The Web, a planet-sized computer, is comparable in complexity to a human brain. Both the brain and the Web have hundreds of billions of neurons (or Web pages). Each biological neuron sprouts synaptic links to thousands of other neurons, while each Web page branches into dozens of hyperlinks.

That adds up to a trillion “synapses” between the static pages on the Web. The human brain has about 100 times that number – but brains are not doubling in size every few years. The Machine is.

Since each of its “transistors” is itself a personal computer with a billion transistors running lower functions, the Machine is fractal. In total, it harnesses a quintillion transistors, expanding its complexity beyond that of a biological brain. It has already surpassed the 20-petahertz threshold for potential intelligence as calculated by Ray Kurzweil. For this reason some researchers pursuing artificial intelligence have switched their bets to the Net as the computer most likely to think first. Danny Hillis, a computer scientist who once claimed he wanted to make an AI “that would be proud of me,” has invented massively parallel supercomputers in part to advance us in that direction. He now believes the first real AI will emerge not in a stand-alone supercomputer like IBM’s proposed 23-teraflop Blue Brain, but in the vast digital tangle of the global Machine.

In 10 years, the system will contain hundreds of millions of miles of fiber-optic neurons linking the billions of ant-smart chips embedded into manufactured products, buried in environmental sensors, staring out from satellite cameras, guiding cars, and saturating our world with enough complexity to begin to learn. We will live inside this thing.