Speaker 1: Welcome to tex Stuff, a production of I Heart Radios.
Speaker 1: How Stuff Works. Hey there, and welcome to tech Stuff.
Speaker 1: I'm your host, Jonathan Strickland. I'm an executive producer with
Speaker 1: I Heart Radio and I love all things tech. That's
Speaker 1: time for another tech Stuff classic episode where Lauren Voge,
Speaker 1: Obama and I sat down back in February two thirteen.
Speaker 1: This episode published February eleven, and we talked about the singularity.
Speaker 1: The episode was titled tech Stuff Enters the Singularity. So
Speaker 1: sit back and enjoy this discussion about a somewhat controversial
Speaker 1: hypothesis of the future of humanity today. We wanted to
Speaker 1: talk about the future. The future. Yeah, really, we're talking
Speaker 1: about a kind of a science fiction future. We're talking
Speaker 1: about the singularity. And uh, long time listeners to tex Stuff,
Speaker 1: and I'm talking about folks who listen way back before
Speaker 1: we ever talked out at thirty minutes, let alone an hour.
Speaker 1: May remember that we did an episode about how Ray
Speaker 1: Kurtzwild works. And Ray Kurtzwill is a futurist and one
Speaker 1: of the things he talks about extensively, particularly if you
Speaker 1: corner him at a cocktail party, is the singularity. And
Speaker 1: so we wanted to talk about what the singularity is,
Speaker 1: what this idea, you know, we really wanted to kind
Speaker 1: of dig down into it and why is this a
Speaker 1: big deal? And how realistic is this vision of the future. Yeah,
Speaker 1: because some people would take a little bit of uh,
Speaker 1: would would argue with your concept of it being science fiction.
Speaker 1: They take it extremely serious. Oh yeah, they say it's
Speaker 1: science fact, science fact, it's science inevitability. Yeah. The time.
Speaker 1: The term was actually coined by a mathematician, John von
Speaker 1: Newman in the nineteen fifties. Um, but it was popularized
Speaker 1: by a science fiction writer. Yeah, it's also Ah, there
Speaker 1: are a lot of different concepts that are hied up together,
Speaker 1: and it all depends on upon whom you ask what
Speaker 1: it means by the singularity. For instance, there's some people
Speaker 1: who when you hear the term the singularity, what they
Speaker 1: say is, Okay, that's a time when we get to
Speaker 1: the point where technological advances are coming so quickly that
Speaker 1: it's impossible to have a meaningful conversation of what the
Speaker 1: state of technology is because it changes changesseconds. So that's
Speaker 1: one version, but most of the versions that that we're
Speaker 1: familiar with that the futurists talk about incorporate an idea
Speaker 1: of superhuman intelligence or the intelligence explosion, right, a kind
Speaker 1: of combination of of human and technological development that just
Speaker 1: dovetails into this gorgeous you know, space Baby from two
Speaker 1: thousand one. Kind of that's an excellent way of putting it.
Speaker 1: The documentary two thou one. Uh, I remember specifically when
Speaker 1: the space baby looked at Earth. Okay, that documentary example
Speaker 1: doesn't work at all. It usually does, but not this time,
Speaker 1: not this time. S Space babies are a poor example
Speaker 1: in this in this one instance. But but metaphorically speaking, yes,
Speaker 1: you're right on track, because the intelligence explosion that was
Speaker 1: a term introduced by someone known as Irving John Good,
Speaker 1: or if you want to go with his birth name
Speaker 1: is the door Jacub Gudak. I can see why he
Speaker 1: changed it. Yeah he uh. He actually worked for a
Speaker 1: while at Bletchley Park with another fellow who who made
Speaker 1: sort of a name for himself in computer science, a
Speaker 1: fellow named Alan Turing. Oh, I guess I've heard of him. Yeah,
Speaker 1: Touring will come up in the discussion a little bit later,
Speaker 1: but but for right now, so Irving John Good just
Speaker 1: just a little quick anecdote that I thought was amusing.
Speaker 1: So Good was working with touring to try and help
Speaker 1: break German codes. I mean that's what Bletchley Park was
Speaker 1: all about, right, So Good apparently one day drew the
Speaker 1: ire of touring when he decided to take a little
Speaker 1: cat nap. But because he was tired, and he was.
Speaker 1: It was Good's philosophy that being tired did not mean
Speaker 1: that he meant that he was not going to work
Speaker 1: at his best, and he might as well go ahead
Speaker 1: and nap, exactly, take a nap, get refreshed, and then
Speaker 1: tackle the problem again, and you're more likely to solve it.
Speaker 1: Whereas touring was very much a workhorse, you know he
Speaker 1: was he was no rest, no rest type it, so
Speaker 1: touring when he discovered that Good had been napping, decided
Speaker 1: that that this was the Good was not so good
Speaker 1: um and and touring touring sort of treated him with disdain.
Speaker 1: He began to essentially not speak to Good. Good meanwhile,
Speaker 1: began to think about the letters that were being used
Speaker 1: to in Enigma codes to code German messages, and he
Speaker 1: began to think, one, if these letters are not completely random,
Speaker 1: What if the Germans are relying on some letters more
Speaker 1: frequently than others, and he began to look at frequency
Speaker 1: of these letters being used. He made up a table
Speaker 1: and mathematically analyzed the frequency that certain letters were used
Speaker 1: and discovered that there was a bias, there was a pattern. Yeah,
Speaker 1: so he said, well, with this bias, that means that
Speaker 1: we can start to narrow down the possibilities of these codes.
Speaker 1: And in fact, he was able to demonstrate that this
Speaker 1: was a way to help break German codes, and Touring,
Speaker 1: when he saw Goods work, said the sworn I tried that,
Speaker 1: but but clearly that showed that it worked well. And
Speaker 1: then good and another point apparently went to sleep one
Speaker 1: day and they've been working on a code that they
Speaker 1: just could not break. And while he was sleeping, he
Speaker 1: dreamed that perhaps when the Germans were encoding this particular message,
Speaker 1: they used the letters in reverse of the way they
Speaker 1: were actually printed, and so he tried that when he
Speaker 1: woke up, and it turned out he was right. And
Speaker 1: so then his argument was Touring, I need to go
Speaker 1: to bed. So yeah, yeah, what the moral of the
Speaker 1: story here is that knaps are good and no one
Speaker 1: should talk to you, right, yeah, that's how I live
Speaker 1: my life. But yeah, so so Goods point. Anyway, he
Speaker 1: came up with this term of the intelligence explosion, and
Speaker 1: it was this this sort of idea that we're going
Speaker 1: to reach a point where we are increasing either our
Speaker 1: own intelligence or some sort of artificial intelligence so far
Speaker 1: beyond what we are currently capable of understanding, that life
Speaker 1: as we know it will change completely. And because it's
Speaker 1: going to go beyond what we know right now, there's
Speaker 1: no way to predict what our life will be like
Speaker 1: because it's beyond our because it is it is by definition,
Speaker 1: out of our comprehension. Yes, as the Scots would say,
Speaker 1: it's beyond our ken are we going to be doing
Speaker 1: accents this episode? That was a terrible one. I actually
Speaker 1: regret doing it right now. I already knew I couldn't
Speaker 1: do Scottish and yet there I went. Anyway, your trail
Speaker 1: placing again, So to kind of backtry a bit before
Speaker 1: we really get into the whole singularity discussion. That was
Speaker 1: just a brief overview. A good foundation to start from
Speaker 1: is the concept of Moore's law. You know, originally Gordon Moore, who,
Speaker 1: by the way, it was a co founder of a
Speaker 1: little company called intel uh he he originally observed back
Speaker 1: in nineteen sixty five in a paper that I'm going
Speaker 1: to I'm gonna with this, but it was called something
Speaker 1: like cramming more components onto integrated circuits something like that.
Speaker 1: That was that was actually cramming was definitely one of
Speaker 1: the words used um and circuit probably was to Anyway,
Speaker 1: he noticed that over the course of I think originally
Speaker 1: it was twelve months, but today we consider it two years. Uh,
Speaker 1: the eighteen to twenty four months, I think is the
Speaker 1: official unofficial right right, right, Yeah, that that the number
Speaker 1: of discrete components on a a square inch silicon wafer
Speaker 1: would double due to improvements in manufacturing and efficiency, so
Speaker 1: that in effect, what this means to the layman is
Speaker 1: that our electronics and particularly our computers get twice as
Speaker 1: powerful every two years. So if you bought a computer
Speaker 1: in and then bought another computer in two thousand, in theory,
Speaker 1: the computer in two thousand would be twice as powerful
Speaker 1: as the one from This is exponential growth. That's an
Speaker 1: important component this idea of exponential growth. And it goes
Speaker 1: without saying that if you continue on this path, if this,
Speaker 1: if this continues indefinitely, then you know, you quickly get
Speaker 1: to computers of almost unimaginable power just a decade out certainly,
Speaker 1: although I mean I still don't really understand what a
Speaker 1: gigabyte means because when when I first started using computers,
Speaker 1: we were not counting in that. I mean, I mean
Speaker 1: I was still impressed by kilobytes at the time. So yeah, Now,
Speaker 1: I remember the first time I got a hard drive,
Speaker 1: I think it had like two fifty megabyte hard drive,
Speaker 1: and I thought, like, needs that much space? Now, grad
Speaker 1: that's that's space we're talking about, not even processing time. Absolutely,
Speaker 1: so yeah, it's it's it's one of those things where
Speaker 1: the older you are, the more incredible today, is right,
Speaker 1: because you start looking at computers and you think, I
Speaker 1: remember when these things came out, and they were essentially
Speaker 1: the equivalent of a of a really good desktop calculator. Right. So,
Speaker 1: but Moore's law states that this advance will continue indefinitely
Speaker 1: until we hit some sort of fundamental obstacle that we
Speaker 1: just cannot engineer our way around, right, you know, and
Speaker 1: people that that's why it's it's kind of in contention
Speaker 1: right now because people are saying that, well, there's there's
Speaker 1: only so much physical space that you can fit onto
Speaker 1: with with silicone. There's there's there's a physical limitation to
Speaker 1: the material in which there's only so much you can
Speaker 1: do about it, and so does more It's law still
Speaker 1: apply if we're talking about other materials, and what's you know, right?
Speaker 1: And and how small can you get before you start
Speaker 1: to run into quantum effects that are impossible to work around? Uh?
Speaker 1: And then do you change the geometry of a chip?
Speaker 1: Do you go three dimensional instead of two dimensional? Wouldn't
Speaker 1: that help? And you know, there are a lot of
Speaker 1: engineers are working on this, and frankly, pretty much every
Speaker 1: couple of years, someone says, all right, this is the
Speaker 1: year Moore's law, and it's good, it's it's over, it's gone,
Speaker 1: it's done with. Five years later, you're still going strong.
Speaker 1: And then on the sixth year, someone else says, Moore's
Speaker 1: Law is gonna end. It's a little bit of a
Speaker 1: self fulfilling prophecy. I think that a lot of companies
Speaker 1: attempt to keep it going, to keep it going, sure, yeah, yeah, yeah.
Speaker 1: No one wants to be the ones to say, guys,
Speaker 1: guess what, we can't keep up with Moore's law anymore.
Speaker 1: No one wants to do that. So it is a
Speaker 1: good motivator. Also, if I can footing out myself real quick.
Speaker 1: I'm pretty sure that I just pronounced silicon is still
Speaker 1: a cone, and I would like I would like to
Speaker 1: stay for the record that I know that those are
Speaker 1: two different substances. Okay, that's fair. Anyway, I was I
Speaker 1: was going to ask you about it, but by the
Speaker 1: time you you were finished talking, I thought, let's just
Speaker 1: go Yeah, that's cool. It's all right if you knew
Speaker 1: how many times I have used that particular pronunciation to
Speaker 1: to hilarious results. So moving on with this, this whole
Speaker 1: idea about Moore's law, I mean, the reason this plays
Speaker 1: into the singularity is with the technological advances, you start
Speaker 1: to be able to achieve pretty incredible things, and uh,
Speaker 1: even within one generation of Moore's law, which kind of
Speaker 1: a meaningless term. But let's say let's say you arbitrarily
Speaker 1: pick a date and then two years from that date
Speaker 1: you look and see what's possible with the new technology,
Speaker 1: and getting to twice as much power however you wanted
Speaker 1: to find it doesn't necessarily mean that you've only doubled
Speaker 1: the amount of things you can do with that power.
Speaker 1: You may have limitless things you can do. So with
Speaker 1: that idea. You're talking about being able to power through
Speaker 1: problems way faster than you did before. And there's lots
Speaker 1: of different ways of doing that. For example, UM, grid computing.
Speaker 1: Grid computing is when you are linking computers together to
Speaker 1: work on a problem all at once. Now, this works
Speaker 1: really well with problems, parallel problems we call them. Uh.
Speaker 1: These are problems where there are lots of potential solutions
Speaker 1: and each computer essentially is working on one set of
Speaker 1: potential solutions. And that way you have all these different
Speaker 1: computers working on it at the same time. It reduces
Speaker 1: the overall time it takes to solve that parallel problem. Uh.
Speaker 1: And so UM, like if you've ever heard of anything
Speaker 1: like folding at home or the set project, where you
Speaker 1: could dedicate your computer's idle time. So the problem, the
Speaker 1: idle processes, the processes that are not being used while
Speaker 1: you're serving the web or writing how the singularity works,
Speaker 1: or I don't know, uh, building a architectural program in
Speaker 1: in in some sort of CAD application. Anything that you're
Speaker 1: not using can be dedicated to one of these projects.
Speaker 1: Same sort of idea that uh, you don't necessarily have
Speaker 1: to build a supercomputer to solve complex problems if you
Speaker 1: use a whole bunch of computers, whole bunch of small ones,
Speaker 1: large had drunk lighter does this although they use very
Speaker 1: nice advanced computers, but they do a lot of grid
Speaker 1: computing as well. So, uh so, just using those kind
Speaker 1: of models, we see that we're able to do much
Speaker 1: more sophisticated things than we could otherwise if we were certainly. Yes, networks,
Speaker 1: as it turns out, are pretty cool. Yeah, and networks
Speaker 1: play a part in this idea of the singularity. Um. Actually,
Speaker 1: I guess now is a good time. We'll we'll kind
Speaker 1: of transition into Verner Vengees and I honestly, I don't
Speaker 1: know how to say his last name. I say venge
Speaker 1: and it could end up being VINGI. But I just
Speaker 1: went with what you said. So that's great, that's fine.
Speaker 1: What we'll say that Vench says everything is silicone. Uh
Speaker 1: So Verner though he Verne, I call him vern He
Speaker 1: He suggested four different potential pathways that humans could take,
Speaker 1: or really that the world could take to arrive at
Speaker 1: the technological singularity. Okay, what are they? The four ways
Speaker 1: are we could develop a superhuman artificial intelligence. So computers
Speaker 1: suddenly are able to think on a level that's analogous
Speaker 1: to the way humans think and can do it better
Speaker 1: than the right. Whether or not that means computers are conscious,
Speaker 1: that's debatable. We'll get into that too. Computer networks could
Speaker 1: somehow become self aware. That's number two. So yes, sky
Speaker 1: net So like the grid computing we were just talking
Speaker 1: about that, somehow using these grid computers, the network itself
Speaker 1: having enough cycles and enough pathways and enough loops back around,
Speaker 1: it starts going like, hey, I recognize this starts thinking
Speaker 1: about like like like like thinking about IBM S Watson.
Speaker 1: But it's distributed across a network. So computers you can
Speaker 1: think of computers is all being super powerful neurons in
Speaker 1: a brain, and that the network is actually neural pathways.
Speaker 1: And it's definitely a science fiction e way of looking
Speaker 1: at things. Doesn't mean it won't open, but stranger things,
Speaker 1: my friends. It feels like a matrix kind of thing
Speaker 1: to me. Then we have the idea that computer human
Speaker 1: interfaces are so advanced and so intrinsically tied to who
Speaker 1: we are, that humans themselves evolved beyond being human, we
Speaker 1: become trans human. So this is an idea that we
Speaker 1: almost merge with computers at least on some level via
Speaker 1: kind of nanobot technology. You know, stuff stuff running through
Speaker 1: our bloodstream, stuff in our yep. Or we have just
Speaker 1: brain interfaces where our scientiousness, our consciousness is connected to
Speaker 1: So so for example, we might have it where instead
Speaker 1: of connecting to the Internet via some device like a
Speaker 1: smartphone or a computer, yeah, it's right there in our
Speaker 1: our meat brains, so that you know, you're sitting there
Speaker 1: having a conversation with someone. Then you're like, oh, wait,
Speaker 1: what movie was that guy in? Let me just look
Speaker 1: up I am dB in my brain and then you
Speaker 1: you know, depending on how good your connection is, which means,
Speaker 1: by the way, if you are a journalist and you
Speaker 1: attend C E S, you will automatically be dumber because
Speaker 1: all the all the internet connectivity will be taken up
Speaker 1: and so you'll be sitting there trying to ask good
Speaker 1: questions and drool will come out of your mouth, which
Speaker 1: to me is a typical C E S. I can
Speaker 1: I can only assume that that wireless technology would advance
Speaker 1: also at this point, but one can only hope fingers cross.
Speaker 1: There are certain technologies that are not advancing at the
Speaker 1: exponential rate of Moore's law, which is another problem we'll
Speaker 1: talk about that. Uh. And then the fourth and final
Speaker 1: method that Werner had suggested the world may go would
Speaker 1: be that humans would advance so far in biological sciences
Speaker 1: that that would allow us to engineer human intelligence so
Speaker 1: that we could make ourselves as smart as we wanted
Speaker 1: to be. This is sort of that Gattica future where
Speaker 1: we've got all the another another great documentary, where we
Speaker 1: we engineer ourselves to be super smart. So those are
Speaker 1: the four pathways artificial intelligence, computer networks to become self aware,
Speaker 1: computer human interface has become really really awesome, or we
Speaker 1: have biologically engineered human intelligence and uh. And all four
Speaker 1: of these lead to a similar outcome, which is this
Speaker 1: intelligence explosion. And this is the idea that some form
Speaker 1: of superhuman intelligence is created, either artificially or within ourselves,
Speaker 1: and that at that point we will no longer be
Speaker 1: able to predict what our world will will be like,
Speaker 1: because by definition, we will have a superhuman intelligent entity involved.
Speaker 1: And because that's superhuman, it's beyond our ability to predict
Speaker 1: which is you know which, which makes thought experience experiments
Speaker 1: about it a little bit uh, philosophical. That's the kind
Speaker 1: way of putting it, uh, pointless would be another way
Speaker 1: of putting up like we could we could, you know,
Speaker 1: sit there and and and spitball a whole bunch of
Speaker 1: possible futures. But that's the thing, they're possible. We don't
Speaker 1: know which one could come out. We don't even know
Speaker 1: if these four pathways are inevitable. We have futurists who
Speaker 1: truly believe that this is something that will happen at
Speaker 1: some point. There are other people who are more skeptical,
Speaker 1: but we'll talk about them in a bit. So one
Speaker 1: of the outcomes that Werner was talking about, uh, and
Speaker 1: it's it's a fairly popular one in futurist circles is
Speaker 1: the idea of the robo apocalypse. Essentially, this is where
Speaker 1: you've got the humans are bad, destroy all humans idea. Essentially,
Speaker 1: the the ideas that humans would become extinct, either through
Speaker 1: definition because we've evolved into something else or because whatever
Speaker 1: the super human intelligence is it besides we are a problem. Yeah,
Speaker 1: and a lot a lot of futures are a lot
Speaker 1: more positive about that. They're they're more looking forward to
Speaker 1: it than being scared of it. It's less of oh, no,
Speaker 1: big scary robots are coming to take over society and
Speaker 1: more of a the robots are coming to take oversus
Speaker 1: society like free Day. Yeah exactly. Yeah, I don't have
Speaker 1: to work anymore, and and I don't because robots are
Speaker 1: are supplying all the things we need. There's no need
Speaker 1: for anyone to work anymore. There's no need for money anymore,
Speaker 1: because the only reason you need money is so you
Speaker 1: can buy stuff. But if everything is free, then you
Speaker 1: don't need you. So it becomes Star Trek and we
Speaker 1: all know run around in jumpsuits and punch people. And
Speaker 1: if you're Kirk, you make out a lot. I mean
Speaker 1: a lot. That dude every week Becauson Ryker. If you
Speaker 1: add them together, make one Kirk. And yes, in this
Speaker 1: documentary series Star Trek, I don't know about Archer because
Speaker 1: I never watched Enterprise, So you guys have to get
Speaker 1: back to me on that. Yeah, sorry, sorry about that. That That.
Speaker 1: It's also a gap in my personal understanding. Just took
Speaker 1: one look at that decontamination chamber and said, yep, I'm
Speaker 1: out um anyway. So that's that's Werner Avenge. It's he's
Speaker 1: sort of popularized this idea, but he's there are other
Speaker 1: people who have I think their names are synonymous with it.
Speaker 1: Hey guys, it's robo Jonathan from here to interrupt, because
Speaker 1: even in the future, we need to take a break
Speaker 1: to thank our sponsors and now back to the show.
Speaker 1: So Werner Venge again very much associated with the idea
Speaker 1: of the singularity. But there's another name that comes up
Speaker 1: all the time, Ray Kurtswile, Rate Kurtswile. And this is
Speaker 1: a fellow who has been referred to in various circles
Speaker 1: as as the Thomas Edison of modern technology or um
Speaker 1: or or perhaps more colorfully, the Willy Wonka of technology.
Speaker 1: That was by Jeff Duncan of Digital Trends, and I
Speaker 1: just wanted to shout out because that was great, but
Speaker 1: you get nothing. I shared a remix of Willy Wonka
Speaker 1: earlier today and it's still playing through my head. We're fans,
Speaker 1: we might be fans of the Gene Wilder Willy Wonka.
Speaker 1: Every when everyone homework assignment, go watch that. It has
Speaker 1: nothing to do with the singularity singularity at all. I
Speaker 1: don't know there's some chocolate singularity in their chocolate singularity.
Speaker 1: I want episode on that band. If I were better
Speaker 1: at cover band names. I totally would have said something
Speaker 1: witty right there. Yeah, all right, well, fair enough, we'll
Speaker 1: say it's the Archies, Sugar Sugar, oh dear, Oh my goodness. Okay,
Speaker 1: So Ray kurtswhile Ray Kurts, while Um is the kind
Speaker 1: of cat who you know, when he was in high school,
Speaker 1: Um invented a computer program. And this isn't in the
Speaker 1: mid nineteen sixties, This isn't like last year or something.
Speaker 1: In the mid nineteen sixties, created a computer program that
Speaker 1: listened to classical music, found patterns in it, and then
Speaker 1: created new classical music based on that. So its a
Speaker 1: computer that composed classical music following the rules of classical
Speaker 1: music that other composers had created. Yes, that's kind of cool.
Speaker 1: That's just that's just something he did, you know. And yeah,
Speaker 1: that's dudes got credentials. Yeah, it's He also kind of
Speaker 1: invented flatbed scanners, has done a whole bunch of stuff
Speaker 1: in speech recognition, and uh, which that's interesting because well,
Speaker 1: and we'll talk about that in a second. But but
Speaker 1: one of Kurt's well's big points is that he thinks
Speaker 1: that by and this all depends upon which interview you
Speaker 1: read of Kurt Kurts well, but in various interviews he
Speaker 1: said that essentially by twenty thirty we will reach a
Speaker 1: point where we will be able to make an artificial brain. Well,
Speaker 1: we'll we'll have reverse engineered the brain, and we'll be
Speaker 1: able to create an artificial one. Uh. And there's a
Speaker 1: lot of debate in in UH, in smarter circles than
Speaker 1: the ones I move in. UH. That's not a that's
Speaker 1: not a slap against my friends. They're pretty bright, but
Speaker 1: none of us are neuro churologically gifted at that point. UM.
Speaker 1: I include myself in that in that circle. So, but
Speaker 1: there there's some very bright people who debate about this
Speaker 1: point whether or not we'll be able by the year
Speaker 1: twenty thirty two reverse engineer the brain and design an
Speaker 1: artificial one. And I think the debate is not so
Speaker 1: much on whether or not will have the technological power
Speaker 1: necessary to to uh simulate a brain. We can simulate
Speaker 1: brains on a certain superficial level today. I mean hypothetically
Speaker 1: we could connect enough computers that we could make it go.
Speaker 1: I think, yeah, we could probably get the computer horsepower,
Speaker 1: especially by thirty to simulate a human brain. The question
Speaker 1: is whether we will understand the human brain exactly. So
Speaker 1: that's that's sort of where the debate lies. It's not
Speaker 1: so much on the technological side of things as it
Speaker 1: is the biological side of things, which is kind of interesting. Um.
Speaker 1: I've read a lot of critics who who have really
Speaker 1: jumped on Kurtzwild for this. Particularly PS Myers has written
Speaker 1: some pretty um yeah, strongly worded, strongly worded criticisms to
Speaker 1: Kurtzwild's theories, saying that that Kurtswild simply does not understand
Speaker 1: neurological development and activities, and that you know, the nature
Speaker 1: between the environment and are are the way our brains
Speaker 1: develop over time versus the you know, nurture versus nature,
Speaker 1: all of this stuff with hormonal changes, electrochemical reaction, saying
Speaker 1: that there's there's so many little bits that make up
Speaker 1: our brains, so many hormones, so many processes, and we
Speaker 1: understand such a small fraction of what they do. This
Speaker 1: is why a lot of psychiatric drugs, for example, are
Speaker 1: kind of like, oh, well, we invented this thing, and
Speaker 1: we guess it does this thing, right, take it and
Speaker 1: see what happened we did stuff we don't. It tends
Speaker 1: to make you happy. It also makes you perceive the
Speaker 1: color red as having the smell of oranges. Like you
Speaker 1: know that that we don't we don't understand it fully.
Speaker 1: And in fact, there are other people like Stephen Novella,
Speaker 1: who is uh he's the author of the Neurological Blog,
Speaker 1: and he also is a host on a wonderful podcast
Speaker 1: called Skeptics Guide to the Universe. If you guys haven't
Speaker 1: listened to that, you should try that out if you,
Speaker 1: especially if you like skepticism and critical thinking. But he's
Speaker 1: he's a doctor and a proponent of evidence based medicine,
Speaker 1: and he talks about how, uh, you know, we don't
Speaker 1: know how much we don't know about the brain, like
Speaker 1: we we have no way of knowing where the endpoint
Speaker 1: is as far as the brain is concerned, and therefore
Speaker 1: we cannot guess at how long it will take us
Speaker 1: to reverse engineers, simply because we don't know where the
Speaker 1: finish line is, right right, Yeah. Kurt kurts Wells Kurtzwell
Speaker 1: has a new book new as of we're recording this
Speaker 1: in January, just came out in November called How to
Speaker 1: Create a Mind. The Secret of Human Thought Revealed and
Speaker 1: and in the book, he theorizes that, um, okay, if
Speaker 1: you'll follow me for a second, atoms are tiny bits
Speaker 1: of data DNA. It's a form of a program. The
Speaker 1: nervous system is a computer that coordinates bodily functions and
Speaker 1: thought is kind of simultaneously a program and the data
Speaker 1: that that program contains. Gotcha. Now, this is another problem
Speaker 1: that some scientists have, is reducing the human brain to
Speaker 1: the model of a computer, right, because it's you know,
Speaker 1: it's it's a very it's a very elegant, interesting proposition
Speaker 1: and and it's kind of sexy like that because you
Speaker 1: go like, oh, well that's that that sort of makes sense.
Speaker 1: Man Like, let's go get a pizza and talk about
Speaker 1: this more. Let me let me get a program that
Speaker 1: will allow me to suddenly know all kung fu. Right,
Speaker 1: And when you're a programmer, that's a great plan. Yeah,
Speaker 1: I mean that sounds that sounds terrific. But yeah, there's
Speaker 1: one one specific guy found. Jarren Lanier wrote a terrific
Speaker 1: thing called one Half of a Manifesto, which is a
Speaker 1: really entertaining read if you guys like this kind of thing,
Speaker 1: where and he was saying that what futurists are talking
Speaker 1: about when they talk about this singularity is basically a religion.
Speaker 1: He was calling it cybernetic totalism. Uh, you know, like
Speaker 1: like about fanatic ideology. He compares it to Marxism at
Speaker 1: some point. But yeah, um, and he was saying that that,
Speaker 1: you know, it's this, This theory is a trific theory
Speaker 1: if you want to get into the philosophy of who
Speaker 1: we are and what we do and what technology is.
Speaker 1: But that you know, cybernetic patterns aren't necessarily the best
Speaker 1: way to understand reality, and that they're not necessarily the
Speaker 1: best model for how people work, for how culture works,
Speaker 1: for how intelligence works. And that's saying so is an
Speaker 1: gross over simplification. That's a good point. And we should
Speaker 1: also point out that it all depends on how you
Speaker 1: define intelligence as well, because Kurtzwell himself has worded his
Speaker 1: own predictions in such a way that that some would
Speaker 1: argue Novella argues, for example, that he has given himself
Speaker 1: enough room where he's going to be right no matter what,
Speaker 1: like saying that we will be able to reverse engineer
Speaker 1: basic brain functions, and novellas is, well, technically you could
Speaker 1: argue that now, so that kind of gives you a
Speaker 1: lot of room. Yeah. But but whether or not it
Speaker 1: means total brain function, that's that's a totally different question.
Speaker 1: And so the other point is that we could theoretically
Speaker 1: create an artificial intelligence that does not necessarily reverse engineer
Speaker 1: the brain. It doesn't follow the human intelligence model. I mean,
Speaker 1: that's IBM S Watson again, a good example of artificial
Speaker 1: intelligence that you know, in some ways it mimics the
Speaker 1: brain because it kind of has to. You know, we're
Speaker 1: coming at this. Human beings are the ones creating this technology,
Speaker 1: and so as human beings creating this technology, it's going
Speaker 1: to follow the rules that as we understand them. So
Speaker 1: there's going to be some indigree there. But but IBM
Speaker 1: S Watson, you know, you think about that, it doesn't
Speaker 1: really understand necessarily the data that's passing through it. It's
Speaker 1: looking for the connections and making just making making connections
Speaker 1: and recognizing pattern and spitting out useful information. Yeah, it's
Speaker 1: it's looking for whatever answer is most likely the right one.
Speaker 1: It's all probability based, right, so, and if it doesn't
Speaker 1: reach a certain threshold, it doesn't provide the answer. So
Speaker 1: if arbitrarily speaking, I don't know what the threshold is
Speaker 1: so I'm just making a number. Let's say it has
Speaker 1: to be certain or higher for it to give that answer.
Speaker 1: If that if the if the certainty falls below that threshold,
Speaker 1: no answer is given. That's essentially how it worked when
Speaker 1: Watson was on Jeopardy. It would it would analyze the
Speaker 1: the the the answer in Jeopardy terms, and then come
Speaker 1: up with what it thought was probably the most accurate
Speaker 1: question for that answer, and occasionally it was wrong to
Speaker 1: hilarious results. But it did sort of seem to kind
Speaker 1: of mimic the way humans think, at least on a
Speaker 1: superficial level. And oh, I mean the thing about humans
Speaker 1: is that they're they're wrong a lot more than a
Speaker 1: lot more than what that fifteen percent at the time. Yeah,
Speaker 1: it's you know, it's we've we've got well, we give
Speaker 1: answers even if we're not short the question. I certainly do,
Speaker 1: because we all know from going to trivia nights. Yeah,
Speaker 1: and and there's there's a lot of I've read a
Speaker 1: lot on online about arguments of how it's our deficiencies
Speaker 1: are memory biases, are rational behavior? Are weird hormonal stuff
Speaker 1: going on? Or what makes us human? And that you
Speaker 1: can't teach a computer to be irrational, that's true. Although
Speaker 1: you can't teach you to swear. You can. We just
Speaker 1: we read a story last week, Yeah, where IBM allowed
Speaker 1: Watson to read the Urban Dictionary, and then Watson got
Speaker 1: a little bit of a potty mouth. It got it
Speaker 1: got kind of fresh. It did it did it started
Speaker 1: it started to say that. Oh see what was it?
Speaker 1: Oh I'm going to say something and it's going to
Speaker 1: be bleaped out, right, Tyler Tyler, Tyler just said so. Uh. Anyway,
Speaker 1: so there's one point where a researcher asked a question
Speaker 1: of Watson, and Watson included within the answer the word
Speaker 1: so since I was bleeped out, you probably don't know
Speaker 1: what it was, so go look it up. It was funny.
Speaker 1: It was really funny. Yes. And then and then they
Speaker 1: basically nuked that part of Watson from orbit. They were like,
Speaker 1: you know what, never mind, it was the only way
Speaker 1: to be sure. They wiped out the Urban Dictionary from
Speaker 1: Watson's memory. They also said that a very similar thing
Speaker 1: happened when they let Watson read Wikipedia. No judgments here,
Speaker 1: just saying what what IBM said. Anyway, Again, the computer
Speaker 1: was unable to determine when when there was appropriate and
Speaker 1: what's the appropriate context for dropping a swear word. It
Speaker 1: didn't know, so it just started to speak kind of
Speaker 1: like my wife does. So yeah, it was I'm going
Speaker 1: to pay for that later. Uh So, anyway, that that
Speaker 1: that's an interesting point though again you're you're showing how
Speaker 1: machine intelligence and human intelligence are different because the machine
Speaker 1: intelligence doesn't have that content. Sure, and of course you
Speaker 1: know we're talking about about science fiction or science future,
Speaker 1: however you want to term it, so that you know,
Speaker 1: we might very well come up with a fancy little
Speaker 1: program script that lets you that lets you introduce that
Speaker 1: kind of bias. But you know, but again from that
Speaker 1: documentary Star Trek, I mean data never figured out these contractions.
Speaker 1: Hi guys, it's Jonathan. I have merged entirely with technology
Speaker 1: at this point, but I still got to pay the bills.
Speaker 1: So let's take a quick break. Touring actually had a great,
Speaker 1: uh mental exercise really, and it's called the touring test,
Speaker 1: and this this applies to artificial intelligence. Tourings point, and
Speaker 1: we've talked about the train test in previous episodes of
Speaker 1: Tech Stuff, But just as a refresher, Touring had suggested
Speaker 1: that you could create a test and that if a
Speaker 1: machine could pass that test at the same level as
Speaker 1: a human. In other words, if you were unable to
Speaker 1: determine that the person who took that test was human
Speaker 1: or machine, the machine had passed the touring test and
Speaker 1: had had essentially simulated human intelligence. And uh. It usually
Speaker 1: works as an interview, So you have someone who's who's
Speaker 1: conducting an interview, and you have either a machine answering
Speaker 1: or a human answering, and there's a barrier up so
Speaker 1: that of course the person asking the questions cannot see
Speaker 1: who is responding, and of course they're responding through you know,
Speaker 1: text usually because if they're responding through a voice, it's like,
Speaker 1: I think the answer as far you know, you'd be like, well,
Speaker 1: either it's a robot or the most boring person in
Speaker 1: the world. Uh. The idea being you would ask these
Speaker 1: questions over a computer monitor, get text responses, and if
Speaker 1: you were unable to to answer with a certain degree
Speaker 1: of accuracy whether or not it was a machine or
Speaker 1: a person, then you would say the machine passed the
Speaker 1: test and uh. And and you could argue, well, that
Speaker 1: could just mean that the machine is very good at
Speaker 1: mimicking human intelligence, it does not actually possess human intelligence.
Speaker 1: Turing's point is, does that matter? Because I know that
Speaker 1: I am intelligent, I speak with someone like Lauren, who
Speaker 1: I assume is also intelligent based upon the responses she gives.
Speaker 1: But she could just be simulating intelligence. However, I have
Speaker 1: I have already bestowed in my mind the the feature
Speaker 1: of intelligence upon Lauren, because what she does is very
Speaker 1: much akin to what I do. So Touring said, if
Speaker 1: you extend the courtesy to your fellow human being that
Speaker 1: they are intelligent based on the fact that they act
Speaker 1: like you do, why would you not do the same
Speaker 1: thing for a machine. Does it matter if the machine
Speaker 1: can actually think. If the machine simulates thought well enough
Speaker 1: for it to pass as human, then you're giving it
Speaker 1: the same benefit of doubt if you word anyone else.
Speaker 1: This is what a lot of science fiction movies are about. Actually,
Speaker 1: there's a lot of philosophy, and a lot of philosophy,
Speaker 1: lot of Isaac Asthma, of a lot of Blade Runner
Speaker 1: and and and that's not an author. Sorry, well no,
Speaker 1: but you know Philip K. Dick. Look him up. So anyway,
Speaker 1: thank you to Android's dream of electric Sheep. I won't.
Speaker 1: I won't spoil it for you. Uh. They to kind
Speaker 1: of wrap this all up, getting back into the discussion
Speaker 1: of philosophy. Uh, we had very recently we did a
Speaker 1: podcast about are we living in a computer simulation? And
Speaker 1: that kind of plays into this idea of the singularity
Speaker 1: because that argument stated that if the singularity is in
Speaker 1: fact possible, if it's inevitable, if we are going to
Speaker 1: reach this level of transhumanism where we are no longer
Speaker 1: able to really predict what the present will be like
Speaker 1: because it will be beyond our understanding, then one thing
Speaker 1: we would expect to do is create simulations of our
Speaker 1: past to kind of study ourselves and to see what
Speaker 1: happens play around variables. Yeah. We like good experiments. Yeah,
Speaker 1: and we could. We could, if we're that advanced, could
Speaker 1: in theory, creates such a realistic simulation that the inhabitants
Speaker 1: of that simulation would be incapable of knowing that they
Speaker 1: were artificial and would be completely you know, self aware
Speaker 1: of themselves. You know that was totally redundant, self aware
Speaker 1: and uh, but unable to know that they were a simulation. Uh.
Speaker 1: He said that if those things are possible, then there's
Speaker 1: no way of knowing that, you know, the the overwhelming
Speaker 1: uh possibility is that we are in a computer simulations,
Speaker 1: computer simulation right now, because yeah, if that's if that's
Speaker 1: what's gonna happen, then there's no way of saying with
Speaker 1: certainty that we are not in fact the product of that.
Speaker 1: And so uh, the point being not necessarily that we
Speaker 1: are in fact living in a computer simulation, but that
Speaker 1: perhaps this singularity, this transhumanism thing might not be realistic.
Speaker 1: It might not be the future that we're headed to.
Speaker 1: Maybe it ends up being a pipe dream that's not
Speaker 1: really possible for us to attain. Or maybe we'll wipe
Speaker 1: ourselves out through some terrible war or catastrophic accident. Um,
Speaker 1: maybe we create a biological entity that wipes us out.
Speaker 1: Allah the stand Why create a black hole at the LHC,
Speaker 1: Which come on, people don't write me. I already know
Speaker 1: about that and how tiny and and and almost non
Speaker 1: existent they are because it lasted so quickly. Let's say
Speaker 1: that they do that thing where you look at that
Speaker 1: one website where the black hole forms in the parking
Speaker 1: lot outside the LHC and you just see the whole picture.
Speaker 1: Go um, which funny video anyway, that's that argument plays
Speaker 1: back into this. So I don't know, I don't know
Speaker 1: if we're going to ever see a future where the
Speaker 1: singularity becomes the thing. Oh and we never really talked
Speaker 1: about it. But one of the big points that kurts
Speaker 1: Well really punches in his Singularity talks is the idea
Speaker 1: of digital immortality, right right, And he's been obsessed with
Speaker 1: this I and and obsessed is probably a judgmental word.
Speaker 1: I apologize, that's but he's been very focused on this concept.
Speaker 1: His father died when he was about twenty four, and
Speaker 1: he's been exploring theories on life extension ever since then,
Speaker 1: and supposedly takes all kinds of supplements and sells them
Speaker 1: as well to extend life, has all kinds of kinds
Speaker 1: of health plans, dietary plans that he has exercise all
Speaker 1: the idea that the idea being that if he can
Speaker 1: preserve his own line last long enough that we hit
Speaker 1: the singularity, then he can become immortal. Right and either that,
Speaker 1: you know, we attain immortality through one of a thousand
Speaker 1: different ways. For example, we end up uploading our own
Speaker 1: intelligence into the cloud, and then we've become part of
Speaker 1: a group consciousness, so we are no longer really individuals,
Speaker 1: or we merge with computers in some other way so
Speaker 1: that we are technically immortal that way. Or we just
Speaker 1: conquer the genes that all guide eight the aging process,
Speaker 1: and we stop it, and we stop disease, you know,
Speaker 1: we we take like in transmant you just take a
Speaker 1: cancer pill and then you don't get cancer, because that's
Speaker 1: what you do. Yeah, so I think again the singularity.
Speaker 1: That's kind of why I think a lot of critics
Speaker 1: also point to it as being more of a religion,
Speaker 1: because it's kind of this sort of utopian pipe dream
Speaker 1: in their minds. There's the former CEO of Lotus, Mitch
Speaker 1: Kapoor Capper, I'm not sure how you say it, once
Speaker 1: called called it the intelligent design for the i Q
Speaker 1: one forty people. Yeah ouch ouch, Well, I mean, well,
Speaker 1: kurtz Wild's kind of laughing all the way to the bank.
Speaker 1: I hear that company that rhymes with schmoogle hired him
Speaker 1: little little people, I mean, we're you probably wouldn't have
Speaker 1: heard of him, but yeah, they just tired him on
Speaker 1: to be I have it in my notes at the
Speaker 1: official title. I think it's the director of Engineering a
Speaker 1: director of engineering over there. Um, they get they get
Speaker 1: some big names. I mean, they had Vince Surf as
Speaker 1: the chief evangelists, and of course he was one of
Speaker 1: the fathers of the Internet. So Google's Google's gotta they're
Speaker 1: own for for getting some really smart people. And and
Speaker 1: to be fair, while the singularity may or may not
Speaker 1: ever happen, I think it's important that we have optimists
Speaker 1: in the field of technology who are really pushing for
Speaker 1: our development to try and make the world a better
Speaker 1: place for people. Now, you know, absolutely so, even if
Speaker 1: we're even if we never reach the point of digital
Speaker 1: immortality in our lifetimes or any other it's I mean,
Speaker 1: if if someone wants to think so big that that
Speaker 1: they want to put in nanobots to make my body awesomer,
Speaker 1: I mean and and not that connected that came out
Speaker 1: that came out possibly crude. I mostly means that I
Speaker 1: don't get cancer and die, um kind of stuff. That's
Speaker 1: that's terrific. I can I can't argue with any part
Speaker 1: of that. Yeah, I'm gonna be on video so much
Speaker 1: this year that I definitely need my body to be awesomer,
Speaker 1: So I'm all for that. Well either way, yes, and
Speaker 1: and and Google. You know, Google looks forward so much
Speaker 1: too to augmented reality. Augmented reality. I'm sorry, I'm I
Speaker 1: can't pronounce anything today. I am on a non role
Speaker 1: in the Internet of Things and all of that wonderful
Speaker 1: future tech that it seems like a terrific fit. Yeah. Yeah,
Speaker 1: so we'll see how how it goes. I mean, obviously,
Speaker 1: the nice thing about this is that all we have
Speaker 1: to do is live long enough to see it happen
Speaker 1: or not happen. And most predictions have the Singularity hitting
Speaker 1: somewhere between twenty Yeah, it all depends on upon which
Speaker 1: futurist you're asking. I hope you guys enjoyed that classic
Speaker 1: episode about the singularity. I have touched on that topic
Speaker 1: multiple times, both on tech Stuff and on other shows
Speaker 1: like Forward Thinking. So if you're really interested in it
Speaker 1: and you want to hear even more, feel free to
Speaker 1: do searches both on Forward Thinking and on tech Stuff.
Speaker 1: You can search on tech Stuff going to the website
Speaker 1: tech stuff podcast dot com. We have an archive there
Speaker 1: of every episode that's ever published Forward Thinking. You might
Speaker 1: have to do a little more googling, but it is there,
Speaker 1: including podcasts and videos, so go check that out. If
Speaker 1: you would like to get in touch with me and
Speaker 1: suggest future topics for tech Stuff, you can do so
Speaker 1: with the email address text Stuff at how stuff works
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