Robots R Us

The aspiration to build human-level androids can be regarded as the ultimate challenge in artificial intelligence. To do it, we need to understand not just human cognition but also our physical skill-it is, after all, a critical part of what the brain does. Coordinating intention with movement in a complex environment is largely the responsibility of the cerebellum, which comprises more than half the neurons in the brain. And the body itself represents much of our complexity: There is more information in the human genome, which describes the human body, than in the design of the brain.

We are making tremendous strides toward being able to understand how the brain works. The performance/price ratio, capacity and bandwidth of every type of information technology, electronic and biological alike, is doubling about every year. I call this pervasive phenomenon the law of accelerating returns. Our grasp of biology is proceeding at an accelerating pace, also exponentially increasing every year. It took scientists five years to be able to sequence HIV, for example, but the SARS virus required only 31 days. The amount of genetic data that's been sequenced has doubled every year since the human genome project began in 1990, and the cost per base pair has come down by half each year, from $10 in 1990 to about a penny today. We are making comparable gains in understanding how the genome expresses itself in proteins and in understanding how a broad range of biological mechanisms work. Indeed, we are augmenting and re-creating nearly every organ and system in the human body: hearts and pancreases, joints and muscles.

The same progression applies to our knowledge of the human brain. The three-dimensional resolution of brain scans has been exponentially increasing, and the latest generation of scanners can image individual neuronal connections firing in real time. The amount of data that scientists are gathering on the brain is similarly increasing every year. And they are showing that this information can be understood by converting it into models and simulations of brain regions, some two dozen of which have already been completed. IBM also recently began an ambitious effort to model a substantial part of the cerebral cortex in incredible detail.