<?xml encoding="utf-8"?>
<A HREF="Content064#b" NOPUSH><</A>
human tissue -- both spatial and temporal -- is doubling every year, and so is our knowledge of the workings of the brain. The brain is not one big neural net, the brain is several hundred different regions, and we can understand each region, we can model the regions with mathematics, most of which have some nexus with chaos and self-organizing systems. This has already been done for a couple dozen regions out of the several hundred.

\"We have a good model of a dozen or so regions of the auditory and visual cortex, how we strip images down to very low-resolution movies based on pattern recognition. Interestingly, we don\'t actually see things, we essentially hallucinate them in detail from what we see from these low resolution cues. Past the early phases of the visual cortex, detail doesn\'t reach the brain.

\"We are getting exponentially more knowledge. We can get detailed scans of neurons working in vivo, and are beginning to understand the chaotic algorithms underlying human intelligence. In some cases, we are getting comparable performance of brain regions in simulation. These tools will continue to grow in detail and sophistication.

\"We can have confidence of reverse-engineering the brain in twenty years or so. The reason that brain reverse engineering has not contributed much to artificial intelligence is that up until recently we didn\'t have the right tools. If I gave you a computer and a few magnetic sensors and asked you to reverse-engineer it, you might figure out that there\'s a magnetic device spinning when a file is saved, but you\'d never get at the instruction set. Once you reverse-engineer the computer fully, however, you can express its principles of operation in just a few dozen pages.

\"Now there are new tools that let us see the interneuronal connections and their signaling, in vivo, and in real-time. We\'re just now getting these tools and there\'s very rapid application of the tools to obtain the data.

\"Twenty years from now we will have realistic simulations and models of all the regions of the brain and [we will] understand how they work. We won\'t blindly or mindlessly copy those methods, we will understand them and use them to improve our AI toolkit. So we\'ll learn how the brain works and then apply the sophisticated tools that we will obtain, as we discover how the brain works.

\"Once we understand a subtle science principle, we can isolate, amplify, and expand it. Air goes faster over a curved surface: from that insight we isolated, amplified, and expanded the idea and invented air travel. We\'ll do the same with intelligence.

\"Progress is exponential -- not just a measure of power of computation, number of Internet nodes, and magnetic spots on a hard disk -- the rate of paradigm shift is itself accelerating, doubling every decade. Scientists look at a problem and they intuitively conclude that since we\'ve solved 1 percent over the last year, it\'ll therefore be one hundred years until the problem is exhausted: but the rate of progress doubles every decade, and the power of the information tools (in price-performance, resolution, bandwidth, and so on) doubles every year. People, even scientists, don\'t grasp exponential growth. During the first decade of the human genome project, we only solved 2 percent of the problem, but we solved the remaining 98 percent in five years.\"

But Kurzweil doesn\'t think that the future will arrive in a rush. As William Gibson observed, \"The future is here, it\'s just not evenly distributed.\"

\"Sure, it\'d be interesting to take a human brain, scan it, reinstantiate the brain, and run it on another substrate. That will ultimately happen.\"

\"But the most salient scenario is that we\'ll gradually merge with our technology. We\'ll use nanobots to kill pathogens, then to kill cancer cells, and then they\'ll go into our brain and do benign things there like augment our memory, and very gradually they\'ll get more
<A HREF="Content066" NOPUSH>></A>