Inventor, futurist Ray Kurzweil on How to Create a Mind @ Talks at Google (Full Transcript)
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Boris Debic: Welcome everyone, to yet another Authors@Google Talk. It is my distinct privilege today to host Dr. Ray Kurzweil, and my good friend here, Peter Norvig, from our Artificial Intelligence group, former director of research at Google.
So just to give you a little bit of context why I am hosting this talk. When I was a kid and I wrote my first lines of code in elementary school, I saw a tremendous potential in that toy that I was playing with. And I said to all my friends, you know what? One of these days, these are going to be as smart as humans. We just have to work a lot at it.
And they would say, oh, no, that’s impossible. How can you say something like that? I really didn’t have a good answer in those times. I was just a kid. But I told them, look, I mean it’s all built of atoms, right? The CPUs in this thing, that’s atoms, and our brains, that’s atoms. So there’s no theoretical impossibility for this to happen.
Well, today, I’m very happy to host two guys who can explain why this will happen in much more detail. Please welcome Dr. Ray Kurzweil to Google.
Peter Norvig: I think it’s redundant to introduce Ray. You all know him as an inventor, author, a futurist. And you know, there was a book a few years back that accused Xerox PARC of fumbling the future. And I would say, to continue that metaphor, Ray has intercepted the future and returned it for a touchdown, multiple times. He has done it with the flatbed scanner, with OCR, with print-to-speech, text-to-speech, speech recognition, music synthesis, and so on and so on. I won’t list all the honors, but he’s been recognized by Presidents Johnson, Clinton, and Reagan, and by Bill Cullen. Those of you who are younger, you’ll have to Google that.
But let me put it this way. Have you heard of Plato, Aristotle, Socrates? Philosophers. And Ray is a philosopher, too. But more importantly, foremost, he’s an engineer. And when it comes to these tough questions of creating the mind, philosophers are useful, but I’m putting my money on the engineers.
Ray Kurzweil- Inventor, futurist
Well, thanks for that, Peter. Can you hear me back there? Yeah?
I agree with that. In fact, I decided I wanted to be — well, I called it an inventor when I was five. And I had this conceit. I know what I’m going to be, and it kind of reflected my family philosophy that if you have the right ideas, you can overcome any problem. And I particularly like coming here. This is actually my third time at Authors@Google. I was here in 2005. I wouldn’t exactly say Google was a young upstart at that time. It was, I think, about 4,000 people. I did it in the lunchroom near here. The spirit hasn’t changed. I think you’re about 10 times the size. 40,000 is like the size of a small city.
But you’re still actually a start-up compared to the opportunity, because the world is increasingly based on knowledge and information. In fact, 65% of American workers are knowledge workers. So the mission of organizing and providing intelligent access to all the world’s knowledge is the most important task in the world, and Google is clearly the leader in that. And there’s tremendous potential, because knowledge is growing exponentially.
So I want to say a few words about exponential growth and my law of accelerating returns, which was the primary message of “The Singularity is Near.” But I think Google is actually a very good example of that exponential growth. I happened to be on Moira Gunn’s “Tech Nation” NPR program yesterday, and she was reminiscing about her 2001 interview with Larry and Sergey, who came in with dark suits and ties. And they were trying to explain this cool computer they were going to create. And she didn’t quite understand what it was. And Larry said, well, it’s going to be like HAL. And then Sergey said, but it won’t kill you, so.
So I think we got the second part of that. The first part of that we have, in the sense that Google is pretty amazing in terms of finding information. I’m amazed by it every hour. But I think we can go further in that direction, and that’s what I’d like to talk about. You all have these billions of pages of millions of books, and very good access to it, but there’s a lot of information there that’s reflected in the natural language ideas. And computers, now, I think can begin to understand those. And that’s something I’m working on. That’s something I talk about in this book. And I’d like to share that idea with you.
First, I’ll say a few words about the law of accelerating returns. I mentioned I decided to be an inventor when I was five. I realized 30 years ago that the key to being successful is timing. Those inventors whose names you know are the ones who got the timing right. So Larry and Sergey had this great idea about reverse-engineering the links on the internet to provide a better search engine, but they did it at exactly the right time.
And so in 1981, I was thinking, my project has to make sense when I finish the project, and the world will be a different place two, three, four years from now. That was even true in ’81. It’s even more true today.
Acceleration is another feature of the law of accelerating returns. Our first communication technology, spoken language, took hundreds of thousands of years to develop. Then people saw that stories were drifting. People didn’t always retell the story in the same way, so we needed some record of it. So we invented written language. That took tens of thousands of years. Then we needed more efficient ways of producing written language. The printing press actually took 400 years to reach a mass audience. I gave a speech at the University of Basel recently on the occasion of its 550th anniversary. It was founded 20 years after Gutenberg’s invention, right near the spot where he invented it.
And I said, well, you must have had some of his books when you opened your doors. And they said, yes, we got them very quickly. It was only a century later. I mean, that was the Google of that time. It took maybe a century to find the right information. So you didn’t really find it in your lifetime. It took 400 years for that really to reach an appreciable number of people.
The telephone reached 25% of the US population in 50 years. The cell phone did that in seven years. Social networks — wikis, blogs — took about three years. Go back three or four years ago, most people didn’t use social networks, wikis and blogs. Ten years ago, most people didn’t use search engines. That sounds like ancient history, but it wasn’t so long ago.
And then we very quickly become dependent on these brain extenders. I mean, during that one-day SOPA strike, I felt like a part of my brain had gone on strike. Because there was a way around it, but I didn’t know that until the day came. So I really felt like I’m going to lose part of my mind. Yet this was not technology that I had even a few years earlier.
What’s driving this is the exponential growth of information technology. In 1981, I began to look at data, being an engineer. But I started out with the common wisdom that you cannot predict the future. And that remains true as to which company, which standard will succeed. But if you measure the underlying properties of information technology — the first one I looked at, in a classical one, the power of computation per constant dollar. So the calculations per second per constant dollar. Or the number of bits we’re moving around wirelessly, or the number of bits on the internet, or the cost of transmitting a bit, or the spatial resolution of brain-scanning, or the amount of data we’re downloading about the brain, or the cost of sequencing a base pair of DNA or a genome, or the amount of genetic data we’re sequencing — I mean, these fundamental measures follow amazingly predictable trajectories, really belying the common wisdom that you cannot predict the future.
And what’s predictable is that they grow exponentially. And that is not intuitive. Our intuition about the future is that it’s linear, not exponential. If you ever wondered, why do I have a brain? It’s really to predict the future, so we could predict the consequences of our actions and inactions. So I’m walking along, and, OK, that animal’s going that way towards a rock, and I’m going this way. We’re going to meet in about 20 seconds up at that rock. I think I’ll go a different way. That proved to be useful for survival. That became hardwired in our brains.