It was alluded to earlier that the pace of change is getting faster and faster. That's something that I've studied and that I will talk to you about. I happened to give a speech on the 500th hundred anniversary of the University of Basel about a year ago. This university was started 20 years after Gutenberg invented the printing press not too far away from where he made that invention. I said well that's exciting you must have had some of Gutenberg's books when you opened your doors in something like 1440. They said yes we got them very quickly. It was only a 100 years later! That is how technology moved in those days.
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took 400 years for the printing press to reach a large audience. The telephone reached the quarter of the population of the United States, Europe and Russia in about 50 years. Cell phones did in about 7 years. Social networks, wikis, blogs, some other recent technologies have done that in 3 years. So the pace of change is getting faster and faster. What's driving that is what I call the law of accelerating returns, which is that the exponential growth of information technology.
The way I encountered that, I decided that I wanted to be an inventor when I was 5 as I mentioned and I realized thirty years ago in 1981. As I started to look at the inventors that were successful, their timing was perfect. They did things exactly at the right time. It turns out that timing is important for just about anything, whether it's business investment or romance, you have to be in the right place at the right time. Most inventors actually get their projects to work, but usually inventors are too early or too late. So I wanted to study technology trends. I wanted to anticipate where the world would be by the time I finished the project. The project takes three or four years, it will be a different world three or four years later. It certainly is true today but it was also true in 1981. You can't shoot at the target where it is, you have to figure out where it's going to be. So, being an engineer I gathered a lot of data I did not expect to find anything very predictable. The common wisdom was and in most quarters is that you cannot predict the future. The future is unpredictable. There are certainly many examples of people who made bad predictions in the past about the future.
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But I made a very surprising discovery. If you measure the underlying properties of information technology, for example the power of computers in instructions per second per dollar, or, the number of bits that are moving around wirelessly in the whole world, or the number of base pairs of DNA for sequencing, I can mention a hundred measures like that, they follow very predictable trajectories. And what that predictable trajectory is, is an exponential progression. It basically doubles every period of time. That doubling time itself gets faster and faster. The world of computation, of computers, got started with the collection of the United States Census in 1890. It's been growing exponentially ever since. The power of computers for the same price doubled every three years around 1900, every two years around 1950, it was 12 months in the year 2000, went on to 11 months. It's a very smooth very predictable exponential trajectory. So I have this curve and I'll show it to you, up to 1980. I continued the curve through 2050, and now we're at 2012 exactly right on that curve. The power of computation has continued to flow exactly on that curve.
What's predictable is exponential and exponentials are very surprising. They're also not our intuition. We have an intuition about the future. We have a brain in fact to predict the future. That's why we have intelligence. When I walked through the fields a thousand years ago, I saw there's an animal going that way I'm going this way and I'd make a prediction, we're going to meet in about two minutes, we should go this over way. That 's turned to be good for survival. And I was making a prediction of where I would be of where the animal would be, a big decision. That's why intelligence is useful. These predictions about the future are lineal. I assumed we would keep going at the same pace. That worked out quite well in terms of the problems we needed to solve a thousand years ago. It turns out to be very inaccurate when it comes to predicting the pace of information technology.
Technologies before they become information technologies progress linearly like health and medicine, I'll talk about that in a moment. But once it becomes an information technology, it grows exponentially and that's not our intuition. So one of the differences between my own predictions and I have a thirty year track record in which I have been accurate, and my critics, using their intuition, hardwired in our brains, which is a linear prediction of the future, but it's simply not accurate when it comes to information technology.
Well you might say well what difference does it make is it really that different between a linear and an exponential projection? It doesn't make much difference in the short term, but it makes a huge difference in the long term. Most models that governments use to be able to predict the future, (it seems we have debates about Social Security, which is our old age retirement for the nation, the prediction that in 27 years it will run out of money) are all baed on linear projections of the future.
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Linear projections work out quite well for the short term, they're totally ridiculous for 10-20 years. If I take a step linearly, (that's our intuition about the future), 1, 2, 3, 4 by step 30 I am at 30. If I take 30 steps exponentially, 2, 4, 8 , 16, that is the reality of information technology. I get to a billion, it make a huge difference in the reality of what will happen. This is not just an idle speculation of the future. This is several billion times more powerful per dollar or per ruble then the computer that thousands of us shared when I was a student. It's also a thousand times smaller. And this will continue, in 25 years, this will again be a billion times more powerful. It will be 1,000 times smaller again, the size of a blood cell. Slowly we will begin to integrate with them, a completely new phenomena.
There are people walking today with computers connected to their brain, for example if you're a Parkinsons patient, or someone who has a cochlear implant for the deaf. There re computerized organs like computerized pancreases being implanted in people. So this happening requires surgery today, but when it's the size of a blood cell, it will go through the blood stream and this is one way in which we will integrate with machines.
I wanted to mention one other thing, which is that this exponential growth in information technology is very transformative. It does not just apply to these gadgets. It ultimately will apply to everything we care about.
Information Technology's Influence on Medicine
Take for example in Medicine, which didn't use to be an information technology. We would find things that happen to work. Oh here is something for high blood pressure. Here's something that kills the HIV virus. They were discovered accidentally. We would then systematically go through 10,000 compounds to see which would work. It's called drug discovery. That's not an information technology. But with the collection of the genome, which is basically the software of life, we are actually now beginning to treat biology as the information process which it truly is, as our little software programs. How long can you go without updating the software on your phone? This is probably updating itself now as I speak. But I have software running in my body, which hasn't been updated for thousands of years.
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| Insulin Fat Receptors via: Aging |
It's not just a metaphor. It's literally true. The fat insulin receptor genes, for example, says hold on to every calorie, because the next hunting season may not work out so well. That was a very good idea about a thousand years ago. It assumed there would be much available food. You did not know where your next meal would come from, so you would store every calorie in your body. So you would last until the next meal came along. I would like to tell my fat insulin receptor gene, you don't have to do that anymore.
That's exactly what was done in animal experiments. We turned that gene off. These animals ate an enormous amount and remained slim. It wasn't a fake slim. They didn't get Diabetes. They didn't get heart disease. They lived twenty percent longer. They got the benefits of caloric restriction while doing the opposite. There's pharmaceutical companies rushing to bring that to the human market. That's just one example of hundreds of projects where people are turning off or adding new genes.
I'm involved with a project where we take cells out of the body, lung cells, add a new gene, that's for people who have a disease, pulmonary hypertension caused by the lack of a certain gene. Missing a particular gene, you'll get this disease. The disease is particularly fatal within 12 months. Children 5 or 6 years old, if they do not have this gene get this disease and generally don't last more than a year.
We took these lung cells out of the body, added a new gene we were missing, replicated that a million fold and injected it back into the body. It went through the body, went through the blood stream then into the lungs and actually cured this disease. This procedure is now undergoing human trials. So this is just one example of many of actually reprogramming biology. It is inherently an information process.
We will continue with the rest of Kurzwei's lecture in our next installment.
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