WEBVTT - How Ray Kurzweil Works

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<v Speaker 1>Brought to you by the reinvented two thousand twelve Camray.

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<v Speaker 1>It's ready. Are you get in touch with technology? With

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<v Speaker 1>Here there, everybody, welcome to the podcast. My name is

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<v Speaker 1>Chris Poulett. I'm an editor here at How Stuff Works.

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<v Speaker 1>And next to me, as always is senior writer Jonathan Strickland.

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<v Speaker 1>How do folks? And uh, we're going to continue our series,

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<v Speaker 1>this being the second series, so I guess technically it's

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<v Speaker 1>not a serious yet we have to have one more,

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<v Speaker 1>okay unless you're the Braves in case those two games

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<v Speaker 1>are winning streak. Now, Um, we're going to talk about

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<v Speaker 1>some uh, some famous tech people here and there in

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<v Speaker 1>our podcasts, and today we have chosen to speak of Ray.

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<v Speaker 1>That's right, Ray Kurtzwile. Uh and if you haven't heard

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<v Speaker 1>the name before, um, shame on you. No, No, We're

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<v Speaker 1>we're gonna fix that. We'll start off slow. I want

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<v Speaker 1>to talk about kind of his entry into the whole

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<v Speaker 1>tech world. He was interested in computers back when computers

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<v Speaker 1>were pretty much brand new. Yeah, we're talking punch cards. Yeah,

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<v Speaker 1>and um uh he was known for being he was

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<v Speaker 1>one of the people first people who was really interested

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<v Speaker 1>in artificial intelligence for computers. Um, starting off with simple

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<v Speaker 1>pattern recognition, where you could teach a computer to recognize

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<v Speaker 1>a pattern of information and identify it and respond when

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<v Speaker 1>it detects that pattern. Uh. And one of the famous

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<v Speaker 1>first attempts that he made was a program that he

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<v Speaker 1>created for a computer where it could um analyze classical

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<v Speaker 1>music and look at all the different uh features of

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<v Speaker 1>classical music from famous composers, and then compose music itself

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<v Speaker 1>based upon the information that it gleaned by looking at

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<v Speaker 1>this music. And uh. He actually went on a kind

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<v Speaker 1>of a goofy little game show where they played this

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<v Speaker 1>music and they had the contestants had to guess that

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<v Speaker 1>it was the computer that made it. But anyway, I

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<v Speaker 1>just thought it was kind of cool that he created

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<v Speaker 1>this computer program in the first place. You know, I

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<v Speaker 1>gotta say it's a classic game show. It was I've

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<v Speaker 1>Got a Secret with with Ray Allen and his host

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<v Speaker 1>and uh, I just did point out this was in

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<v Speaker 1>ve and he was in high school when he was

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<v Speaker 1>on national TV doing this with a computer program that

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<v Speaker 1>he had created that that did that had this pattern

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<v Speaker 1>recognition ability. That's pretty amazing. That's pretty awesome, I gotta

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<v Speaker 1>say so. But that's just the very beginning of his

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<v Speaker 1>amazing career. Oh yeah, yeah. Um. He went on to

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<v Speaker 1>UH to work at m I T yep UM and

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<v Speaker 1>there he actually created a program that would try to

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<v Speaker 1>match kids and colleges together for the best fit and

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<v Speaker 1>not necessarily hit with the parents. No, because it left

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<v Speaker 1>out some pretty important schools. It seemed it didn't seem

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<v Speaker 1>to recommend certain big name schools like Harvard and Yale.

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<v Speaker 1>Is there a call, Yes, well, you know, if you're

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<v Speaker 1>suited for Podunk Community College. It was going to tell

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<v Speaker 1>you the truth, right right. But he sold that business

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<v Speaker 1>and made the tidy profit. I think it was for

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<v Speaker 1>about a hundred thousand dollars, which is a good chunk

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<v Speaker 1>of change. And uh, that was not the first time

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<v Speaker 1>that he founded a company and then later sold it.

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<v Speaker 1>In fact, he's kind of made a career of that.

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<v Speaker 1>Speaking of pattern recognition, we've noticed as we were doing

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<v Speaker 1>the research for Mr Kurtzwild that he has sold off

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<v Speaker 1>several of his companies, and I think all of them

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<v Speaker 1>are still in existence in some form. All the all

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<v Speaker 1>of the four major companies are still operating in some

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<v Speaker 1>form or another. That's a good that's a good h

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<v Speaker 1>that's not a bad track record at all. And you

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<v Speaker 1>look at the companies that are around these days and

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<v Speaker 1>which ones aren't around. So yeah, In nineteen seventy four

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<v Speaker 1>he founded UH, the Kurtswild Computer Products Incorporated Company UM

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<v Speaker 1>and that was one where again pattern recognition came into play.

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<v Speaker 1>That's where he was looking at ways for computers to

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<v Speaker 1>recognize printed text and UH to be able to actually

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<v Speaker 1>read that printed text. So this came in very handy

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<v Speaker 1>for people who are visually impaired. You could have a

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<v Speaker 1>computer that could when when you scanned a sheet of

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<v Speaker 1>paper that text on, it could interpret that text UM

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<v Speaker 1>and read it back. And and this is trickier than

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<v Speaker 1>you would first think. I mean you might think, oh, well,

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<v Speaker 1>you just have to teach it. One A looks like

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<v Speaker 1>you can't just teach a computer. One A looks like

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<v Speaker 1>you have to teach it, teach it. What a times

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<v Speaker 1>New Roman A an aerial A, A comic sans A

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<v Speaker 1>a handwritten A. I mean no, you know, not all

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<v Speaker 1>a's are created equally. And you had to do this

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<v Speaker 1>for every single letter. It had to be able to

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<v Speaker 1>interpret on the fly sometimes because you don't always have

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<v Speaker 1>the most clean copy of text either. Um. So Kurt's

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<v Speaker 1>well dedicate a lot of time and energy into perfecting this,

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<v Speaker 1>and um he got a lot of attention for it. Yeah.

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<v Speaker 1>You might know this technology by by its initials O

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<v Speaker 1>c R, which is optical character recognition. And you say, oh, yeah,

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<v Speaker 1>that's the uh, that's the system they use on my

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<v Speaker 1>flatbed scanner. Well, funny you should mention that because, as

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<v Speaker 1>Jonathan pointed out, this is this is a very useful

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<v Speaker 1>thing for people who can't see because, um, a suggestion

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<v Speaker 1>came in from a visually impaired person and said, you know,

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<v Speaker 1>it'd be really cool if you could use this for that.

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<v Speaker 1>And so they invented the flatbed scanner and a text

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<v Speaker 1>to speech program to work together with this optical character

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<v Speaker 1>recognition and do exactly that. And it ended up being

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<v Speaker 1>called the kurtswhile Reading Machine, which debuted in January of

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<v Speaker 1>seventy six. And uh, that that you know there was

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<v Speaker 1>a reasonably well known fan of that system. Oh wait,

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<v Speaker 1>I think I know who you're talking about, not Wondering, No,

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<v Speaker 1>I now I know Stevie Wonder. Stevie Wonder. I did

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<v Speaker 1>read that. I was thinking, you know, I think I

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<v Speaker 1>know who said that. But and you know, Stevie Wonder

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<v Speaker 1>was he was the first customer, wasn't it he about

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<v Speaker 1>the first one. He bought the very first one. And

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<v Speaker 1>and just this a note before, you know, let Jonathan

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<v Speaker 1>get back on that. But when I started, we were

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<v Speaker 1>talking about ideas for people, famous people. Um I kurs

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<v Speaker 1>Wild has been on on my reading list for a while.

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<v Speaker 1>He has several books out. We'll talk about that in

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<v Speaker 1>a minute. But um, I thought, you know, that's the

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<v Speaker 1>guy who makes the musical instruments. Well, this is the

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<v Speaker 1>start of all that. When he became friends with Stevie

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<v Speaker 1>Wonder as a result of developing this reading machine, they

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<v Speaker 1>developed a partnership for music. Uh you know, which we'll

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<v Speaker 1>talk about a minute. But that's where I knew him from,

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<v Speaker 1>was the musical instrument. So delving into his past, he's

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<v Speaker 1>got all these different things that he's done. It's just

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<v Speaker 1>a personal note. Sorry, no, no no, no, look, I think

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<v Speaker 1>I think we should just keep on building on that. Yeah,

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<v Speaker 1>and and he he founded h kurts Wild Music and U.

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<v Speaker 1>Together with Stevie Wonder, he managed to create a synthesizer

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<v Speaker 1>that sounded more like a an actual piano than any

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<v Speaker 1>synthesizer up to that time. And in fact, in blind tests,

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<v Speaker 1>many musicians could not tell the difference between the synthesizer

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<v Speaker 1>and a real grand piano um which of course was

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<v Speaker 1>a huge, huge achievement because up to that point computer

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<v Speaker 1>instruments sounded a lot like a craft work record, right,

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<v Speaker 1>computer instruments, I was gonna say they sounded they sounded

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<v Speaker 1>did They sounded artificial? They did not sound natural at all.

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<v Speaker 1>So Kurtswild really made some some great progress into U

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<v Speaker 1>into breaking that barrier so that you could have a

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<v Speaker 1>more natural sound coming from a digital instrument. Yep, and UH.

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<v Speaker 1>As a matter of fact, that company got sold They

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<v Speaker 1>actually created Kurtzwild Music Systems, and that company got sold

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<v Speaker 1>off to uh UM, Asian company called Young Chang Um

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<v Speaker 1>and it's still doing business. He was actually a consultant

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<v Speaker 1>for a while. Apparently is no longer, but he's got

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<v Speaker 1>some other stuff he's done. Um, you know, like speech recognition.

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<v Speaker 1>For example, he came up with the first large vocabulary

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<v Speaker 1>speech recognition system. Yeah, you might be sensing a pattern here,

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<v Speaker 1>pattern recognition. Hey. Now instead of text, he's looking at speech.

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<v Speaker 1>This was part of the kurts While Applied Intelligence initiative

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<v Speaker 1>that you made. Um, yeah, it's uh so once again,

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<v Speaker 1>he's looking at ways that computers and people interact, trying

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<v Speaker 1>to break those barriers down as much as possible so

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<v Speaker 1>that the interaction becomes very natural and almost to the

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<v Speaker 1>point ideally, you get to the point where you're not

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<v Speaker 1>even conscious of the interface anymore. It's just it just happens.

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<v Speaker 1>And of course we're we're miles away from that right now,

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<v Speaker 1>but it's because of things like like the speech recognition

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<v Speaker 1>and the text recognition that Kurtswhile worked on, that we're

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<v Speaker 1>making progress toward that goal. True. So yes, And speaking

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<v Speaker 1>of print to speech, there was another company founded, Chris

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<v Speaker 1>Wild Educational Systems. Yet yet another program, and there were

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<v Speaker 1>a whole bunch of other little things that he's done.

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<v Speaker 1>They're just fascinating. Um fat cat, for example, I thought

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<v Speaker 1>it was really cool using a computer algorithms to predict

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<v Speaker 1>the patterns of the markets, right, you would you're essentially

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<v Speaker 1>trying to create a a an artificially intelligent stock market trader,

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<v Speaker 1>So you would you would follow the the guidance of

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<v Speaker 1>an artificially intelligent you know, I've met some stock market traders.

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<v Speaker 1>I would suggest that a lot of their intelligence is

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<v Speaker 1>completely artificial. So I don't see this as a big stretch. Yeah,

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<v Speaker 1>that's the whole thing is it's not really their fault.

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<v Speaker 1>The markets just do what the markets do. You wonder, like,

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<v Speaker 1>can you program in that kind of intuition? I am

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<v Speaker 1>very curious as to how fat cat performs actually, because

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<v Speaker 1>uh so much of the stock market is beyond just

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<v Speaker 1>just logic. I mean, you have to you have to

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<v Speaker 1>take in so many factors into account, just crowds ecology

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<v Speaker 1>for one. We're we're seeing right now in the markets

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<v Speaker 1>where they're bouncing up and down, that that as people

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<v Speaker 1>gain confidence and lose confidence, so goes the market. And

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<v Speaker 1>you know, it's kind of hard to just predict that

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<v Speaker 1>all on its own. Yeah, I think we probably have

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<v Speaker 1>all experienced in proof of that. Wise, Right, let's let's

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<v Speaker 1>not think of our ferro One case at the moment,

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<v Speaker 1>showing um other things Mr Kurtzwil has been involved with,

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<v Speaker 1>you know, the Medical Learning Company which has a patent

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<v Speaker 1>for online doctor training. Yeah. Um, and uh, the Kurtswild

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<v Speaker 1>cyber Art, which is a digital art software company that

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<v Speaker 1>apparently no longer has its program available for download. But

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<v Speaker 1>essentially it was tricking your computer into drawing things for you,

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<v Speaker 1>which was kind of cool. I think it was more

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<v Speaker 1>of a just a messing around type thing, but um,

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<v Speaker 1>messed around with some other stuff. I know that if

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<v Speaker 1>you go to the Kurtswild ai uh site, he has

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<v Speaker 1>a was it roberta the artificially intelligent creature that you

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<v Speaker 1>can ask it questions and answers. I played with that

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<v Speaker 1>a little bit before the podcast and uh, and it's

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<v Speaker 1>definitely not up to the touring test just yet. But um,

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<v Speaker 1>but you know, you can see where where his interests are.

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<v Speaker 1>In fact, we should probably talk about that as kurtswell

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<v Speaker 1>is is. You know, we're talking about a lot of

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<v Speaker 1>his past accomplishments, but you might be saying, well, what's

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<v Speaker 1>he up to today? He's right on the forefront of

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<v Speaker 1>all the people who are talking about something that, um, well,

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<v Speaker 1>you might call it a convergence. You might call it

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<v Speaker 1>the singularity. But it's this idea of reaching a point

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<v Speaker 1>where we have artificially intelligent machines. He likes to call

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<v Speaker 1>it accelerated intelligence, UM, but artificially intelligent machines that can

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<v Speaker 1>create new, smarter, artificially intelligent machines. And we just reached

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<v Speaker 1>this point where it becomes is the tipping point really

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<v Speaker 1>where innovation comes at at shorter and shorter gaps, so

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<v Speaker 1>eventually get to a point where it's just con stantly innovation,

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<v Speaker 1>and no one really knows what that's going to look like. UM.

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<v Speaker 1>And Uh, he's one of the people who really is

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<v Speaker 1>is kind of a proponent of this idea. UM. He's

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<v Speaker 1>talked about the singularity many times, and it seems very

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<v Speaker 1>very enthusiastic about it, UM, as opposed to some people

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<v Speaker 1>who are really scared of it. Yeah, that's that's true. Um.

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<v Speaker 1>The singularity was actually proposed some time back by a

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<v Speaker 1>mathematician named John von Newman. UM. And he was saying,

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<v Speaker 1>you know, this is a point after which human affairs

0:12:34.440 --> 0:12:40.600
<v Speaker 1>cannot continue as normal. That's short of vague description. Verner VINGI, Yeah,

0:12:42.320 --> 0:12:44.640
<v Speaker 1>this is an article that that Jonathan just wrote not

0:12:44.760 --> 0:12:48.599
<v Speaker 1>too long ago. UM, he was talking about the possibility

0:12:48.640 --> 0:12:53.120
<v Speaker 1>that machines will become artificially intelligent and you know, design

0:12:53.240 --> 0:12:56.800
<v Speaker 1>venter machines and decide we're irrelevant and that you know,

0:12:56.880 --> 0:13:00.160
<v Speaker 1>we should just go away right or the other out

0:13:00.160 --> 0:13:02.599
<v Speaker 1>of the coin. He doesn't say that that's necessarily what

0:13:02.640 --> 0:13:05.800
<v Speaker 1>would happen. Um. He does say that no matter what,

0:13:05.960 --> 0:13:08.600
<v Speaker 1>our lives will be completely different, and to the point

0:13:08.600 --> 0:13:11.240
<v Speaker 1>where it's almost it's almost pointless to try and imagine

0:13:11.240 --> 0:13:13.360
<v Speaker 1>what our lives will be like because there's no way

0:13:13.400 --> 0:13:17.000
<v Speaker 1>of knowing right now. But we it could be the opposite.

0:13:17.040 --> 0:13:19.280
<v Speaker 1>We could be living in a paradise where machines are

0:13:19.280 --> 0:13:22.400
<v Speaker 1>doing everything we need them to do for us. Um.

0:13:22.440 --> 0:13:24.720
<v Speaker 1>We don't have to do anything for ourselves, and we

0:13:24.760 --> 0:13:27.120
<v Speaker 1>can pretty much spend our lives just you know, learning

0:13:27.160 --> 0:13:32.640
<v Speaker 1>new things or uh, pursuing art or fooling around, you know,

0:13:32.679 --> 0:13:36.720
<v Speaker 1>whatever happens to be your your purpose for life. You

0:13:36.760 --> 0:13:39.080
<v Speaker 1>don't necessarily have to clock in and clock out every

0:13:39.120 --> 0:13:42.080
<v Speaker 1>day because machines are doing it for you. Um. I'm

0:13:42.080 --> 0:13:45.079
<v Speaker 1>sure that psychologists and psychiatrists will still be in great demand.

0:13:45.679 --> 0:13:48.679
<v Speaker 1>Doctors will probably still be in demand. I mean, there's

0:13:49.000 --> 0:13:52.360
<v Speaker 1>farmers definitely I mean, some things humans will probace still

0:13:52.440 --> 0:13:55.160
<v Speaker 1>have a hand in, although a lot of those tasks,

0:13:55.200 --> 0:13:58.360
<v Speaker 1>even in those fields, will be automated by machines according

0:13:58.400 --> 0:14:00.640
<v Speaker 1>to this vision. And I even get to a point

0:14:00.679 --> 0:14:03.439
<v Speaker 1>where we don't even need them anymore, perhaps our consciousness

0:14:03.480 --> 0:14:07.839
<v Speaker 1>will merge with some sort of computer network, which sounds

0:14:07.880 --> 0:14:10.400
<v Speaker 1>really far out right now. But these are the kind

0:14:10.440 --> 0:14:12.640
<v Speaker 1>of things that hurts Weill and and Verne as I'll

0:14:12.640 --> 0:14:15.559
<v Speaker 1>like to call him talk about. I mean, they they

0:14:15.600 --> 0:14:19.960
<v Speaker 1>they are not outside the realm of possibility in their minds. Well, yeah,

0:14:20.000 --> 0:14:22.040
<v Speaker 1>it's it's funny, uh, that you said that, because I

0:14:22.080 --> 0:14:25.120
<v Speaker 1>was going to point out that Ray kurtzwill is believe

0:14:25.200 --> 0:14:28.120
<v Speaker 1>that this is actually going to be a good thing. Um,

0:14:28.200 --> 0:14:32.400
<v Speaker 1>And instead of being the end of human conscious consciousness,

0:14:32.720 --> 0:14:36.840
<v Speaker 1>thank you. Um, it's actually kind of be that the

0:14:36.880 --> 0:14:39.720
<v Speaker 1>start of something really cool where it's going to prolong

0:14:40.240 --> 0:14:43.960
<v Speaker 1>human consciousness and preserve human consciousness, which is why he's

0:14:43.960 --> 0:14:49.280
<v Speaker 1>been doing a lot of preparation. An article and Wired

0:14:49.360 --> 0:14:52.600
<v Speaker 1>earlier in two thousand and eight, Um, I read that

0:14:53.040 --> 0:14:57.040
<v Speaker 1>he is taking massive doses of vitamin supplements and doing

0:14:57.080 --> 0:14:59.560
<v Speaker 1>a lot of exercise to try to prolong his life

0:14:59.600 --> 0:15:02.400
<v Speaker 1>in order to catch up to the singularity so that

0:15:02.480 --> 0:15:06.360
<v Speaker 1>his consciousness can be among those preserves. He actually he

0:15:06.400 --> 0:15:09.480
<v Speaker 1>wrote a book about that, in fact, about about living

0:15:09.480 --> 0:15:12.080
<v Speaker 1>a healthy lifestyle. He was able to uh beat heart

0:15:12.080 --> 0:15:16.960
<v Speaker 1>disease and diabetes. Diabetes. Yeah, that's pretty serious stuff. So

0:15:17.040 --> 0:15:20.200
<v Speaker 1>um yeah, he's definitely determined to see this come about.

0:15:20.320 --> 0:15:23.840
<v Speaker 1>And according to uh to Urn, uh, we should expect

0:15:23.920 --> 0:15:26.280
<v Speaker 1>it before the year. Say, I think it was a

0:15:26.720 --> 0:15:31.240
<v Speaker 1>thirty something like that, so so not too far off,

0:15:31.280 --> 0:15:33.800
<v Speaker 1>I mean, uh. And the whole point on that is

0:15:33.840 --> 0:15:36.560
<v Speaker 1>just the idea of this development cycle. It's getting shorter

0:15:36.640 --> 0:15:39.120
<v Speaker 1>and shorter and shorter for us to make more and

0:15:39.160 --> 0:15:41.360
<v Speaker 1>more powerful machines. Now, whether or not we hit a

0:15:41.920 --> 0:15:46.720
<v Speaker 1>barrier before we can hit the artificial intelligence slash accelerated

0:15:46.760 --> 0:15:49.960
<v Speaker 1>intelligence goal post that remains to be seen. We may

0:15:49.960 --> 0:15:52.640
<v Speaker 1>not be able to achieve it as fast as everyone thinks,

0:15:52.640 --> 0:15:55.560
<v Speaker 1>because we might actually hit physical limitations on what we

0:15:55.640 --> 0:15:58.400
<v Speaker 1>can what we can really do, and that could slow

0:15:58.480 --> 0:16:00.960
<v Speaker 1>us down. Next thing, you know, it might be twenty six.

0:16:01.640 --> 0:16:05.360
<v Speaker 1>Yeould be really depressing. They're always putting off good stuff

0:16:05.400 --> 0:16:09.400
<v Speaker 1>like that, you know, when the machines take over. Anyway,

0:16:11.280 --> 0:16:14.120
<v Speaker 1>the book that I was most interested in was the

0:16:14.120 --> 0:16:18.080
<v Speaker 1>the age of spiritual machines when human computers exceed human intelligence,

0:16:18.160 --> 0:16:19.880
<v Speaker 1>and that that sort of gives you an idea of

0:16:19.920 --> 0:16:24.680
<v Speaker 1>the um the concept that he's got the crush Wells

0:16:24.680 --> 0:16:28.000
<v Speaker 1>got of what he expects from the singularity in in

0:16:28.000 --> 0:16:33.120
<v Speaker 1>in the future. So it would be interesting to check out. Yeah, yeah,

0:16:33.120 --> 0:16:36.520
<v Speaker 1>we'll definitely have to keep our eyes on that. You know. Um,

0:16:36.560 --> 0:16:40.480
<v Speaker 1>I've got something a similar field that Kurt Swell is

0:16:40.480 --> 0:16:43.480
<v Speaker 1>actually interested in that relates to this that I want

0:16:43.520 --> 0:16:47.080
<v Speaker 1>to talk about. But before we do, Okay, I'd like

0:16:47.120 --> 0:16:50.760
<v Speaker 1>to take a moment to thank our sponsor. Yes, so

0:16:50.800 --> 0:16:53.680
<v Speaker 1>we have our sponsor, audible dot com And if you

0:16:53.800 --> 0:16:57.800
<v Speaker 1>sign up at www dot audible podcast dot com slash

0:16:57.920 --> 0:17:01.400
<v Speaker 1>text stuff, you'll get a free download when you when

0:17:01.400 --> 0:17:03.720
<v Speaker 1>you sign up, you can download any book for free,

0:17:03.920 --> 0:17:06.400
<v Speaker 1>and they have fifty thousand books on audible dot com.

0:17:06.440 --> 0:17:09.679
<v Speaker 1>It's a huge library. And we each came up with

0:17:09.720 --> 0:17:13.520
<v Speaker 1>a an a book to suggest that kind of sort

0:17:13.560 --> 0:17:15.440
<v Speaker 1>of relates to our topic. Christy, want to you want

0:17:15.440 --> 0:17:18.040
<v Speaker 1>to go first? Sure, since we were talking about verner VINGI.

0:17:18.920 --> 0:17:22.400
<v Speaker 1>He is a noted science fiction author and his book

0:17:22.480 --> 0:17:27.360
<v Speaker 1>Rainbows end is available now at audible podcast dot com.

0:17:28.000 --> 0:17:31.280
<v Speaker 1>Nice and uh, you know it could be an interesting

0:17:31.280 --> 0:17:36.520
<v Speaker 1>and worthwhile reading insight into his uh his background there right, mine, mine,

0:17:36.600 --> 0:17:40.080
<v Speaker 1>I I played a little bit here. Um. I'm also

0:17:40.119 --> 0:17:45.000
<v Speaker 1>a science fiction fan. But I chose Pattern Recognition by

0:17:45.000 --> 0:17:47.600
<v Speaker 1>William Gibson. Yeah, so, um, yeah, I wanted to go

0:17:47.640 --> 0:17:50.000
<v Speaker 1>with neuromancwer but I didn't see that on audible dot com.

0:17:50.040 --> 0:17:54.000
<v Speaker 1>But they have Pattern Recognition, which is another William Gibson book.

0:17:54.080 --> 0:17:56.720
<v Speaker 1>It's not actually about the same sort of pattern recognition

0:17:56.720 --> 0:17:59.880
<v Speaker 1>that Kurt Swell was talking about, but it's a great mystery.

0:18:00.160 --> 0:18:01.760
<v Speaker 1>But and and it is a good book. It is

0:18:01.760 --> 0:18:04.000
<v Speaker 1>a good but a real real page turner. Or if

0:18:04.040 --> 0:18:06.760
<v Speaker 1>you're listening to it on audible dot com, it's an

0:18:06.800 --> 0:18:10.080
<v Speaker 1>excellent listen. You should definitely listen to it. That could

0:18:10.080 --> 0:18:11.800
<v Speaker 1>be one of your that could be your free download

0:18:11.840 --> 0:18:15.359
<v Speaker 1>if you wanted, right, so, you can sign up for

0:18:15.400 --> 0:18:19.440
<v Speaker 1>that at www dot audible podcast dot com. Slash tech

0:18:19.480 --> 0:18:23.480
<v Speaker 1>stuff And now let's get back to what I was

0:18:23.520 --> 0:18:25.159
<v Speaker 1>going to talk about. The technology I was going to

0:18:25.200 --> 0:18:30.320
<v Speaker 1>talk about. The Kurtswell is very much interested in nanotechnology.

0:18:30.320 --> 0:18:33.879
<v Speaker 1>It's definitely part of this whole concept of the singularity

0:18:34.000 --> 0:18:38.679
<v Speaker 1>um building devices that are on the nanoscale, which is

0:18:38.840 --> 0:18:44.440
<v Speaker 1>incredibly tiny. We're talking like on the atomic level. And uh,

0:18:44.640 --> 0:18:46.919
<v Speaker 1>nanotechnology is one of those things that probably is going

0:18:46.960 --> 0:18:50.159
<v Speaker 1>to be necessary in order to achieve these goals. I mean,

0:18:50.200 --> 0:18:54.000
<v Speaker 1>we're already building transistors that are on the nanoscale. So

0:18:54.080 --> 0:18:55.960
<v Speaker 1>if you want to learn more about that, I recommend

0:18:55.960 --> 0:19:02.680
<v Speaker 1>you read How Nanotechnology Works. That's by Jonathan Strickland. Not

0:19:02.840 --> 0:19:05.760
<v Speaker 1>to toot my own horn, but how Manamail Technology Works.

0:19:05.760 --> 0:19:08.439
<v Speaker 1>And it's live right now at how stuff works dot

0:19:08.520 --> 0:19:14.199
<v Speaker 1>com and we'll talk to you again soon. Let us

0:19:14.240 --> 0:19:17.160
<v Speaker 1>know what you think. Send an email to podcasts at

0:19:17.160 --> 0:19:23.919
<v Speaker 1>how stuff works dot com. Brought to you by the

0:19:23.960 --> 0:19:27.280
<v Speaker 1>reinvented two thousand twelve camera. It's ready, are you