if they are based on viable precepts. However, I do think we need to have a more thoughtful discussion of the immediate and long-term issues, with a wider range of participants and perspectives, and some attention to alternatives and priorities, before we dedicate increasingly limited, long-term public funding to such an effort — starting with $100 million per year and a proposed rise to at least $300 million per year for at least 15 years.

Senior scientists in the president’s administration have compared the brain-mapping initiative to the human genome project, but in a recent New York Times article, John Markoff and James Gorman rightly pointed out that, “It is different however, in that it has, as yet, no clearly defined goals or endpoint.”

In a subsequent interview with Jonathan Hamilton on National Public Radio, the director of the National Institutes of Health, Francis Collins, made the same point. In an article last month, also in the New York Times, Tim Requarth pointed out: “Other critics say the project is too open-ended — that it makes little sense without clearly defined criteria for success. ‘It’s not like the Human Genome Project, where you just have to read out a few billion base pairs and you’re done,’ said Peter Dayan, a neuroscientist at University College London. ‘For the human brain, what would you need to know to build a simulation? That’s a huge research question, and it has to do with what’s important to know about the brain.’”

Every scientist (including me) would love to be able to get a grant without having to specify any goals, hypotheses or endpoints, but is this a realistic way to do science?

Why is this mapping initiative more important than other possible initiatives? Is it more important than finding a cure for AIDS? More relevant than beating cancer in all its manifestations? Although the notion of mapping everything going on in the brain has curb appeal, such an open-ended endeavor calls for at least some solid evidence that it is likely to produce substantive changes in disease outcome, understanding of diseases and better public health for the nation.

Consciousness Raising for neuroscience

A deep problem hampering this discussion is the near-universal lack of awareness about the limited, historically determined, very probably transient character of our prevailing assumptions about the relationship between gray matter and brain function.

An 1883 phrenology chart (credit: People’s Cyclopedia of Universal Knowledge/Wikimedia Commons)

The attraction of brain mapping owes much to an obsolete scientific paradigm. Attempts to map and parcellate the human (and animal) brain into morphologically and anatomically distinct areas, each with its specific function, have been around for more than a century.

In the mid-1800s it became scientifically fashionable in neurology to discover and “map” the functions of the cerebral cortex using a variety of methods and techniques available at any given moment. This was called phrenology, and this mapping paradigm became the major focus of the neurological disciplines that led to the doctrine of cerebral localization of functions.

The phrenological trend continues to the present; its ever more sophisticated technologies mask what some of us consider an obsolescent concept (the article by Cold Spring Harbor Laboratory professor Partha Mitra in Scientific American presented a good example).

Mapping the brain with modern technology is a direct extension of that same paradigm. The paramount question here is not about the technology per se, but whether what it represents and what it measures is an accurate reflection what we want to know about how the brain works. Given what we’ve learned so far, we have to ask whether the concept is valid or whether we are calling for a lot of effort and spending based on an outmoded paradigm.

Is mapping a valid concept?

Although it is well established that the connections between dendrites and synapses in the brain are in a state of constant change, we cannot seem to get out from under the idea that brain activity has some kind of shape — a geography that lines up with function. The brain does not sleep and nothing ever gets turned off in the brains of living creatures.

The map of what connects to what must always be changing. Any one instant of imaging will represent just that instant and perhaps nothing more. A map of how “billions, if not trillions of nerve cells interact” has also to account for the role of the billions upon billions of support cells called glia that also make up the brain. No one associated with the mapping initiative seems to be asking what these critical cells contribute to normal and abnormal functions of the brain — so the dynamics and dynamical changes that are always in flux are not going to be characterized by temporally static or even dynamic measures, no matter how technologically sophisticated they may be.

“Maps” are, at absolute best, only limited approximations of the constantly intense dynamics of brain activity, structure and function. The neuroscience community cannot agree as to what it is, exactly, that should be mapped. Molecular changes? Genomic changes? Proteins? Structural changes? Electrical? Biochemical? All of those “events” involve vast numbers of signaling pathways, each of which affects the others in a vibrant, ever-changing cascade. And this doesn’t even begin to address how environmental and behavioral feedback loops affect these mechanisms.

In the present state of neuroscience, there is no consensus about the best approach to mapping, and which approaches should be given the highest priority. And as Mithra notes, even if we could map the action potentials for every single neuron in the mammalian brain, how do we make the jump to complex behavior that emerges from the measurement of action potentials? When, and for how long, will recording have to be done to generate that information?

This is no small issue. Others have also expressed concern that current imaging technologies have often been incorrectly applied, leading to the wrong conclusions about how the brain is “wired” and how it functions in a dynamic state.

How should we proceed?

Before we try to map brains (even brains of worms and fruit flies and mice), we need to work out better concepts of what needs to be measured, and then apply the appropriate technologies to measure it. As it now stands, we have high-level technology with no clear concept of what to measure and no defined goals or endpoints. Does the project simply go on forever? When will we know that we have the answers? I agree with others that despite the rhetoric of administration spokespersons and those who will benefit directly, this is not at all like the genome or moon-landing projects.

In my own field of specialization, traumatic brain injury and stroke, we know that even humans with massive damage to the brain can make remarkable recoveries of function — under the right conditions — sometimes almost instantly. The problem we face is how to unlock those conditions. Brain maps cannot account for this extensive plasticity and repair at all, any more than most diseases can be attributed to the regulation and expression of just one gene — as most systems biologists will tell you if given the chance.

What practical outcomes do we expect?

Some have argued that investing in the mapping project will generate new jobs and wealth, and this could happen. The Human Genome Project is generating considerable wealth and biomedical startup companies (for example, screening genomes for individual clients) — certainly more than the initial dollars invested. However, the actual benefit to patients has so far been very limited. We now know a lot about the human genome map, but how many diseases have been cured?

New York Times reporter Gina Kolata, recently reporting on DNA testing for rare disorders, noted that sequencing of the entire genome of patients with rare diseases is becoming so popular that the costs are now down, from $7,000 to $9,000 for a family, and demand is soaring — hence the commercial value of such tests. Yet all the sequencing offers no panacea, she says: “Genetic aberrations are only found in about 25 percent of cases, less then 3 percent get better management of their disease and only about 1 percent get an actual treatment and a major benefit.”

With the Brain Mapping Initiative, are we about to make a very heavy investment in a project that promises no end-points and nothing specific in the way of actual benefit? If so, we ought to be clear about it and not let the public think that “miraculous cures” and full understanding of brain functions are just around the corner.

We need to talk

I urge that we need broader and more considered discussion of how we want to invest our research resources. I marvel that a small group of scientists were able to catch the president’s attention and support, but is this kind of earmarking in lieu of salient peer-review the way we want to decide allocations for research? We hate it when Congress does this (if we’re not the beneficiaries), so do we want to adopt the same model? These questions should all be a part of the debate.

Whether I agree with the paradigm or not, I most certainly support those who still want to continue research on brain mapping. But we need to look again at whether it merits the disproportionate investment and prestige proposed for it, especially now, in a time of severe, perhaps permanent curtailments in biomedical research funding.

This is not about big science or small science and this is not just about the $100 million kick-start — the stakes and costs will be much higher. This is about good science and bad science, or at best, not-so-good science. In the current zero-sum game of funding, many other areas of critical biomedical research, including hundreds of small, or smaller, projects with potential for important near-term clinical application, will suffer as the money goes elsewhere and as students and researchers flock to where the money is. Is this good for biomedical research? Are we sure?

LIncoln Cannon’s opening address (credit: Giulio Prisco)

Like every year, I attended the yearly conference of the Mormon Transhumanist Association (MTA), on April 6 in Salt Lake City.

It is no mystery that I am very fond of the MTA. I think it represents the best example of successful integration of transhumanist ideas in a mainstream religion, and one of the best transhumanist communities.

Man becoming godlike: belief or heresy?

The Church of Jesus Christ of Latter-Day Saints (LDS), aka Mormon Church, has a concept of boundless elevation and exaltation of Man, through all means including science and technology, until he becomes like God.

Conversely, God was once like Man before attaining an exalted status. “[Mormonism] allows for humans to ascend to a higher, more godlike level,” writes Max More in his introduction to The Transhumanist Reader, “rather than sharply dividing God from Man.”

Mormon transhumanists are persuaded that we will become like God — through science and technology — in a progression without end, and this seems a more faithful interpretation of the teachings of Joseph Smith and a return to the roots of the Mormon religion.

Not all Mormons agree with this transhumanist formulation of their faith but, according to MTA president Lincoln Cannon, it is a correct interpretation of the writings of Joseph Smith, the founder of the Mormon Church, close to the historic and philosophical roots of the LDS doctrine, as shown by the King Follet discourse and the quotes of Smith and other Mormon authorities collected here.

All Mormons are familiar with this aspect of their faith, but many modern Mormons seem to sweep these concepts to the back of their mind, as they do for other controversial issues such as polygamy, promoted (and practiced) by Smith and the founding fathers but frowned upon in modern times.

The tension between the progressive approach of the MTA and the more conservative approach of the Mormon Church at large was especially evident in Brad Carmack’s talk on the rights of LGBT and transgendered persons.

In the first keynote, longevity researcher Aubrey De Grey said that medical Strategies for Engineered Negligible Senescence (SENS) may soon permit eliminating aging, and that failing to do so would be a “sin.” He countered many frequent “ethical” objections to extreme longevity research, showing that life extension is inseparable from healthy aging.

Computational theology?

In the more visionary part of this visionary conference, Alcor’s Mike Perry, author of Forever for All, presented his thoughts on far-future sciences and technologies able to resurrect the dead. In my own talk, I showed how the Problem of Evil — why a benevolent and omnipotent God permits evil and suffering — can be framed and “solved” in terms of the computational physics of a simulated universe.

In the second keynote, renowned historian Richard Bushman, the author of Rough Stone Rolling, a biography of Joseph Smith, put the ideas of the MTA in a Mormon historical perspective. He could hardly be expected to fully endorse the openly transhumanist vision of the MTA, but he departed holding a copy of Ray Kurzweil’s latest book.

As in Max More’s observation, the Mormon Church may be an especially fertile ground for the emergence of a transhumanist religion. But according to musician Micah Redding, similar openings can also be found in mainstream Christianity, albeit in a less explicit form.

Not all speakers were transhumanist-religion-friendly. Carl Teichrib, editor of Forcing Change, criticized transhumanist spirituality from a Christian perspective (see his review of the 2010 conference on Transhumanism and Spirituality), and Peter Wicks criticized the introduction of religious elements in transhumanism.

I would like to begin by stating that I am a huge fan and supporter of yours. I read your book The Singularity Is Near last year, and I was enchanted by all of your ideas on the exponential development of human technology and science. I am 100% singularitarian.

I understand that you are a very busy man, but I would tremendously appreciate it if you could take a moment of your time to read this email and respond with your own thoughts on the issue I am about to present to you.

I have recently read an article which discusses your views on the challenge of eliminating the process of aging. As I read the article, a disturbing thought came to my mind: What if humans were to completely eliminate the process of aging in, say, the next ten or twenty years (probably before the technological singularity)?

What would be the worldwide consequences of such a development? Would the elimination of aging, and thereby the elimination of death, ultimately, have good or bad consequences?

I believe that the consequences of such a development would be terrible for the entire human race in general.

I will present to you my personal prediction of what will occur. If, say, 15 years from now, the solution to death had been found and made available to all, mostly everyone would be eager to obtain it.

Once humans have been cured of aging and death, they will probably continue their lives and still reproduce with each other: this creates an obvious problem. The world’s population, already growing incredibly fast, will become enormous.

Less resources will be available for everyone, and the world’s average standard of living will greatly decline.  Naturally, people, seeing that they do not have enough resources to care for their children, will gradually stop reproducing, and less and less children will be born each year.

It must be kept in mind that, although the cure for age-related death has been found, death will still occur due to other factors, such as starvation. Thus, people will continue to die and be replaced by means of reproduction, and the world’s population will eventually level out. However, people everywhere will be living in terrible conditions, as, once the population has leveled out, there will be just enough resources in the world to support this population.

Although age-related death has been eliminated, billions and billions of people will be living in absolutely horrid conditions. Given these possible developments, would it not be best for a scientist who has found a cure for aging not to reveal his discovery, for the good of all mankind?

In your response could you please tell me what you think of the accuracy my prediction, or if you totally disagree with it, what your own personal prediction is? If my prediction is somewhat accurate, what can be done today to prevent such a disastrous outcome? I am deeply unsettled by this issue, and any response would be enormously appreciated. Thank you very much for your time.

— Rish Vaishnav

Hi Rish Vaishnav,

The same technologies that will radically extend human longevity will radically expand available resources.  For example, we have 10,000 times more free energy from the sun falling on the Earth than we need to meet 100% of our energy needs.

Total solar energy is doubling every two years and is about seven doublings from meeting all of our needs.  There are similar scenarios for water, food, housing.  Try taking a train trip anywhere and you’ll see that almost all of the land is unused.

— Ray

Ray,

Thank you so much for your response! I feel much better now about this issue, knowing that you have a much more optimistic (and definitely much more accurate) prediction than I do. I guess that we can also take into account that with a greater population, there will be much more people (along with more advanced technology) available to collaborate in the search for more and more resources to support the infinitely growing population. Once again, thank you so much for your response.

— Rish Vaishnav

Related:
SENS Research Foundation — “reimagine aging”

A DARPA-funded Harvard experiment in creating superintelligent rats goes out of control when rats buy up Bitcoins (credit: wikia.nocookie.net)

OK, it’s April 1 again, so let’s see who’s been paying attention over the past year. Which of these are:

a. An actual KurzweilAI news or blog post, based on facts.
b. An actual KurzweilAI news or blog post, but based on speculation.
c.  Fake news.

1. Rats can communicate with other rats 1000s of miles away, helping other rats navigate mazes.

2. Reality is created by a program running on a quantum computer the size of the entire Universe.

3. We actually live inside a mathematical equation.

4. A new robot can make burgers faster than people.

5. By 2025, we will place a human brain into a working robot and have that person’s consciousness transfer to the robot.

6. People can control movements of cancer drugs with their mind and heal themselves.

7. We can stop global warming by spraying sulfuric acid all over the world from high up in the sky.

8. IBM is working on miniaturizing Watson to fit into your smartphone.

9. Machines can read your mind and determine what images you are thinking about.

We’ll reveal the answers, with links, tomorrow. (Note: the other posts today are not April Fools items, although they may look like that.)

UPDATE April 3, 2013 And the answers are….

1 a
2 b
3 b
4 a
5 b
6 c
7 b
8 a
9 a

If you live in Italy, the answer is si, thanks to Italy’s health minister, Renato Balduzzi, who has decreed that a stem-cell treatment can continue in 32 terminally ill patients, mostly children — even though the stem cells involved are not manufactured according to Italy’s legal safety standards.

The unexpected decision on March 21 has horrified some scientists, who consider the treatment to be dangerous because it has never been rigorously tested. In the opinion of stem-cell researcher Elena Cattaneo of the University of Milan, “It is alchemy.” Nature News reports.

Activists against restrictions of stem cell treatments (credit: Benvegnù/Guaitoli/Cimaglia)

The therapy was developed by the Brescia-based Stamina Foundation (“Cellule staminali” means stem cells in Italian) and has been repeatedly banned in the past six years.

But patient groups are pushing for the treatment to be available to anyone with an incurable illness. Hundreds protested in Rome last week, including a naked woman with pro-Stamina slogans painted on her skin (video below).

However, in a letter to Balduzzi, more than a dozen scientists criticized the decision, saying it “seems to be dictated by emotions raised by public opinion rather than scientifically based reasons,” according to Times Live of South Africa.

Of course the “bureaucrats of science” of the Italian and European science establishment  were united against the pioneering, yet controversial stem cell treatment that was saving lives, including the life of a little girl, and forced the interruption of the treatment and even a police raid on the hospital. But a wave of public outrage forced them to back off.

Avanti!

The treatments should continue, despite court rulings to the contrary, Health Minister Renato Balduzzi said Thursday, Gazzetta del Sud reports. “The (decision) is based on the ethical principle that medical treatment which has already started without serious side effects should not be stopped,” said Balduzzi.

Of course I side with Balduzzi, with the people, and against these “scientists” who, if I could have things my way, should be sent to the fields to do some hard work for once in their lives. They complain that the new treatments have not been rigorously tested, and I look forward to more comprehensive tests and pee-reviewed (sorry, that was peer-reviewed) studies.

But medicine is about saving lives, not about doing things by the book. Terminally ill patients are, indeed, terminally ill — conventional medicine has given up, and they have only a short time to live. Why on Earth shouldn’t they be allowed to test new, experimental procedures? Is trying to live longer, or better, a crime?

Of course the new treatments may not prove as effective as hoped after all, and those who have chosen to experiment may even die sooner. But if they have made an informed decision to accept the risk, why should the bureaucrats of science be allowed to stop them?

In 2001 my own mother died after having battled cancer for years. She refused “conventional” medicine and opted for a highly controversial experimental treatment instead. She probably lived longer than most cancer patients, and without the debilitating effects of highly aggressive, conventional cancer therapies.

But the point that I want to make is that it was her decision to make, and her own life. Self-ownership is a fundamental right, and it must remain so.

Beppe Grillo (credit: Niccolò Caranti/Wikimedia Commons)

Bring in the clowns

A few weeks ago 25% of the people didn’t vote at the Italian political elections, and another 25% voted for the anti-system, populist-party “5-Stars Movement” led by former comedian Beppe Grillo, whose spectacular victory has made headlines everywhere.

With this vote, the Italian people raised the middle finger at the ridiculous bureaucracy and endemic corruption.

A couple of decades ago we hoped that “being in Europe” would address this problem, but what happened was that the rest of Europe went the Italian way instead, establishing a byzantine and useless bureaucracy in Brussels with hordes of control-freaks who claim the right of telling European citizens what to do and think.

Today I am proud of my country, and I hope that we, the citizens, the people, will be able to fight the bureaucrats and take back the ownership of our lives.

A supercomputer simulation of the evolution of the universe (credit: Andrey Kravtsov/University of Chicago)

There is a fastest, optimal, most efficient way of computing all logically possible universes, including ours — if ours is computable (no evidence against this). Any God-like “Great Programmer” with any self-respect should use this optimal method to create and master all logically possible universes.

At any given time, most of the universes computed so far that contain yourself will be due to one of the shortest and fastest programs computing you. This insight allows for making non-trivial predictions about the future. We also obtain formal, mathematical answers to age-old questions of philosophy and theology.

Transcript of Jürgen Schmidhuber’s TEDx talk at UHasselt, Belgium, Nov. 10, 2012

I will talk about the simplest explanation of the universe. The universe is following strange rules. Einstein’s relativity. Planck’s quantum physics. But the universe may be even stranger than you think. And even simpler than you think.

Is the universe being created by a computer program?

Konrad Zuse

Many scientists are now taking seriously the possibility that the entire universe is being computed by a computer program, as first suggested in 1967 by the legendary Konrad Zuse, who also built the world’s first working general computer between 1935 and 1941. [1]

Zuse’s 1969 book Calculating Space discusses how a particular computer, a cellular automaton, might compute all elementary particle interactions, and thus the entire universe.

The idea is that every electron behaves the same, because all electrons re-use the same subprogram over and over again.

First consider the virtual universe of a video game with a realistic 3D simulation. In your computer, the game is encoded as a program, a sequence of ones and zeroes. Looking at the program, you don’t see what it does. You have to run it to experience it.

Reality has still higher resolution than video games. But soon you won’t see a difference any more, since every decade, simulations are becoming 100–1000 times better, because computing power per Swiss Franc is growing by a factor of 100–1000 per decade.

A few decades imply a factor of a billion. Soon, we’ll be able to simulate very convincing heavens and hells. It will seem quite plausible that the real world itself also is just a simulation.

To a man with a hammer, everything looks like a nail. To a man with a computer, everything looks like a computation.

Skeptics might say: What about quantum physics, and Heisenberg’s uncertainty principle, and Bell’s inequality? Don’t they imply that the universe cannot be produced by a deterministic program? Not at all. Bell himself knew well that deterministic universes including deterministically computable observers are fully compatible with all available physical observations.

The universe as the sum of all mathematics

“Calculating space,” a painting by Konrad Zuse

When my brother Christof was a teenager in the early 1980s in Munich, he told me and others: the universe, or quantum multiverse, is the sum of all mathematics. I believe he is the reason why such ideas emerged in Munich.

He was younger than me. He still is. He also was smarter than me. He went on to become a physicist at Munich, Caltech, Princeton, and CERN, and he lived in Berne next door to where Einstein lived.

It took me a while to understand what my brother meant. In 1996, I formalized his idea through a computation. I generalized Everett’s many worlds theory, pointing out that there is a very short and fast program that not only computes our own universe, or multiverse, but also all other logically possible universes, even those with different physical laws. For example, universes with anti-gravity.

In fact, there is a fastest, optimal, most efficient way of computing all logically possible universes, including ours — if ours is computable (no evidence against this).

(Credit: TEDx)

The optimal method can be programmed with only ten lines of code. I wrote it down for you — here it is! [Holds up a piece of paper.] [2]

Any God-like “Great Programmer” with some self-respect should use this optimal method to create and master all logically possible universes.

Suppose he runs it for a while. At some point, many of the executed programs will have computed universes that contain you! You, as you are sitting here and staring at me with incredulous eyes.

You could even become a “Great Programmer” yourself, using the optimal method [holds note up again] to simulate all possible universes in nested fashion. (But this would not necessarily help to figure out the future faster than by waiting for it to happen. The computer on which to run this program would have to be built within our universe, and as a small part of the latter would be unable to run as fast as the universe itself.)

Anyway, now it’s easy to see that due to the nature of the optimal method, at any given time, most of the universes computed so far that do contain yourself will be due to one of the shortest and fastest programs computing: YOU.

Predictions

This insight allows for making non-trivial predictions about the future. There are many possible futures of your past so far. Which one is going to happen? Answer: given the probability distribution induced by the optimal method, most likely one of the few regular, non-random futures with a fast and short program.[3] (Because the weird futures where suddenly the rules change and everything dissolves into randomness are fundamentally harder to compute, even by the optimal method. Random stuff by definition does not have a short program.)

This implies that the decay of neutrons, widely believed to be random, most likely is not random, but pseudo-random, like the decimal expansion of PI, which looks random, but isn’t, because it is computable by a short and fast program.

Why quantum computing may never scale

The optimal method also implies that quantum computation will never work well, essentially because it is consuming so many basic computational resources. I first made this prediction a dozen years ago. Since then there has not been any progress in practical quantum computation, despite lots of efforts. (The biggest number factored into its prime factors by any existing quantum computer is still 15.) Quantum computation is sexy, but dead.

What about free will? Free will is overrated. In my group at the Swiss AI Lab IDSIA, we often program simulated worlds including simulated observers with simulated artificial brains. Through pseudo-random trial and error they even learn from experience to become smarter over time, acting as if they had free will. They have no idea that every thought in their artificial neural networks is computed by a deterministic program. (In a way, they do have free will — it’s just deterministically computed free will.)

Computational theology

Nevertheless, computer science is now giving us formal, mathematical answers to old questions of philosophy and theology. One of the results of my Computational Theology is this: your own life must be very important in the grand scheme of things.

You may think that your life is insignificant, because you are so small, and the universe is so big. But given the Great Programmer’s optimal way of computing all universes, it is probably very hard to edit your life (or mine) out of our particular universe: Any program that produces a universe like ours, but without you, is probably much longer and slower (and thus less likely) than the original program that includes you.

So with high probability, your life essentially has to be this way, with all of its ups and downs. Your life is not insignificant. It seems to be an indispensable part of the grand scheme of things.[4]

This is compatible with religions claiming that “all is one,” “everything is connected to everything.” May this thought lift you up in times of frustration.

Footnotes:

(Credit: iStockphoto)

1. A recent KurzweilAI news article mentioned somewhat related ideas by Max Tegmark (1997/1998). How does Schmidhuber’s approach differ?

“My paper on all computable universes called ‘A computer scientist’s view of life, the universe, and everything’ got submitted/published in 1996/1997,” Schmidhuber told KurzweilAI.

“Back then, Max also was based in Munich (at LMU). He put forth this somewhat vague and not really formally well-defined notion of a mathematics-based ensemble of universes.

“He assumed a uniform prior distribution on this ensemble, which unfortunately cannot even exist, as there is no uniform distribution on countably infinite things. Over the years, Max and I had quite a few little chats about this :-) . I think a mathematical analysis of this type really must focus on the formally well-defined, limit-computable mathematical structures/universes.

“Max also completely ignores computation time, while the talk above is all about computation time, which makes a big difference between easy-to-compute and hard-to-compute universes, and greatly affects their probabilities, and thus the most likely futures of observers inhabiting them. I also addressed such differences in an additional 2000 paper on all formally describable universes (and also in the 2012 survey paper for H. Zenil’s book, A Computable Universe).

“I also wrote that I suspect my brother Christof Schmidhuber is the real reason why such ideas emerged in Munich. At the age of 17 he declared that the universe is the sum of all math, inhabited by observers who are mathematical substructures (private communication, Munich, 1981).

“As he went on to become a theoretical physicist at LMU Munich, Caltech, Princeton, and CERN, discussions with him about the relation between superstrings and bitstrings became a source of inspiration for writing both the first paper  and later ones based on computational complexity theory, which seems to provide the natural setting for his more math-oriented ideas (private communication, Munich 1981-86; Caltech 1987-93; Princeton 1994-96; Berne/Geneva 1997–; compare his notion of “mathscape”).”

2. The preprint of a recent overview paper by Schmidhuber includes pseudocode (a simplified generic version) for the ten lines of code mentioned in the talk (see also slides):

FAST Algorithm
for i := 1, 2, . . . do
Run each program p with l(p) ≤ i for at most 2^i−l(p) steps and reset storage modified by p
end for

[here l(p) denotes the length of program p, a bitstring]

Schmidhuber explains: “This is essentially a variant of Leonid Levin’s universal search (1973), but without the search aspect. The code systematically lists and runs all possible programs in interleaving fashion. It can be shown that it computes each particular universe as quickly as this universe’s (typically unknown) fastest program, save for a constant factor that does not depend on the universe size.

From this asymptotically optimal method, we can derive an a priori probability distribution on possible universes called the Speed Prior. It reflects the fastest way of describing objects, not necessarily the shortest. (BTW, note that any general search in program space for the solution to a sufficiently complex problem will create many inhabited universes as byproducts.)”

3. Assume you are running computations for all universes in parallel, says Schmidhuber. Some contain you at a given time. So among those universes computed so far that contain you, which are the most likely ones, that is, what’s your most likely future? In a Bayesian framework, “Speed Prior” permits non-trivial answers to questions of this type.

4. “Because most likely the universe to which you owe your current existence has a high a priori probability,” explains Schmidhuber. “Other possible variants of your life are less likely because they are harder to compute, even by the optimal method.”

The insights mentioned in this talk were first published between 1996 and 2000, and further popularized in the new millennium. Detailed mathematical papers as well as popular high-level summaries can be downloaded from Schmidhuber’s overview site on all computable universes.

For information on a Master’s Degree in Artificial Intelligence through courses taught by Schmidhuber and colleagues, visit this site: Master’s Degree in Informatics with a Major in Intelligent Systems

For new jobs for postdocs and PhD students in Schmidhuber’s research group, visit this site: http://www.idsia.ch/~juergen/eu2013.html

Edge-on view of our solar system with Sun (white) in the center, showing the population of near-Earth asteroids (NEAs) and potentially hazardous asteroids (PHAs) that scientists think are likely to exist based on the NEOWISE survey. Positions of a simulated population of PHAs on a typical day are shown in bright orange, and the simulated NEAs are blue. Earth’s orbit is green. (Credit: NASA/JPL-Caltech)

If you think the events of the post-Valentine’s day surprise of the Russian Meteor and 2012 DA14 near miss are one of a kind, think again. “We know there are 500,000 to 1 million asteroids the size of DA14 or larger. So far we have found fewer than 1% of that ‘cosmic hailstorm’ through which we sail in our yearly orbit around the Sun,” said the Association of Space Explorers in a recent statement.

We are tracking fewer than 10,000 of them. Even our pathetically limited space situational awareness of the threat shows that there were a total of ten close approaches just this month and there are many more near-approaches on the way, including as many as 1,381 already-mapped potentially hazardous objects.

Near-Earth asteroids (NEAs) are asteroids with closest approach to the Sun (perihelion) less than about 121 million miles). So far, 9644 NEAs have been discovered, as of Feb. 22, 2013.

Potentially hazardous asteroids (PHAs) are the subset of NEAs with the closest orbits to Earth’s orbit, coming within 5 million miles (about 8 million kilometers). They are also defined as being large enough to survive passage through Earth’s atmosphere and cause damage on a regional or greater scale. The latest results provide the best count yet of the total PHA population, finding about 4,700 plus or minus 1,500 with diameters larger than 330 feet (about 100 meters). The NASA NEOWISE team estimates that about 20 to 30 percent (1,381) of the PHAs thought to exist have actually been discovered to date.

Sources: NASA Survey Counts Potentially Hazardous Asteroids, Near-Earth Asteroid Discovery Statistics, NEO Groups

A federal asteroid policy

This diagram illustrates the differences between orbits of a typical near-Earth asteroid (blue) and a potentially hazardous asteroid, or PHA (orange). PHAs are a subset of the near-Earth asteroids (NEAs). They have the closest orbits to Earth’s orbit, coming within 5 million miles (about 8 million kilometers), and they are large enough to survive passage through Earth’s atmosphere and cause damage on a regional or greater scale. (Credit: NASA/JPL-Caltech)

In 2008 some prescient members of Congress wrote HR 6063, which tasked the Director of the President’s Office of Science and Technology Policy to develop a policy for notifying federal agencies and relevant emergency response institutions of an impending near-Earth object threat, if near-term public safety is at stake.

The bill also recommended a federal agency or agencies to be responsible for protecting the nation from a near-Earth object that is anticipated to collide with Earth, and for implementing a deflection campaign, in consultation with international bodies, should one be required.

In the winter 2008 issue of Ad Astra, I argued that it would not be long before this issue was raised to presidential-level attention, given that the Association of Space Explorer’s report to the United Nations Committee on the Peaceful Uses of Outer Space had said that, as new telescopes come online, in a little over a decade we are likely to be tracking as many as 1 million near-Earth asteroids (NEAs) — of which 10,000 may have some probability of impacting Earth in the next 100 years, and 50 to 100 will appear threatening enough to require active monitoring and/or deflection.

In August 2009, in an article for The Space Review, I advised that the forthcoming national space policy should establish a lead agency and supported/supporting relationships for the now fully established asteroid/comet hazard.

And I gave my breakout of recommendations for who should be in charge of what. This was based upon my experience having conceived and executed the only official U.S.  government multi-agency simulation (USAF-NASA-OSD-NSC-DOE) of how we would attempt to either deflect or do emergency response for an asteroid threat.

In 2010 the Air Force sent me on a CFR fellowship to India’s premier strategic think tank to explore “big ideas” that might advance the U.S.-India strategic partnership. I floated both Planetary Defense and Asteroid Mining as two such big ideas and argued that they should be included as topics for the Indo-U.S. civil-space dialog, as well as potential deliverables for the President’s visit to India in 2010, as responsive to the administration’s stated national interests of engaging key centers of influence and shaping a rules-based global order.

Later in 2010 I spoke to NASA on planetary defense considerations for a human mission to an asteroid, suggesting that this be a primary and not secondary objective for such a mission.

Earlier this year, in fact just prior to the dramatic announcements of Planetary Resources and Deep Space Industries, I argued in ASPJ that space strategists and policymakers needed to be thinking actively about a future space environment where commercial space industries might have capabilities to mine and exploit asteroids.

Most recently I argued for elevating the prominence of asteroid threats and opportunities in my OpEd on KurzweilAI and an interview for DoDLive.

A wakeup call

Meteor rains down on central Russia, injuring up to 1,200 people (credit: Independent/amateur video)

But look: meteors raining fire down on Russia injuring hundreds of people, and the closest pass of an asteroid ever forecast and recorded (2012 DA14) as a post-Valentine’s day surprise need to be a wakeup call. The longer we go without a proactive space policy on asteroids, the more we sacrifice international leadership, hold back our industry, and reduce our chances of being able to effectively deal with the threat.

The timing is perfect for a second Obama administration — an administration that sought a manned mission to an asteroid, and which has continued and expanded the Bush legacy of being friendly toward commercial space — to re-issue a revised national space policy that contains a real policy on Asteroids.

Such a real policy, a proactive policy — a visionary and durable policy for the decades and centuries ahead — needs to include the following elements:

1) The United States intends to lead the world in the creation of a planetary defense architecture, and shape the accompanying global regime. It will proactively engage the key centers of influence on the subject and pursue active collaboration with the friendly space powers. It will introduce discussions such as exploring necessary exceptions or modifications to the Limited Test Ban Treaty and Outer Space Treaty as may be required to protect planet Earth.

2) The United States intends to promote and incentivize asteroid mining and space industrialization. It will seek to create a global regime that is favorable to private industry generally, and that seeks to put American industry in a position to lead.

The United States will broaden the discussions of the International Code of Conduct to ensure it reflects the equities of future space development and is private-industry-friendly. The United States will welcome discussion on a revised space regime that creates property-like incentives that encourage early market entry into a new market that could so dramatically advance prospects for long-term human survival and sustainable development.

As a nation, we need to be prepared to promote “space resource utilization” (aka asteroid and lunar mining) as a strategic industry, using the same techniques we used in our westward expansion and railroad building and the development of our aviation industry. We should set as a goal that it should be an American company to mine the first asteroid, and set the precedent for a responsible and open in-space commerce system.

3) Planetary defense will be established as a formal mandate to one or more of the appropriate organizations, with a single agency responsible for developing and executing an actual asteroid deflection mission (I have elsewhere argued that this should be USSTRATCOM). This organization should be tasked with creating a roadmap to specific increments of capability, beginning with deflecting small “city-killer” 50-meter objects like 2012 DA14, and progressing to kilometer-class civilization-ending threats in difficult-to-reach inclinations.

The U.S. government will have an encouraging policy to source asteroid-related space-situational awareness from private industry.

4) Pre-competitive research enabling private industry will be given as a formal mandate to an appropriate organization (such as NASA, Dept of Commerce’s Office of Space Commercialization, or FAA’s office of space transportation).

Without a lead agency that perceives itself to have a mandate, and clear policy stating where we desire to go, we leave both our government officials and our private industry disempowered to deal with the dangers and advance the opportunities that near-Earth asteroids present.

A tiny microscope equipped with a microendoscope images hippocampus CA1 pyramidal neurons expressing GCaMP3, a green fluorescent protein (credit: Yaniv Ziv et al./Nature Neuroscience)

Want to read a mouse’s mind — observing hundreds of neurons firing in the brain of a live mouse in real time — to see how it creates memories as it explores an environment?

You’ll just need some fluorescent protein and a tiny digital microscope implanted in the rodent’s head, Stanford University scientists say.

Here’s how:

1. First, you catch your mouse.

2. Light up some hippcampus (memory) neurons — specifically, CA1 pyramidal cells. To do that, genetically engineer (using viral vector AAV2/5-CaMKII-GCaMP3)  the neurons to express a green fluorescent protein (GCaMP3), which is sensitive to the presence of calcium ions. (When a neuron fires, the cell naturally floods with calcium ions. Calcium stimulates the protein, causing the entire cell to fluoresce bright green.)

3. Implant a tiny microscope just above the mouse’s hippocampus — a part of the brain that is critical for spatial and episodic memory to capture the light of about 700 neurons. The microscope is connected to a digital camera chip. (A Stanford spinoff called Inscopix has been set up to make and sell the device, called nVista HD. (Inscopix’s Neuroscience Early Access Program (NEAP) is currently accepting applications from leading neuroscientists for access to this revolutionary imaging technology)

Miniature fluorescence microscope, nVista HD (credit: Inscopix)

4, Connect the  camera to a computer, which then displays near-real-time video of the mouse’s brain activity as a mouse runs around an arena (a small enclosure). Think Gladiator in miniature, with whiskers instead of swords.

Calcium ions are shown here as red (the fluorescence is green); blood vessels appear as shadows. Scale bar: 100 microns (.1 mm). (Credit: Yaniv Ziv et al./Nature Neuroscience)

5. Decode the image. The neuronal firings look like tiny green fireworks, randomly bursting against a black background. (Makes for a great light show too, although not as good as this one.)

Mark Schnitzer, an associate professor of biology and of applied physics and the senior author on the paper (in the journal Nature Neuroscience) advises:

“We can literally figure out where the mouse is in the arena by looking at these lights.” When a mouse is scratching at the wall in a certain area of the arena, a specific neuron will fire and flash green, he explains. When the mouse scampers to a different area, the light from the first neuron fades and a new cell sparks up.

“The hippocampus is very sensitive to where the animal is in its environment, and different cells respond to different parts of the arena. Imagine walking around your office. Some of the neurons in your hippocampus light up when you’re near your desk, and others fire when you’re near your chair. This is how your brain makes a representative map of a space.”

6. Use this tool for studying new therapies for neurodegenerative diseases such as Alzheimer’s.

A mouse’s neurons fire in the same patterns, even when a month has passed between experiments, the researchers found. “The ability to come back and observe the same cells is very important for studying progressive brain diseases.”

For example, if a particular neuron in a test mouse stops functioning, as a result of normal neuronal death or a neurodegenerative disease, researchers could apply an experimental therapeutic agent and then expose the mouse to the same stimuli to see if the neuron’s function returns.

Although the technology can’t be used on humans, mouse models are a common starting point for new therapies for human neurodegenerative diseases, and Schnitzer believes the system could be a very useful tool in evaluating pre-clinical research for for neurodegenerative diseases such as Alzheimer’s.

The song was written predominantly by Michael Jackson, with help from Lionel Ritchie, at the suggestion and with the production of Quincy Jones. The process began as an idea of Harry Belafonte. (Credit: JET)

Dr. Martine Rothblatt suggests inviting the entire world’s population on-board the 100YSS by uploading, at no cost, their mindfiles — a 1 TB (or less) digital file of an individual’s mannerisms, personality, recollections, feelings, beliefs, attitudes and values — into a central database that will be carried onboard the starship. Presented at the 100 Year Starship (100YSS) 2012 Public Symposium Sept. 13–16, 2012 in Houston.

In 1985 We Are the World, the first-ever multi-platinum single, got tens of millions of people singing “There is a choice we’re making; we’re saving our own lives.” [1]. These words may never apply to a project more meaningfully than to the 100 Year Starship (100YSS), intended to “make the capability of human travel beyond our solar system to another star a reality over the next 100 years.”.

Digital size of a person

Research from several groups show that a digital file of a person’s mannerisms, personality, recollections, feelings, beliefs, attitudes and values can be represented by less than one terabyte (1TB) of structured information [2] [3] [4] [5]. This is because a limited number, n, of human universals, m, yield millions of unique human combinations via (n!)/(m!*(n-m)!).

Add to this a few gigabytes of unique memories and you can account for the billions of diverse human mindsets, notwithstanding a very modest toolkit of building block characteristics.

For example, a megabyte of information about one’s daily experiences amounts to under 20 GB of information in 50 years. That daily megabyte is adequate to handle all of one’s tweets, texts and emails plus some compressed photos, audio and video. Combined with structured answers to personality inventories [5] and socio-cultural contextual information, a TB is ample space to provide a comprehensive digital reflection of your consciousness, known as a “mindfile.” The vast majority of information we store is redundant.

Websites exist that collect video streaming of an individual’s daily interactions. While such video streams can rapidly exceed many terabytes in volume, they far exceed the amount of information needed to accurately reflect a person’s mannerisms, personality, recollections, feelings, beliefs, attitudes and values. Advanced versions of pattern recognition software will be able to abstract from such continuous digital records such information as uniquely contributes to a mindfile. These pattern recognition based-abstracts are unlikely to require more than a TB of storage, especially when intelligently structured.

Digital size of all human mindfiles — the “Human Sapienome”

Digital memory of approximately 10²² bytes, the size of all human mindfiles in aggregate, what should be called the human “sapienome,” will be available within 20 years at less than 1% of the likely weight and cost of the 100 YSS. Ten billion people, times one trillion bytes, yields 10²² bytes.

Daedalus starship (credit: David Hardy)

The Project Daedelus starship, either in its original British Interplanetary Society version or in subsequent self-replicating conceptualizations, had a payload mass of on the order of 500 tons [6]. Orion Starship designs of Freeman Dyson had estimated costs ranging from a tenth 10% to 100% of 1968 US GNP [7].

The past five decades of relatively steady, 18-month doubling rates in constant cost for digital memory is not expected to change over the coming decades, due to economic demand, competition and the availability of three-dimensional traditional and novel computing substrates [8].

Hence, by exponential growth, today’s terabyte of memory will become a giga-terabyte of memory in 45 years. Ten such memory modules would hold a ten billion person human sapienome at that time. Alternatively, a few thousand mega-terabyte modules could contain the human sapienome about 30 years from now.

A terabyte today costs around $100 and weighs about 0.5 kg. These numbers are not significantly different from lesser amounts of memory in years past, and are considered by Ray Kurzweil to remain constant or shrink with exponential growth [8]. Hence, 45 years from now, the mass and cost of the human sapienome on a 100YSS would be insignificant. Even 30 years from now, the mass would be a few thousand pounds and the cost about $1 million. This represents less than 1% of the mass and cost of the starship.

Lifenaut members (credit: LifeNaut)

Universal access to information technology needed to create a mindfile is at hand. Already three-fourths of the world’s population has a mobile phone, about one-fourth of which are smartphones capable of full mindfile creation capabilities.

Specialized websites to create mindfiles, such as LifeNaut.com and CyBeRev.org, as well as more generic websites that can also be used to create mindfiles, such as Google+ and Facebook, are free to the public.

Virtually every human being will be able to freely create a mindfile, as smartphone ownership becomes all-but universal over the next decade (with shared access to one for individuals in deep poverty). Hence, there are neither economic nor technological barriers to the creation of a human sapienome.

(Credit: CyBeRev.org)

Activation of mindfiles with consciousness operating system software, or “mindware”

It may well be feasible to activate the individual mindfiles within the sapienome with consciousness operating system software, known as “mindware.” This would enable all participating members of the human race to be digitally present, via software agent extensions of themselves, and interfaced with sensors upon arrival at the 100 YSS destination.

However, even if such mindware activation is not possible, the entire human race can still be conceptually — and in a sense spiritually and philosophically — “present” at the interstellar destination by virtue of their mindfiles being present onboard the starship.

As noted above, dozens (n) of mannerism, personality and feeling types (m) yield many thousands of unique human combinations via (n!)/(m!*(n-m)!).

Once you add to these thousands of personality and worldview templates differential recollections, beliefs, attitudes and values (within the terabyte of mindfile information), there are many billions of unique possible combinations of human psyches, one of which will be a best-match for digitally stored mindfiles of each 100YSS participating biological person.

Mindware best fits one of the “m” compound mannerisms, personality and feeling types to that analyzed from stored mindfiles, and then populates it with the recollections, beliefs, attitudes and values evident from that stored mindfile. These combinations and correlations can be accomplished with software that needs be nowhere near the complexity of synaptic connectivity of the human brain, and yet still appears as true to the original person as to persuade others, and their digital self, that the same personal identity is present, albeit via a digital extension.

In the last century people became accustomed to the notion that electro-acoustic waves via telephony represented a biological original person. In the coming century, an analogous association is likely with digital simulacra of unique conscious minds.

Downloading into bodies… WOW (credit: Twentieth Century Fox)

To be clear, it is not expected that all of the code for a person’s patterns of mindedness would be line-by-line coded. Instead, the mindware, or mind operating system, will be learning software [9].

It will designed to seek out and adopt or “auto-tune” to idiosyncratic data and patterns in each participant’s mindfile in accordance with fundamental pre-programmed universal patterns of human thought and socio-economically specific cultural knowledge.

Iterative internal quality assurance cycles will result in revisions until a stopping point is reached based on matches to pre-set parameters between the learned software-mind and all material elements of its biological precursor as reflected in the mindfile.

Cyberconsciousness can be OK, says Martine Rothblatt’s avatar in Second Life (credit: Martine Rothblatt)

Self-awareness functionality will be activated once cyberconsciousness health and safety checks are complete.

Digital environments such as future iterations of Second Life will accommodate the social needs of digitally conscious humans.

Growth rates in software sophistication, even if less impressive than hardware efficiency, are nevertheless impressively compounding [10]. While it is not expected that such mindware will be available prior to the launch of the 100YSS, it could be transmitted to the starship in a series of software updates, gradually awakening ever more of the mindfiles, in accordance with their informed consent, as expressed upon participation in the Human Sapienome Project.

Socioeconomic research on project ownership

Socioeconomic research is presented in the paper showing that a sense of personal ownership in a project is a major element in determining the support of an individual or a group for the costs of a project. Hence, the We Are the World sub-project helps to enhance the size and durability of public funding for the 100 YSS.

En-route software updates at the speed of light (credit: NASA)

Participatory development has been shown to enhance project success, provided that individuals have a meaningful opportunity to engage with a project that may be of benefit to them [11] [12]. For example, merely completing an informational questionnaire about blood donation increased the rate of blood donation from under 1% to over 85% among a sample of college students in India [13] There is a robust literature demonstrating increased citizen willingness to pay taxes for which the citizens have meaningfully participated in the tax budgeting process [14].

It is not obvious how the lay public can participate meaningfully in the highly complex undertaking of an interstellar starship. Yet, due to the very high cost of the venture, and its long duration, public support is essential.

The solution to this dilemma can be found in the field of participatory project development and ownership. By giving the public a feel that they “own” the 100YSS project, the socioeconomic research cited above, and many concordant studies, strongly indicates the public will be much more willing, and for a much longer period of time, to support 100YSS costs from public treasuries.

Human Sapienome Project, complement to the 100YSS (credit: Photo Wall)

This paper proposes giving the public ownership of the 100YSS via a “We Are the World” human sapienome project. It will be explained to the public that a grass-roots organization called “We Are the World” has been formed to help transcend war and conflict by collecting the life experiences of every human willing to participate into a massive database similar to Facebook and Google+, but not-for-profit.

The project helps to transcend war and conflict because the database’s social networking features will enable everyone to better experience the perspectives of diverse peoples they may not meet face-to-face. The project will also help to transcend war and conflict by opening itself to social scientists who may study the database — which will scientifically be known as the Human Sapienome Project — for insights into how to better organize societies for harmonious cooperation.

Finally, the project has a quantitative goal — to include the mindfiles of 10 billion human beings, living or passed, and to store them as the real passengers, on an interstellar starship, within 100 years. The We Are the World Project is at once a scientific project, a participatory development project and an ark project, depending upon one’s perspective.

Human Sapienome Project and its freemium potential to help support the 100YSS (credit: Martine Rothblatt)

We Are the World as a 100YSS freemium venture

The We Are the World structure will serve as a platform for “freemium” offerings that in many other endeavors have shown significant abilities to generate revenue. Some of the wide variety of income opportunities that arise from the 100 YSS unique hosting of what could be one of the largest databases of individual psycho-social information are:

• Individuals choosing to pay for digital and database functionality beyond the hosting of their mindfile and the ability to interact with other mindfiles;
• Organizations willing to pay for anonymous but demographically tagged information from participants in the Human Sapienome Project;
• Sponsorship fees from organizations that wish to be known as sponsors of the Human Sapienome Project or the We Are the World website;
• Licensing fees from software, firmware and hardware advancements that emanate from the development and growth of the We Are the World and Human Sapienome Projects.

The intrinsic freemium and extrinsic negotiated revenues that flow from these projects will go to supporting the long-term costs of the 100YSS organization. A special focus of these revenues should be an unceasing education and outreach effort to achieve the quantitative goal of 10 billion mindfiles within 100 years safely stored onboard an interstellar starship. In this way, the project becomes a self-fulfilling prophecy.

As ever more people deposit mindfiles with what is known as either the Human Sapienome Project or the We Are the World Project, they are in a very real sense voting with their digital souls for the success of a 100YSS. This will help to give the project greater momentum during a century-long design and build period, plus the interstellar transit period that follows.

Every individual can feel a sense of ownership because their digital self will be on board the starship. Furthermore, there is a realistic hope that with a century of software development, that digital self will be able to actually experience the thrill of taking footsteps amidst the stars.

References

1. Jet, April 8, 1985 pp 60-64. The song was written predominantly by Michael Jackson, with help from Lionel Ritchie, at the suggestion and with the production of Quincy Jones. The process began as an idea of Harry Belafonte.

2. Brown, D., “Human Universals,” McGraw Hill, New York NY, 1991.

3. Costa, P.T. and McCrae, R. R., “Personality In Adulthood,” Guildford Press, New York NY, 1990.

4. Landauer, T., “How much do people remember? Some estimates of the quantity of learned information in long-term memory,” Cognitive Science 10, 4 (1986) pp. 477-493.

5. Bainbridge, W., “Massive Questionnaires for Personality Capture,” Social Science Computer Review 21, 3 (2003) pp. 267-280.

6. Grant, T.J. 1978 “Project Daedalus: An Engineering Assessment,” Journal of the British Interplanetary Society Supplement, S180, S187 (1978)

7. Dyson, F., “Interstellar Transport,” Physics Today, October 1968, pp. 41-45

8. Kurzweil, R., “The Singularity Is Near: When Humans Transcend Biology,” Viking, New York NY, 2005, pp. 75-77

9. Bock, P., “The Emergence of Artificial Cognition: An Introduction to Collective Learning,” World Scientific, New Jersey, 1993 p. 52.

10. Vinge, V., “Signs of the Singularity,” IEEE Spectrum 45, 6 (2008) pp. 77-79.

11. Sen, A., “Rationality and Freedom”, Harvard Belknap Press, Cambridge MA, 2002.

12. Sen, A., “Development as Freedom,” Oxford University Press, Oxford UK, 1999.

13. Bharatwaj, R.S. , “A Descriptive Study of Knowledge, Attitude and Practice with Regard To Voluntary Blood Donation Among Medical Undergraduate Students In Pondicherry, India,” Journal of Clinical and Diagnostic Research 6, 602-604.
http://www.jcdr.net/articles/pdf/2145/14%20-%203715.pdf

14. Ebdon, C., “Citizen Participation in Budgeting Theory,” Public Administration Review, May/June 2006.

Albert Einstein

Ray,

I just finished reading How to Create a Mind. I found it both interesting and informative. At the end, I believe that there is an inherent difference between a human brain and an AI system, a difference that can’t be overcome by any amount of added speed and capacity. To illustrate this difference I have included a thought experiment:

Take the most powerful artificial brain in existence. Include all programs necessary to make it function as an independent, self-conscious entity. Let it read everything in existence up to, but not beyond, the birth of Albert Einstein.

With no further human intervention of any kind, how long do you think it will take this artificial brain to develop the theory of relativity?

Feel free to use the artificial intelligence capability you think will exist in 2029; but, again, limiting the knowledge input to that which was available to Einstein.

It is my belief that the actual human brain is sufficiently different from an artificial intelligence system that without any human intervention this theory would never be forthcoming. If you believe otherwise, I would be interested in seeing the process modeled.

Again, since the artificial intelligence system is a self-conscious entity, presumably capable of self-direction, I would expect no human intervention whatsoever in this process.

— Bob Caine

Bob,

Interesting point but keep in mind that all — biological — human brains at the time (except for Einstein’s) did not come up with relativity either.

Einstein’s brain was ahead of the curve, but nonbiological intelligence will continue to improve both in hardware and software (algorithmically) past 2029.

So perhaps it is the AI of 2035 or 2040 who would be able to come up with relativity in your thoughtful thought experiment.

— Ray Kurzweil

My point in using Einstein’s Theory of Relativity in my thought experiment on AI equivalence to the human brain was not related to whether or not Einstein had the support of others or how exceptional his mind was.

Rather, it had to do with the ability of an AI system to have a “sense of purpose” of its own without human intervention. My question had to do with how an AI system would decide, without human assistance, that there is any reason to want to know the exact relationship between matter and energy; the relationship between the speed of light and the relative motion of those observing that light; or, for that matter, the relationship between the cosmic microwave background and the Big Bang.

Given the task, I can readily see the role an AI system could play in deriving a solution. But how would it decide on its own that studies such as these should even be undertaken and then design, execute, and assess the related research to arrive at a verifiable theory?

— Bob Caine

MOMS

We recently got a note from Evan Younger, vocalist/bassist for Brooklyn-based orchestral rockers Miracles of Modern Science mentioning a single he wrote, “The Singularity.” How could I resist? I punched up the podcast link.

Yes! Very nice! Powerful lyrics that definitely get it, and the music combines the richness and intelligence of acoustic strings with the energy of a rock beat. Accelerates my thinking. I have to say it’s the most inspiring music I’ve heard in a long time. So what was the back story? Younger explained in a followup note.

“In 2011 I shared a house with our band’s mandolinist. One night I was browsing his bookshelf for bedtime reading, and his copy of The Singularity Is Near caught my eye. Not knowing what to expect, I started to read and was immediately spellbound. Despite my useless arts and literature background, I wanted to become a part of the movement.

“So I immersed myself in AI literature and even started an intensive crash course in computer science (via MIT OCW, the inaugural Udacity courses with Sebastian Thrun and David Evans, and this awesome book).

“I actually made myself a little crazy on our band’s subsequent national tour: every day I’d drive 8–12 hours, play a show, do coding assignments all night, and then get up to do it again. My pace of learning eventually slowed as MOMS got back to writing songs for a new album, but I remained enraptured with Singularitarian ideas.”

Younger said he poured all his excitement and optimism into the lyrics for “The Singularity,” a new single that is also featured on the group’s upcoming EP, MEEMS (more below — preorder here).

“I hope that the song’s optimistic message resonates with Singularitarians and perhaps inspires unfamiliar listeners to learn more about Kurzweil, AI, and the Singularity.”

Lyrics

MOMS

By the time that we all go deaf, I know that we’ll find a cure for it, yeah

People say that we’ll die someday, but we just don’t believe it
Long before we are old and gray, we’ll find a way to beat it
Fight against physical decay, keep our bodies breathing
By the next quarter century we won’t even need them

So shoot the supplements into our veins so we can reprogram our genes
And let the nanobots swim through our brains to keep our neurons sharp and clean
There’s not a problem that we cannot solve with our technology
Just as long as we can stay alive until the singularity

Maybe you think we’re mental
But if you doubt anything we say, check out our man’s credentials
Our evolution is underway, and it’s exponential
There’s no reason to be afraid

We’ll shoot the supplements into our veins so we can reprogram our genes
And let the nanobots swim through our brains to keep our neurons sharp and clean
And we will all transcend biology and merge with our machines
Just as long as we can stay alive until the singularity

So play it loud, turn up the kick
Cause by the time that we lose our hearing, we’ll have a fix for it
So play it loud, crank it up to ten
Cause by the time that our ears are broken, we’ll have no use for them

From MEEMS, released 19 February 2013

Miracles of Modern Science upcoming EP, MEEMS

MOMS

Orchestral rockers Miracles of Modern Science’s upcoming EP, MEEMS, will be available February 19, 2013. The release will be followed by Miracles of Modern Science’s largest national tour to date, including stops at the 2013 SXSW Music Festival.

Miracles of Modern Science are a string section in mutiny: guitars overboard! The Brooklyn, NY band squeezes together classical textures, disco kinetics, and explosive dynamics you might file under “post-rock” if their instruments weren’t decidedly pre-rock.

The band began at Princeton University, where vocalist/double bassist Evan Younger and mandolinist Josh Hirshfeld shared a hall their freshman year. Feeling out of place at a school where cover bands and Top 40 DJs dominated the nightlife, they hijacked open mics with off-kilter acoustic collaborations.

They found kindred spirits in other restless musicians from the school’s orchestras and jazz bands: conductor-by-day cellist Geoff McDonald, Aussie violinist Kieran Ledwidge, and finally drummer Tyler Pines, who spurred them to plug their miniature orchestra into amps.

Since then, MOMS have been uniting crowds of discerning musicians and dancing party-goers alike through their brand of orchestral rock.

MOMS’ 2011 debut LP Dog Year earned raves from NPR and Paste and ended up on year-end best-of lists for Wired and Beats Per Minute.

Their new followup EP, MEEMS, pushes the limits of their acoustic instruments even further, ending up both crazier and catchier than its predecessor. The result resembles pop music, but you can sense the band ripping apart and rearranging its underlying mechanics like mad scientists.

“Miracles of Modern Science play consummate major-key space-pop that sounds like something new,” says Wired.

Tracklist

1. Ahem
2. Dear Pressure
3. Breather
4. Don’t You See?
5. The Singularity
6. Physics Is Our Business

Tour Dates

Feb 21 – New York, NY – MEEMS release party @ The Studio at Webster Hall (tickets)
Mar 6 – Washington, DC – 9th and Beats (tickets)
Mar 7 – Charlottesville, VA – The Southern (tickets)
Mar 8 – Durham, NC – The Garage @ Motorco Music Hall
Mar 9 – Athens, GA – Athens Slingshot Fest @ The World Famous
Mar 10 – Nashville, TN – Cause A Scene
Mar 11 – Hattiesburg, MS – The Thirsty Hippo
Mar 12-16 – Austin, TX – SXSW
Mar 19 – Phoenix, AZ – TBA
Mar 20 – San Diego, CA - TBA
Mar 22 – Los Angeles, CA – The Hotel Cafe (tickets)
Mar 23 – San Francisco, CA – Hotel Utah Saloon (tickets)
Mar 25 – Mountain View, VA – Googleplex
Mar 26 – Portland, OR – Bunk Bar
Mar 28 – Seattle, WA – The High Dive
Mar 29 – Boise, ID – Red Room
Mar 30 – Salt Lake City, UT - Kilby Court
Apr 1 – Denver, CO – The Walnut Room (tickets)
Apr 2 – Lawrence, KS – TBA
Apr 3 – Ames, IA – TBA
Apr 4 – Madison, WI – TBA
Apr 5 – Chicago, IL – TBA
Apr 6 – Pittsburgh, BA – TBA
Apr 7 – Philadelphia, PA - World Cafe Live

Bacteria that predominate in the human body (credit: National Human Genome Research Institute)

Did you know that foreign microoganisms outnumber our own cells by 10:1, and that we know almost nothing about how they affect our personal health?

Neither did I. But biotech startup µBiome, a UCSF Quantitative Biosciences Institute spinoff, hopes to fix all that by launching the world’s first citizen science effort to fully map the human “microbiome” (all the microbes in your body), using crowdsourced funding at indiegogo.

µBiome has raised an impressive $232,556 as of Wednesday night), but the project expires just before midnight Thursday Jan. 31.

I encourage you to check this out. (To deal with my own digestive problems, I just signed up for their $79 GI Microbiome kit — delivery: May 2013.)

The full microbiome analysis will be available with uBiome’s $1,337 Delta Five kit (credit: µBiome)

How to discover your microbiome

This may creep you out, but these microbes are all over your body — literally every inch of your skin and inside you.

However, these microbes are mostly not harmful, but rather are co-evolved symbionts, essential collaborators in our physiology, explains uBiome co-founder Jessica Richman, a Stanford grad and now DPhil student at Oxford University’s Internet Institute (also a c0-founder of the #pdftribute movement).

“Like the rainforest, the healthy human microbiome is a balanced ecosystem. Recent research suggests that the correct balance of microbes serves to keep potential pathogens in check and regulate the immune system. Microbes also perform essential functions such as digesting food and synthesizing vitamins.”

As we’ve noted on KurzweilAI (see Related links below), studies have linked the microbiome to human mood and behavior, as well as many gut disorders, eczema, and chronic sinusitis.

Escherichia coli, one of the many species of bacteria present in the human gut (credit: NIAID/NIH)

“We have two aims with µBiome,” said co-founder Zachary Apte, who has a PhD in biophysics from UCSF. “First, we want to make the science and the technology available to everyone. Now anyone can have their microbiome sequenced. Second, we want to curate the world’s largest microbiome dataset.

“Citizen science is the answer. If you’d told me even five years ago that high throughput sequencing technology would be in the hands of citizen scientists, I would have told you that you’d been watching way too many science fiction movies. Today, uBiome makes this dream a reality.”

µBiome will be using techniques from the NIH’s $173 million dollar Human Microbiome Project to find out what microbes are living in your body, compare you to others, and keep you up to date on research that applies to your data.

Five Things Your Microbiome Can Tell You

1. Obesity. Ley et al (2006) and others have identified gut microbes associated with obesity, such as Eubacterium rectale. In addition, Upadhyay et al (2012) did experiments with mouse models and suggested the possibility that the microbiome could be manipulated for weight control in the near future

2. Dietary composition. Wu et al (2011) found that gut enterotypes were strongly associated with long-term diets, particularly protein and animal fat (Bacteroides) versus carbohydrates (Prevotella).

3. Antibiotics. If you have recently taken antibiotics, your gut microflora may not yet have been replenished. Dethlefsen et al (2008) found that ciprofloxacin treatment influenced the abundance of about a third of the bacterial taxa in the gut. Similarly, Jernberg et al (2007) found that long after the selection pressure from a short antibiotic exposure has been removed, there are persistent long term impacts on the human intestinal microbiota that remain for up to two years post-treatment.

4. Allergies. Is your nasal microbiome associated with the profile of chronic sinusitis? Abreu et al (2012) found that multiple, phylogenetically distinct lactic acid bacteria were depleted concomitant with an increase in the relative abundance of a single species, Corynebacterium tuberculostearicum, in patients suffering from chronic sinusitis.

5. Bacterial vaginosis. If you have a penis, your microbiome may be correlated with bacterial vaginosis in women. Price et al (2010) found that two families found in certain penis microbiomes — Clostridiales Family XI and Prevotellaceae — have been previously associated with bacterial vaginosis. This may correspond to frequent infections in your partner.

DIY BioPrinter (credit: BioCurious/Instructables)

Bioprinting is printing with biological materials.

There’s a lot of work being done at research labs and big companies like Organovo on print human tissues and human organs, with an eye towards drug testing, and transplantation into humans.

Check out these amazing TED talks by Anthony Atala, for example:

Anthony Atala: Growing new organs
Anthony Atala: Printing a human kidney

The basic technologies are very accessible — based on inkjet and/or 3D printing. So a bunch of us at BioCurious decided we wanted to play around with this technology ourselves — and the BioPrinter Community Project was born! (Come join us, every Thursday evening at BioCurious!)

We wrote this instructable in part to document our project for our fellow Citizen Scientists in the DIYbio community. For a quick 1-minute intro, you may want to check this little video.”

(Read more on Instructables)

Aaron Swartz in 2012 protesting against Stop Online Piracy Act (SOPA) (credit: Daniel J. Sieradski/Wikimedia Commons)

If you are a scientist, you can pay the best and most effective tribute to the memory of Aaron Swartz by sharing PDFs of your published work on pdftribute.net via the hashtag #pdftribute on Twitter.

Researchers are now offering open-access versions of their work using this hashtag.

I also suggest to boycott the pay-walled journals of the science mafia and publish on arXiv, or one of the many excellent open access science journals like PLoS and eLife. Hit them in the wallet where it hurts; it is the only effective way to protest.

New Scientist | Hundreds of researchers have been sharing PDFs of their work on Twitter as a tribute to Aaron Swartz, the internet freedom activist who committed suicide on Friday.

Swartz was facing hacking charges from the U.S. government after accessing the network of the Massachusetts Institute of Technology and downloading nearly 5 million articles from the digital library JSTOR.

In a statement following his death, Swartz’s parents criticized the Massachusetts U.S. attorney’s office for pursuing charges against their son, and MIT for failing to support him. [NOTE: see also Time | Aaron Swartz’s Suicide Prompts MIT Soul-Searching.]

Tim Berners-Lee, inventor of the world wide web, tweeted his own tribute: “Aaron dead. World wanderers, we have lost a wise elder. Hackers for right, we are one down. Parents all, we have lost a child. Let us weep.”

Update Jan. 15, 2013: ars technica | On Monday afternoon, a group of online archivists released the “Aaron Swartz Memorial JSTOR Liberator.” The initiative is a JavaScript-based bookmarklet that lets Internet users “liberate” an article, already in the public domain, from the online academic archive JSTOR. By running the script — which is limited to once per browser — a public domain academic article is downloaded to the user’s computer, then uploaded back to ArchiveTeam in a small act of protest against JSTOR’s restrictive policies.

Yeah, like all the time — especially because my calls come in via Skype so callers often get a blast of a YouTube video or Spotify song, so I …

Uh, OK, but how does it work?

Cool, so how do I get it?

“We are so excited and pleased to release a new version [of Flutter] that allows you to control music & videos in Google Chrome using gestures — just in time for the holiday season. Flutter now supports YouTube, Pandora, Grooveshark & Netflix. We will be updating AppStore version in early 2013. For now direct download the new version.”

Nice, I thank you, my callers will thank you!

Artwork: The bright star Alpha Centauri and its surroundings (credit: ESO)

The awesome 100 Year Starship (100YSS) initiative by DARPA and NASA proposes to send people to the stars by the year 2100 — a huge challenge that will require bold, visionary, out-of-the-box thinking.

There are major challenges. “Using current propulsion technology, travel to a nearby star (such as our closest star system, Alpha Centauri, at 4.37 light years from the Sun, which also has a a planet with about the mass of the Earth orbiting it) would take close to 100,000 years,” according to Icarus Interstellar, which has teamed with the Dorothy Jemison Foundation for Excellence and the Foundation for Enterprise Development to manage the project.

“To make the trip on timescales of a human lifetime, the rocket needs to travel much faster than current probes, at least 5% the speed of light. … It’s actually physically impossible to do this using chemical rockets, since you’d need more fuel than exists in the known universe,” Icarus Interstellar points out.

Daedalus concept (credit: Adrian Mann)

So the Icarus team has chosen a fusion-based propulsion design for Project Icarus, offering a million times more energy compared to chemical reactions. It would be evolved from their Daedalus design.

This propulsion technology is not yet well developed, and there are serious problems, such as the need for heavy neutron shields and risks of interstellar dust impacts, equivalent to small nuclear explosions on the craft’s skin, as the Icarus team states.

Although Einstein’s fundamental speed-of-light limit seems solid, ways to work around it were also proposed by physicists at the recent 100 Year Starship Symposium.

However, as a reality check, I will assume as a worse case that none of these exotic propulsion breakthroughs will be developed in this century.

That leaves us with an unmanned craft, but for that, as Icarus Interstellar points out, “one needs a large amount of system autonomy and redundancy. If the craft travels five light years from Earth, for example, it means that any message informing mission control of some kind of system error would take five years to reach the scientists, and another five years for a solution to be received.

“Ten years is really too long to wait, so the craft needs a highly capable artificial intelligence, so that it can figure out solutions to problems with a high degree of autonomy.”

If a technological Singularity happens, all bets are off. However, again as a worse case, I assume here that a Singularity does not happen, or fully simulating an astronaut does not happen. So human monitoring and control will still be needed.

The mind-uploading solution

The very high cost of a crewed space mission comes from the need to ensure the survival and safety of the humans on-board and the need to travel at extremely high speeds to ensure it’s done within a human lifetime.

One way to  overcome that is to do without the wetware bodies of the crew, and send only their minds to the stars — their “software” — uploaded to advanced circuitry, augmented by AI subsystems in the starship’s processing system.

The basic idea of uploading is to “take a particular brain [of an astronaut, in this case], scan its structure in detail, and construct a software model of it that is so faithful to the original that, when run on appropriate hardware, it will behave in essentially the same way as the original brain,” as Oxford University’s Whole Brain Emulation Roadmap explains.

It’s also known as “whole brain emulation” and “substrate-independent minds” — the astronaut’s memories, thoughts, feelings, personality, and “self” would be copied to an alternative processing substrate — such as a digital, analog, or quantum computer.

An e-crew — a crew of human uploads implemented in solid-state electronic circuitry — will not require air, water, food, medical care, or radiation shielding, and may be able to withstand extreme acceleration. So the size and weight of the starship will be dramatically reduced.

Combined advances in neuroscience and computer science suggest that mind uploading technology could be developed in this century, as noted in a recent Special Issue on Mind Uploading of the International Journal of Machine Consciousness).

Uploading research is politically incorrect: it is tainted by association with transhumanists — those fringe lunatics of the Rapture of the Nerds — so it’s often difficult to justify and defend.

The connectome (credit: NIH Human Connectome Project)

Creating a brain

But MIT neuroscientist Sebastian Seung has speculated that if models of brains become increasingly accurate, eventually there must be a simulation indistinguishable from the original.

In Connectome: How the Brain’s Wiring Makes Us Who We Are, he explains how mapping the human “connectome” (the connections between our brain cells) might enable us to upload our brains into a computer.

In fact, “neuroscience is ready for a large-scale functional mapping of the entire neural circuits,” Harvard scientist George Church and other researchers conclude in a landmark 2012 Neuron paper.

I suggest that developing mind-uploading technology for software e-crews may make the 100YSS project practical, while delivering equally important spinoffs in neuroscience, computer science, and longevity, perhaps even including indefinite life extension.

The new brain can be much more resistant and long-lived than the old biological brain, and it can be housed in a similarly resistant and long-lived robotic body. Robots powered by human uploads can be rugged, resistant to the vacuum and the harsh space environment, easily rechargeable, and much smaller and lighter than wetware human bodies.

Eventually, human uploads augmented by AI subsystems can be implemented in the solid-state circuitry of the starship’s processing system.

Boredom and isolation will not be a problem for e-crew members, because the data processing system of a miniaturized starship will be able to accommodate hundreds and even thousands of human uploads.

Light sails

Light sail concept (credit: NASA)

The huge reduction in weight resulting from uploading would allow for radical propulsion systems, such as “light sails” (aka “solar sails”) — spacecraft driven by light energy alone. The Planetary Society currently has a research project to develop light sails .

The low mass of light sails — combined with the e-crew’s ability to withstand extreme acceleration — might allow for achieving a substantial fraction of the speed of light, so the time to go to the stars would be significantly reduced.

E-crewed interstellar missions have been described by science fiction writers. Greg Egan was one of first in Diaspora. In Charlie Stross‘ Accelerando, the coke-can-sized starship Field Circus, propelled by a Jupiter-based laser and a light sail, visits a nearby star system with an e-crew of 63 uploaded persons who have a hell of a lot of fun on the way.

Here we are, sixty something human minds. We’ve been migrated — while still awake — right out of our own heads using an amazing combination of nanotechnology and electron spin resonance mapping, and we’re now running as software in an operating system designed to virtualize multiple physics models and provide a simulation of reality that doesn’t let us go mad from sensory deprivation!

And this whole package is about the size of a fingertip, crammed into a starship the size of your grandmother’s old Walkman, in orbit around a brown dwarf just over three light-years from home.

Of course. a light sail powered by lasers back home, can only push a starship on an one-way trip,but the data from the uploaded astronauts would will be beamed home via the Interplanetary Internet.

The “starwisp” concept proposed by Robert L. Forward is a variation of a light sail remotely driven by a microwave beam instead of visible light (but has known problems).

Sideloading

One problem with implementing mind uploading is that it’s plagued by metaphysical discussions about the continuity of personal identity (“is only a copy”), which are irrelevant here. Even if I thought that uploads will be only copies, I would be not only happy, but also grateful and honored if my upload copy could participate in the first interstellar mission.

But even coarse, preliminary uploading technology could be sufficient. “Sideloading,” proposed by science fiction writer Greg Egan in Zendegi, is the process of training a neural network to mimic a particular organic brain, using a rich set of non-invasive scans of the brain in action.

Egan describes a “Human Connectome Project,” completed in the late 2020s, that produces detailed connectome maps from brain scans of thousands of volunteers. The maps could be used to build an average human neural network, which could serve as a model of a generic human brain.

Then the model could be tweaked and fine-tuned to emulate a specific living person, using in-vivo brain scans and supervised training sessions in a VR environment. In Zendegi, the resulting personalized model passes the Turing Test and often behaves as a convincing emulation of the original.

Why not send AI’s?

If strong AI is developed, perhaps smarter than humans, why should we bother to upload humans? One answer is that most of us will want human minds on our first journey to the stars.

However, I agree with Ray Kurzweil’s speculation that we will merge with technology, so many future persons will not be “pure” humans or pure AIs, but rather hybrids, blended so tightly that it will be impossible to tell which is which.

Ultimately, I think space will not be colonized by squishy, frail and short-lived flesh-and-blood humans. As Sir Arthur C. Clarke wrote in Childhood’s End, perhaps “the stars are not for Man” — that is, not for biological humans 1.0.

It will be up to our postbiological mind children, implemented as pure software based on human uploads and AI subsystems, to explore other stars and colonize the universe. Eventually, they will travel between the stars as radiation and light beams.

AA: In several contests and machine-learning benchmarks, your team’s NNs are now outperforming all other known methods. As The New York Times noted Friday, last year, a program your team created won a pattern recognition contest by outperforming both competing software systems and a human expert in identifying images in a database of German traffic signs.

The German Traffic Sign Benchmark (credit: Institut für Neuroinformatik, Bochum)

“The winning program accurately identified 99.46 percent of the images in a set of 50,000; the top score in a group of 32 human participants was 99.22 percent, and the average for the humans was 98.84 percent,” the Times pointed out. Impressive. What is the importance of traffic sign recognition in this field?

Don’t try this on the 101: In 1995, Ernst Dickmanns’ famous S-class car autonomously drove 1678 km on public Autobahns from Munich to Denmark and back, up to 158 km without human intervention, at up to 180 km/h (112.5 mph), automatically passing other cars. (Credit: Ernst Dickmanns)

JS: That was from the IJCNN 2011 Traffic Sign Recognition Competition. This is highly relevant for self-driving cars as well as modern systems for driver’s assistance.

BTW, if you don’t obey a traffic sign in Switzerland,  you go to jail. However, across the border there is Italy. There you’ll also find traffic signs in the street, but only for decoration. :)

AA: What’s your team’s secret?

JS: Remarkably, we do not need the traditional sophisticated computer vision techniques developed over the past six decades or so. Instead, our deep, biologically rather plausible artificial neural networks (NNs) are inspired by human brains, and they learn to recognize objects from numerous training examples.

I discuss this in detail in a talk at AGI-2011, “Fast Deep/Recurrent Nets for AGI Vision” (only voice and slides though):

We often use supervised, artificial, feedforward, or recurrent (deep by nature) NNs with many nonlinear processing stages. When we started this type of research over 20 years ago, it quickly became clear that such deep NNs are hard to train. This is due to the so-called “vanishing gradient problem” identified in the 1991 thesis of my former student Sepp Hochreiter, who is now a professor in Linz. But over time we found several ways around this problem. Committees of NNs improve the results even further.

LSTM-controlled multi-arm robot learns how to tie a knot. The recurrent neural network memory is necessary to deal with ambiguous sensory inputs from repetitively visited states. (Credit: H. Mayer, F. Gomez, D. Wierstra, I. Nagy, A. Knoll, J. Schmidhuber/TU Munich & IDSIA)

In addition, we use GPUs (graphics cards), which are essential to accelerate learning by a factor of 50. This is sufficient to clearly outperform numerous previous more complex machine learning methods.

One of the reviewers called this a “wake-up call to the machine learning community.”

For sequential data, such as videos or connected handwriting, feedforward NNs do not suffice. Here, we use our bidirectional or multi-dimensional Long Sort-Term Memory recurrent NNs, which learn to maximize the probabilities of label sequences, given raw training sequences.

AA: You said that the field is currently experiencing a Neural Network “ReNNaissance.” What are the key awards your team has won?

JS: In the past three years, in addition to the IJCNN 2011 Traffic Sign Recognition Competition mentioned above, they won seven other highly competitive international visual pattern recognition contests:

• ICPR 2012 Contest on “Mitosis Detection in Breast Cancer Histological Images.” This is important for breast cancer prognosis. Humans tend to find it very difficult to distinguish mitosis from other tissue. 129 companies, research institutes, and universities in 40 countries registered; 14 sent their results. Our NN won by a comfortable margin.
  

  Telophase stage of mitosis in a eukaryotic cell (credit: Catherine Genestie Hopital de la Pitie-Salpetriere, Paris)

• ISBI 2012 challenge on segmentation of neuronal structures. Given electron microscopy images of stacks of thin slices of animal brains, the goal is to build a detailed 3D model of the brain’s neurons and dendrites. But human experts need many hours to annotate the images: Which parts depict neuronal membranes? Which parts are irrelevant background? Our NNs learn to solve this task through experience with millions of training images. In March 2012, they won the contest on all three evaluation metrics by a large margin, with superhuman performance in terms of pixel error. (Ranks 2–6: for researchers at ETHZ, MIT, CMU, Harvard.) A NIPS 2012 paper on this is coming up.
  

  Example of ssTEM neuronal image and its corresponding segmentation (credit: IEEE International Symposium on Biomedical Imaging and Albert Cardona et al./PLoS Biology)

• ICDAR 2011Offline Chinese Handwriting Competition. Our team won the competition although none of its members speaks a word of Chinese. In the not-so-distant future you should be able to point your cell phone camera to text in a foreign language, and get a translation. That’s why we also developed low-power implementations of our NNs for cell phone chips.
  

  Our team also just won the ICDAR Offline Chinese Handwriting Competition (1st & 2nd place), without speaking a word of Chinese (credit: D. C. Ciresan, U. Meier, L. M. Gambardella, J. Schmidhuber)

• Online German Traffic Sign Recognition Contest (2011, first and second rank). Until the last day of the competition, we thought we had a comfortable lead, but then our toughest competitor from NYU surged ahead, and our team (with Dan Ciresan, Ueli Meier, Jonathan Masci) had to work late-night to re-establish the correct order. :)
• ICDAR 2009 Arabic Connected Handwriting Competition (although none of us speaks a word of Arabic).
• ICDAR 2009 Handwritten Farsi/Arabic Character Recognition Competition (idem).
• ICDAR 2009 French Connected Handwriting Competition. Our French also isn’t that good. :)

AA: Is that a record for international contests?

JS: Yes. Our NNs also set records in important machine-learning benchmarks:

• The NORB Object Recognition Benchmark.
• The CIFAR Image Classification Benchmark.
• The MNIST Handwritten Digits Benchmark, perhaps the most famous benchmark. Our team achieved the first human-competitive result.

AA: Were the algorithms of your group the first deep learning methods to win such international contests?

JS: I think so.

AA: Did any other group win that many?

JS: No. All of this would not have been possible without the hard work of team members including Alex Graves, Dan Ciresan, Ueli Meier, Jonathan Masci, Alessandro Giusti, and others. And of course, our work builds on earlier work by great pioneers including Fukushima, Amari, Werbos, von der Malsburg, LeCun, Poggio, Hinton, Williams, Rumelhart, and many others.

AA: What are some of the practical applications of these techniques?

JS: These NNs are of great practical relevance, because computer vision and pattern recognition are becoming essential for thousands of commercial applications. For example, the future of search engines lies in image and video recognition, as opposed to traditional text search. The most important applications may be in medical imaging, e.g., for automated melanoma detection, cancer prognosis, plaque detection in CT heart scans (to prevent strokes), and hundreds of other health-related areas.

Autonomous robots depend on vision, too — see the AGI 2011 keynote (at Google HQ) by the robot car pioneer Ernst Dickmanns:

Our successes have also attracted the interest of major industrial companies. So we started several industry collaborations. Among other things, we developed:

• State-of-the-art handwriting recognition for a software company.
• State-of-the-art steel defect detection for the world’s largest steel maker.
• State-of-the-art low-power, low-cost pattern recognition for a leading automotive supplier.
• Efficient variants of our neural net pattern recognizers for apps running on cell phone chips.

More information on this can be found here and here.

Generally speaking, there is no end in sight for applications of these new-millennium neural networks.

AA: How do your team’s techniques differ from Google, Microsoft, and Nuance approaches to automated speech and image recognition?

JS: Of course I cannot officially speak for any particular firm. Let me just say that in recent years leading IT companies (whose names are known by everybody) have shown a lot of interest in our work. Many companies (and academic researchers) are now using the deep learning neural networks we developed and published over the years.

AA: What are your team’s future research plans?

JS: While the methods above work fine in many applications, they are passive learners — they do not learn to actively search for the most informative image parts. Humans, in contrast, use sequential gaze shifts for pattern recognition. This can be much more efficient than the fully parallel one-shot approach.

That’s why we want to combine the algorithms above with variants of our old method of the 1990. Back then, we built what to our knowledge was the first artificial fovea sequentially steered by a learning neural controller.

We also intend to combine this with our Formal Theory of Fun (FTF) and Curiosity & Creativity (see here and here)

As an artificial explorer driven by the FTF interactions with its environment, it is rewarded not only for solving external, user-defined problems, but also for inventing its own novel problems (e.g., better prediction of aspects of the environment, speeding up or simplifying previous solutions), thus becoming a more and more general problem solver over time.

Here some of our video lectures on artificial creativity:

About Asimov’s “The Last Question” — I was captivated by Asimov’s story as a child, and again some 50 years later in reading Ray’s version of the answer in The Singularity Is Near.

Looking forward to getting his new book!

Thank you,
Ron Eckhardt

Dear Ronald,

Thanks. Yes, the evolution of intelligence runs counter to the second law.

Best,
Ray

Related:
short story | “The Last Question”
Wikipedia | second law of thermodynamics

About “The Last Question”

Wikipedia | “The Last Question” is a science fiction short story by Isaac Asimov. It first appeared in the November 1956 issue of Science Fiction Quarterly. It was Asimov’s favorite short story of his own authorship, and is one of a loosely connected series of stories concerning a fictional computer called Multivac.

SPOILER ALERT:

In conceiving Multivac, Asimov was extrapolating the trend towards centralization that characterized computation technology planning in the 1950s to an ultimate centrally managed global computer.

After seeing a planetarium adaptation, Asimov “privately” concluded that this story was his best science fiction yet written. ”The Last Question” ranks with “Nightfall” and other stories as one of Asimov’s best-known and most acclaimed short stories.

The story deals with the development of computers called Multivacs and their relationships with humanity through the courses of seven historic settings, beginning in 2061. In each of the first six scenes a different character presents the computer with the same question — namely, how the threat to human existence posed by the heat death of the universe can be averted.

The question was: “How can the net amount of entropy of the universe be massively decreased?” This is equivalent to asking: “Can the workings of the second law of thermodynamics (used in the story as the increase of the entropy of the universe) be reversed?”

Multivac’s only response after much “thinking” is: “INSUFFICIENT DATA FOR MEANINGFUL ANSWER.”

The story jumps forward in time into newer and newer eras of human and scientific development. In each of these eras someone decides to ask the ultimate “last question” regarding the reversal and decrease of entropy. Each time, in each new era, Multivac’s descendant is asked this question, and finds itself unable to solve the problem. Each time all it can answer is an (increasingly sophisticated, linguistically): “THERE IS AS YET INSUFFICIENT DATA FOR A MEANINGFUL ANSWER.”

In the last scene, the god-like descendant of humanity (the unified mental process of over a trillion, trillion, trillion humans that have spread throughout the universe) watches the stars flicker out, one by one, as the universe finally approaches the state of heat death. Humanity asks AC, Multivac’s ultimate descendant, which exists in hyperspace beyond the bounds of gravity or time, the entropy question one last time, before humanity merges with AC and disappears.

AC is still unable to answer, but continues to ponder the question even after space and time cease to exist. Eventually AC discovers the answer, but has nobody to report it to; the universe is already dead. It therefore decides to show the answer by demonstrating the reversal of entropy, creating the universe anew. The story ends with AC’s pronouncement — and AC said: “LET THERE BE LIGHT!” And there was light.

(Credit: NASA)

If so, you might want to read this before logging onto Facebook or Twitter after (or during) your Thanksgiving dinner.

Dr. Uri Nitzan of Tel Aviv University‘s Sackler Faculty of Medicine and the Shalvata Mental Health Care Center presented three in-depth case studies from his own practice linking psychotic episodes to computer-mediated communication (such as Facebook or chats), and they had those two specific things in common (and no prior major psychiatric disorder).

In each case, there was “gradual development and exacerbation of psychotic symptoms, including delusions, anxiety, confusion, and intensified use of computer communications.”

All three of Dr. Nitzan’s patients sought refuge from a lonely situation and found solace in intense virtual relationships. Although these relationships were positive at first, they eventually led to feelings of hurt, betrayal, and invasion of privacy, reports Dr. Nitzan.

“All of the patients developed psychotic symptoms related to the situation, including delusions regarding the person behind the screen and their connection through the computer,” he says.

They described a “hyperpersonal” relationship with a stranger, mistrust of the aims and identity of the other party, blurred self boundaries, misinterpretation of information, and undesirable personal exposure in cyberspace.

Two patients began to feel vulnerable as a result of sharing private information, and one even experienced tactile hallucinations, believing that the person beyond the screen was physically touching her.

The good news is that all of the patients, who willingly sought out treatment on their own, were able to make a full recovery with proper treatment and care, Dr. Nitzan says.

Factors that can contribute to a patient’s break with reality and the development of a psychotic state, he warns: the absence of non-verbal cues, and the tendency to idealize the person with whom someone is communicating, becoming intimate without ever meeting face-to-face.

(Yes, it’s only three cases, but Dr. Nitzan notes that further research is warranted to validate their hypothesis.)

Has Facebook (or other social media) driven you crazy? Confess in the computer-mediated communication below!

Single-chip cloud computer (credit: Intel)

Intel researchers are working on a 48-core processor for smartphones and tablets — making them many times more powerful than today’s desktop computers within the next five to ten years, reports Computerworld.

Intel is distributing 100 of the experimental 48-core chips so researchers can work on the advanced parallel-computing programming models and software need to support these cores.

Intel says it’s using a prototype of a ”single-chip cloud computer” to develop the chip.

Adding cores to processors is a power-efficient way of boosting chip performance, instead of increasing CPU clock speed, which led to excessive heat dissipation and power consumption.

Intel CTO Justin Rattner said functions such as speech recognition and augmented reality will push the need for this kind of computational power.

“If we’re going to have this technology in five to 10 years, [the smartphone] won’t have just one camera,” said Enric Herrero, a research scientist at Intel Labs in Barcelona. “It would have two to three cameras that are always on. It could build a three-dimensional map of what it’s looking at and do object recognition.”

Smarter, faster cloud search

But can these functions be achieved with dedicated chips, better software, and tight cloud integration — instead of the humungous 25 to 125 Watts (two light bulbs!) needed, according to Intel — compared to less than ~5 Watts max with current cell phones?

Case in point: I’m impressed with the voice search feature in the just-released iOS/Android Google Search app upgrade, which blows away Siri in speed (I clocked it repeatedly at less than a second for Google searches on an iPhone 5), and with excellent voice recognition and voice quality (replacing Siri’s irritating robot voice).

Granted, it can’t access contacts and launch apps, like Siri, but for fast, intelligent searching, move over Siri: it will be Google voice search + Watson.

Examples of questions the Google Search app can answer (via Official Google blog):

• “What does Yankee Stadium look like?” Google will show you hundreds of pictures instantly.
• “Play me a trailer of the upcoming James Bond movie.” The trailer starts playing immediately right within Google Search.
• “When does daylight savings time end?” The answer will appear above the search results, so you can set your clock without having to click on a link.
•  “Who’s in the cast of The Office?” See a complete cast list and find out who made you crack up last night.

Also, if we’re talking 10 years, we’re probably in post-silicon land, perhaps with intelligent low-power neurosynaptic chips based on carbon nanotubes or instant graphene devices on demand, powered by solar cells painted onto our devices or clothing.

Will power-gulping multiple cores still be relevant?

(Credit: iStockphoto)

Let me propose to you four interesting statements about the future:

1. As I argue in this video, chemical brain preservation is a technology that may soon be validated to inexpensively preserve the key features of our memories and identity at our biological death.

2. If either chemical or cryogenic brain preservation can be validated to reliably store retrievable and useful individual mental information, these medical procedures should be made available in all societies as an option at biological death.

3. If computational neuroscience, microscopy, scanning, and robotics technologies continue to improve at their historical rates, preserved memories and identity may be affordably reanimated by being “uploaded“ into computer simulations, beginning well before the end of this century.

4. In all societies where a significant minority (let’s say 100,000 people) have done brain preservation at biological death, significant positive social change will result in those societies today, regardless of how much information is eventually recovered from preserved brains.

These are all extraordinary claims, each requiring strong evidence. Many questions must be answered before we can believe any of them. Yet I provisionally believe all four of these statements, and that is why I co-founded the Brain Preservation Foundation in 2010 with the neuroscientist Ken Hayworth. BPF is a 501c3 noprofit, chartered to put the emerging science of brain preservation under the microscope. Check us out, and join our newsletter if you’d like to stay updated on our efforts.

I’ll occasionally review and report evidence and arguments relevant to the statements above, try to explain why I’m optimistic about these technologies, and to enlist your help in pushing forward their validation or falsification as fast as feasible. If validated, I’ll be pitching to you for help in getting brain preservation access and affordability to the world as fast and affordably as possible. To these ends, thank you for any frank and constructive feedback you can leave in the comments.

In this post, I’d like to try to provisionally answer a question relevant to the first three statements above:

To preserve the self for later emulation in a computer simulation, what brain features do we need?

We can distinguish three distinct information processing layers in the brain[1]:

1. Electrical Activity (“Sensation, Thought, and Consciousness”)
   These brain features are stored from milliseconds to seconds, in electrical circuits.
2. Short-term Chemical Activity (Short-and Intermediate-term Learning — “Synapse I”)
   These brain features are stored from seconds to a few days in our neural synapses (synaptome), by temporary molecular changes made to preexisting neural signaling proteins and synapses.
3. Long-term Molecular Changes (Long-term Learning — “Nucleus and Synapse II”)
   These are stored from years to a lifetime in our neuron’s connectome, nucleus (epigenome) and synaptome, by permanent molecular changes to neural DNA, the synthesis of new neural proteins and receptors in existing synapses, and the creation of new synapses.

At present, it is a reasonable assumption that only the third layer, where long-term durable molecular changes occur, must be preserved for later memory and identity reanimation. The following overview of each of these layers should help explain this assumption.

1. Electrical Activity (“Sensation, Thought, and Consciousness”)

Our electrical brain includes short-distance ionic diffusion in and between neurons and their supporting cells (i.e., calcium wave communication in astrocytes), action potentials (how neurons send signals from their dendrites to their synapses), synaptic potentials (how signals cross the gaps between neurons), circuits (loops and networks) and synchrony (neurons that fire in unison, though they are widely separated). Electrical features operate at very fast timescales, from milliseconds to a few seconds, and are variable (not exact), volatile, and easily disrupted.

Neural synchrony — our leading model of higher perception and consciousness (credit: Daniel Senkowski et al./Trends in Neurosciences)

These features certainly feel very important to us. They include our sensations (sensory memory) and current thoughts (commonly called “short-term” memory by neuroscientists).

Recurrent loops, special electrical circuits that cycle back on themselves, hold our current thoughts (when you rehearse some information to avoid forgetting it, you are literally keeping it “in the loop”). Neural synchrony creates our conscious perceptions, and when it happens in the self-modeling areas of our brain, it gives us self-aware consciousness.

Yet electrical features are also fleeting. When you sleep, or are knocked unconscious, or are given an anesthetic, your consciousness disappears, only to be “rebooted” later, from more stable parts of your brain. Our memories aren’t even recalled with precision but are rather recreated, as volatile electrical processes, from these molecular long-term stores, in ways easily influenced by our mental state and cognitive priming (what else is on our mind). That’s why eyewitness testimony is so variable and unreliable.

The electrical features of our self are thus like the “foam” on the top of the wave of our long-term memories and personality. They make us unique for a moment, as they hold only our most immediate thinking processes[2]. Amazingly, people who undergo special surgeries that stop their heart, and some who drown in very cold water, can have no detectable EEG (electrical patterns) for more than thirty minutes, and their brains successfully reboot after rewarming them.

Essentially, these individuals are recovering from clinical brain death. Not only do they not have consciousness during this period, they have no unconscious thoughts. Yet because their deeper layers aren’t too disrupted, they can restart their electrical activities.

An excellent book about neural spikes, loops, and synchrony is Rhythms of the Brain, Gyorgy Buzsaki, 2006. It explains the emergent properties and integrative functions of these “highest order” electrical features of our brain. My late mentor at UCSD, Francis Crick, and his Caltech collaborator, Christof Koch, call this topic the search for the Neural Correlates of Consciousness.

It’s a great phrase. Consciousness is not a mystery we’ll never solve, but according to a number of neuroscientists it is a physical process of neural synchrony, in particular regions of your brain. These brief, rhythmic synchronizations share information between groups of neurons in distant regions of the brain by tightening up (“binding”) their interdependent sequences of action potentials.

The synchronizations are controlled by the inhibitory neurons in our brain, which use the GABA neurotransmitter. Disrupt gamma synch, as with anesthesia, and you take away consciousness. Give a drug like zolpidem, which activates GABA neurons and increases gamma synch, to patients who are in persistent vegetative state, and you wake 60% of them up from their comas, to varying degrees!

Wikipedia doesn’t yet have a good explanation of the gamma synchrony model of consciousness, but they will in a few more years. Laura Colgin at Kavli has found two reliable gamma synch mechanisms in rat hippocampus. She speculates that slow gamma makes stored memories available to current consciousness, and fast gamma integrates sensations to create conscious perceptions. Though neuroscientists don’t yet all agree on the details, many have found neural correlates of sensations, thoughts, emotions, and consciousness in the electrical features of our brains. These features, in conjunction with the short-term chemical changes we will describe next, represent the moment-by-moment updates to our long-term memory, self, and intelligence.

2. Short-term Chemical Activity (Short- and Intermediate-term Learning — “Synapse I”)

Short-term chemical activity is the next layer down. It involves all our short- and intermediate term learning and memory, everything beyond our sensations, current thoughts, and consciousness, but not including our long-term memories. We can call this layer “Synapse I.”

As your electrical experiences and thoughts race around the various circuits in your head, you make a number of short-term learning changes in your neural networks to capture, for the moment, what you’ve learned. These involve changes to preexisting proteins in your preexisting synapses (communication junctions), changes that last for minutes (short-term) to days (intermediate-term).

These are changes in both the mechanics of neurotransmitter release and short-term facilitation (strengthening) or depression (weakening) of synaptic effectiveness. Synapses are modified by the precise timing and frequency of electrical signals (action potentials) received by the postsynaptic neuron, a process called spike-timing dependent plasticity.

There are short-term changes in signaling molecules (neurotransmitters, cAMP, Ca++, CamKII, PKA, MAPK), and membrane receptors (NMDA). Phosphorylation states (chemical tags) are altered on some of these molecules, and a temporary equilibrium between kinases (enzymes that add phosphates to key molecules) and phosphatases (enzymes that take them away) is established in the synapse.

[Note: On Oct 15, 2012, Ye et. al. showed in Aplysia how precise spatiotemporal signaling in the synapse involving PKA holds short-term memories in synaptic electrochemical networks, and the interaction of PKA and MAPK holds intermediate-term memories in these networks, in a process called synaptic facilitation.

If the short- or intermediate-term learning or memory is to become long-term, communication with the cell nucleus must now occur, and new membrane proteins and synapses are then built, involving new or altered circuits in the connectome. If not, the new memory dies out[3].

Every night, when we sleep, our short- and intermediate-term brain writes important parts of its experiences to our long-term memory, building durable new synaptic connections, where this learning can now stay with us for years to life, in a process called memory consolidation. This process moves a subset of our recent learning and memories, apparently the most relevant parts, from temporary spatiotemporal signaling states to permanent new synaptic structures, anchored to the cytoskeleton of each neuron.

We can think of these new proteins, synapses, and circuits established in neural synapses and nuclei in a way that is very roughly like DNA, as they are long-term stable structures, encoded in a partly digital form, that will endure all the flux and variability of the biochemistry within each neuron, over a lifetime. It is these unique synaptic and epigenetic networks that we must preserve, scan, and upload in creating neural emulations, as we will discuss.

Long-term memory formation happens best when we are in slow wave (deep and dreamless) sleep, which we get in cycles during the night (and especially well if our sleeping room is dark and quiet) and also during a good nap (a great way to “lock in” what you’ve learned, after a demanding learning period that will naturally make you sleepy).

Neural dendrites, cell body, action potential, and synapses (credit: Gallant’s Biology Stuff)

All our neurons work in circuits, and strengthen or weaken their connections based on chemical and electrical activity, in a process called Hebbian learning. Just like your muscles, which come in two sets that oppose each other around every joint, neural circuits are both excitatory and inhibitory at many decision points in the network.

Perhaps most important decision points are the cell bodies of each neuron, where the nucleus is. The electrochemical current from all the dendrites (“roots”) of each neuron flows toward its cell body, and action potentials (current waves) flow from the cell body to its synapses (“branches”), along the single axon (“trunk”) of each neuron.

Glutamate is the main neurotransmitter we use to send excitatory current from a synapse to the dendrite of the next neuron in a circuit (the postsynaptic neuron). Glutaminergic synapses are thus called “positive” in sign, and they promote electrical activity throughout the brain. GABA is the main neurotransmitter we use to let inhibitory current leak out of a postsynaptic dendrite. GABAergic synapses are thus called “negative” in sign, and they depress circuits throughout the brain.

Each neuron sums the net result of the positive and negative inputs it receives from its dendrites, over milliseconds to seconds. If the current exceeds that neuron’s threshold, it sends an action potential (depolarizing electrochemical signal) to all its synapses. As the brain learns, our synapses enlarge or shrink, giving them greater or lesser excitatory or inhibitory effect, and we may grow more or lose our synapses. With few exceptions, each neuron also uses just one type of neurotransmitter (eg., glutamate or GABA), or the same small set of neurotransmitters, at all its synapses.

The architecture of memory, thought, emotion, and consciousness may thus be reducible to a surprisingly simple set of algorithms, connections, weights, signaling molecules and electrical features in each neuron, working together in a massively parallel way to create computational networks that are far more complex than the individual parts.

Hippocampus and frontal lobes (credit: NIH)

In higher animals, the neurons in our hippocampi (two c-shaped organs in each hemisphere of our brain), and the connections they make to the rest of our cerebral cortex (especially to our frontal cortex), store all kinds of episodic (experiential) and declarative (fact-based) information, all from our last few days of life.

At the same time, neurons in our cerebellum (a more primitive, “little brain” at the base of our skull) store procedural learning and memory (how to move our bodies in space).

Experiments with rats and primates tell us that each hippocampus makes perhaps tens of thousands of new neurons every day, from neural stem cells. Other than for repair after certain kinds of injury, no other part of the adult brain is able to use stem cells in detectable numbers, as far as we know.

The rest of our brain is postmitotic (unable to use cell division to maintain its structure), as neuroscientists learned in an elegant experiment in 2006. Our neurons must be maintained by our immune and repair systems, and as they die via natural aging, or kill themselves in apoptosis, memories start to die.

Hippocampal dendritic spines (credit: Fiala & Harris/J Am Med Inform Assoc)

Our hippocampal neurons have the very tough job of temporarily holding, in their uniquely dense synapses, and via their connections to the rest of the cortex, much of the new information we have learned over the last day or two, during our entire adult life.

Here is a picture of a computer reconstruction of a small section of ten columns of synapse-rich “spiny dendrites,” from the CA1 (input) region of the hippocampus. CA1 contains areas like place cells, imprinted genetically with detailed maps of 3D space.

Like the digestive cells lining our gut, and the skin cells at our fingertips, certain hippocampal neurons appear to get worn out on a regular basis by this demanding short-term memory holding function, and so some neuroscientists think new ones must regularly grow and mature to replace them.

People whose hippocampi are both surgically removed, like the memory disorder patient Henry Moliason, who had this done at the age of 27, can’t update their long-term episodic and declarative memories. H.M.’s long-term memory was mostly “frozen” at 27. He could occasionally add bits of new information to long-term memories of the same type he’d built before the surgery, and he could learn new procedural (spatial and muscle) memories in his cerebellum, but he had no cerebral knowledge that he’d added these memories.

H.M.’s amazing life suggests that if the brain preservation process damaged the hippocampus, but not the rest of our brain, we’d come back without our most recent experiences (retrograde amnesia), but our older memories and personality would still be intact. Ted Berger at USC managed to build a simple version of an artificial electronic hippocampus for mice in 2005, so there’s a good reason to believe that this part of our brain, though important, isn’t irreplaceable.

As long as you could install an artificial hippocampus in the computer emulation constructed from your scanned brain, you’d be back in business as a learning organism, with only some of your more recent memories and learning erased. This all helps us understand that what Daniel Dennett would call our center of narrative gravity, our most unique self, is our long-term memory.

The fact that only special areas of our hippocampus can add new cells during life exposes a harsh reality about our biological brains. We are all born with a very large but fixed long-term memory capacity, and this capacity gets increasingly used up, pruned and potentiated, the older we get. Anyone over 40, like myself, knows they are considerably less flexible at learning new things than they were at 20.

It’s far easier for older people to add more twigs to branches of knowledge we’ve previously built in our “tree of experience” than to form new branches. We can do it, but gets progressively tougher and slower the older we get.

This means, if we want to be lifelong learners in a world of accelerating technological and job change, it is critical to get an early education that is as categorically complete (global, cosmopolitan, and scientific), moral (socially good, positive sum) and evidence-based as possible.

Our children need the best mental scaffolds they can get early on, or they’ll spend the rest of their lives trying to prune away harmful and untrue thoughts and beliefs acquired in their youth. Psychologists have long known that it is much easier to add increasing specificity to a neural network than it is to unlearn (depress) any branch, once it’s built. We need to be careful about what we allow into our memory palaces.

That said, children also benefit greatly from freedom, early on in life, to study what they themselves desire to learn, and to have a good degree of control over learning outcomes and style. This freedom, and appropriate rewards for effort of any kind, induce them to build intricate mental specializations in areas they are personally passionate about.

For those who want to know how to implement a 50/50 balance of broad, state-mandated learning in future-critical STEM fields, analytical thinking, and civics (the “hilt of the sword”), and a personalized program of student-directed specialized learning, creativity, and play in the other half of the time (cutting into and mastering whatever they can convince their teachers is worth studying, or the “blade of the sword”), I strongly recommend The Finland Phenomenon, 2010 .

This film, and to a lesser extent Tony Wagner’s book Creating Innovators, 2012, demonstrate key elements of the future of learning for enlightened societies, in my opinion. It may take 20 years for the evidence to be incontrovertible and for this model to be implemented in the US, but you can give it to your child now, if you find it appealing.

MyCyberTwin – Virtual Assistants Will Be Useful for Many of Us By the Early 2020′s

It is also liberating to realize that while our biological brains are less able to learn fundamentally new things as they age, all the digital technologies we use, technologies which will bring our emulations back at an affordable price later this century, will continue to get exponentially more powerful every year.

Most of us don’t realize this, but everyone who uses a social network, email, or any other technology to capture things they say, see, and write about is also creating a digital simulation of themselves. By 2020 we’ll all be talking to and with our best search engines in complex sentences (the conversational interface), and shortly thereafter, we’ll all be able to use simple software agents, cybertwins, which will have crude maps of our interests and personality, so they can serve us better.

Computational linguists know that if you capture what a person says for just two years, we are so repetitive about what we care about that a cybertwin could whisper into our ear the word that natural language processing algorithms predict we want when we are having a senior moment, and they’ll be right most of the time.

That’s how repetitive we are, and how good web search will be by 2020. As I wrote in 2005, people who don’t run cybertwins will be much less productive, so they’ll be very popular, even though they’ll bring lots of new social problems in their first generation.

These simulations won’t be turned off by our loved ones when we die. Our children will use them to interact with a simulation of us, and to keep the best of our thoughts, experiences and personalities accessible to them. Teaching our children and ourselves to be digital natives and digital activists is thus a very important way for us to build an ever more capable cybertwin, even as our biological self naturally slows down and simplifies (prunes away branches of knowledge and memories we once had ready access to) with advancing age.

Now we arrive at our truest self, the part we care most about preserving and sharing with our loved ones and society. It is this self that I expect will later merge with the cybertwin that many of us will leave behind, as strange as that might sound.

3. Long-term Molecular Changes (Long-term Learning – “Nucleus and Synapse II”)

Experience-based learning (credit: Graham Paterson/Children’s Hospital Boston)

The production of long-term memory, personality, and identity requires all the short-term synaptic changes above, plus permanent molecular changes in the neuron’s Nucleus (DNA and its histones, or wrapping proteins), and the permanent creation of new cellular proteins, synapses, and circuits (Synapse II).

Here’s a brief summary of our understanding of the process[4]:

Nucleus (“Genome, Transcriptome, and Epigenome”)

1. Retrograde transport and signaling from the synapse to the nucleus
2. Activation of nuclear transcription factors and induction of gene expression
3. Chromatin alteration and epigenetic changes in gene expression (gene-protein networks)

Synapse II (“Connectome and Synaptome”)

4. Synaptic capture of new gene products, local protein synthesis, and seeding of new synaptic sites
5. Permanent synaptic changes, activation of preexisting silent synapses, formation of new synapses.

We used several “-ome” words above. Let us briefly consider each. They are very roughly ordered below in terms of their likely contribution to our unique self, from least to most important:

The Genome. These are inherited genes and gene regulatory networks that control instinctual behaviors. Our genome includes the unique alleles we received from our parents. It is easy to preserve, as it is the same in all cells. With one tissue sample we can create a clone later, either physically, or far more likely, in a computer simulation. But this clone has only our inherited uniqueness. We’ll need contributions from the next four “omes” to add our life memories and learning to the emulation.

The Transcriptome. This is the set of proteins made (transcribed) by cells. While proteomics (another “ome” word) is in its infancy, scientists estimate each of our cells has the DNA to express ~20,000 basic protein types. Each type can be further modified after creation by adding or removing chemical tags like phosphate, methyl, ubuquitin, and other small molecules, so that more than a million protein subtypes may exist in a typical human body.

Fortunately, each of our ~220 cell types only uses around 5,000 of these 20,000, and perhaps less than 2,000 of the 5,000 are unique to each cell type. Neurons and glia, the cell types we are most interested in, may use just a few hundred protein types to store our higher learning and memory in the nucleus and synapses. The other proteins are there to keep all of our cells alive, which is a critical precondition to being able to store long-term memories in a special subset of neural structures.

All this suggests the proteomics of memory and identity, and of later memory and identity reconstruction from scanned brains, are not impossibly complex, but rather highly challenging, fascinating and eventually solvable problems.

The Epigenome. These are learning-based changes in gene-protein networks that happen in the nucleus of each neuron, mostly during the life of the organism. The Dutch famine of 1944 and the Överkalix study in Sweden tell us that some epigenetic changes can be inherited in humans, so we all should seek good nutrition and avoid toxin exposure, as we may pass some of that to our children in the form of compromised and undermethylated epigenomes.

But there is a lot more to the epigenome story still to be uncovered, as this 2011 article on epigenetic regulation in learning and memory in Drosophila makes clear. Our epigenome is a gene-regulatory layer that involves chemical changes, mostly methylation, to DNA and to the histone proteins that wrap and expose DNA in the cell nucleus. These changes determine how DNA, RNA, and protein are expressed in the nucleus, and they may affect how the cell body integrates incoming electrical signals and manages its synapses.

The Connectome. This is a map of our neural cell types, and how they connect. Our connectomes and much of our dendrite structure is very similar in all of us. This shared developmental structure makes it easy for us to communicate as collectives, for ideas or “memes” to jump from brain to brain. Yet with 100 billion neurons making an average of 1,000 connections to other neurons, and most of these not being developmentally controlled, we’ve got the ability to make 100 trillion connections, the large majority of which will be unique to each individual.

The Synaptome. These are key features of the ~1,000 synapses that each neuron makes to others. They are the particular long-term molecular features that determine the strength and type of each synapse, its signaling states and electrical properties, as we’ve described them above. The synaptome is the weight and type of the 100 trillion connections described above, and this information may be the most important “recording” of our unique self.

Fortunately, because memories are stored in a highly redundant, distributed, and associative manner in our synaptic connections, our synaptome is to some degree fault tolerant to cell death. Both artificial and biological neural networks experience graceful degradation (partial recall, incremental death) of higher memories as individual neurons die.

We also know the molecular code of long term memory is fault tolerant to the noise, deformations, and chaos of wet biology. The feedback loops between the electrical and gene-protein network subsystems interact somehow to stabilize long term memories in a special subset of durable molecular changes, in spite of all the other biochemistry furiously going on to keep the cell alive.

I am sure the distinguished futurist and technologist Ray Kurzweil will have a lot more to say about these topics in his next book, How to Create a Mind, which comes out next month. You can preorder a copy here.

To understand how these subsystems interact in a living organism, let’s start in as simple a model organism as we can find, single-celled animals, organisms that don’t even have nervous systems as we know them. Wetware, Dennis Bray, 2009 is a great tour of these animals.

Single-celled eukaryotes like Stentor, Paramecium, and Amoeba do complex information processing, and hold short-term memories in their chemical networks.

In 2008, we learned that Amoeba remember and anticipate cold shocks, for example. These networks include the cell’s genome, epigenome, cellular proteins, cytoskeleton, receptors, and cell membrane. They are true computational networks, with both neural-network like and Boolean logic properties.

Genes and proteins integrate signals from other genes and proteins, and selectively switch and transmit signals, just like neurons do. The genes in each cell, via RNA, determine which proteins are made, when and where.

Most protein changes are part of the short term computation being done in a cell, but a special few will lead to lasting changes in the epigenome and the cytoskeleton and receptors in and on the surface of the cell. These long-term changes are the ones we care most about, as they store the cell’s unique memory and identity.

Single-celled animal (credit: Anthony Horth)

Until computational neuroscience[5] can predictively model how the gene-protein networks in a Paramecium allows these animals to evaluate options, assign priorities, regulate their moment-by-moment computational attention, continually vary strategies for chasing prey and avoiding toxins, and chemically store their representations, habituations, and memories in an intracellular environment, all without a proper nervous system, the field will be missing its Rosetta Stone.

Electrical waves exist in these single-celled animals, but with the exception of mitochondrial energy production, they are of the most primitive, diffusion-based kind. All the considerable intelligence in these animals is coursing, moment by moment, through their gene-protein networks.

In multicellular organisms with neurons, the cytoskeleton and receptors have specialized into the synaptome, the pre-and post-synaptic molecular modification of our synapses, including phosphorylation of switching proteins like calmodulin kinase II. While there are over 50 known neuromodulators and 14 neurotransmitters in our brain, only six neurotransmitters have been regularly implicated in long term learning and memory in our synaptome.

It is these and their partner molecules in the synapse and nucleus that are probably most important to understand and model to crack the long-term memory code.

C. elegans connectome (credit: OpenWorm.org)

Fortunately, even with our very partial molecular and functional maps today we have still managed to work out some basics of neural network interaction in very small neural ensembles, like the somatogastric nervous system (~30 neurons) in lobsters.

We’ve even created early maps of very small whole-animal neural systems, like the nematode worm C. elegans, with its 302 neurons and ~6,000 synapses. We mapped the C. elegans connectome in 1986, but we still know just pieces of its synaptome and transcriptome, and even less about its epigenome.

Fabio Piano et. al. give us an overview of the state of C. elegans gene-protein network knowledge in 2006. Note their subtitle is “A Beginning.” Jeff Kaufman has recently summarized the very early status today of whole brain emulation in nematodes.

David Dalrymple in Ed Boyden’s lab at MIT is working on C. elegans simulation, and he is optimistic about new tools in neural state recording, optogenetics, and viral tagging for characterizing each neuron’s function. As Derya Unmatz reports in a blog post that sounds like science fiction, Sharad Ramanathan et. al. at Harvard can now take control of C. elegans locomotion by firing precisely targeted lasers at individual neurons in an optogenetically modified worm’s brain, controlling its chemotactic behavior and convincing it that food is nearby.

A small international collaboration exists to emulate the C. elegans nervous system, called OpenWorm. There’s even a Whole (Human) Brain Emulation Roadmap, started in 2007 by Anders Sandberg and Nick Bostrom at Oxford, and a few other visionary folks in biology, computer science, and philosophy. These important projects are quite early and extremely underfunded at present. The biggest problem today is getting more funded people working on them.

To emulate how C. elegans, Drosophila, Aplysia, Danio, Mus, and other neural networks actually work, and to begin to extract even crude and partial memories from the scanned brains of any of these and other model organisms, we’ll need a better understanding of behavioral plasticity, and the way the synapse, the nucleus, and neuromodulators bias the pattern generators in neural circuits into a particular set of behavioral patterns.

This may require not only better neural circuit maps, but better maps of several still partly-hidden intracellular systems involved in long-term memory formation: gene regulatory networks, the transcriptome, and the epigenome[6]. There are gene-protein networks controlling human neural development, neural evolution, and our long-term learning and memory. A special few of these regulatory networks, their proteins, and the epigenomic changes these networks store during a lifetime of human learning may be as important as the synapse, if not more, in determining how our brain encodes and stores useful information about the world.

A great textbook on gene regulatory networks is The Regulatory Genome: Gene Regulatory Networks in Development and Evolution, Eric Davidson, 2006. It will amaze you how much Davidson’s group has learned about these networks, primarily by studying the evolutionary development of one simple organism, the sea-urchin, over several decades.

Last month, Isabelle Peter and others in Davidson’s group at Caltech published the first highly predictive model of how these networks control all the steps in sea urchin embryo development over the first 30 hours of its life. 50 genes are involved, and their regulatory interactions can be fully described in Boolean logic.

Now they want to model all of development, and some of the networks controlling its variational processes. Consider the magnitude of their achievement: Davidson et. al. have reduced an incredibly complex biochemical process down to a far simpler algorithm. This is what must happen in long-term memory, if we are to use scanned brains to abstract the key subsets of molecular structures that reliably encode it in our neurons.

Protein microarrays — an exciting new tool (credit: Eye-Research.org)

Neural proteomics and the transcriptome are entering an exciting new phase as we use DNA and RNA microarrays, and now protein microarrays to catalog neural transcriptomes and compare them to other types of human cells, and to other primate and mammal neurons.

In August, Genevieve Konopka and colleagues published an exciting paper comparing human, chimpanzee, and rhesus monkey neural transcriptomes. We’re finding genes and proteins unique to particular areas in human brains, especially our frontal lobes. We’re building our first maps of the critical differences in the gene and protein regulatory networks that allowed us to wake up, make tools, and walk out of Africa less than two million years ago.

Epigenome (methylated DNA and modified histones) cartoon (credit: RoadmapEpigenomics.org)

We recently learned that what was long called “Junk” DNA, the 98% of each cell’s non-exonic DNA (DNA that doesn’t code directly for proteins), participates at various levels in gene regulatory networks, and through epigenomics these networks can change to some degree over the life of the cell. We’re learning now to map gene-protein interactions in these networks, including epigenomic changes, using tools like Chromatin ImmunoPrecipitation and sequencing (ChIP-seq).

Unfortunately, this work is also seriously underfunded. We’ve known about the importance of the epigenome for over a decade. Epigenomic changes can be inherited (watch what you do with your body, as your kids will inherit a record of some of your bad or good life habits in their epigenome!), and thus record unique learning in each cell over its lifetime, in ways we are still uncovering.

The NIH started a Roadmap Epigenomics Project for mapping the human epigenome in 2008, but the funding is a pittance, roughly $40 million a year. There is also a global collaborative research database, ENCODE, for sharing what is presently known about all the functional elements in the human genome. We give it roughly $20M/year, barely life support.

There are also various Human Proteome Projects under way, but no one seems to be funding any of these seriously, either. None of the politicians or key philanthropists who could make the Human Proteome and Epigenome into national research priorities have proposed any big initiatives, as far as I know. Even our science documentaries don’t adequately convey the promise of these fields. The scientific community is tooling along as best it can in spite of the fact that the public still hasn’t gotten the clue on how much better medicine would be in ten years if we were spending a whole lot more money on this right now.

Recall by contrast the Human Genome Project, which began with fanfare in 1990 and was rough draft completed in 2000, for $3 billion, a price gladly paid by the U.S. and four other motivated nations. The Human Genome Project was, to put it in proper perspective, our planet’s Moon Shot in the 1990’s, our species latest great leap into “inner space.”

As those who’ve read my Race to Inner Space post know, I think understanding the machinery of life and intelligence, and nanotechnology in general, is a destination far, far more valuable to us than outer and human scale (as opposed to cell and molecule-scale) space. We need an international Human Proteome and Epigenome Project race. With good funding and leadership, we might nail our first good maps of the neural gene-protein interaction layer in a decade. With business-as-usual, it will likely take much longer.

As we learn the languages of gene regulatory networks, the transcriptome, and the epigenome in coming years, we should learn how to influence these networks in many powerful ways. Do you think the trillion dollar global pharmaceutical industry is big now? Wait for the therapeutics that may start to arrive in the late 2020s, as we begin to learn how to intervene in these networks.

I think it is only when we have good maps of these gene-protein networks that we can finally expect medical advances like better learning and memory formation, elimination of a vast range of diseases including cancer and Alzheimer’s, immune system boosting, aging reduction (epigenomics repair), and perhaps even the uncovering of genetically latent skills like tissue regeneration and hibernation.

We are not talking about gene modification (inserting new genes in the germline, or in an adult), but rather about improving dysfunctional gene network regulation, and learning how to assay and minimize important parts of the network dysregulation that goes wrong in each of us as we get older and get various diseases.

Ken Hayworth

There’s a nice analogy here, pointed out by my Brain Preservation Foundation co-founder, Ken Hayworth. The Human Genome Project gave the world affordable gene sequencing in the mid-2000’s, and ten years later, we are beginning to see the major fruits: the uncovering the previously hidden worlds of gene regulation networks, the transcriptome, and the epigenome.

Likewise, the Human Connectome Project and the still-unfunded Human Proteome and Epigenome Projects could get us affordable neural circuit tracing and functional gene regulatory network modeling in the late 2010s.

Just as the Human Genome Project showed us we had a lot fewer genes than we thought (~21,000 rather than 100,000) the Human Epigenome Project may tell us that our gene regulatory networks are simpler than we currently think, and that of the ~5,000 proteins in a typical cell, there are just a handful that matter to our long-term self.

With luck, the remaining hidden layers of the neural transcriptome and epigenome will be functionally understood in the late 2020s. In that exciting time, our ability to understand memory and learning, to read memories from the scanned brains of model organisms, and to build biologically-inspired computer models, will all be greatly enhanced.

So to answer our original question, we need to find out if both chemical preservation and cryopreservation will preserve the connectome, the synaptome, and any long-term memory-related changes in the epigenome in a living brain.

Our Brain Preservation Technology Prize, which focuses on the connectome and many but not all features of the synaptome, is an important start down this road. As we understand better what molecular features in the synaptome and epigenome need to be preserved to capture and later retrieve memories, we’ll also need to find out if either chemical or cryopreservation, or ideally both, will reliably preserve those structures at the end of our biological lives, and whether it will be possible for future scanning algorithms to repair any damage done by the preservation process.

We’re too early to answer such questions today, but it is encouraging to remember that long-term memory is a very redundant, resilient and distributed system. Extensive neural destruction can occur in brains via Alzheimer’s, stroke, and other diseases before our memories are substantially erased and cognitive reserve is no longer available.

Sixty years of histology practice tells us that good perfusion of special chemical fixatives such formaldehyde and glutaraldehyde at death will immediately preserve everything we can see by electron microscopy in neurons.

A great book on how this works is John Kiernan’s Histological and Histochemical Methods: Theory and Practice, 4th Ed., 2008. Kiernan has been publishing since 1964, and is a leader in the theory and practice of chemical fixation. There are even a few published fixation methods for whole mice brains.

Here’s a 2005 paper by Kenneth Eichenbaum et.al. demonstrating a whole brain fixation technique that claims “complete preservation of cellular ultrastructure,” “artifact-free brain fixation” and “no signs of cellular necrosis” in an entire mouse brain.

Presumably these methods also protect DNA methylation and histone modification in the epigenome, the phosphorylation of dendritic proteins like CamKII, the anchoring of AMPA receptors in the synapse, and any other elements of long-term memory formation. Presumably these molecules are protected today for years just by aldehyde fixation, if kept at low temperature (4 degrees).

Companies like Biomatrica have even developed ways to store human and bacterial DNA and RNA at room temperature for years. Long term storage of whole brain connectomes, synaptomes and epigenomes at room temperature, an ideal outcome for simplicity and affordability, may work today via additional chemical fixation steps like osmium tetroxide, a process that crosslinks fats and cell membranes, and plastination, a process that draws all the water out of a preserved brain and replaces it with resin.

But all this remains to be proven. If you know of experts who have done work in this area who would be willing to help BPF write position papers on these topics, and who can envision research projects that will answer these questions more definitively, please let me know, in the comments or by email at johnsmart{at}gmail{dot}com. Thanks.

Footnotes:

1. There is a much older layer of unique learning in each of us that is also important, the intelligent behaviors that gene networks have recorded in each of us over evolutionary time, as instinctual programs, and the unique assortment and variants of genes we each received at birth.

Such networks determine our inherited neural programs, instincts and behaviors that are executed mostly unthinkingly and robustly, and during which other forms of learning, like short-term learning, often does not even occur. To preserve this layer we just need a DNA sample of the preserved person, and that particular uniqueness can be incorporated in any future emulation, assuming future computers are up to the task.

2. Some scientists working on brain emulation, like BPF Advisor Randal Koene, suspect that measuring and modeling the brain’s electrical processes, a topic called Computational Neurophysiology, will give us powerful new insights into artificial intelligence. There are new tools emerging for in situ functional recording of electrical features of the neuron.

These may be critical to establish the “reference class” of normal electrical responses, for each type of neuron and neural architecture, the class of electrical representations of information. But if the model I’ve presented here is correct, we won’t need to record any electrical features of individual brains in order to successfully reanimate them later. We’ll see.

3. In Aplysia (sea slug), the sensory neuron neurotransmitter serotonin (5-HT) binds to postsynaptic receptors, activates adenylyl cyclase (AC) in the cell to make the second messenger cAMP, causing a short-term facilitation (STF) in strength of the sensory to motor neuron connection. More of the excitatory neurotransmitter glutamate is released by the neuron to its follower motor cells, and Aplysia pulls away harder from its shock.

The neuron is also sensitized: K+ channels are depressed, more Ca++ enters the presynaptic terminal, and the action potential spike broadens. Kinases and phosphatases (phosphate adding and removing enzymes) including cAMP-dependent PK, PKA, PKC, and CamKII control duration and strength of these changes. In facilitation, the spike broadens temporarily, as both pre- and post-synaptic Ca++ and CamKII make molecular changes that temporarily strengthen the electrical signal across the synapse.

In short-term depression (STD), the same mechanism temporarily weakens the signal. If water is gently shot at Aplysia’s gills ten times in a row, it temporarily learns not withdraw them, via synaptic depression of motor circuits. This short-term memory lasts for ten minutes, and involves a short-term reduction in the number of glutamate vesicles that are docked at presynaptic release sites in sensory neurons (undocked vesicles can’t be immediately used).

Repeat this training four times and the slug will turn this into an intermediate-term memory, making chemical and electrical changes in the synapse that now last for three weeks. Again, all this involves changes only to preexisting proteins and synaptic connections in neurons.

4. In rat and human hippocampus, the primary excitatory neurotransmitter is glutamate. This causes Ca++ influx through NMDA receptors at postsynaptic membranes, and activation of CamKII, PKC, and MAPK. Permanent synaptic changes (Early LTP) include increased insertion of AMPA receptors in the membrane, and phosphorylation of proteins to change the properties of the channel.

These receptors are anchored to the neural cytoskeleton, so they have reliable long term effects. Later LTP involves recruitment of pre- and postsynaptic molecules to create new synaptic sites. A few key gene-regulatory networks are involved, with transcriptional and translational control at both the nucleus and the synapse, and control molecules including BDNF, mTOR, CREB, and CPEB.

We’ve recently found a memory encoding master control gene, Npas4, that encodes nuclear transcription factors (the copying of other genes into messenger RNA) which interact with hippocampal neurons to encode episodic memory. When Npas4 is knocked out of mice, they can’t learn. We’ve found RNA binding proteins like Orb2, that bind to genes involved in long-term memory.

A great and reasonably current text on the molecular basis of memory and learning is Mechanisms of Memory, David Sweatt, 2009. We’re still figuring out the epigenomic regulation that occurs in long-term learning and memory, so you’ll need to go to journals for most of that story, like this 2011 PloS Biology paper on epigenetic regulation of learning and memory in Drosophila.

The full size of the memory puzzle is becoming clearer every day. Now we just need to fund the work to complete it. We sure could use this knowledge in all kinds of good ways today, if we had it. Here’s a cartoon of long-term memory formation in both Aplysia and rat hippocampus, from Mechanisms of Memory(Vol 4., David Sweatt, p. 14):

Long-term memory formation in Aplysia and rat hippocampus, from Learning and Memory, John Byrne (Ed.), 2008 (Vol 4., David Sweatt, p. 14)

5. Computational Neuroscience seeks to model brain function at multiple spatial-temporal scales. The brain uses a vast range of different schemes for representation and manipulation of information, and it passes some of this information from one system to another all the time.

Consider the way neurons integrate signals from the receptors at their dendrites, the timing and shape of their action potentials, the way synapses interact with postsynaptic dendrites from other neurons, how neurons encode and store associative memory, specialize for perceiving and storing certain types of information (edge detection, grandmother cells), do inference and other calculations, work in functional subunits like cortical columns, and organize receptive fields. It all seems formidably complex, but useful simplifications exist, as we’ve described above.

6. Most folks in the neural emulation community don’t talk much about modeling gene regulatory networks or the epigenome and its interaction with the synaptome, and I think that’s their loss. Some focus only on easier stuff to see, like electrical features, and assume that might be enough to get a predictive model.

But I think that’s like looking for your keys under the streetlights when they are in the shadows. If spikes, loops, and synchrony are a network layer that has grown on top of cell morphology and gene-protein networks, the way single-celled animals eventually grew neurons, we may learn surprisingly little by measuring and modeling electrical features.

Attempting to do so may be like trying to infer the structure of hidden layers in a very large neural network [genome, epigenome, connectome, synaptome, and electrical features] by analyzing just the input/output layer, electrical features. We need all the hidden layers if we expect to have enough computational complexity to predictively characterize learning, memory, and behavior.

Reprinted with permission from Ever Smart World

After an incredible decade, in which the number of planets known beyond our solar system increased from zero to several thousand, astronomers have detected an Earth-sized world orbiting between the two major stars nearest to our system, Alpha Centauri A and Alpha Centauri B.

Much too hot to sustain life, it nevertheless will help in narrowing down the search space for others. (“News from Alpha Centauri.” Cool to say that!)

In a related matter – I’ve posted an essay, Are we alone in the universe? about the the Fermi Paradox, the Drake Equation and all that where-are-the-aliens jazz on the web site of Orbit Books, in conjunction with the upcoming release in the U.K. of the trade paperback version of Existence…

…soon to be followed by Orbit’s special new omnibus collections of my Uplift Series of novels. A gorgeous-big volume entitled UPLIFT will contain Sundiver, Startide Rising and The Uplift War.  Another omnibus compendium  — EXILES — combines Brightness Reef, Infinity’s Shore and Heaven’s Reach.  Soon to follow… beautiful reprints of Earth and The Postman.

A Potpourri of Cool Science!!!

Researchers discover a beluga whale, named NOC — whose vocalizations were remarkably close to human speech.

To amplify the comparatively low-frequency parts of the vocalizations, a beluga named NOC over-inflates what is known at the vestibular sac in his blowhole – which normally acts to stop water entering the lungs. In short, the mimicry was no easy task. So they ARE trying to meet us halfway, after all!

A recent study published in Trends in Genetics suggests that a person’s genes may affect their later political thinking and views of the world almost as much as his circumstances or upbringing do, and far more than many social scientists have been willing, until recently, to admit.

It seems that the degree to which you are politically knowledgeable is largely genetically determined, while your party affiliation is acquired from upbringing… though this then later diverges after adults leave the nest. And yes, researchers found a further 11 genes, different varieties of which might be responsible for inclining people – in general personality ways, not doctrine, of course – towards liberalism or conservatism.

Interesting to compare to other recent science showing differences in which parts of the brain are used to think about political matters. And what this has to say about the fact that American scientists have voted with their feet, abandoning one of the parties en masse.

Want to see the reason distilled? Click to see the original of this little poem, which is sooooo redolent in this political season.

“SCIENCE:

If you don’t make mistakes, you’re doing it wrong.
If you don’t correct those mistakes, you’re doing it really wrong.
If you can’t accept that you might be mistaken, you’re not doing it at all.”

Ocean acidification: deadly and undeniable

More than half of the six billion-plus metric tons of carbon released annually into the atmosphere is absorbed by the Ocean. Phytoplankton alone process an estimated 22 million tons of CO2 each day. This carbon sink does not come without consequence. In the last 100 years, our seas have become 30% more acidic, and that pace is accelerating. This increased acidity is impacting soft-shelled organisms such as crabs, shrimp, and oysters, many of which are unable to maintain their shells in this new, man-made acidic Ocean.

Now the crux. The ocean acidification trend lines come from entirely different sciences than those that study the greenhouse effect — research establishments in twenty countries that have nothing to do with atmospheric studies. And no Koch-supported “institute” has found anything wrong with them.

Unlike atmospheric studies, here’s an area where your denialist uncle could take the samples and measure them, himself. Two-thirds of our oxygen comes from the Ocean. But if rising acidity collapses the oceanic food chain, including phytoplankton, suffocation might be just one of many things we’ll sue the denialists for. And tell your uncle that includes him. The refugees will need homes. The denialists will share or lose theirs, by simple tort law. Time to adapt, out of simple self-interest.

Open source and hope

In a recent blog I described a vast array of ways that folks are empowered (or not) to engage in citizen science or open source development. Now comes another aspect to that movement. Can the open source science movement extended lessons derived from its central core — programming?

Software engineer and Linux pioneer Linus Torvalds saw a solution to this problem—“git,” a system that allows for collaborative development. This in turn inspired Preston-Werner and Hyett to create GitHub.com, a hosting site that allows multiple programmers to work on the same source code at the same time, with changes getting unique signatures.

I’ll be keynoting a Qualcomm conference on Open Source on November first. Here’s a site that explains some aspects, and that will link you to Clay Shirky’s fascinating TED talk about the great hope … how open source software might lead to “a new way to argue.” (I portray this happening in EXISTENCE and also in a scholarly paper.)

Space!

Don’t get your hopes up just yet for a comet extravaganza. But do make plans to keep an eye on the sky in late 2013! Comet ISON will pass very close to the sun and may become the brightest in all our life-times.  Well, perhaps. Learn all about these cosmic visitors (the topic of my PhD thesis) in HEART OF THE COMET!

The Japanese IKAROS spacecraft is (at last) a full scale solar sail test mission, something NASA for some reason avoided doing for half a century. The test probe has already passed Venus. And now it’s time to start using this naturally attractive (if slow) means of travel a lot more often in space.

Spiders from (on) Mars? With apologies to David Bowie… Are the mysterious black “spider” discolorations in some dune area of Mars from CO2 geysers? Or some even weirder explanation?

And speaking of the Red Planet: Craig Venter and Jonathan Rothberg are competing to put a DNA sequencing machine on Mars, each claiming that it is the best way to search for and confirm Marian life. ”This will work only if the DNA on Mars is exactly the same in its fundamental structure as on Earth,” says Steven Benner, president of the Foundation for Applied Molecular Evolution in Gainesville, Florida.

He says he’s skeptical that will be the case: “It is very unlikely that Terran DNA is the only structure able to support Darwinian evolution.”  Though I lean slightly toward Venter.  Some of the chemistry of DNA life has been shown to imply have the best combinations of stability and just the right breakability and attachment probabilities in the bonds.

And more sci potpourri

A very nifty innovation called MosquitoDMZ offers a new kind of trap that lures females to lay their eggs in  a place where they cannot thrive.  A clever technique. Though I still like the laser zappers I predicted in EARTH!

Imagine a clock that will keep perfect time forever, even after the heat-death of the universe … a “space-time crystal,” a four-dimensional crystal that has periodic structure in time as well as space.   The concept of a crystal that has discrete order in time was proposed earlier this year by Frank Wilczek, the Nobel-prize winning physicist at MIT. … And now other scientists claim they know how to made one.

How cool is this?  A singularity laser? ”The idea is to create a black hole next to a white hole so that their event horizons are separated by just a few hundred micrometres and create a small cavity. Then they show that when light is fired into this cavity, it is reflected off the white hole horizon onto the black hole horizon, back to the white again and so on.

Researchers show (theoretically, for the foreseeable future) that during each reflection, stimulated emission of Hawking radiation (from the stressed vacuum itself) effectively adds to the beam, thereby amplifying it. They say this additive process is logarithmic so a small seed of light ends up producing an intense beam of radiation.

“Their real triumph, however, is in showing how such a device could be made in the lab. They point out that the refractive index of certain materials depends on the intensity of light inside them. So the light itself changes the refractive index. That means a very intense beam can create a huge gradient in the refractive index. This gradient can be so steep that it behaves like an event horizon. In fact, a single pulse can create black hole horizon at its leading edge and a white hole horizon at its trailing edge. They go on to say that it ought to be possible to do this in optical waveguides made of diamond.”

Schades of Schadenfreude! This new game lets you play a virus or nanoplague and acquire new characteristics in search of the way to slay all life on Earth!

iO9 offers a pretty cool and logical and interesting appraisal of time travel fiction.  Very smart… if nowhere near complete.  I can think of five other scenarios…

Professor Sandy Pentland of MIT discusses Big Data and how the tsunami of information about you and me may be used by corporations and elites… and possibly in a way that’s fair to common folk. Or else become a tool for Big Brother.

Methods for performing encrypted communications using quantum-entangled “teleportation” are moving forward rapidly. Recent experiments have achieved results over several kilometers. Chinese teams are even planning soon to launch a satellite to test quantum-entangled communications back and forth to orbit and EUropean and Japanese groups are also in the race. But not (apparently) the United States… for some strange bureaucratic reasons.

Meanwhile, there are advances in the field of quantum computing, with the latest endeavor featuring an alliance with Amazon-founder Jeff Bezos and the CIA’s research group In-Q-Tel, to support the D-Wave company’s latest quantum computer — 512 super-chilled , superconduction niobium loops are arrayed in a layout of qubits that conforms to an algorithm that solves a particular kind of optimization problem at the core of many tasks difficult to solve on a conventional processor. It’s like a specialized machine in a factory able to do one thing really well — the range of “optimization” problems.

Reproduction without any(!) sex at all?

Want baby mice? Grab a petri dish. After producing normal mouse pups last year using sperm derived from stem cells, a Kyoto University team of researchers has now accomplished the same feat using eggs created the same way.  In other words, stem cells can be turned into sperm and ova and viable offspring result.

I admit surprise. I truly thought that mammalian meiosis — the division of (say) our human diploid 46 chromosome cells into subtly shuffled sets of haploid gametes (reproductive sperm or ova) with 23 choromosomes each) would turn out to be a complex process, requiring not only pluripotent stem cells and a triggering set of environmental cues, but the ongoing participation of a surrounding, complex organ, like the ovaries or testes, to take the cells through a multi-stage process.

In retrospect, I am not sure why I felt that to be likely.  Perhaps because the shuffling and separation and creation of the surrounding active cells seems fraught with potential for so many errors… by comparison, fertilization and creation of a blastocyst zygote and embryo seems simple!  Just a matter of cellular automata sorting themselves out through neighbor interactions.  But clearly, I was wrong. (I’ve been known to be! Remember that poem about science?) This just keeps getting stranger.

Questions? Are the offspring fully re-methylized… completely young?  Or do they inherit the donor’s aged chromosomes, the way the cloned Dolly the Sheep did?  And does this mean the only remaining miracle is the womb?  That women can now well and truly do without males, by creating their own sperm?  Do NOT anger that woman researcher at the next lab bench, fellows.

The latest from “are we in a simulation?”

I recall when “are we all living in a simulation?” was a really cool and surprising question!  Yes, I’m that old.  So old that my novelette “Stones of Significance” explores a few aspects of this topic for the first time, before they became cliches.  But time… or its simulated effects… moves on, and now there’s serious thought to how physics itself might test whether this “existence” of ours is in the original universe or one of the mazillion simulated ones being run in super advanced computers in that “real realm.”

(Or is it turtles (simulations) all the way down?)

Some first order reasons to imagine it is so?  Well, the simulators would have to save money or computational power somehow, by limiting the burdens of the simulation.  One way to limit the size of the space the inhabitants can experience directly (rather than just observe with telescopes) is to have an upper speed limit. Also a bottomost temperature.  And a limit to the degree that you can parse position and momentum… or energy and time… so that you cannot dive into the small to an infinite — or fractal — degree.

Now see a paper that suggests experiments that might actually observe the mathematical latticework within which we are being simulated.  Assuming that lattice of time and position is cubic, as are all our current cellular automata models, then that spacing should show up in high energy physics experiments. (Of course, the uber-modellers might use a different stacking of cells, to mess us up! Better check for hexagonal and other crystal structures, as well!)

And finally…

Science is not immune to controversy, especially around the edges. (Indeed, scientists are among the most competitive humans that our species has ever produced.) With science itself under concerted and deliberate attack by one entire wing of U.S. political life — (and sneered at by a few far-extremists of the other wing) — it would be surprising not to see the issues fester and broil even at sites like discovermagazine.com.

See this essay, in particular, discussing why author Robert Wright has taken a sudden veer, inviting “prominent creationists” to inveigh upon his “bloggingheads” show without proper counter-weight foils or challenge.  Yes, he also brings on prominent atheists. All should be challenged in the spirit of reciprocal accountability.

While I have long recommended Wright’s book NONZERO as a good way to introduce folks to the concept underlying our enlightenment — the positive sum game — I have grown increasingly worried by Wright’s foray’s down avenues that veer away from science, modernity or even history.  Well well. It’s too soon to judge… and maybe it’s just a different standard of looseness in style of disputation. Indeed, I would generally trust Wright over his accusers! Still, we live in an era when polemic too-often trumps reason. Your reportage on this is welcome.

And yes, there will be more social-political commentary soon. So far, I have covered two major topic areas that ought to be significant (and overwhelming) for any U.S. citizen who claims to truly care about the future of America, the Western Enlightenment Experiment, and our species. The Eight Reasons for Our Budget Deficit and the stark Difference Between the Ways that Democrats and Republicans Wage War.

I don’t expect to have much influence — those who are persuadable by facts and evidence have long  ago taken sides, favoring the candidate who most often mentions the word “science.”  Still, it’s important.  And we all have uncles and aunts who just might listen.  Or read with a willingness to learn.

Getnet Aseffa

In February of this year, KurzweilAI.net’s Amara Angelica put me in touch with an enterprising young Ethiopian engineer named Getnet Aseffa, who was interested in advanced technologies and their implications, and especially in their potential application to help Ethiopia and other African nations.

After some email dialogue, Getnet arranged for me to give a talk via Skype to an audience at Addis Ababa Institute of Technology. The themes of the talk were the Singularity and AGI; it was very well received, with many excellent questions at the end, covering everything from near-term practical AI applications to the potential risks of superhuman AGI.

Inspired by the strong reception of my Skype talk, and based on an invitation from Getnet, I recently spent four days in Ethiopia — mostly in the capital, Addis Ababa — with a main mission of better understanding the science and technology scene there, and forming a picture of what sort of AI-related opportunities might be available.

I spent some time at the university (Addis Ababa Institute of Technology) and gave a seminar there, and also talked to a host of technologists, entrepreneurs and scientists. Of course, four days is barely enough time to form an initial impression — but I did form a fairly strong one. I came away convinced that there are great opportunities to use AI technology to help Ethiopia confront some of the various problems it faces, and also to collaborate with Ethiopians on pursuing advanced AI R&D, along with other kinds of software and technology development.

I have written an H+ Magazine article giving a more personal account of the visit and some of the interesting conversations I had. Here I will take a broader view, and synthesize some of my impressions and opinions on the potential near and medium term future of AI in Ethiopia.

Ethiopia’s rapid growth

Before connecting with Getnet last year, my main impressions of Ethiopia had to to with famine and the Ethiopia/Eritrea war. But of course these tragic events are history now, and Ethiopia is the third fastest growing country in the world, and the fastest growing African nation.

The majority of Ethiopians are still rural farmers, and poverty, unemployment and income inequality are all high. However, starvation is a thing of the past, and disease is being controlled by an increasingly sophisticated medical system. Education is now widespread, with 95% graduating primary school, 60-70% graduating high school, and the number of universities pushing 100.

There is a highly energetic and rapidly increasing population of businesspeople, entrepreneurs and technologists, explicitly striving to better their country and maintain its fantastic growth rate by starting and executing a huge variety of projects. There’s also a significant foreign presence, especially Indian, Chinese and Korean. The government has explicitly looked to Korea as a guide for rapid, carefully state-managed development.

AI in Ethiopia?

Getnet Aseffa explains Ray Kurzweil’s exponential growth of computing at a Singularity seminar in Ethiopia (credit: Getnet Aseffa)

At first glance, the idea of doing AI in a developing country like Ethiopia may seem a non sequitur. One might think that developing countries have a lot of other more basic problems to deal with, before they need to start thinking about advanced technologies like artificial intelligence.

But actually, this is an overly limited perspective. Many decision-makers in Ethiopia and other developing countries recognize the existence of opportunities to leapfrog past stages of development that currently developed countries have passed through, using new technologies to hop directly into the future.

The most notable example of this is the tendency of developing nations to bypass the widespread laying of communication cables in rural regions, relying on wireless instead. Similarly, even though currently developed countries didn’t have much to do with AI during their earlier stages of development, different opportunities may exist for developing countries today.

In fact, I believe there are great opportunities for AI to help developing countries such as Ethiopia, and for these countries to help advance AI. And not only do such opportunities exist, but there is real appetite in Ethiopia (and quite likely other developing nations as well) for exploring them. Getnet has been organizing advanced technology seminars in Addis Ababa every couple months, with 700+ attendees each time, coming to hear about topics like AI, the Singularity, nanotech and self-driving cars.

How AI might help Ethiopia

I found that Ethiopian academics, technologists and businesspeople were full of ideas regarding how AI technology might help Ethiopia. At the tail end of a seminar I gave at Addis Ababa Institute of Technology, I discussed a few possibilities — some of which were my own ideas, some of which came from Getnet or other Ethiopian scientists or technologists in conversation:

• AI-based modeling, prediction & decision support for economic growth. This would require the creation of a comprehensive database of information regarding the Ethiopian economy — which would be a good thing in itself. Exploring this possibility in depth turned up various subsidiary problems, such as the fact that much of the needed data exists only in Amharic textual format, and no available solution for Amharic OCR exists.
• Smart power grids. I’ve previously done work using the OpenCog AI system to predict power transformer failures. This sort of application is extremely interesting to Ethiopians, given their rapidly growing and sometimes rickety power grid
• AI-controlled microdrones — these are already in use for surveillance purposes, but supplying them with better machine vision could allow them to be used more broadly, e.g., to survey crops and track the spread of agricultural disease. Similar technology could enable microdrones to be used to help with mining prospecting.
• AI-powered bioinformatics, such as I’ve been doing with Biomind, could be used to help understand Africa-specific health problems, and help accelerate genetic engineering of crops
• AI dialogue systems, accessible via cellphone, could be used to provide medical & other decision support
• AI tutors, provided via smartphone, could enhance the education system. The reason why 30% or more primary school graduates don’t attend high school is mainly transportation. If there’s no high school in your village, it may be a very long commute to and fro to high school, which is especially problematic if your help is needed around the house and farm. Tele-education may be part of the solution.
• Smartphone-based medical diagnostics. With a microscope attachment, a smartphone can analyze blood samples and message the pictures to servers where AIs or human doctors can analyze them. A host of other portable, automated diagnostic possibilities exist — this is related to the current Tricorder X-Prize.

My seminar at the university overall was 2.5 hours in length, covering a variety of topics including Singularity, AGI, AI-based bioinformatics, life extension and machine learning.

The academic, programming and engineering expertise exists in Ethiopia, right now, to carry out nearly all of these things. Furthermore, the government has sufficient funds and motivation to pursue these sorts of projects. A number of government officials attended my seminar, and some asked probing questions.

What seems to be lacking at the moment is any organization oriented toward carrying out these sorts of applications. Perhaps in time, Addis Ababa University will formalize an organization similar to MIT Media Lab, bringing together scientists and engineers with various backgrounds to creatively address Ethiopia’s issues and opportunities using AI and other advanced technologies.

How Ethiopia might help AI — and the software industry

Contemporary Addis Ababa gives one the feeling of immense energy and enthusiasm — much of which is untapped. In spite of the rapid growth, unemployment remains high, even among the college educated. I was amazed to find that fully competent computer programmers, with knowledge of languages like C++ and Java as well as the theory of algorithms and data structures and so forth, are generally paid around US$100/month.

Even experienced experts may earn only double that. The cost of living in Ethiopia is also quite low by international standards, with reasonable-quality apartments available for $90/month and others as inexpensive as $20/month (though one can also pay $2000/month or more for a large and luxurious accommodation). But from a business perspective, this seems to pose an interesting opportunity.

The Ethiopian infrastructure is still at an early stage of development, but for some industries, this doesn’t matter that much. Software is a good example. The average Internet bandwidth in Ethiopia is distressingly low, but for a relatively modest price one can get a decent connection (say, hundreds of U.S. dollars per month). And the bandwidth situation is rapidly improving. Computer hardware and repair are readily available.

There’s no fundamental reason that I can see why Ethiopia shouldn’t have a booming software outsourcing industry. The cost of outsourcing to traditional locations like India, China and Eastern Europe is rapidly increasing, causing outsources to look to other locations such as Vietnam. But the prices Ethiopia offers are hard to match.

I’m speaking about Ethiopia in this context because it’s the place I happen to have made contacts and gained knowledge — but it’s highly possible that some other African countries may offer similar opportunities. One thing that may make Ethiopia especially appropriate, however, is its relatively high-quality education system. Programming and algorithms are about the same anywhere. Where technical matters are concerned, the students and faculty I met at Addis Ababa University might just as well have been at any engineering school in the developed world.

Of all the advanced technologies pushing directly toward Singularity, AI distinguishes itself by requiring the least resources. Nanotech, robotics and biotech require expensive lab equipment, which is difficult to maintain appropriately in a location like Ethiopia, where spare parts are far away. But AI just requires computers and smart programmers, and an Internet connection.

Ethiopia has all of those, and at a remarkably low price. So it seems quite possible that Ethiopia, and other developing countries, could end up serving as the engines of AI advancement — maybe even the location of the breakthrough from narrow AI to Artificial General Intelligence.

Actually, I’m not sure the breakthrough to AGI will occur in any one place — if it’s the OpenCog project I co-founded that makes the breakthrough, then it will occur in a globally distributed manner, since OpenCog developers are working on multiple continents round the clock.

But there’s no reason a major contribution to such an effort can’t be made by teams in developing countries, taking advantage of the unique opportunities offered by their developmental stage. This is a possibility I’ll be actively exploring via ongoing conversations with my Ethiopian colleagues.

The author at Alcor (credit: Ben Goertzel)

This past weekend I attended the Alcor 40 conference, hosted by the cryonics organization Alcor to celebrate its 40th year of operation, and I was extremely impressed.

(Full disclosure: I am an Alcor member, signed up in 2005 so that in the unfortunate event my body comes to meet the criteria of legal death, they will preserve it in liquid nitrogen until the advance of technology is sufficient to allow my reanimation in one form or another.)

The crowd consisted largely but not entirely of Alcor members; there was also a fair number of non-members interested in the technology and ideas. A bunch of folks signed up as members during the conference, as well.

Cryonics meets mainstream science

I was expecting some excellent talks on the current state of cryonics technology, from the particulars of preservation via vitrification with powerful cryoprotectants, to the pragmatics of transitioning a recently deceased body from the site of death to Alcor’s facilities. And the talks on these topics were indeed worthwhile, giving me faith that, in spite of quite limited funding for research and operations, Alcor is steadily improving all dimensions of their practice. Alcor’s new CEO Max More started in the position fairly recently, and from what I can tell he’s been doing a very professional job.

What surprised me was the depth of the talks on longevity science and neuroscience. One definitely got the feeling that cryonics is not nearly as marginalized as it was a decade ago or even five years ago, and is now accepted as a reasonable pursuit by a rapidly increasing subset of the scientific community.

Of course, this is part of a larger trend of the gradual mainstreaming of transhumanist technologies. AGI and nanotechnology, for example, were laughed at by most academics in relevant fields just 10–20 years ago. Now they are much more broadly acknowledged as valid and important pursuits, though there are still differences in vision between the maverick advocates and the interested folks in the academic mainstream.

Regarding longevity, along with some other interesting talks we saw a reprise of the debate between Aubrey de Grey and Michael Rose that occurred at the Humanity+ @ Caltech conference in 2010. Aubrey reported the latest results from his SENS project, including recent tests from a therapy that resolves some but not all of the neural damage associated with Alzheimers disease. Michael Rose presented a strong evolutionary argument for following a Paleo diet, especially for folks aged 40 or over, and presented results of recent experiments with flies on different diets to indirectly support his claim.

[More full disclosure: I consult for Genescient, the firm Michael Rose co-founded to study the genomics of long-lived flies he evolved in his lab. More on that here.]

While the two advocated different approaches, both talks were in the vein of “How to avoid the need to be cryo-preserved, or at least delay it as long as possible.”

Connectomics and cryonic versus chemical brain preservation

The session on brain preservation, with MIT neuroscientist Sebastian Seung and Janelia Labs neuroscientist Ken Hayworth, was perhaps the most interesting from my personal perspective.

Seung has recently written a trade book called Connectome, focused on the hypothesis that the human mind is contained in the neural connectivity structure of the human brain. As he put it:

“Hypothesis: You are your connectome. Your connectome is unique and contains a huge amount of information. That information includes your memories, personality and other aspects of your personal identity.”

Connectome devotes a chapter to cryonics. As he pointed out in his talk, this chapter brought him protests from both the cryonics community and some of his scientific colleagues. Some of his colleagues wondered why he was speaking relatively positively of such wacky stuff. But some cryonicists, such as Ralph Merkle, took exception to the way Seung associated cryonics with religions feelings and inclinations.

Seung also touted eyewire.org … a “citizen science” website, focused on mobilizing volunteers to interact with AI to help map the retinal connectome.

Hayworth discussed the possibilities of brain preservation via chemopreservation, such as plastination, an alternative to cryopreservation such as Alcor currently practices. He also presented the Brain Preservation Prize, a prize to be offered to the first team to prove successful preservation of a human brain’s connectome according to specified criteria. The Brain Preservation Prize is agnostic regarding technique — Hayworth’s own work focuses on chemical preservation, but the prize itself may be awarded to a team doing chemical, cryonic or any other kind of preservation.

While both researchers expressed confidence that the human self and memory are most likely implicit in the brain’s connectome, neither was willing to wholly rule out that other aspects of brain structure might be important, e.g., details of the molecules in the brain beyond mere neural connectivity. As Seung noted, “It’s not enough to say that what you do is based on the best knowledge that neuroscience has to say. Neuroscientists don’t know how the brain works….”  Their consensus seemed to be that, even if ultimately other aspects of the brain prove important too, the connectome — with its trillions of inter-neural connections, adding up to millions of miles in total — is definitely the place to start.

The panel discussion following their talks featured intriguing back-and-forth regarding the benefits and problems associated with both cryonic and chemical preservation of human brains.

An obvious, major difference between the two approaches to brain preservation is: If cryoporeservation is done sufficiently well, it may be plausible to re-animate the cryopreserved person simply by defrosting them in a sufficiently gentle way, and infusing them with appropriate chemicals. On the other hand, if a brain is plastinated, for example (a common method of chemical preservation), then there’s no way to revive that brain without advanced nanotechnology. Instead one has to count on reading out the preserved brain’s connectome; and then re-creating the connectome and hence, presumably, the associated mind in some other substrate.

But it’s not clear that, even given recent advances in cryopreservation technology, it can match the precision with which chemical preservation techniques preserve the connectome and other aspects of brain structure. This is a tricky but important research issue, since cryonic technology is rapidly developing, and since the technology for reading brain structure out of cryopreserved brains is not all that mature (the standard method now involves chemically preserving the cryopreserved brain and then studying it).

The Brain Preservation Prize seems like a great idea, and hopefully will be first in the line of a series of prizes aimed at pushing brain and body preservation technology forwards.

Touring Alcor’s Facilities

(Credit: Alcor)

The conference talks spanned Saturday morning and afternoon and Sunday morning. Sunday afternoon was devoted to a barbecue and a tour of Alcor’s facilities. The barbecue was tasty but the tour was more interesting. The facilities were modern, clean and well-organized, giving the feeling of a top-notch medical establishment. A 3D printer was in evidence, being used to manufacture various doohickeys needed to maintain and enhance the lab equipment, as well as to create small plastic souvenir models of the “Dewar” chambers in which Alcor’s patients are maintained.

Seeing the equipment used to perfuse recently deceased bodies and brains with cryoprotectant chemicals was interesting. But the high point was, of course, the room full of Dewars containing cryonically preserved bodies, waiting for technology to mature sufficiently to enable their reanimation. A thick, bulletproof glass window allows visibility into the Dewar room from the main Alcor conference room — a set-up that doubtless provides Alcor staff with a vivid reminder of what their work is all about, as they carry out their meetings.

My tour through the Alcor facilities was very ably conducted by Alcor CEO Max More. Longevity guru Aubrey de Grey, also taking part in the tour, provided helpful commentary along the way, displaying his own sound knowledge of cryonics procedures and technology.

All in all, it was an interesting and educational weekend. Alcor’s professionalism gives me reasonable faith that, in the unfortunate event I need to make use of their services, my preserved body will be well taken care of.

And now I’ll get back to my usual pursuits — such as working on AGI and on the genomics of longevity — which I hope will obviate the need for me ever to take up residence in one of Alcor’s shiny silver Dewars.

As I always say when discussing cryonics, “Better frozen than rotten…. But, better living than frozen.”

Reprinted with permission from H+ Magazine

Muse wearable brainwave headband (credit; InteraXon)

Finally: a brainwave-sensing gadget disguised as a stylish wearable headband that would fit right in with Google Glass … and not make you look like a Fringe experiment run amok.

InteraXon just announced its Muse tonight. It’s available for pre-order now on crowd-funding platform Indiegogo (to raise $150,000) and due out in Spring 2013, the company says.

It’s not clear to me yet how this gadget differs from other EEG headset devices*, but features include wireless connection to your smartphone or tablet via Bluetooth (iPhone, iPad, Android, Mac, PC, and Linux), and rechargeable battery that lasts for 10 hours of continuous use.

Pricing: $135 including shipping during the first week of the Indiegogo campaign, then $165 until December 7; after that, $199 retail.

Muse (credit: InteraXon)

The company says they’ve been working with neuroscientists (no names provided yet) “under a federal grant right now; they include Dr William Tays, Dr Sylvain Morano, and Dr Norm Farb at Rotman Brain Institute in Toronto,” InteraXon CEO Ariel Garten told KurzweilAI. “Other collaborators have included Tiago Falk, Tim Mullins, Peter Carlen, Kostas Plataniotis (biosignals), and others.” They have also been working with cyborg Dr. Steve Mann, famous for his escapade with McDonald’s in Paris.

InteraXon says it will be designing apps for gaming, memory training, fitness, brain health, stress reduction, education, music, and entertainment, plus there’s a free SDK.

Garten has promised more details Monday morning. InteraXon is based in Toronto are best known for a PR stunt at the 2010 Olympics in Vancouver, with people lighting up three major Canadian landmarks with their brainwaves.

Meanwhile, I’m placing my pre-order. This thing definitely looks awesome.

* Update from InteraXon CEO Ariel Garten: ”We differ from the other EEGs on the market in a few ways: we are a four-sensor system, which gives you good fidelity and coverage in a discreet form factor. All the channels are independent from each other and the reference, giving robust readings.”

UPDATE 12:10 a.m. PDT 10/22/2012 from CEO Ariel Garten, as noted in two locations above.

UPDATE 9:30 a.m. PDT 10/22/2012: end date for Indiegogo funding: Dec. 7

Want double fries with that Big Mac? No prob — just ask for a side order of FGF21! (Credit: McDonald’s)

Woo hoo! 

UT Southwestern Medical Center researchers have found that a starvation hormone markedly extends life span in mice without the need for calorie restriction.

Yes! I am sooo ready. I’ve waited years to have  fries!

Restricting food intake has been shown to extend lifespan in several different kinds of animals. But in the UT study, the researchers found transgenic mice that produced more of the hormone fibroblast growth factor-21 (FGF21) got the benefits of dieting without having to limit their food intake.

Male mice that overproduced the hormone had about a 30 percent increase in average life span and female mice had about a 40 percent increase in average life span,” said senior author Dr. Steven Kliewer, professor of molecular biology and pharmacology.

Yeah, yeah, but where can I get some of that FGF21? Let’s get to the point here!

The study published online in eLife — a new peer-reviewed, open access journal — defined average life span as the point at which half the members of a given test group remained alive. A study to determine differences in maximum life span is ongoing: While none of the untreated mice lived longer than about 3 years, some of the female mice that overproduced FGF21 were still alive at nearly 4 years, the researchers report.

FGF21, a hormone secreted by the liver during fasting that helps the body adapt to starvation, seems to provide its health benefits by increasing insulin sensitivity and blocking the growth hormone/insulin-like growth factor-1 signaling pathway.  When too abundant, growth hormone can contribute to insulin resistance, cancer, and other diseases, the researchers said.

“Prolonged overproduction of the hormone FGF21 causes mice to live extraordinary long lives without requiring a decrease in food intake. It mimics the health benefits of dieting without having to diet,” said co-author Dr. David Mangelsdorf, chairman of pharmacology and a Howard Hughes Medical Institute (HHMI) investigator at UT Southwestern.

“Aging and aging-related diseases represent an increasing burden on modern society. Drugs that slow the aging process would be very desirable. These findings raise the possibility of a hormone therapy to extend life span,” said Dr. Mangelsdorf, who runs a research laboratory with Dr. Kliewer. They first identified FGF21’s starvation-fighting effects in a 2007 study.

OK, shoot me up, doc!

Lead author Dr. Yuan Zhang, an instructor of pharmacology, said the study was considered risky because all involved understood it would be at least two years — an average mouse life span — before there would be any evidence of whether elevated production of FGF21 would affect longevity.

Two years??!! I was planning to have a happy meal this afternoon!

Previous research has found that FGF21 can reduce weight in obese mice. The mice that overproduced FGF21 in this latest study were lean throughout their lives and remained lean even while eating slightly more than the wild-type mice, the researchers said.

The hormone does have some downsides: FGF21 overproducers tended to be smaller than wild-type mice and the female mice were infertile. While FGF21 overproducers had significantly lower bone density than wild-type mice, the FGF21-abundant mice exhibited no ill effects from the reduced bone density and remained active into old age without any broken bones, the researchers said.

Huh? Can’t they fix that?

“FGF21 is not affecting their mobility. These guys are spry. They live nice, long lives,” Dr. Kliewer said. “But the decreased bone density and female infertility will require additional research to determine if it is possible to separate out the hormone’s life span-extending effects from its effect on bone,” he added.

Wait, you mean this only works for mice? 

The study was supported by the National Institutes of Health, the Robert A. Welch Foundation, the Leona M. and Harry B. Helmsley Charitable Trust,and the HHMI.

(Credit: 20th Century Fox)

I’ve been sort of playing around with the concept — “Steal This Singularity” — for several months now. Prior to attending Singularity Summit 2012, I was thinking about it in political terms.

Letting “Singularity” represent, essentially, a buzz word for a future radically transformed by technology, my “Steal This Singularity” notion was simply that the transhuman future should not be dominated by big capital and/or authoritarian government; and that — contrary to the reassurances of many glib futurists — this requires some intentionality, both in terms of programming and activism.

The technology doesn’t insure this by its very nature. And the current general trend in this regard is not positive, but extremely ambiguous at best. But I’ll save that for another essay.

Recoding/uncoding the programming/engineering monkey-mind

Upon spending an afternoon at Singularity Summit and spending an evening vicariously experiencing Joaquin Phoenix’ trickster walkabout, another feeling emerged and, with it, a different sort of “Steal This Singularity” theme. To wit: the clever, logical, programming/engineering monkey-mind should not be allowed to instantiate its limited idea of humanity, the universe and everything, on… well… humanity, the universe and everything.

The tricksters, the freaks, the surrealists, the hedonists, the outsiders — and all the uncodable strangeness that emerges from the biological codes’ diversification into cultural complexity and then into something as perverse and rationally pointless as a multilayered prank in a cinematic celebrity culture — must hijack the engineer’s Singularity and recode it or uncode it so as to allow for liminal spaces outside its totalizing grasp.

We live in a time in which seemingly smart humans love to present us with absolute dualistic options: Republican or Democrat, socialist or free market; believer or atheist; Britney or Christina; Science or Superstition. These discourses are dominant even among an intellectual class that used to know better; and the notion that there could be terrain outside those frames becomes, well, not exactly unthinkable but somehow too trivial to consider as anything but a sideshow.

I’m aware of the risk here in even implying that the instantiation of the biases of the engineering monkey mind over everything is a conscious or unconscious intention that undergirds much of the Singularitarian sensibility. Singularitarianism and — more broadly — transhumanism — has produced a veritable glut of abstract theorizing, so whatever novel perceptions or objections or concerns one may think one is bringing to the party, some smarty pants has probably swatted it away or incorporated it into its logical totality.

Sex and the Singularity

On the other hand, if there was a role for artists in Singularity Summit 2012, I didn’t notice it. Sex — a primary desire for most humans — seemed to be almost unmentionable, if not entirely archaic. Heightened subjective states of consciousness — ecstasy, agape, rapture — seem to be well off the map.

Of course, it’s part of the culture of science that legitimacy requires the maintenance of a bordering-on-Calvinist front, but consider that when I interviewed (with Surfdaddy Orca) Ray Kurzweil for H+ magazine a few years ago, and suggested that the idea of utopia might involve people feeling good and being happy, he immediately leapt to a vision of people hanging around all the time on a morphine-like high.

(I actually think several billion human beings acting out the sort of western ideal of ambitiousness with Singularitarian technology is probably scarier than having most of them in an opiated haze, but I don’t think those are the only options. Anyway, that’s a different rant for a different time.)

This lack — this apparent negligence or denial or trivialization of non-obvious aspects of subjective human experience and peculiarity — may prove to be of minimal importance if transhuman techno-evolution stops short of the Singularity.

A diversity of mindstyles

If we don’t design silicon intelligences that will, for all intents and purposes, replace us — or at least dominate our original biological brains if we take them within us — but, if rather, we simply end up with tools that amplify and enhance, then there’s a reasonable hope for a diversity of mindstyles.

Some will gather in Less Wrong communities where they will continuously refine rationality; some will live in an eternal, amplified Burning Man of lived art, presentation and playful deviance; most will dip into both these and other memeplex scenes while engaging in a world rich in opportunity for all possible expressions of humanness or posthumanness.

But supposing that we do create the vastly superior intelligence. Even if we merge with them, what aspects of humanness that some of us may wish to preserve will be overwhelmed? Will the imp of the perverse, as displayed in my Joaquin Phoenix example, still stun our predictable mentations into momentary silence? Can the engineered superior intelligence experience something as evocative, or is that too vague?

Will some of us still be driven into ecstasy dancing to James Brown? What happens to the human characteristics that have given us characters like Arthur Rimbaud, Salvador Dali, Bob Dylan… you know, people who don’t make any goddamn sense? And what the fuck did Nietzsche mean we he wrote, “I tell you. One must still have chaos within oneself, to give birth to a dancing star.”?

My next Steal This Singularity entry will take on the more sober political and economic implications of the concept.

Excerpted with permission from ACCELER8OR

“The only difference between me and a madman is that I am not mad.” — Salvador Dali (credit: Wikipedia)

Well, this might explain some of my wackier blog posts.

People in creative professions are treated more often for mental illness than the general population, especially writers, according to researchers at Karolinska Institute, whose large-scale Swedish registry study is the most comprehensive ever in its field.

Either that, or Swedes are crazier. Hey, I’m kidding!

Last year, researchers showed that artists and scientists were more common among families where bipolar disorder and schizophrenia is present, compared to the population at large.

They later expanded this to many more psychiatric diagnoses — such as schizoaffective disorder, depression, anxiety syndrome, alcohol abuse, drug abuse, autism, ADHD, anorexia nervosa and suicide — and to include people in outpatient care rather than exclusively hospital patients.

Now they’ve tracked almost 1.2 million patients and their relatives, identified down to second-cousin level. Since all were matched with healthy controls, the study incorporated much of the Swedish population from the most recent decades.

Like their previous study, they found that bipolar disorder is more prevalent in the entire group of people with artistic or scientific professions, such as dancers, researchers, photographers and authors. Authors specifically also were more common among most of the other psychiatric diseases (including schizophrenia, depression, anxiety syndrome and substance abuse) and were almost 50 per cent more likely to commit suicide than the general population.

CureCelebrate your madness!

The researchers also observed that creative professions were more common in the relatives of patients with schizophrenia, bipolar disorder, anorexia nervosa, and, to some extent, autism. But according to Simon Kyaga, consultant in psychiatry and doctoral student at the Department of Medical Epidemiology and Biostatistics, we should reconsider approaches to mental illness.

“If one takes the view that certain phenomena associated with the patients’ illness are beneficial, it opens the way for a new approach to treatment,” he says. “In that case, the doctor and patient must come to an agreement on what is to be treated, and at what cost.”

“Twisted” by Joni Mitchell | lyrics

“Genius” by Pitchshifter | lyrics

What will AIs learn from the Ant Nebula about the future demise of our Sun? (credit: NASA JPL)

In What our civilization needs is a billion-year plan, posted on KurzweilAI September 23, 2012, Lt Col Peter Garretson calls for a long-term plan to assure humanity’s survival, “moving everyone and everything we value off Earth.”

He cites the coming big extinction events for planet Earth, including asteroid collisions, the Sun engulfing the Earth during its transformation to a red giant, and ultimately, the heat death of the Universe. Human survival, he argues, justifies an ambitious future space program, “with articulated goals of space development and space settlement … pushing the technology and logistical capabilities to be able to attain those goals.”

To accomplish this, he predicts, people (perhaps augmented) will be the great interstellar engineers — in charge of intelligent civilization over the next few billions of years.

Unfortunately, Garretson does not mention the single most important development in the future: the coming technological Singularity, when machine intelligence will surpass human intelligence, leading to “technological change so rapid and profound it will represent a rupture in the fabric of human history,” according to Ray Kurzweil.

Is humanity capable of planning beyond the Singularity?

I agree that long-term planning is essential, but our political process in the U.S. barely allows planning beyond the next election. (Look at any session of Congress on C-SPAN for an hour. Does that look like the face of wisdom that we want to draft a billion year plan?)

Looking at the march of evolution through the eyes of Teilhard de Chardin or Arthur C. Clarke, a prevailing belief (held strongly by me) is that humanity is not the last word in intelligence or its highest expression. Rather, we are just a warm-up act — a stepping stone to what comes next in evolution.

But meanwhile, humanity (all 7 billion of us) is a mixed curse. Throughout our history, we have seen the face of evil with the megadeaths of the Stalin Era, with Hitler during the Third Reich, in Cambodia during the Pol Pot regime, during the Rwanda massacres, and currently in Syria. (The Civil War, the bloodiest war in U.S. history was a mere 150 years ago.) That is humanity’s inhumanity to man.

To other species we are even worse — they don’t even count. Except among environmentalists, there is usually not much protest, as the scourge of our propagation envelopes Planet Earth with new homes, roads, buildings, agribusinesses, and dumps. The loss of habitat is leading to an extinction rate comparable to that of the Cretaceous era with an asteroid strike 65 million years ago.

Earth 2050? (credit: iStockphoto)

The biosphere of Planet Earth is one large garbage dump. We have poisoned the soil, rivers, oceans, and atmosphere. The exhaust from our civilization creates more than 98% of new CO2 flowing into the atmosphere. It is likely that the IPCC has underestimated the extent to which Earth will warm during this century: a 5 degrees C rise is quite possible according to Paul Ehrlich).

A catastrophic disruption to agriculture may precipitate global resource wars. The numerous feedback mechanisms among global warming, global toxification, declining ecological services (e.g., death of pollinators), and overpopulation all point toward collapse (video). This litany of threats has been widely documented by Paul Ehrlich, James Hansen, and others.

As another 2.5 billion people are added to the planet by 2050, catastrophic collapse may be all but inevitable. We may not make it to the Singularity.

Can future enhanced humans solve these problems?

Transhumans to the rescue? (credit: iStockphoto)

If our civilization produced literary and scientific giants like Shakespeare and Einstein, isn’t it reasonable to expect that humans augmented by new drugs, stem cells, implants, etc. will be even more talented and will be the astronauts who will build Garretson’s Dyson spheres and travel to the stars?

My answer is no. First, despite future medical advances, drugs, biologicals, and devices intended for human use always require lengthy and costly testing. At present, a new drug typically requires at least ten years and a billion dollars to develop. Frustratingly slow, speaking as a former emergency-room physician!

Several neurobiologists have published articles and videos that promote scanning and uploading the detailed microanatomy of the human brain (Sebastian Seung, Stephen Smith, Randal Koene, Ken Hayworth, and Anders Sandberg.)

I’m optimistic that such an approach will help to elucidate the principles of neurophysiology, but I have reservations (some are discussed here): the role of local fields and oscillations, the roles of glia and of gap junctions, and unexplained intricacy at synapses). I side more with Tony Movshon than with Sebastian Seung in this must-see debate.

But, suppose my “head freezer” friends succeed in being immortalized as was Han Solo in Star Wars when he was embedded in carbonite. Whether run on a mainframe or downloaded into a new titanium exoskeleton in 2100, Humanity 2.0 will still have all our current psychological failings (detailed by Daniel Kahneman in Thinking Fast and Slow).

More fundamentally, early design commitments, frozen into us as we evolved from single cells over billions of years were superbly adapted to local materials and conditions on Earth but are not suitable for space. It’s time for replacement. You cannot make a (bio) neuron that spikes at 3 Ghz or that conducts neural impulses at 300 million meters per second. (The way to speed up a cheetah is not by strapping on a jet engine.)

I also reject Kurzweil’s premise that we will merge with AIs — that’s like merging that cheetah with a jet plane.

AIs as the next intelligence carriers

Instead of humans, post-Singularity AIs (not us) will be the highest intelligences. And they will be calling the shots on design and execution of massive space-based engineering projects a la O’Neill and Dyson.

Long-term, humanity (whether augmented, re-engineered, or uploaded) will be left in the dust by the machines, who will stand in relation to us as we to bacteria. OK, that has a heavy-metal Skynet ring to it, so let me replace it immediately by a term I’ve come to love (from David Grinspoon’s book Lonely Planets): the Immortals.

Who are the Immortals? Perhaps we know who we want them to be: wise, superintelligent, compassionate, and just. And powerful! More powerful than a light-speed rocket, able to leap into intergalactic space in a single bound, and imbued with truth, justice, and the Western democratic way!

Whatever we choose to call them, further evolution of themselves and their tools will be in their hands and not ours. While future advances will greatly benefit humans, humans will be replaced as the helmsmen of a space-faring civilization before the Singularity — probably by 2040 (Philip K. Dick nailed this prediction in Blade Runner).

The evolving prototypes that will eventually leap to the stars will be electronic — informed by human design and concerns, but not constrained by them. Their decisions and wisdom will encompass all that is on the Web and all that is perceived by the world’s sensors. With a solar system full of effectors they will accomplish engineering that we cannot imagine. That is how they will begin their evolution and their journey to the stars.

So let’s leave the really long term planning (post-Singularity) to the Immortals.

Sometime before the Cambrian era 500 million years ago, the first differentiated, multicellular creatures arose. As the reproductive unit changed from a single cell to a multicellular organism, the individual cells had surrendered their autonomy for a greater chance of survival.

I think about the coming superorganism as something that will (at least initially) encompass human beings and confer upon them greater survival and quality of life (see Greg Stock’s Metaman). Just as the Web will embrace all of humanity and our culture, machines will evolve that understand and contribute to the Web.

Robots will autonomously update their databases and plans from the Web. The “rise of the machines” and their gradual metamorphosis into the wise Immortals won’t take place overnight. This will be a gradual evolution, dictated as always by “technology push and demand pull” (initially from human consumers, later from AI consumers).

So what projects should we humans undertake now?

Major spoiler (credit: Don Davis/NASA)

These predictions  will not happen automatically as a consequence of accelerating technology. They will require concerted science and engineering specifically focused on AI, including machine learning, robotics, computer vision, and knowledge representation; non-von Neumann architectures including neuromorphic engineering and other large-scale parallel designs; materials science; neurobiology; neural nets and cognitive science (to mine their principles), and the mathematics of dynamical and stochastic systems (among others).

Funding this type of R&D is civilization’s near-term path to the stars.

To advance the ball down the field, a thriving, productive, high-tech human civilization may be required for another century or two. Whatever slows or halts that development might kill this development.

As Garretson has pointed out, the spoilers include all those near-term, extinction level catastrophes that could derail the phase transition of intelligence: asteroids, propagation and rogue use of WMDs (nuclear and biologic), accidental worldwide war, pandemics, ecologic calamities, resource depletion, natural disasters, economic and societal chaos, etc.

There are also possible theoretical spoilers. Perhaps it is simply not possible to create intelligence or consciousness at parity with humans for as-yet-unknown reasons, famously argued by Roger Penrose. But recent progress in computer vision (Google Driverless Car) makes me intensely skeptical of these limitations.

Primates in Space

(Credit: Wikimedia Commons)

Unfortunately, the current funding environment for science and engineering is extremely limited, so NASA and DOE have had to kill promising projects in annual and decadal reviews.

For example, it was two decades before the spectacularly successful Kepler telescope was funded. The SETI Project, formerly a part of NASA Ames, lost its funding 15 years ago. The promising Terrestrial Planet Finder was cut and even the Hubble repair mission — another spectacular success — had to beg for funding. The vital follow-on to Hubble, the James Webb Telescope (JWST), has limped along with continued funding always in doubt, and the launch is now pushed back to 2018.

Manned space missions typically cost 100X the price of unmanned missions without a commensurate return. Put another way, a single manned expedition may kill scores of science-based, unmanned robotic probes and telescopes. The example du jour is the MSL/Curiosity rover now on Mars.

It cost (a mere) 2.5 billion dollars, in comparison to a manned mission that will cost 100X as much, if funded. My views on manned spaceflight coincide with those of Astronomer Royal Sir Martin Rees (video). I favor humans on the Moon but not on Mars — the key difference is travel time.

Putting humans into space requires the launch of consumables (food, water, shielding, medical supplies) and engenders great concern and over-engineering to assure safe return of the astronauts. Mars missions that are being sketched out for the late 2020s would involve at least two other launches to pre-position caches of consumables.

In 2012 it is easy to tout the superior dexterity, adaptability, intelligence, and autonomy of humans over robots. In 2025 to 2030, when the earliest manned Mars missions might be launching, it is far less clear whether astronauts’ superior abilities will justify their 100-fold expense. When we hit 2100, it’s surely game-over for what I call “primates in space” — which began with the Astrochimps Ham and Enos that orbited in the early sixties.

Ad astra

(Credit: PAC-Caltech)

My view is that humans or other species will go to the stars, only if the Immortals (the AIs) think it is desirable/cost-effective to do so.  I think they will want to transport us away from Earth to prevent our destruction.

Just as our biologists delight in the manifold diversity of Nature, I believe that the Immortals will be interested in preserving and studying us and many other species. Like anthropologists they may find value in studying our primitive culture.

If they decide to transport us, they will easily be able to do so. An old idea (on which I based an unpublished novel  that my cell biologist son grew up with) is simply to transport the DNA sequences of a collection of humans and other animals to a remote in vitro fertilization machine constructed from local material in a distant world.

So, what’s to become of humanity? My view is that we primates will be on Planet Earth for a long time (even if augmented). My hope is that we mature into a wise old race of beings living in harmony with our biosphere.

Humans may even achieve immortality as predicted by Aubrey de Grey’s SENS (but perhaps not on his ambitious timescale).

I glossed over the crucial notion of whether the Immortal AIs will share our values or our feelings — and the key issue of Friendly AI. I can only prognosticate that they will share our values over the next several decades of development. In doing so (by incorporating human values into their utility functions or emulating human emotions) they will assure their commercial success as assistants (SIRI and Asimo), researchers (Watson), or drivers of our cars (Google car). (I’m personally skeptical of the efficacy of friendly AI long-term, concurring with Hugo de Garis; but read Steve Omohundro’s defense here.)

To paraphrase the quote from Lee Valentine that closes Garretson’s article: Mine the sky (by the AIs). Defend the Earth (by humans now, later by AIs). Settle the stars (by the Immortals — our mind children — if we do our job as good parents).

(Credit: iStockphoto)

As we noted in a recent post, physicist David Deutsch said the field of “artificial general intelligence” or AGI has made “no progress whatever during the entire six decades of its existence.” We asked Dr. Ben Goertzel, who introduced the term AGI and founded the AGI conference series, to respond. — Ed.

Like so many others, I’ve been extremely impressed and fascinated by physicist David Deutsch’s work on quantum computation — a field that he helped found and shape.

I also encountered Deutsch’s thinking once in a totally different context — while researching approaches to home schooling my children, I noticed his major role in the Taking Children Seriously movement, which advocates radical unschooling, and generally rates all coercion used against children as immoral.

In short, I have frequently admired Deutsch as a creative, gutsy, rational and intriguing thinker. So when I saw he had written an article entitled “Creative blocks: The very laws of physics imply that artificial intelligence must be possible. What’s holding us up?,” I was eager to read it and get his thoughts on my own main area of specialty, artificial general intelligence.

Oops.

I was curious what Deutsch would have to say about AGI and quantum computing. But he quickly dismisses Penrose and others who think human intelligence relies on neural quantum computing, quantum gravity computing, and what-not. Instead, his article begins with a long, detailed review of the well-known early history of computing, and then argues that the “long record of failure” of the AI field AGI-wise can only be remedied via a breakthrough in epistemology following on from the work of Karl Popper.

This bold, eccentric view of AGI is clearly presented in the article, but is not really argued for. This is understandable since we’re talking about a journalistic opinion piece here rather than a journal article or a monograph. But it makes it difficult to respond to Deutsch’s opinions other than by saying “Well, er, no” and then pointing out the stronger arguments that exist in favor of alternative perspectives more commonly held within the AGI research community.

I salute David Deutsch’s boldness, in writing and thinking about a field where he obviously doesn’t have much practical grounding. Sometimes the views of outsiders with very different backgrounds can yield surprising insights. But I don’t think this is one of those times. In fact, I think Deutsch’s perspective on AGI is badly mistaken, and if widely adopted, would slow down progress toward AGI dramatically.

The real reasons we don’t have AGI yet, I believe, have nothing to do with Popperian philosophy, and everything to do with:

• The weakness of current computer hardware (rapidly being remedied via exponential technological growth!)
• The relatively minimal funding allocated to AGI research (which, I agree with Deutsch, should be distinguished from “narrow AI” research on highly purpose-specific AI systems like IBM’s Jeopardy!-playing AI or Google’s self-driving cars).
• The integration bottleneck: the difficulty of integrating multiple complex components together to make a complex dynamical software system, in cases where the behavior of the integrated system depends sensitively on every one of the components.

Assorted nitpicks, quibbles and major criticisms

I’ll begin here by pointing out some of the odd and/or erroneous positions that Deutsch maintains in his article. After that, I’ll briefly summarize my own alternative perspective on why we don’t have human-level AGI yet, as alluded to in the above three bullet points.

Deutsch begins by bemoaning the AI field’s “long record of failure” at creating AGI — without seriously considering the common counterargument that this record of failure isn’t very surprising, given the weakness of current computers relative to the human brain, and the far greater weakness of the computers available to earlier AI researchers.  I actually agree with his statement that the AI field has generally misunderstood the nature of general intelligence. But I don’t think the rate of progress in the AI field, so far, is a very good argument in favor of this statement. There are too many other factors underlying this rate of progress, such as the nature of the available hardware.

He also makes a rather strange statement regarding the recent emergence of the AGI movement:

The field used to be called “AI” — artificial intelligence. But “AI” was gradually appropriated to describe all sorts of unrelated computer programs such as game players, search engines and chatbots, until the G for ‘general’ was added to make it possible to refer to the real thing again, but now with the implication that an AGI is just a smarter species of chatbot.

As the one who introduced the term AGI and founded the AGI conference series, I am perplexed by the reference to chatbots here. In a recent paper in AAAI magazine, resulting from the 2009 AGI Roadmap Workshop, a number of coauthors (including me) presented a host of different scenarios, tasks, and tests for assessing humanlike AGI systems.

The paper is titled “Mapping the Landscape of Human-Level General Intelligence,” and chatbots play a quite minor role in it. Deutsch is referring to the classical Turing test for measuring human-level AI (a test involving fooling human judges into believing a computers humanity, in a chat-room context). But the contemporary AGI community, like the mainstream AI community, tends to consider the Turing Test as a poor guide for research.

But perhaps he considers the other practical tests presented in our paper — like controlling a robot that attends and graduates from a human college — as basically the same thing as a “chatbot.” I suspect this might be the case, because he avers that

AGI cannot possibly be defined purely behaviourally. In the classic ‘brain in a vat’ thought experiment, the brain, when temporarily disconnected from its input and output channels, is thinking, feeling, creating explanations — it has all the cognitive attributes of an AGI. So the relevant attributes of an AGI program do not consist only of the relationships between its inputs and outputs.

The upshot is that, unlike any functionality that has ever been programmed to date, this one can be achieved neither by a specification nor a test of the outputs. What is needed is nothing less than a breakthrough in philosophy. …

This is a variant of John Searle’s Chinese Room argument [video]. In his classic 1980 paper “Minds, Brains and Programs,” Searle considered the case of a person who knows only English, sitting alone in a room following English instructions for manipulating strings of Chinese characters. Does the person really understand Chinese?

To someone outside the room, it may appear so. But clearly, there is no real “understanding” going on. Searle takes this as an argument that intelligence cannot be defined using formal syntactic or programmatic terms, and that conversely, a computer program (which he views as “just following instructions”) cannot be said to be intelligent in the same sense as people.

Deutsch’s argument is sort of the reverse of Searle’s. In Deutsch’s brain-in-a-vat version, the intelligence is qualitatively there, even though there are no intelligent behaviors to observe. In Searle’s version, the intelligent behaviors can be observed, but there is no intelligence qualitatively there.

Everyone in the AI field has heard the Chinese Room argument and its variations many times before, and there is an endless literature on the topic. In 1991, computer scientist Pat Hayes half-seriously defined cognitive science as the ongoing research project of refuting Searle’s argument.

Deutsch attempts to use his variant of the Chinese Room argument to bolster his view that we can’t build an AGI without fully solving the philosophical problem of the nature of mind. But this seems just as problematic as Searle’s original argument. Searle tried to argue that computer programs can’t be intelligent in the same sense as people; Deutsch on the other hand, thinks computer programs can be intelligent in the same sense as people, but that his Chinese room variant shows we need new philosophy to tell us how to do so.

I classify this argument of Deutsch’s right up there with the idea that nobody can paint a beautiful painting without fully solving the philosophical problem of the nature of beauty. Somebody with no clear theory of beauty could make a very beautiful painting — they just couldn’t necessarily convince a skeptic that it was actually beautiful. Similarly, a complete theory of general intelligence is not necessary to create an AGI — though it might be necessary to convince a skeptic with a non-pragmatic philosophy of mind that one’s AGI is actually generally intelligent, rather than just “behaving generally intelligent.”

Of course, to the extent we theoretically understand general intelligence, the job of creating AGI is likely to be easier. But exactly what mix of formal theory, experiment, and informal qualitative understanding is going to guide the first successful creation of AGI, nobody now knows.

What Deutsch leads up to with this call for philosophical inquiry is even more perplexing:

Unfortunately, what we know about epistemology is contained largely in the work of the philosopher Karl Popper and is almost universally underrated and misunderstood (even — or perhaps especially — by philosophers). For example, it is still taken for granted by almost every authority that knowledge consists of justified, true beliefs and that, therefore, an AGI’s thinking must include some process during which it justifies some of its theories as true, or probable, while rejecting others as false or improbable.

This assertion seems a bit strange to me. Indeed, AGI researchers tend not to be terribly interested in Popperian epistemology. However, nor do they tend to be tied to the Aristotelian notion of knowledge as “justified true belief.” Actually, AGI researchers’ views of knowledge and belief are all over the map. Many AGI researchers prefer to avoid any explicit role for notions like theory, truth, or probability in their AGI systems.

He follows this with a Popperian argument against the view of intelligence as fundamentally about prediction, which seems to me not to get at the heart of the matter. Deutsch asserts that “in reality, only a tiny component of thinking is about prediction at all … the truth is that knowledge consists of conjectured explanations.”

But of course, those who view intelligence in terms of prediction would just counter-argue that the reason these conjectured explanations are useful is because they enable a system to better make predictions about what actions will let it achieve its goals in what contexts. What’s missing is an explanation of why Deutsch sees a contradiction between the “conjectured explanations” view of intelligence and the “predictions” view. Or is it merely a difference of emphasis?

In the end, Deutsch presents a view of AGI that comes very close to my own, and to the standard view in the AGI community:

An AGI is qualitatively, not quantitatively, different from all other computer programs. Without understanding that the functionality of an AGI is qualitatively different from that of any other kind of computer program, one is working in an entirely different field. If one works towards programs whose “thinking” is constitutionally incapable of violating predetermined constraints, one is trying to engineer away the defining attribute of an intelligent being, of a person: namely, creativity.

Yes. This is not a novel suggestion, it’s what basically everyone in the AGI community thinks; but it’s a point worth emphasizing.

But where he differs from nearly all AGI researchers is that he thinks what we need to create AGI is probably a single philosophical insight:

I can agree with the AGI-is-imminent camp: it is plausible that just a single idea stands between us and the breakthrough. But it will have to be one of the best ideas ever.

The real reasons why we don’t have AGI yet

Deutsch thinks the reason we don’t have human-level AGI yet is the lack of an adequate philosophy of mind to sufficiently, definitively refute puzzles like the Chinese Room or his brain-in-a-vat scenario, and that lead us to a theoretical understanding of why brains are intelligent and how to make programs that emulate the key relevant properties of brains.

While I think that better, more fully-fleshed-out theories of mind would be helpful, I don’t think he has correctly identified the core reasons why we don’t have human-level AGI yet.

The main reason, I think, is simply that our hardware is far weaker than the human brain. It may actually be possible to create human-level AGI on current computer hardware, or even the hardware of five or ten years ago. But the process of experimenting with various proto-AGI approaches on current hardware is very slow, not just because proto-AGI programs run slowly, but because current software tools, engineered to handle the limitations of current hardware, are complex to use.

With faster hardware, we could have much easier to use software tools, and could explore AGI ideas much faster. Fortunately, this particular drag on progress toward advanced AGI is rapidly diminishing as computer hardware exponentially progresses.

Another reason is an AGI funding situation that’s slowly rising from poor to sub-mediocre. Look at the amount of resources society puts into, say, computer chip design, cancer research, or battery development. AGI gets a teeny tiny fraction of this. Software companies devote hundreds of man-years to creating products like word processors, video games, or operating systems; an AGI is much more complicated than any of these things, yet no AGI project has ever been given nearly the staff and funding level of projects like OS X, Microsoft Word, or World of Warcraft.

I have conjectured before that once some proto-AGI reaches a sufficient level of sophistication in its behavior, we will see an “AGI Sputnik” dynamic — where various countries and corporations compete to put more and more money and attention into AGI, trying to get there first. The question is, just how good does a proto-AGI have to be to reach the AGI Sputnik level?

The integration bottleneck

Weak hardware and poor funding would certainly be a good enough reason for not having achieved human-level AGI yet. But I don’t think theyre the only reason. I do think there is also a conceptual reason, which boils down to the following three points:

• Intelligence depends on the emergence of certain high-level structures and dynamics across a system’s whole knowledge base;
• We have not discovered any one algorithm or approach capable of yielding the emergence of these structures;
• Achieving the emergence of these structures within a system formed by integrating a number of different AI algorithms and structures is tricky. It requires careful attention to the manner in which these algorithms and structures are integrated; and so far, the integration has not been done in the correct way.

One might call this the “integration bottleneck.”  This is not a consensus in the AGI community by any means — though it’s a common view among the sub-community concerned with “integrative AGI.” I’m not going to try to give a full, convincing argument for this perspective in this article. But I do want to point out that it’s a quite concrete alternative to Deutsch’s explanation, and has a lot more resonance with the work going on in the AGI field.

This “integration bottleneck” perspective also has some resonance with neuroscience. The human brain appears to be an integration of an assemblage of diverse structures and dynamics, built using common components and arranged according to a sensible cognitive architecture. However, its algorithms and structures have been honed by evolution to work closely together — they are very tightly inter-adapted, in somewhat the same way that the different organs of the body are adapted to work together. Due their close interoperation they give rise to the overall systemic behaviors that characterize human-like general intelligence.

So in this view, the main missing ingredient in AGI so far is “cognitive synergy”: the fitting-together of different intelligent components into an appropriate cognitive architecture, in such a way that the components richly and dynamically support and assist each other, interrelating very closely in a similar manner to the components of the brain or body and thus giving rise to appropriate emergent structures and dynamics.

The reason this sort of intimate integration has not yet been explored much is that it’s difficult on multiple levels, requiring the design of an architecture and its component algorithms with a view toward the structures and dynamics that will arise in the system once it is coupled with an appropriate environment. Typically, the AI algorithms and structures corresponding to different cognitive functions have been developed based on divergent theoretical principles, by disparate communities of researchers, and have been tuned for effective performance on different tasks in different environments.

Making such diverse components work together in a truly synergetic and cooperative way is a tall order, yet my own suspicion is that this — rather than some particular algorithm, structure or architectural principle — is the “secret sauce” needed to create human-level AGI based on technologies available today.

Achieving this sort of cognitive-synergetic integration of AGI components is the focus of the OpenCog AGI project that I co-founded several years ago. We’re a long way from human adult level AGI yet, but we have a detailed design and codebase and roadmap for getting there. Wish us luck!

Where to focus: engineering and computer science, or philosophy?

The difference between Deutsch’s perspective and my own is not a purely abstract matter; it does have practical consequence. If Deutsch’s perspective is correct, the best way for society to work toward AGI would be to give lots of funding to philosophers of mind. If my view is correct, on the other hand, most AGI funding should go to folks designing and building large-scale integrated AGI systems.

Until sufficiently advanced AGI has been achieved, it will be difficult to refute perspectives like Deutsch’s in a fully definitive way. But in the end, Deutsch has not made a strong case that the AGI field is helpless without a philosophical revolution.

I do think philosophy is important, and I look forward to the philosophy of mind and general intelligence evolving along with the development of better and better AGI systems.

But I think the best way to advance both philosophy of mind and AGI is to focus the bulk of our AGI-oriented efforts on actually building and experimenting with a variety of proto-AGI systems — using the tools and ideas we have now to explore concrete concepts, such as the integration bottleneck I’ve mentioned above. Fortunately, this is indeed the focus of a significant subset of the AGI research community.

And if you’re curious to learn more about what is going on in the AGI field today, I’d encourage you to come to the AGI-12 conference at Oxford, December 8–11, 2012.

(Credit: iStockphoto)

Dale J. Stephens leads UnCollege, the social movement changing the notion that college is the only path to success. His first book, Hacking Your Education, will be published by Penguin in 2013. Also see the three related posts today (below).

Student/teacher interaction

“What about student/teacher interaction? What about building a social and professional network? How can you get a job without a degree? How will you know you’re succeeding without grades?”

Every seasoned supporter of self-directed education has faced questions like this. If you haven’t yet, you will. Trust me. People often have a hard time understanding how certain elements of education can flourish outside of classrooms. Homeschoolers and unschoolers have found creative solutions — cooperative classes for varying subjects, speech and debate leagues, field trip groups — that decentralize and expand the learning experience.

But what about higher education? Can all the benefits that society associates with traditional higher education be provided and even exceeded with non-traditional methods? The purpose of this post is to look at how startups are doing just that.

UnCollege has written posts with an in-depth look at specific startups, such as Udacity, but here we’re going to take a high-level approach and see how the startup community is providing benefits that traditional higher education institutions claim to have a monopoly on. We’ll do this by focusing on their solutions for content delivery, social interaction, professional feedback, and certification.

Content delivery

If you’ve been following trends in higher education at all, the idea that universities don’t have an edge on content delivery won’t be surprising to you. Institutionalized-ed says that students should learn in a way that allows them to successfully regurgitate information via testing and exams.

Decentralized education says let the student learn in a way that allows them to master the information, not just regurgitate it.. The content is the part of the university that has become most decentralized – it started more than 10 years ago with MIT’s OpenCourseWare and has continued from there.

• Code School is all about not just learning but creation.. Students have a chance to learn and then implement their knowledge throughout the course, so that upon completion the student not only has a workable knowledge of the material, but also the tools to apply it in the real world.
• Udacity emphasizes mastery learning to make sure that students have multiple attempts to demonstrate their new knowledge and only move on when they have completely mastered a subject.

While the content exists, one problem that hasn’t yet been solved is curation — when exploring the Internet, how do you find learning content?. And more importantly, what is good and true?. Startups like LearningJar.com or Learnist are starting to make headway in this area but it’s still a very young space.

Building a community

Campus settings give students the benefit of socializing and networking with other students and teachers. Startups take on this challenge in a variety of ways.

• Livemocha is an online language learning platform. Cultivating a community of language-learners is an important part of their model. They provide a stimulating and safe environment for students to practice their skills with native speakers or tutors.
• Meetup.com is an online network of local groups. You can start or find a group in your area with a huge variety of interests — everything from languages to dancing to education to politics, and lots in between. Udacity even has meetup groups in 292 cities where students can interact and supplement their courses.
• The Open University offers 600+ online courses. They have student forums where students can share and discuss any topics of interest to them.
• Hoot.me lets you convert facebook into study mode to connect with students and tutors around the world.
• Openstudy.com is a social learning network where students can ask questions, give help, and connect to other students studying the same subject.

It’s easy to see that startups actually have the potential to connect students to a much wider network than is available on campus. Students are able to communicate with other students and teachers all around the world, and can also access face-to-face groups using meetup.com. However, this space is still very young.. I envision a day where you can pull out your iPhone, open an app, and walk down to your local coffee shop for a class discussion.

Feedback

Feedback in this case is any way for a student to track and interpret his or her progress. Most non-institutional courses don’t involve grades. How can students evaluate their knowledge?

• Livemocha students receive instant feedback through their interaction with native speakers and tutors.
• Udacity has quizzes built into their videos to ensure that you are understanding the material along the way. There are also problem sets but both quizzes and problem sets are optional and are meant to enhance your learning. Also they offer final exams at the end of the course.
• Code Hero has interactive exercises built into their courses that students must successfully complete before moving on. This allows the students to know they’ve mastered the content before moving on.

In reality, the feedback loop in non-traditional courses tends to be much shorter and more meaningful than a traditional grading system. Students are able to keep a much closer track of their progress, and the feedback is generally more effective. Correction from a native speaker is far more beneficial than an A to F grade on a language exam. Review from multiple sources is much more beneficial than a grade from one instructor.

One problem in the feedback system that has not been addressed is the role of mentoring and coaching traditionally provided by a teacher.. Companies like Clarity.fm are starting to work towards a solution on this but are a long ways from ubiquity.

Certification

This is a big one. Most people would argue that taking online courses that don’t confer college credit is not a very smart move. After all, credits lead to degrees. All employers are looking for degrees, right? That discussion is for another time, but startups are providing records and certifications in a variety of ways.

• Smarterer allows you to take tests in order to prove your skills in a wide span of subjects — from facebook to CSS to English for Business. You can share your scores, and recruiters can even evaluate candidates by comparing Smarterer scores.
• Udacity will give students’ resumes to over 20 partner companies. Their course certifications are recognized by major technology companies who are actively recruiting from the Udacity student body.
• edX, a joint venture between MIT and Harvard, is awarding certificates to students who show a mastery of the subject of their course.
• Coursera offers a certificate of completion for some of their courses.
• Code Hero awards badges when a course is completed.

All these certifications can be compiled into an online or hard copy portfolio. This portfolio can function as your education transcript for personal use or to provide to future employers. Alternatively, it is also possible to take free courses and then take an exam to receive college credit in those subjects.

This rendering of the proposed TALISE probe shows one possible means of propulsion: paddle wheels on either side of the probe (credit: SENER)

NASA landed a rover on Mars. So what’s the next step? Right: land a boat on Titan!

Hey, come on, it’s gotta be the ultimate travel destiny:

• A magical moon that’s actually more like a planet.
• One of the most Earth-like bodies in the Solar System.
• Has an atmosphere (OK, mostly nitrogen — so bring your own oxygen, stop kvetching).
• A vast network of seas, lakes and rivers.

The perfect getaway. Quick, somebody get Richard Branson on the horn!

Just ask the scientists who ran the Cassini-Huygens mission, which studied Titan extensively in the 2000s. It confirmed that lakes, seas and mysterious rivers of liquid hydrocarbons exist, covering much of its northern hemisphere.

Now European explorers want to launch the Titan Lake In-situ Sampling Propelled Explorer (TALISE) — a quasi-mythical amphibious boat propelled by wheels, paddles or screws. (Engineers are presenting their proposals at the European Planetary Science Congress in Madrid on September 27.)

It would land in the middle of Ligeia Mare (the biggest lake, near Titan’s north pole), then boldly set sail for the coast, taking scientific measurements along the way, and presumably make some side trips to check out local attractions.

OK, Titan’s environment is too cold for life as we know it, but hey, its environment is rich in the building blocks of life, including organic compounds and well, ah, hydrogen cyanide (OK, that’s a problem, but never mind all that), which may have played a role in the emergence of life on Earth, so that’s a good thing, right?

An alternate design allegedly rejected by Europlanet. No word if the Blue Meanies have been sighted on Titan. (Credit: United Artists)

Should we welcome our new overlords? Uh, maybe not. (Credit: 20th Century Fox)

Vice just posted an update to their “we’re living in a simulation“ interview with Dr. Rich Terrile of NASA JPL.

“I think our machines will wake up and take over our society,” he said. “They will become us, we will become them. We’ll merge with machines.

Take over? Now wait a minute there, rocket man….

“We have to wake the machines up. Humans look like they’ve already had their day in the sun and we need something better to come along and fix things.

“I think eventually what we’ll want to do is tap into a kind of galactic mainstream. If our future is a machine-evolved society able to transmit information at the speed of light, maybe this kind of communication is already going on all over the universe within other machine societies.”

Ah, that’s … interesting. The Singularity Is Near suggests another approach, based on intelligently merging with technology, rather than being replaced.

Artist’s concept of a Kardashev Type 2 civilization (credit: Chris Cold)

Lt Col Garretson — one of the USAF’s most farsighted and original thinkers — has been at the forefront of USAF strategy on the long-term future in projects such as Blue Horizons (on KurzweilAI — see video), Energy Horizons, Space Solar Power, the AF Futures Game, the USAF Strategic Environmental Assessment, and the USAF RPA Flight Plan. Now in this exclusive to KurzweilAI, he pushes the boundary of long-term thinking about humanity’s survival out to the edge … and beyond. — Ed.

The views expressed are those of the author and do not necessarily reflect the official policy or position of the Department of the Air Force or the U.S. government.

It isn’t enough just to plan for two or 20, or even the fabled Chinese 100 year periods. We need to be thinking and planning on the order of billions of years. Our civilization needs inter-generational plans and goals that span as far out as we can forecast significant events.

For this discussion, I define a “significant event” as an event about which we have foreknowledge and which will fundamentally change our planning assumptions.

Artist’s impression of a red giant engulfing a Jupiter-type planet as it expands (credit: NASA)

For instance, the most significant near-term external problem we can forecast is that we have only about one billion years before the Earth becomes uninhabitable. Somewhere around that time, our Sun will have expanded and start boiling away our oceans. Truly, as the great space visionary Konstantin Tsiolkovsky foresaw, “Unless mankind leaves the Earth, it will surely die there.”

It is a nasty reality that sometimes the solutions to significant problems take time, and last-minute crash programs can fail. It would be a darn shame to end life’s two billion year run (and humanity’s eight million year run) prematurely because of a lack of planning.

Sunshade, using space lens (credit: Mikael Häggström/Creative Commons)

Moving everyone and everything we value off Earth is likely to take some time. The same is likely to be true for any of the alternatives: uploading most of us to exist “in-silico,” putting a sunshade between Earth and the Sun, moving the Earth, or attempting to control the Sun.

It is often a good idea to have at least a cadre of people thinking well in advance about the problem, and designing solutions.

Space colonies and space solar power

Artist’s concept of space colony, exterior (credit: NASA)

Artist’s concept of space colony, interior (credit: Don Davis/NASA)

The obvious solution available to us today to cope with Earth’s eventual non-inhabitability is to build O’Neill style space colonies from material in the Asteroid belt, which is estimated to have a carrying capacity of 10–100 trillion people (1,000 to 10,000 times our current population on Earth).

Of course, to be able to exercise that option, we would need a space policy that recognized survival as the fundamental reason for the space program, with articulated goals of space development and space settlement explicitly stated, and a space program pushing the technology and logistical capabilities to be able to attain those goals.

Energy production history and forecast (credit: Richard C. Duncan, The Peak Of World Oil Production And The Road To The Olduvai Gorge)

Energy availability is a key constraint to human progress and mobility. Spacefaring and space settlement capabilities would need to be developed before some other crisis (such as peak oil) caused a new and likely irrecoverable dark ages, which would reduce the energy capital available to develop the pre-cursor technologies. Nature has provided humanity a bounty of easy energy in the form of fossil fuels, a sort of ”baby fat” for the Earth to grow to adolescence. Use it well to reach new energy sources and we transcend; use it poorly (use it up) and we collapse.

Earth surface temperature given steady 2.3% energy growth, assuming some source other than sunlight is employed to provide our energy needs and that its use transpires on the surface of the planet. (Credit: Tom Murphy)

The case where we transcend a fossil fuel crisis is just as compelling. If we succeed in continuing our population and development growth and find new energy sources, and assuming energy use (including all sources: fossil, nuclear, fusion, etc.) grows at annual rate of 2.3% (reduced from the current 2.9% to be more realistic), we’d only be able to continue growth on Earth for another 420 years before we could not maintain the heat balance of the planet, and started boiling the oceans ourselves.

Of course, a good plan seeks to avoid such extremes, and with a little planning and ambition, we can make the best of those billion years, and both expand our population to “islands in the sky” and take good care of our home planet.

Space solar power satellite, artist’s impression (credit: SpaceWorks Engineering Inc. and Spaceworks Commercial)

With just a little care and proactive maintenance of the biosphere (climate control and some impact sensors), Earth should be good for at least another billion years. It could be a lush, green tourist location with a modest population of 10 billion, all living in relative energy wealth, if it built a ring of solar power satellites in geostationary orbit. (A fully developed civilization living at a U.S. or European equivalent lifestyle would only require on the order of 40–50TW of total electrical energy, and a ring of powersats in geostationary orbit could supply as much as 330 TW).

Sure, Earth might end up being a minor player and backwater tourist location in a solar-system-spacefaring civilization 1,000–10,000 times more populous and better connected, but a planet is a terrible thing to waste, especially when a little maintenance can get you another billion trips around the Sun.

Sun as red giant (credit: Fsgregs /Wikimedia Commons)

Life cycle of the Sun (credit: Wikimedia Commons)

But even the O’Neill solution is temporary, because within only about 5 billion years, our Sun will have first swallowed most of the space in which those colonies had been built on its way to becoming a red giant. Shortly thereafter, the Sun would collapse to a dim white dwarf incapable of supplying the passive solar energy upon which such colonies would depend.

Global power demand under sustained 2.3% growth (Credit: Tom Murphy)

Of course, colonies can be moved, and it’s possible we will have developed more impressive technology by then. As long as the Sun shines, there is energy available, and we can have an ambition to become a Kardashev Type 2 civilization — where we first surround and ultimately encase our Sun to use all of its energy.

A “Dyson swarm” version of a Dyson sphere, consisting of solar power satellites and space habitats orbiting in a dense formation around a star (credit: Wikimedia Commons)

But once our Sun started to dim, even encasing the Sun in a Dyson sphere of solar arrays to capture all the Sun’s energy would not be a sufficient solution.

Artists conception of completion of a Dyson Sphere under construction and a moon being harvested for resources (credit: Adam Burn)

However, the knowledge that the utility and growth horizon of our home star is limited should not lead us to be resigned or pessimistic about our future. Human beings have done fine in the past when the environment constrained growth. Even with constrained growth, there is plenty of Sun to support a space colony-based population of billions to potentially trillions at current energy requirements … for a good 5 billion years.

Beyond the solar system

Artist’s concept of interstellar spaceship (credit: Adrian Mann/Icarus Interstellar)

But as we get close to the 4 billion mark, it would be good to have figured out a non-solar solution to our energy problem or figured out interstellar travel to move to new younger suns. Fortunately, there are already serious efforts to conquer interstellar travel and faster-than-light (FTL) propulsion. (The definitive work on approaches to FTL travel and space-time engineering is Frontiers of Propulsion Science by Marc Millis, founder of NASA’s Breakthrough Propulsion, and Dr. Eric Davis.)

The latest effort is the 100 Year Starship Project (100YSS), begun by the Defense Advanced Projects Agency (DARPA) — the people who brought you the Internet — and NASA, which previously led an effort in the 1990’s called the Breakthrough Propulsion Physics (BPP). The 100YSS is managed by a team of non-profits led by former Astronaut Mae Jemison.

Fusion spacecraft concepts (credit: NASA)

100YSS is not alone. Marc Millis, former head of NASA’s Breakthrough Propulsion Physics program, heads another organization, the Tau Zero Foundation, a volunteer group of scientists, engineers, entrepreneurs, and writers who have agreed to work together toward practical interstellar flight.

(Credit: The Habitable Exoplanets Catalog, Planetary Habitability Library)

In advance of achieving interstellar flight, we can begin to map out where we intend to go.  Fortunately our science presently has this capability. There is already a significant amount of activity in the astronomical community looking at potentially habitable systems.

Each day seems to bring stories of new discoveries of ever more Earth-like planets circling distant stars. Our capabilities to detect exoplanets (planets orbiting another star) are getting better every day, and will receive a major upgrade in 2018, when we launch the James Webb Telescope (JWST).

Our criteria for new suns certainly will include that they have at least have the energy and material we need. While by then we will certainly be at home in space colonies and worlds of our own making, we may still desire systems that have habitable planets where we could recreate much of our entire biosphere or daughter ecosystems.

Artist’s impression of the collision between our Milky Way galaxy and the Andromeda galaxy, as viewed from Earth (credit: James Gitlin/Space Telescope Science Institute)

But as we approach the four billion year point, we need to plan to be a multi-stellar/multi-exo-planetary civilization, as there are other neighborhood events to consider. Around the same time our mother star is going through significant changes, we’ll have another problem we need to plan for. Our galaxy will be colliding with another galaxy, Andromeda.

How exactly that will affect us will become clearer as we get closer; it may present both threats and opportunities. The mix-up may move other stars into proximity with our own, perhaps making it easier to leap to attractive new stellar habitats, but perhaps also disturbing our own system and endangering our civilization.

Shkadov Thruster (credit: Steve Bowers)

In case something nasty was heading our way, it is not too early to think about how we might sidestep a potential collision. There are already ideas for moving entire stars. An example is the Shkadov Thruster, which uses gravity to balance light pressure on a reflector (“statite”), resulting in a net force that moves a star slowly through space.

Spreading out as wide as possible within our galaxy or other galaxies is highly desirable, because there are largely unpredictable events like supernovas and gamma-ray bursts that are like a grenade going off in a crowd, killing any solar systems in their proximity. The farther we spread, the more we spread our risk.

NASA simulation of a gamma ray burst (credit NASA)

But the remote possibility that we could be a victim of a gamma ray burst is no reason for defeatism. If we can figure out a way to do interstellar travel, we should have a nice long run as a multi-star civilization.

However, if we forecast out a little more, we see that again, our planning assumptions to start to change. Even as a long-living civilization capable of interstellar travel, we face limits. The stars themselves are limited resources.

But even here, there are ideas of fundamentally re-engineering space-time to literally give us a “new lease on life,” perhaps deliberately engineered black holes or wormholes that allow for the creation of entirely new baby universes — possibly even “intelligent black holes” — and restarting the entire process of creation.

Even the galaxies are moving farther and farther away. Eventually, as the Stelliferous Era comes to an end, it will be “slim pickins” as new stars form less and less. Still, our civilization could enjoy a nice life to a ripe old age of one trillion to one quadrillion years before things really got bad.

That is a lot of time for creation of poetry, literature, art and science! We should not let a few small obstacles a mere 1–5 billion years in our future slow us down, and deprive us of the chance to spread life, intelligence and art farther in the universe.

Further in the future, in the Degenerate Era (10¹⁴ to 10⁴⁰ years) we will need to have figured out some serious magic to perpetuate life and intelligence, or we will have to make our peace with entropy as we approach the Heat Death of the Universe.

Wormhole travel as visualized for NASA (credit: Les Bossinas/NASA (left) and Harold White/NASA)

But even here, there are ideas of fundamentally re-engineering space-time to literally give us a “new lease on life,” perhaps deliberately creating black holes or wormholes that allow for the creation of entirely new baby universes, and restarting the entire process of creation. The exploration of fundamental engineering of spacetime itself is being pursued by the same community seeking to make interstellar travel a reality.

Near-term threats

Of course, even before 1 billion years, we’ve also got some near-term “bad weather” to plan for. Before the Sun starts boiling us, we’ll have major dust storms as the Sun’s 250-million-year-orbit around the center of the galaxy pushes us through cosmic clouds of dust as we climb and descend through the galactic disk, say astronomers.

That dust could penetrate our heliosphere as early as 2,500 years from now, possibly even reaching Earth to deplete our atmosphere of vital gases and strip away protection from cosmic rays (as may have happened in previous mass extinctions).

Our interstellar neighborhood (credit: Richard Powell/Creative Commons)

Distance of nearest star over the next 80,000 years (credit: Wikipedia)

In only 10,000 to 35,000 years, four stars (Proxima and Alpha Centauri, Barnards, and Ross 248) will be close enough to disturb the Oort cloud and send giant comets our way, such as those that killed the dinosaurs (only 65 million years ago).

An illustration of the Kuiper Belt orbit (KBO) and Oort Cloud in relation to our solar system (credit:NASA)

And in less than 1 million years, the star Gliese 710 is going to race past our solar system and come within just three quarters of a light year from our Sun, well inside the Oort cloud.

In that same time period, we can count on more than a few asteroid strikes, which luckily will be completely preventable. According to NASA, more than a million near-Earth objects are larger than 40 m in diameter (the approximate threshold for penetration through the Earth’s atmosphere).

Asteroids as big as 2 kilometers can discharge an impact energy of a million megatons and create an effect similar to a nuclear winter, with loss of crops worldwide and subsequent starvation and disease. Still larger impacts can cause mass extinctions, like the one that ended the age of the dinosaurs 65 million years ago (15 km diameter and about 100 million megatons).

Artist’s concept of Laser Bees spacecraft swarming around a dangerous asteroid to move it into a safe orbit (credit: Planetary Society )

So to reach our billion year plan goals, we will need a planetary-defense asteroid detection system and a deflection system up and running “lickedly split,” or we forfeit a lot of good years! Fortunately that is a comparatively easy problem to solve, and the same suite of competencies that allow us to divert an asteroid enable us to capture and mine it.

Creating the plan

Strategy in 3 dimensions (credit: Paramount Television)

But any plan about the future is really about how we intend to allocate resources today. Our first priority needs to be planetary defense and space-solar power so we can lock in the full billion years of value Earth can provide.

The next priority is developing the competencies to make use of space resources to enable closed-cycle life support for the free-flying space settlements that will allow us to extend our civilization to the full five billion years warranty on the Sun. All the while, we need to be trying to find a way to build starships before this Sun goes bust.

Some people think a billion years is too far out to plan for. If it isn’t in their or their children’s lifetime they don’t care. Or it is so far away that they think no one will be around, or if there are, then it will be “their problem.”

That’s silly. It is good not to allow really big looming problems. And, planning for a long-term problem does not mean you need to ignore near-term problems. It is possible both to put money away in an IRA while you maintain your car. Planning for events like your children’s college or retirement might seem a long way away, and that there is plenty of time ahead to get busy, but the same factors apply — a little bit of early investment compounds over time and is worth a LOT of investment later on.

Of course, any person alive today should realize that “objects in the future may be closer then they appear.” Proximity is based on perception. Our perception of the distant future is measured against our own individual life span — and that is undergoing change as well.

(Credit: iStockphoto)

Our billion-year plan needs to consider the likely and predictable problem of time-contraction: 1,000 years is just not what it used to be! If thinkers like Aubrey de Grey and Ray Kurzweil are right, our civilization is on an exponential technology curve that will eventually result in “longevity escape velocity,” meaning that for every year a person lives, medical science advances to allow them to live one additional year. Already, there may be people alive today that may have indefinite life spans.

The idea that a post-Singularity world might allow us to exist “in-silico” as uploaded simulations and control our own “clock speed” poses even more radical time contraction. Even if we only succeed in extending human life a mere tenfold to 1,000 years, or an unrealistically low doubling to 200 years, every number discussed above is twice or ten times closer in terms of individual “care factor” and potentially much closer to home.

(Credit: iStockphoto)

But even if human life span remained constant, it is a responsibility of life to plan for its offspring, and civilization to seek to continue itself. At least the part of civilization I live in has this essential mission enshrined as the most basic task in our U.S. Constitution: “Secure the blessings of liberty to us and our posterity.” To do that requires planning. Planning allows time itself to be our resource and acts as our lever to do great things.

Many look at the significant events discussed above as “doomsday scenarios,” but to me, they are just eventualities to be planned for, and chance favors the prepared mind. It’s also a happy consequence that the farther out you look for problems, and the bigger problems you try to tackle, the more likely you are to perceive and be able to bring ambitious thinking to more proximate problems.

If we had not been building instruments in space to look far out into space, we would not even know about the threats of asteroids, comets, gamma-ray-bursts or galactic collisions. We also would not have the space-based surveillance to know about the hurricane or tsunami on its way. Lifting our eyes to the horizon pays.

Of course, there are more proximate threats, and several of our own creation. But personally, I bet on humanity, not against humanity. We are the life carriers, the intelligence, and the gametes of Gaia. It is our destiny to spread not just human life, but the entire clan of life, and intelligence, first to the Solar System, and then to the stars.

The great strategist John Boyd told us that it is the nature of all organisms to seek to “Survive, survive on their own terms, and improve their capacity for independent action.” Ultimately, the space program is about survival, growth, and flourishing. Not just of ourselves, but all life.

And for at least a billion years, the plan needs to be (as beautifully stated by Lee Valentine of Space Studies Institute): “Mine the sky, defend the Earth, settle the Universe.”

The Voice of Science (credit: Aviador Dro)

A spectre is haunting the world — the Singularity. All the powers of the old world have entered into a holy alliance to exorcise this spectre — the Pope and the ayatollahs, the banks and the political parties, and “bioethicists” of both the right and the left. …

So says KurzweilAI transhumanist editor Giulio Prisco, who will give a talk Saturday (Sept. 22) at the La Voz De La Cienzia (The Voice of Science) conference in Madrid on “Un fantasma recorre el mundo: ¿Está cerca la Singularidad?” (“A spectre is haunting the world: Is the Singularity near?”).

Prisco will present “elephant in the room” harbingers of the Singularity — like three stories this week on KurzweilAI (Humanoid robot presents…, Blue Brain predicts… and Chemical brain preservation…) — and will comment on traditional political discourse, which is “frozen in obsolete political categories such as right and left,” he says.

Upwingers: orthogonal to right and left

“We are upwingers [futurist FM2030's term] who wish to move above and beyond right and left, and overcome both the savage social darwinism of the right and the nanny-state dictatorship of the left. Let the ruling classes tremble at the Singularity. Humans 1.0 have nothing to lose but their chains. They have a universe to win.”

The conference will focus on cyborgs, nanotechnology and health, the Singularity, women in science, social networks, and “author 2.0.”

Electronic music band Aviador Dro and their The Voice of Science organization will present the conference, with the support of Fundación Telefónica, Fundación Autor, and CSIC. The event will be streamed live on the Web at 10 am to 7 pm in Spain (Saturday 4 am to 1 pm EDT).

Aviador Dro

(Credit: Internet Archive)

This is fantastic news for journalists and voters: the Internet Archive has launched the free TV News Search & Borrow service.

The collection now contains 350,000 news programs collected over 3 years from national U.S. networks and stations in San Francisco and Washington D.C.  The archive is updated with new broadcasts 24 hours after they are aired.  Older materials are also being added.

“This service is designed to “help engaged citizens better understand the issues and candidates in the 2012 U.S. elections by allowing them to search closed captioning transcripts to borrow relevant television news programs,” the announcement reads.

They plan to extend this all the way back to the beginning of television.

For another story today on automated drone and aircraft collision avoidance, I tried it out with a search on “drone” and “collision” since June, and instantly got these very relevant TV news clips:

I did find that it isn’t working well yet with the Chrome browser.

Note: I was once assigned to develop a similar TV news system before the Web. I quickly discovered there was no practical way to do it,  so I’m definitely impressed. Kudos to the amazing Brewster Kahle and his team!

Neuroscientists today can preserve small volumes (<1mm³) of animal brain tissue immediately after death with incredible precision — the features and structure of every synapse within these volumes is well-protected down to the nanometer scale, using an inexpensive, room-temperature process of chemical fixation and plastic embedding, or “plastination.” This image is an example of plastination and local circuit tracing, occurring in leading neuroscience labs around the world today. (Credit: Brain Preservation Foundation)

Here’s my 45 minute talk on Chemical Brain Preservation at World Future Society 2012. Given the progress we’ve seen in the relevant science and technologies it’s a topic I’m presently very optimistic about. I had a great audience with lots of questions at the end, but in the interest of brevity I’m just uploading the talk. Let me know your thoughts in the comments, thanks!

A number of neuroscientists, working today with simple model organisms, are investigating the hypothesis that chemical brain preservation may inexpensively preserve the organism’s memories and mental states after death. Chemically preserved brains can be stored at room temperature in cemeteries, contract storage, even private homes.

Our 501c3 nonprofit organization, the Brain Preservation Foundation, is offering a $100,000 prize to the first scientific team to demonstrate that the entire synaptic connectivity (“connectome”) of mammalian brains can be perfectly preserved using either chemical preservation or more expensive cryopreservation techniques.

Such preserved brains may be “read” in the future, analogous to the way a computer hard drive is read today, so that either memories or the complete identities of the preserved individuals can be restored or “uploaded” in computer form.

Chemical preservation techniques are already being used to scan and upload the connectomes of very small animal brains (C. elegans and OpenWorm, zebrafish, soon flies). Though these scans are not yet sufficiently complex to extract memories from the uploaded organisms, give them a little more time, we’re very close now to cracking long-term memory. We just need to know a bit more about this process at the protein/receptor/gene level: http://en.wikipedia.org/wiki/Long-term_potentiation

Amazingly, if information technologies continue to improve at historical rates, a person whose brain is chemically preserved in 2020 might have their memories read or even fully return to the world in a computer form not centuries but just a few decades from now, while their children and loved ones are still alive. Given progress in electron microscopy and connectomics research to date, we can even forsee how this may be done as a fully automated and inexpensive process.

Today, only 1% of people in developed societies are interested in living beyond their biological death (see When I’m 164, David Ewing Duncan, 2012). With chemical brain preservation, this 1% may soon have a validated, low-cost method that will allow them to do just that. Once it becomes a real option, and recovery of simple memories has been demonstrated in model organisms, this 1% may grow larger as well.

I am particularly excited by chemical brain preservation’s ability to improve the social contract: what benefits we may reasonably expect from the universe and society when we choose to live a good and moral life. I believe that having the option of chemical brain preservation at death, if the science is validated, may help all our societies become significantly more science-, future-, progress-, preservation-, sustainability-, truth and justice-, and community-oriented in coming years.

Would you choose chemical brain preservation at death if it was widely available, validated, and inexpensive? If not, why not? Would you do it to donate your brain to science? Your memories to your children or others who might want them? Would you be willing to come back in person, if that turns out to be possible? If it is sufficiently inexpensive, would it be best to preserve your brain at death, and let future society decide if either your memories or your identity are “worth” reanimating?

Please let me know what you think in the comments, thank you.

(Credit: USAF)

The U.S. Air Force just released today a jaw-droppingly impressive, fast-paced video on accelerating change, “Welcome to 2035…the Age of Surprise” (see video below).

Produced by the U.S. Air Force Center for Strategy and Technology at The Air University, the video was based on Blue Horizons, a multi-year future study being conducted for the Air Force Chief of Staff, a “meta-strategy for the age of surprise.”

“We can predict broad outlines, but we don’t know the ramifications,” the video says. “Information travels everywhere; anyone can access everything — the collective intelligence of humanity drives innovation in every direction while enabling new threats from super-empowered individuals with new domains, interconnecting faster than ever before. Unlimited combinations create unforeseen consequences.”

Blue Horizons: air, space, and cyberspace in 20 years

The last major internal study of the future, Air Force 2025, was done at Air University in 1996 where over 260 officers worked through the research that led to a multi-volume report outlining alternative futures and technologies required for those complicated and dangerous worlds.

The Blue Horizons study is designed to answer questions similar to those addressed in the Air Force 2025 study. These include: What are the emerging technologies that will shape the US Air Force and the conflict arena in which it must operate in 20 years in the future?  What could air, space and cyberspace power look like 20 years in the future?  Who will have access to emerging technologies that can make a difference?  How soon will these important technological achievements become fielded systems?

Under their leadership, the students researched future systems and technological concepts working closely with subject matter experts from the Air Force Research Laboratory, the Defense Research Projects Agency, major universities and businesses, and other government laboratories and agencies.  In addition to producing the reports posted here, the result was a cadre of officers conversant enough in critical areas of emerging technologies to ask critical questions and make assessments of systems in directed energy, biotechnology, nanotechnology and cyber technologies and what they mean for the future of the U.S. Air Force.

Blue Horizons 2007 was only the beginning of a series of annual long range vision studies which are known collectively as “Blue Horizons.”  These annual studies serve as an input for the development of Title X wargames, Strategic Planning Guidance, Quadrennial Defense Review scenarios and the development of service requirements.

(Watch for our forthcoming blog post, “Billion Year Plan,” by one of the originators of the Blue Horizons project, USAF Lt. Col. Peter Garretson.)

Turn up your sound, choose 1080p HD (if you can), and go full-screen:

Such advanced technology may be developed in a couple of decades, transforming us into a “telepathic” species. But what if we already have “natural” psychic abilities, emergent properties of quantum-entangled neurons, waiting to be unlocked by appropriate training?

Or both? Can transhumanist human enhancement and the paranormal abilities co-exist? Or are they on an inescapable collision course?

These are some of the questions that U.K.-based writer and journalist Martin Higgins sets out to explore in his novel Human+, a just-published science-fiction page-turner inspired by of futures studies, psychic spy research, and the transhumanist movement.

Adapted from a movie script, the novel combines reality-warping and edge-of-your seat action scenes reminiscent of Wild Palms, Vanilla Sky, and The Bourne spy series.

Smartdust and spooks

David, a Manhattan heroin drug addict, is rehabibiliated by Dr. Wharton, a psychiatrist with a spooky past, and finds himself in a new-agey program to develop his latent remote-viewing psychic powers. Dr. Wharton and his staff are somehow associated with Future Proof, a Soho futures-studies consultancy. David becomes David McKinley, a highly paid futurist and expert on advanced nanotech and biotech — knowledge that he actually accesses psychically.

Future Proof is funded by billionare venture capitalist Thomas Ames to develop a roadmap for a futuristic nanotech-biotech breakthrough: inhalable “smartdust” — nanobots small enough to pass through the lungs and the blood-brain barrier, and act as neurons — enhancing mood, extending life, and enabling direct networking with the world via wireless brain-computer links.

Their new company, Thetis, plans to accumulate wealth beyond their wildest dreams. But things go awry when David’s instructor and now colleague Lawrence attempts to blow the cover of what appears to be a nefarious scheme to control humanity, linked to the Defense Intelligence Agency’s remote viewing/psychic spy program.

Singularity or Spirituality?

I am persuaded that advanced transhumanist technologies will bring very radical change, someday soon. For example, early technologies similar to Thetis’ smartdust and brain-computer interfaces are already emerging from the research labs. I am less persuaded of naturally occurring psychic abilities and otherworldly realms. But I hope to be wrong, because these things would also be cool — very cool.

If both the Singularity and transcendent psychic abilities are on the horizon, I would totally agree with Dr. Wharton’s dictum: “Who’s to say the two can’t develop together — technology and human potential — perhaps should develop together?”

Human+ has KurzweilAI readers directly in its bullseye. I highly recommend it for its thought-provoking reading pleasure — and I look forward to seeing Human+ the movie.

Kindle Fire HD (credit: Amazon)

No, this is not about WWII SS, although it’s about another form of evil, maybe.

This is mostly a reaction to the sales pitch from Amazon CEO Jeff Bezos, presenting the new Kindle Paperwhite and Kindle Fire HD at a much touted press conference yesterday.

I’m not talking about a new phenomenon, nor mere $$$, but with Bezos orchestration, which is just a perfectly rational answer to the forces shaping current consumer electronics, this is just too much IMHO.

The Santa Monica presentation to the press was scheduled about 10 days ago. 6 days ago, the first images of a “Paperwhite” device surfaced from a website called TheVerge. About 10 hours before the presentation, a 1 minute 20 ad was broadcast along the first NFL game of the season.

About one hour before the presentation, CNET, a web site specialized in gadgetry evaluation, proposed a special talk show where two knowledgeable people filled the void by speculating on the specs and target market of the new Kindle models.

Alongside, journalists were gathering in the conference room, each one with a laptop or some instantaneous reporting device to transcribe Bezos’ holy talk to the rest of the planet, me included.

And the true stars were announced. I won’t go into the specs here, you can find them from Amazon.

So, what’s the fuss, aren’t those lovely gadgets with a lot of bang for the buck?

Welcome to the silo

Sure, but let’s go now to the evil part, the SSS part.

When you are buying a Kindle, you are not buying yet another Android eReader or tablet; you are entering an ecosystem. Each Kindle sale is a peculiar sale; I’m calling it SSS, for Single Silo Sale.

The first thing you are supposed to do after having unpacked the item, plugged in the charger and powered on the device, is to ACTIVATE it. This means binding the Kindle to a specific Amazon account for access to the growing galaxy of Amazon services. First and foremost, all content, books, music, movies should be acquired through Amazon.

You will be enticed to join the Amazon Prime club for rebates on books, limited sharing capabilities on your library, remote storage of your stuff on the Amazon cloud and so on.

Besides reading, watching TV or movies on your shiny tablet, maybe you would like to play. No problem, Amazon has its own approved lot of games on its App store alongside other Android apps. But yet again, the offer is a subset of the full Android market, subsidized by Amazon through the target device, this devilish lovely Kindle.

Amazon is pushing hard to entice you to buy, buy and buy again. For example, watching a movie delivered by Amazon, you can stop it, be introduced to the list of characters, when they are appearing in the movie (for further reference) and be presented a list of other movies where your fetish actor/actress is playing too. This service is a synergy with IMDB, a giant movie database acquired by Amazon. Of course, all those other movies are just one click away for buying with immediate Amazon delivery.

Now take a book, you read the 20 first pages on the living room, yet another 15 pages, light off, in your bed with the glowing Paperwhite screen. Next day, when commuting, you can start again your reading but synchronized with an audio version. So, say you’re in traffic jam, your book will be spoken to you from page 35. This will not be the mechanical voice from the bundled text to speech transcriber but a true audio version spoken by a professional actor. Of course, you’ll have to buy both book versions for that service, hopefully at a bundle price.

And what about kids? Bezos has 4 children, and he said he knows, for access to the screen, that it’s all about negotiation with the kids. So now you have parental control with individualized user’s profile and timed access (e.g. 30 minutes video, 1 hour on comics reading but unlimited reading time on textbooks) and that’s it.

Command and control

This ought to be a formidable platform for education, but no, it will be yet another dumbing-down device milking the consumer.

SSS, or this trick to lock you in a silo of possible purchases from the seminal acquisition of the device, has been pioneered by Apple with the Macintosh strict GUI guidelines and its specific market place, but at that time it was a more open process, as Apple didn’t control the entire market. Individual software brands could thrive without special ties with Apple.

Then, the model has been emphasized by the big Telcos with their subscription plans, where they made no money on the (smart)phone itself but on the services. Now, it’s epitomized by Amazon and its Kindle brand. But with the ever expanding capabilities of consumer electronics, the trend is going from bad to worse, now that the device is constantly spying on you, reporting your habits, location, reading patterns (e.g. from monitoring page shuffling, the new Kindle will present you at the bottom of the screen an estimated time before chapter completion!).

In our soft Orwellian world, dominated not by an all-powerful state but by a cartel of mega corporations dictating their vision of “progress,” the way to push technology is not through collective empowerment anymore.

Instead, in an unabated promotion of individualism, people are lured to technology by teasing of their lower instincts.

Abiding to this trend, yesterday, Amazon didn’t present devices for empowerment, but yet another means of aiming at narcissistic entertainment fulfillment for dumbed-down consumers.

As usual, clever people will shrug, smile and say so what? Take the shiny device at dumped price, jailbreak it and throw everything at the little devil for free, including millions of DRM stripped copyrighted material!

Yes you can, but isn’t it all too bad for you to have to take the runaway road to feel free, sailing the world without any “buy this, try that, don’t miss those…” ubiquitous solicitations?

There was a time when society really strived for empowerment of the people by technological advances, fostering education to achieve a proud sense of collective progress. This time is lost.

Now it’s time for control and profit, period.

Atomic clusters of metals are an emerging class of extremely interesting materials occupying the intermediate size regime between atoms and nanoparticles. (credit: Reji Philip et al./Nano Letters)

Think of the possibilities.

University of Central Florida assistant professor  Jayan Thomas, in collaboration with Carnegie Mellon University Associate Professor Rongchao Jin, has developed a new material based on gold nanoparticles smaller than 2 nanometers, in a regime between atoms and nanoparticles called nanoclusters.

Thomas and his team found that nanoclusters developed by adding atoms in a sequential manner could provide interesting new optical properties that make them suitable for creating surfaces that would diffuse laser beams of high energy.

Protecting pilots and instruments from laser beams

Think of commercial pilots or fighter pilots’ glasses or helmet shield could be coated with nanoclusters that potentially diffuse high-energy beams of light, such as laser beams.

Highly sensitive instruments needed for navigation and other applications could also be protected in case of an enemy attack using high-energy laser beams.

Real time 3D telepresence 

Thomas is also exploring the use of these particles in the polymer material used for 3D telepresence to make it more sensitive to light. If successful, it can take current polymers a step closer to developing real time 3D telepresence.

3D-Telepresence, aka the holodeck, would provide a holographic illusion to a viewer who is present in another location by giving that person a 360-degree view (in 3D) of everything that’s going on. It’s a step beyond 3-D and is expected to revolutionize the way people see television and in how they participate in activities around the world. For example, by allowing a viewer to “walk around” a remote location as if in a virtual game, a surgeon could help execute a complicated medical procedure from thousands of miles away.

Others who contributed to the new material include: Reji Philip from the UCF’s NanoScience Technology Center, Panit Chantharasupawong from UCF’s College of Optics and Photonics, and Huifeng Qian from Department of Chemistry at the Carnegie Mellon University.

I wonder what would happen if they combined this with a metamaterial? A diffusion-based cloaking device?

Foglets

Foglet (credit: J. Storrs Hall)

Taking the a step research further out, in 1993 J. Storrs Hall conceived the idea of utility fog, consisting of a swarm of nanobots (“foglets”) that can take the shape of virtually anything, and change shape on the fly.

Perhaps Thomas’ nanoclusters could one day be developed into self-assembling modules that actualize Storrs’ concept — and take it from the micron level down to the nanometer level?

In Utility Fog: The Stuff that Dreams Are Made Of, Storrs suggested that an appropriate mass of Utility Fog can be programmed to “simulate most of the physical properties of any macroscopic object (including air and water), to roughly the same precision those properties are measured by human senses.

That could include cars, houses, and just about any other object. “The pattern you both set your houses to could be anything, including a computer-generated illusion. In this way, Utility Fog can act as a transparent interface between ‘cyberspace’ and physical reality.”

“Consider the application of Utility Fog to a task such as telepresence. The worksite is enclosed in a cloud of Fog, which simulates the hands of the operators to assemble the parts and manipulate tools. The operator is likewise completely embedded in Fog. Here, the Fog simulates the objects that are at the worksite, and allows the operator to manipulate them.”

So what would you do with nanocluster foglets?