Magnetic data storage is not covered under Moore's Law, since it involves packing information on a magnetic substrate, which is a completely different set of applied physics, but magnetic data storage has very regularly doubled every year. In fact there's a second level of acceleration. It took us three years to double the price-performance of computing at the beginning of the century, and two years in the middle of the century, but we're now doubling it in less than one year. This is another feedback loop that has to do with past technologies, because as we improve the price performance, we put more resources into that technology. If you plot computers, as I've done, on a logarithmic scale, where a straight line would mean exponential growth, you see another exponential. There's actually a double rate of exponential growth.

Another very important phenomenon is the rate of paradigm shift. This is harder to measure, but even though people can argue about some of the details and assumptions in these charts you still get these same very powerful trends. The paradigm shift rate itself is accelerating, and roughly doubling every decade. When people claim that we won't see a particular development for a hundred years, or that something is going to take centuries to do accomplish, they're ignoring the inherent acceleration of technical progress.

Bill Joy and I were at Harvard some months ago and one Nobel Prize-winning biologist said that we won't see self-replicating nanotechnology entities for a hundred years. That's actually a good intuition, because that's my estimation — at today's rate of progress — of how long it will take to achieve that technical milestone. However, since we're doubling the rate of progress every decade, it'll only take 25 calendar years to get there— this, by the way, is a mainstream opinion in the nanotechnology field. The last century is not a good guide to the next, in the sense that it made only about 20 years of progress at today's rate of progress, because we were speeding up to this point. At today's rate of progress, we'll make the same amount of progress as what occurred in the 20th century in 14 years, and then again in 7 years. The 21st century will see, because of the explosive power of exponential growth, something like 20,000 years of progress at today's rate of progress — a thousand times greater than the 20th century, which was no slouch for radical change.

I've been developing these models for a few decades, and made a lot of predictions about intelligent machines in the 1980s which people can check out. They weren't perfect, but were a pretty good road map. I've been refining these models. I don't pretend that anybody can see the future perfectly, but the power of the exponential aspect of the evolution of these technologies, or of evolution itself, is undeniable. And that creates a very different perspective about the future.

Let's take computation. Communication is important and shrinkage is important. Right now, we're shrinking technology, apparently both mechanical and electronic, at a rate of 5.6 per linear dimension per decade. That number is also moving slowly, in a double exponential sense, but we'll get to nanotechnology at that rate in the 2020s. There are some early-adopter examples of nanotechnology today, but the real mainstream, where the cutting edge of the operating principles are in the multi-nanometer range, will be in the 2020s. If you put these together you get some interesting observations.

Right now we have 10^26 calculations per second in human civilization in our biological brains. We could argue about this figure, but it's basically, for all practical purposes, fixed. I don't know how much intelligence it adds if you include animals, but maybe you then get a little bit higher than 10^26. Non-biological computation is growing at a double exponential rate, and right now is millions of times less than the biological computation in human beings. Biological intelligence is fixed, because it's an old, mature paradigm, but the new paradigm of non-biological computation and intelligence is growing exponentially. The crossover will be in the 2020s and after that, at least from a hardware perspective, non-biological computation will dominate at least quantitatively.

This brings up the question of software. Lots of people say that even though things are growing exponentially in terms of hardware, we've made no progress in software. But we are making progress in software, even if the doubling factor is much slower. The real scenario that I want to address is the reverse engineering of the human brain. Our knowledge of the human brain and the tools we have to observe and understand it are themselves growing exponentially. Brain scanning and mathematical models of neurons and neural structures are growing exponentially, and there's very interesting work going on.