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