Ray Kurzweil: Well, part of the image enhancement is to use a polarizing filter that gets rid of glare . So, that was a bit of engineering that we did.
But mostly, the intelligence of the image enhancement is in the software. There's seven or eight different types of image degradation that occur with a handheld camera, and with three different degrees of freedom of tilt and rotation, uneven illumination, curved lines, out of focus images, and things like that.
Mark David: You talked a bit already—this is one of the questions I was going to ask—and it was really interesting what you were already saying about what's next in the vision for the future where the device would be used to recognize things beyond print.
Sort of two questions coming out of that. Having worked on this project, do you see any new sorts of applications for OCR outside of the blind reading field? And then within devices for the blind, do you have additional comments based on the experiences you've gained in this project; does it change your vision for where things are going?
Ray Kurzweil: Well, we're focused on this application.
There's a whole world of print out there, and....
Mark David: So, there's so much more for this. Right?
Ray Kurzweil: Products like the Kurzweil 1000 are optimized for printed documents like books and magazines. Print in the real world actually has much more variety in terms of formats and can exist...amidst the trees and other vagaries of real world images. And trying to figure out where the print is in a real world scene is different than the kind of assumptions you can assume if this was "a document." We're not just reading documents. And it actually works quite well, but we have a series of improvements we're making on that. This is a software-based product, so users will be able to easily update their software on an SD card.
And in terms of a more advanced direction, I mentioned we are seriously pursuing object recognition so this can be more than a reading machine. It can really be like a sighted assistant. It ultimately could be quite sophisticated in recognizing people and objects and describing real world scenes. Well, a seeing eye dog gives you some information, but this could actually be more like a sighted person describing what's in a room to you. So, that's where we're [heading]....
Mark David: ...Getting into coupling, what has been machine vision, but object recognition, and then also some biometrics, even, if you wanted to get specific about face recognitions and so forth?
Ray Kurzweil: Right. I mean there is face recognition software that actually works quite well, and we're working on integrating that into this application.
Mark David: But again, the challenge to bring it into the portable unit and to make it work for these unique applications....
Ray Kurzweil: ...Yeah....
Mark David: ...Gives you a lot to work on, for sure.
Again, considering our audience of engineers and designers, and your quite impressive track record in your career, do you have any sort of more general advice you might want to share? You talked about timing the market right. And that's very interesting that you got into being a futurist because it allowed you to help time your inventions....
Ray Kurzweil: ...I mean, it's more than a casual observation....
Mark David: ...Right....
Ray Kurzweil: ...And I've spent a lot of time on that. And actually, I have a group of ten people that gather data methodically in different fields, and...
Ray Kurzweil: ... I've written a whole series of books on it. And so, it's actually gone beyond just touting my inventions. Although I will say that the primary application I have for this technology forecasting is to time my inventions. And this project's a good example of that.
Ray Kurzweil: But, it does enable us to, I think, get very realistic ideas of what computation, communication, and even biological technologies will be like in 2020 or 2030. And it's...I mean, this gets me into a whole different area about which I could say a lot.
Ray Kurzweil: But people say that you can't predict the future. And I maintain, actually, there's certain aspects of the future that you can reliably anticipate. And I say this now, not just looking backwards, but I've been making forward-looking predictions for 25 years.
My first book, which I wrote 20 years ago, predicted in the '80s the emergence of a worldwide communication network in the mid-'90s. And computer taking the world's chess championship by '98, which happened in '97. The dominance of intelligent weapons in warfare. And a lot of other...hundreds of predictions about the 1990s, certainly the 2000 years, which have tracked very well.
I have a whole theory as to why this is. You know, specific projects are unpredictable, but the overall impact of information technology is predictable.
And another example of where you can get predictable results out of unpredictable events is thermodynamics. The path of any one molecule in a gas is completely unpredictable. And you have this whole gas made up of a large number unpredictable, chaotically, randomly interacting particles. But the overall properties of the gas are very predictable, according to the laws of thermodynamics, to a very high degree of precision.
And the whole evolution of technology is a similarly dynamic, chaotic, rich system that has predictable outcomes. And the power of price performance, capacity, and bandwidth of information technologies doubles every year, which is pretty phenomenal. It's a factor of 1,000 in 10 years and 1 billion in 30 years. And we're also shrinking the size of technology at a predictable rate. And this also applies to biological technologies. The amount of genetic data we've sequenced has doubled every year. Cost has come down by half every year. So, what was $10.00 in 1990 is a penny today. I could actually go on for hours about this.
Mark David: Well, it's fascinating observations. And particularly, I mean, for an audience of people who are... our readers are the ones who are working to keep that Moore's Law on track and to keep the technology moving forward. And so, you have to think about the future when things are moving as quickly as they are in this field.
Ray Kurzweil: A key point, though, is Moore's Law is really just one example of many of what I...of this broader phenomenon, which I call the law of accelerating returns.
Ray Kurzweil: You see it in areas that have nothing to do with chips.
Really, if you can measure the information content, it generally doubles in capacity or price performance—whatever it is you're measuring—every 11 months, 12 months, 13 months, depending on what you're measuring. It grows exponentially. And people don't factor that into consideration. People tend to think linearly. I call that the intuitive linear view. But, it's wrong.
The historically correct view is exponential. And if you [look at it]...and it's highly predictable. Not necessarily what society will do with these capabilities, but the capabilities are predictable.
So, I have pursued this quite seriously. I have a group of ten people that help me gather data and develop these mathematical models.
Mark David: Very interesting.
Okay. Well, I won't take up more of your time today because I promised you that we'd keep it around a half an hour. Thanks so much, Ray.
Ray Kurzweil: Yep. Yep....
Mark David: ...Pleasure talking with you....
Ray Kurzweil: ...Likewise.
Mark David: Bye.