http://www.thinredlinenews.com/darpa-starts-agi-program.html

Not so. See *The Cognitive Brain* (MIT Press 1991). Also:

http://people.umass.edu/trehub/YCCOG828%20copy.pdf

and

http://theassc.org/documents/where_am_i_redux

and

http://evans-experientialism.freewebspace.com/trehub01.htm

I suggest looking towards evolutionary processes to create lifeforms that can adapt to an environment. You evolve cells and organs that interact in some virtual environment and watch interesting behavior.

In fact, you could not even define or describe “going out into space” without implying every bit of that current reality, along with all the events that led up to it.

But here is a mystery which maybe someone here can help me understand: Why should I have to write this? Isn’t all the above completely obvious?

http://www.youtube.com/watch?v=mthDxnFXs9k

http://www.youtube.com/watch?v=oozFn2d45tg&list=PL032B233624CCC2CE&feature=plpp_play_all

From my personal perspective, that is false – the personal case of 1 falsifying the claim.

He makes the further claim “the field of ‘artificial general intelligence’ or AGI — has made no progress whatever during the entire six decades of its existence” – which is again completely false as far as I see. We can now simulate neural activity to a high degree.
We now understand how the predictive model of reality is created and maintained and entrained in the cortex. Work done by David Eagleman and many others is giving us great insight.
That we do not yet have hardware capable of runnning a model in anything like real time does not mean that no progress has been made.
There has also been a lot of work done on data storage and retrieval, that combined with the many levels of work done on holographic and analogous systems of storage and retrieval (which is very different to normal one to one storage); has given some of us a very clear picture of how to create AGI, even if the current generations of hardware do not allow us to create such a thing.

While I agree with much of what he says about the problems of confining ones thinking within particular paradigms, he makes a huge error when he states “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.” That is simply false. There are many classes of computer programs that one cannot define their output before running them. Systems of these classes are clearly involved in the many levels of systems required to produce and AGI.

It does not seem to me that there is any single idea missing.
What is missing is a lot of work, with many levels of systems integration, and a lot of hardware to run it all on. Simulating holographic storage on a von Neumann architecture is unlikely to be productive. Development of effective holographic memory is still some time off – probably decades.

So yeah – some of what he says is interesting, and most of it is clearly a matter of ignorance and opinion on his part.
And such is the normal course of scientific development – recall how Wegener’s idea of plate tectonics was treated by the scientific establishment during his lifetime (or how evolution is still treated by many people).

Obviously David Deutsch hasn’t understood the problem. His essay could have been written in sixties when computers could do a few thousand instructions per second and they had a few kb of memory, not enough to even hold the words in the english language…

Computer power is needed. Think about it. We analyze reality in at least 10 frames per second and and at least 1 miljon pixels. That means you would need at least 10 million instructions per seond to just process the information from our eyes and then we assume RAM access is as fast as accessing a register…

It wasn’t untill 20 years ago we had computer power to go through the pixels. There is a reason we didn’t have digital TV in the eighties and monitors had low resolution. It was lack of computer power, it had nothing to do with philosophy. or that nobody had thought about doing high-res screens before.

We will need computers that are about 100 000 faster than todays desktop computers before we can reach human level intelligence..We will get there in about 20 years.

2. Deutsch probably has no more insight into breaking through the “logjam” than all the other very smart people who have worked on this problem over the past 60 years.

3. I guess that means we’ll all have to go the way of all flesh after all, unless you can get cryosuspended. Sorry about your fantasies of becoming “immortal” by 2045 or whatever arbitrary date Ray Kurzweil uses these days.

F./

On my web site (AEyeC.com) I suggest how an AGI can be constructed and how far I’ve progressed.

For example, if our intelligence, relative to lower-intelligence animals or machines, is just a consequence of higher levels of pattern recognition, strategically interconnected, then producing similar structures artificially may not be very problematic relative to our current levels of technology.
Should this be the case, then such grand claims are, for the first time, valid.
There WILL be a first time for such valid claims.
How likely it is to be now, or soon, is growing all the time.

Genetics *predisposes*, and culture, education, weather, time available, circumstances, health, etc. *disposes*

The main purpose of emotions is not giving us pleasure, but to provide information, tell us and robots what is important for humans and robots for survive or adapt.

Human and robot ability to recognize and appreciate the Qualitative components of existence will be a reality very soon. Appreciation of Beauty, Love, Music will be a reality in 5 years or less from Turing Test point of view. Is required to implement now the correct “AI consciousness bricks”, a high level layer specialized applications over basic internet protocols TCP/IP in CLOUD ROBOTICS for cheap, popular, intelligent, empathic, social, mass production, and emotional personal cloud-robots, the best friends and usefully tools of their human owner’s which they will provide feedback to their cloud-robots for changing their own state and learn for changing their future behaviour.

In my opinion neither robots nor humans (that we are not so different from machines, we haven’t nothing of “heavenly” in NDA or brain), can’t control the things that happen to robots and humans, but you can control the way they REACT to them. Let’s create CLOUD ROBOTICS for AGI with really cheap cloud-robots , the ROBOLUTION.

In 1989 was “invented” the WWW which is the high level layer of application for humans over low level layer protocols TCP/IP created by DARPA in 60′s years of last century for defense purposes. Now it’s time to create the new high level layer application for robots with thousands (millions?) of specialized tools which I call “AI bricks”. Will be used standards protocols in communications for structure mission information, as XML, uploading multimedia & sensor magnitudes, etc. to the cloud and obtaining a response “on demand”.

The big opportunity as important and big as WWW or Web 2.0 is *NOW* because:

1) Mobile new technologies (Smartphones) are mature and growing exponentially in features, latency delay times and bandwith with wifi (indoor robots) or 3G, 4G, … (outside home). Smartphones are already produced in big scale and are commodities, so prices will decrease. (Client side brain=cheap robot = AI robots become popular)

2) Cloud Computing technologies are mature and growing exponentially (server side brain = millions of expert tools, learning tools, NLP, etc. AI tools or “bricks” for hard process and quick calculations and access to data, correlations of patterns for Artificial vision, voice recognition, etc)

The big opportunity is for *EVERYBODY*:

- Key players for image, video, face and voice recognition on cloud. High power calculate correlations and high storage of patterns giving service to millions of concurrent cloud-robots: Google, Apple, Microsoft…
- Startups and enterpeneurs with a high knowhow of specific field of knowledge and field of human behavior.
- Middle companyes with some expertise in human behaviour or knowhow.
- Open Source community. Academic community.
- AI institutes and departments (exists from 1956, and they have had success in so many years in a lot of fields)

Examples of thousands (milions?) of AI bricks very intelligent in their specialization and silly in other tasks:

- RTS (Robot Tools Server) for redirecting each cloud-robot to the optimal specialized tool (like DNS in WWW) for complete a mission.(*)

- Expert tools: chess (Deep Blue machine won the human world champion Kasparov on 1997), psicology, emotional intelligence, lawyer, languages, empathy, medical, history, mycology, weather, philosophy, etc…

- Prediction tools.

- Technic tools: Artificial vision for pattern recognition of thousands of objects with millions of patterns hosted in the Cloud. Voice recognition, Face recognition, etc.

- Downloading specialized programs and firmware “on demand” for robots.

- Learning tools: the robots can learn from their own past experience depending on if a past mission failed or not, memory, knowhow, etc. A human from his born is always learning from it’s own experience and delays 18 years in get a bit of maturity, and more than 30 years in working professionally with experience… lets give the same time to strong and generalist AI cloud robots to learn!

(*) The way to integrate these bricks for not being a “large number of airplane parts flying in formation” is key. So I introduce the concept of RTS (Robotics Tools Server) than in human high level layer of application WWW over TCP/IP is something conceptually similar as DNS (Domain Name Server), thought for humans because humans we don’t remember IP numbers, but we remember alphanumeric names and words and domains. In worldwide DNS, thousands of machines, are automatically updated when only one DNS is updated with a new domain name in less than 24h, and this extraordinary network of machines is largely distributed for assurance the service.
RTS (Robot Tool Server) is similar, but more complex: a robot provides to RTS a mission in XML predefined format, with optional attached URL files (information, multimedia, etc. uploaded and hosted in cloud), and the RTS redirects the robot to the optimal machine (IP) to complete his mission like DNS redirects to a IP when it receives a domain name. A regulated register of AI bricks or tools and tasks is required. AI Bricks in RTS will survive by natural selection on depending of feedback from cloud-robots or it’s owner humans on depending of success of robot missions and tasks.

More information:
- http://www.slideshare.net/ROBOTonica/robtica-al-servicio-del-pensamiento-creativo-with-executive-summary-of-cloud-robotics

- http://www.robotica-personal.es/search/label/Cloud%20Robotics

Best regards.
Toni Ferraté
http://es.linkedin.com/in/antoniferrate

Technically there is NO distinction between data and code. It is an artificial distinction to simplify machine microarchitecture, therefore “clever enough code” to adapt like this would inexorably require a change in behavior — said “rules” to get said results — equivalent to what is currently called “self-modifying code, THUS my one-term summary. (though it kinda defeat the purpose if I have to come around to explaining it to those who dont like generalities =P)

>> OR an insanely smart, though masochistic, computer scientist. Which we dont have either =)

Since I`m not masochistic. ;-)

Thanks for clearing it up though – irony is hard to get over the internet often.

It seems that our brains build models of reality that our awarenesses then interact with (as if they are reality).

In so far as what is in reality is concrete and common, then there seems to be a very high probability that there is a close correspondence between models and their use of language referring to the external via the models.

The more abstract the concept, the greater the probability of error in the process.

Most people rapidly become aware of the very many potentials for error, and are alert in conversations for indications of error. There is a lot of power in face to face communication, where one can be alert to observational minutiae that indicate confusion on the part of the other party, and can thus give one a clue that some concept is absent or mis-constructed.

Actually the problem isn’t as bad as one might first think, as many of the abstracts exist in quite discrete sections of possibility space (check out Wolfram’s work with general computational space).
It is a real problem in some domains, those with infinite gradations; and not so much of a problem in spaces that are more discrete in nature.

Hey, this was just (not very ironed out) irony!
So, now you truly deserve this story for your edification.

Once upon a time, octopuses were the the dominant species on Earth. They were so clever they imagined they could worship God himself. And with all their tentacles they worshipped idols and idols, made out of fishbones, out of coral, out of ephemeral submarine floral compositions.

God send them angels as messengers to remind them, they ought not represent him and idolatry was sinful. But the playful octopuses were oblivious of the Lord command. And how could it have been different?

The angels wings were so impractical, they couldn’t reach the bottom of the sea where the octopuses were adorning their idols, so they couldn’t properly warn them and the poor angels were so shameful, they didn’t dare to report to God they were unable to execute the mission.

But the Almighty saw that.

God frowned, the octopuses had uncovered a ridiculous flaw in his marvelous creation, he was very upset.

Then God punished the octopuses. All in a sudden, they had to reach adulthood in a few months, they had to find their soul mates very soon, as they would die only after 2 years!

Now God is pleased: the octopuses don’t have time enough to see their natural intelligence outreach in so futile attempts at representing him. They are now so short lived, so busy at reproducing themselves before dying.

And no need for angels to remind them anything anymore. Oh yes, God is pleased by the perfection of his creation!

Our current AI is short as it can’t reflect on whether it should apply its intelligence or abilities. This seems to be a result of humans trying to recreate their own processes and outcomes. It might be better if we set a series of frameworks that allowed evolution with computers. How this could be programmed, I have no idea. The problem doesn’t seem to be computing power or hardware, more it is a reflection of our own limitations as programmers and a attempt to invent the wheel (us) rather than set a new species running.

http://www.halfsigma.com/2012/10/real-reasons-for-high-unemployment.html#comments