On Monday, Computerworld published a portion of my phone interview with Ray Kurzweil for The Grill. There wasn't enough room in the print version of Computerworld to display the complete transcript, so below I am including some of the other questions and answers from the interview.
Kurzweil's additional comments to my question about the "exponential growth" of computational power:
First of all, in terms of "knee of the curve" and the exponentialist view that doesn't have any discontinuities, [it's] nonetheless explosive. If I count to 30 steps linearly, I get to 30, if I could exponentially, 2-4-8-16, I get to a billion. So it's really quite a big difference. And technology, particularly if we can measure the information content, proceeds exponentially, not linearly. And a lot of people don't realize that, and that's one of the reasons long-term forecasts generally fall substantially short of the ultimate reality.
We see this in both biological and technological evolution. An evolutionary process creates a capability, then it incorporates that capability. Therefore the next stage goes more quickly. So it took a billion years for DNA to evolve, but then evolution used DNA ever since, and the Cambrian explosion came, and it went 100 times faster, and it only took 10 million years, biological evolution kept accelerating, and homo sapiens evolved in only a few hundred thousand years, and then really the cutting edge of evolution, which is really the increase of complexity in our environment, switched to technological evolution, and the first steps of that were only tens of thousands of years ago.
Then we always use the latest tools to create the next set of tools, so that process has accelerated. So we now have paradigm shifts in just a few years' time. If you look at computers, the first computers were actually designed on pen on paper and wired with screwdrivers and took years, and today you can specify some high-level formulas to a CAD program and generate 12 layers of intermediate design automatically.
... In fact, there's a second level of exponential growth. It took three years to double the price/performance of computing in 1900. Two years in the middle of the 20th century. It was 12 months in the year 2000, it's now actually down to 11 months.
And doubling every year, even ignoring the second level of exponential growth, is multiplying by a billion in 30 years, and because of the second level of exponential growth, its actually 25 years. And if you look at how influential information technology is already, and you imagine multiply that by a billion over the next quarter century, you get an idea of what would be feasible.
And the last point I'll make about this is that it's not just limited to computers. People don't have to have been around very long to -- even teenagers have even noticed how rapidly computation and communication technology has advanced in a short period of time. In my cell phone, I have 1000 times as much computation as all of MIT had when I was a student there.
But it's not just a computer. It's also other areas of science and technology are now becoming information technologies. A very important one is biology, which didn't use to be an information technology. There was some information in it, but it was basically hit or miss. But now that we have collected the genome, and actually have the tools to reprogram the biologies, the way we reprogram our computers, we can turn genes off with RNA interference, we can add new genes with gene therapy and so on.
This is becoming an information technology and therefore it is subject to this doubling of price/performance every year. And these technologies will be a thousand times more powerful than they are today ten years from now.
And we saw that in the genome project. The amount of genetic data has doubled every year, very smoothly. So halfway through the 15-year project, skeptics said, "I told you this wasn't going to work. You're halfway through the project, and you're only through 1% of the project." But that in fact is the correct trajectory for an exponential, because that 1% doubled every year for the next seven years, and the project got done on time.
And we've continued the exponential growth, both with genetic data and with every other aspect of biology, and it's also true of reverse-engineering the human brain, and this ultimately will solve problems that you wouldn't think are remotely related to information, like the energy crisis, because we'll use nanotechnology, which is a form of information technology, basically reorganizing matter and energy at the molecular level, to create extremely inexpensive, efficient, solar panels that can capture enough sunlight to completely eliminate fossil fuels, which I believe we'll do within 20 years. Because we actually have 10,000 times more sunlight that falls on the earth than we actually need to meet all of our energy needs.
So ultimately, everything is going to be transformed by information technology. We're moving toward tabletop devices that can actually create three-dimensional objects. Right now you can take an information file, and turn that into a movie, or a book, or a sound recording, and those things used to be physical products, and now are just information.
Well, the same thing will be true of what we now think of as physical products. We'll be able to have an information file, and be able to turn it into any three-dimensional object that you need, such as a module for a house, a solar panel, a toaster, or even the toast, or a blouse, by basically reorganizing matter and energy from very basic input materials, which will be recycled, to create physical products, and there are a number of roadmaps to get there, and I believe we'll see those kinds devices within 20 years.
Whether or not people are receptive to his ideas:
Well, if I have enough time to explain it, I generally get a very positive response. The idea is not just one idea that people can lay on their [garbled] for understanding. There are a number of different aspects to it and it also takes a certain amount of data to see how convincing a story this is. If you look at these curves lets say for the price of a transistor, buy one transistor for a dollar in 1968, it's about 300 million today for a dollar. We've heard those fantastic numbers, but if you look at the graph on a logarithmic scale, it's a perfectly straight line with very little wobble to it.
It's remarkable how predictable these trends are. In computation, which is the classical most important example, this goes back a 110 years, with the data processing equipment used in the 1890 census. It's not just Moore's Law, because Moore's Law didn't kick in until about 60 years later in the 1960s -- 70 years later.
So when I show 20, 30, 40 of these graphs, and people see how persistent and how predictable over long periods of time, these trends are, it does make a convincing case.
I've not just been looking backwards recently. I've been making forward looking predictions based on these trends for about a quarter of a century. The projections I made in my first book, which I wrote in the 1980s, provided a very accurate roadmap in the 1990s and the first decade of the 21st century. It was considered very radical back then and now the predictions seem quite mundane, like the emergence of a worldwide communications network in the mid-1990s cause I saw the DARPAnet doubling every year and so on.
There are some additional parts to the transcript, which I'll post in a separate entry. Stay tuned ...
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