Speaker 1: Welcome to tech Stuff, a production from iHeartRadio. Say hey there,
Speaker 1: and welcome to tech Stuff. I'm your host, jonvan Strickland.
Speaker 1: I'm an executive producer with iHeart Podcasts and how the
Speaker 1: tech are you. So it's January second, twenty twenty four.
Speaker 1: As you listen to this, it's actually back in the
Speaker 1: past in twenty twenty three when I record it and
Speaker 1: we are on vacation. You know, I brought you a
Speaker 1: whole bunch of new episodes over the holidays, but I
Speaker 1: feared it's about time for Jonathan to maybe rest a
Speaker 1: little bit, So we're going to listen to a classic
Speaker 1: episode today. This episode is called tech Stuff Enters the Singularity.
Speaker 1: I mean, after all, we're in a new year, so
Speaker 1: why not talk about the future a little bit. This
Speaker 1: was recorded way back in February eleventh, twenty thirteen. Lauren
Speaker 1: Vogelbaumb now host of brain Stuff and Savor along with
Speaker 1: other Things, was my co host at the time, and
Speaker 1: we sat down to talk about this vision of the future,
Speaker 1: the singularity. What does it mean that when we're talking
Speaker 1: about the technological singularity? That is So sit back, relax
Speaker 1: and enjoy this classic episode from twenty thirteen called tech
Speaker 1: Stuff Enters the Singularity. Get in touch with technologies with
Speaker 1: tex Stuff from HowStuffWorks dot com. Hey there, everyone, and
Speaker 1: welcome to tech Stuff. My name is Jonathan Strickland, Host Extraordinaire.
Speaker 2: And I'm Lauren vocal Bam, host Extraordinarier.
Speaker 1: That's very true, and today we wanted to talk about
Speaker 1: the future. The future. Yeah, really, we're talking about kind
Speaker 1: of a science fiction future. We're talking about the singularity.
Speaker 1: And long time listeners to tech Stuff and I'm talking
Speaker 1: about folks who listened way back before we ever talked
Speaker 1: out at thirty minutes, let alone an hour. May remember
Speaker 1: that we did an episode about how Ray Kurtzwel works
Speaker 1: and Ray Kurtzwell is a futurist and one of the
Speaker 1: things he talks about extensively, particularly if you corner him
Speaker 1: at a cocktail party, is the singularity. And so we
Speaker 1: wanted to talk about what the singularity is, what this idea,
Speaker 1: you know, we really wanted to kind of dig down
Speaker 1: into it and why is this a big deal and
Speaker 1: how realistic is this vision of the future.
Speaker 2: Yeah, because some people would take a little bit of
Speaker 2: a would would argue with your concept of it being
Speaker 2: science fiction. They take it extremely seriously.
Speaker 1: Oh yeah, they say it's science fact, science fact, it's
Speaker 1: science inevitability.
Speaker 2: Yeah. The term was actually coined by a mathematician, Jean
Speaker 2: von Newman in the nineteen fifties, but it was popularized
Speaker 2: by a science fiction writere.
Speaker 1: Yeah, it's also a There are a lot of different
Speaker 1: concepts that are tied up together, and it all depends
Speaker 1: on 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 changes by the milliseconds. Right. So that's one version,
Speaker 1: But most of the versions that we're familiar with that
Speaker 1: the futurists talk about incorporate an idea of superhuman intelligence
Speaker 1: or the intelligence explosion, right.
Speaker 2: A kind of combination of human and technological development that
Speaker 2: just dovetails into this gorgeous you know, space baby from
Speaker 2: two thousand and one kind of that's.
Speaker 1: An excellent way of putting it. The documentary two thousand
Speaker 1: and one. I remember specifically when the space baby looked
Speaker 1: at Earth. Okay, that documentary example doesn't work at all.
Speaker 1: It usually does, but not this Yeah, not this time.
Speaker 2: Sorry, space babies are a poor example in this one instance.
Speaker 1: But metaphorically speaking, yes, you're right on track because the
Speaker 1: intelligence explosion. That was a term introduced by someone known
Speaker 1: as Irving John Good or if you want to go with,
Speaker 1: his birth name is Adore Jakub Gudak. I can see
Speaker 1: why he changed it. Yeah. He actually worked for a
Speaker 1: while at bletch Lee Park with another fellow who made
Speaker 1: sort of a name for himself in computer science, a
Speaker 1: fellow named Alan Turing. Oh oh, I guess I've heard
Speaker 1: of him. Yeah. Touring will come up in the discussion
Speaker 1: a little bit later, but for right now, So, Irving
Speaker 1: John Good just just a little quick anecdote that I
Speaker 1: thought was amusing. So Good was working with touring to
Speaker 1: try and help break German codes. I mean that's what
Speaker 1: Bletchley Park was all about, right right, So Good apparently
Speaker 1: one day drew the ire of touring when he decided
Speaker 1: to take a little cat nap because he was tired
Speaker 1: and he was it was Goods philosophy that being tired
Speaker 1: did not mean that he meant that he was not
Speaker 1: going to work at his best, and he might as
Speaker 1: well go ahead and nap, exactly, take a nap, get refreshed,
Speaker 1: and then tackle the problem again, and you're more likely
Speaker 1: to solve it. Whereas touring was very much a workhorse,
Speaker 1: you know he was he was no rest, no rest,
Speaker 1: We have to.
Speaker 2: Do so touring.
Speaker 1: When he discovered that Good had been napping, decided that
Speaker 1: this was the Good was not so good and and
Speaker 1: touring touring sort of treated him with disdain. He began
Speaker 1: to essentially not speak to Good. Good meanwhile, began to
Speaker 1: think about the letters that were being used in Enigma
Speaker 1: codes to code German messages, and he began to think,
Speaker 1: what if these letters are not completely random? What if
Speaker 1: the Germans are relying on some letters more frequently than others.
Speaker 1: And he began to look at frequency of these letters
Speaker 1: being used. He made up a table and mathematically analyzed
Speaker 1: the frequency that certain letters were used and discovered that
Speaker 1: there was a bias. There was a pattern. Yeah, so
Speaker 1: he said, well, with this bias, that means that we
Speaker 1: 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, I could have sworn
Speaker 1: I tried that, but clearly that showed that it worked well.
Speaker 1: And then good and another point apparently went to sleep
Speaker 1: one day and they've been working on a code that
Speaker 1: they just could not break, and while he was sleeping,
Speaker 1: he dreamed that perhaps when the Germans were encoding this
Speaker 1: particular message, they used the letters in reverse of the
Speaker 1: way they were actually printed, and so he tried that
Speaker 1: when he woke up, and it turned out he was right.
Speaker 1: And so then his argument was Touring, I need to
Speaker 1: go to bed.
Speaker 2: So yeah, yeah, what the moral of the story here
Speaker 2: is that naps are good?
Speaker 1: Yes, and no one should talk to you, right, yeah, yeah,
Speaker 1: that's how I live my life. But yeah, so so
Speaker 1: Goods point. Anyway, he came up with this term of
Speaker 1: the intelligence explosion, and it was this this sort of
Speaker 1: idea that we're going to reach a point where we
Speaker 1: are increasing either our own intelligence or some sort of
Speaker 1: artificial intelligence so far beyond what we are currently capable
Speaker 1: of understanding, that life as we know it will change. Completely,
Speaker 1: and because it's going to go beyond what we know
Speaker 1: right now, there's no way to predict what our life
Speaker 1: will be like, right because it's beyond our because it
Speaker 1: is it.
Speaker 2: Is Yeah, by definition out of our comprehension.
Speaker 1: Yes, as the Scots would say, it's beyond our ken.
Speaker 2: Are we going to be doing accents of this episode?
Speaker 1: So that was a terrible one. I actually regret doing
Speaker 1: it right now. I already knew I couldn't do Scottish
Speaker 1: and yet there I went. Anyway, you're trail placing again. Yeah,
Speaker 1: So to to kind of backtrack a bit before we
Speaker 1: really get into the whole singularity discussion, that was just
Speaker 1: a brief overview. A good foundation to start from is
Speaker 1: the concept of Moore's law. You know, Originally Gordon Moore,
Speaker 1: who by the way, was a co founder of a
Speaker 1: little company called Intel, he originally observed back in nineteen
Speaker 1: sixty five in a paper that I'm going to I'm
Speaker 1: going to with this, but it was called something like
Speaker 1: cramming more components onto integrated circuits something like that. That
Speaker 1: was actually cramming was definitely one of the words used,
Speaker 1: and circuit probably was too. Anyway, he noticed that over
Speaker 1: the course of I think originally it was twelve months,
Speaker 1: but today we consider it two years.
Speaker 2: Eighteen to twenty four months, I think is the official, unofficial.
Speaker 1: Right, right, right, Yeah, that the number of discrete components
Speaker 1: on a square inch silicon wafer would double due to
Speaker 1: improvements in manufacturing and efficiency, so that in effect, what
Speaker 1: this means to the layman is that our electronics and
Speaker 1: particularly our computers get twice as powerful every two years.
Speaker 1: So if you bought a computer in nineteen ninety eight
Speaker 1: 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 nineteen ninety eight. This is exponential growth.
Speaker 1: That's an important component, this idea of exponential growth, right,
Speaker 1: And it goes without saying that if you continue on
Speaker 1: this path, if this, if this continues indefinitely, then you know,
Speaker 1: you quickly get to computers of almost unimaginable power just
Speaker 1: a decade.
Speaker 2: Out certainly, although I mean I still don't really understand
Speaker 2: what a gigabyte means, because when I first started using computers,
Speaker 2: we were not counting in that. I mean, I mean,
Speaker 2: I was still impressed by kilobytes at the time.
Speaker 1: So yeah, Now, I remember the first time I got
Speaker 1: a hard drive, I think it had like a two
Speaker 1: hundred and fifty megabyte hard drive. I thought, you're like,
Speaker 1: who needs that much space? Now? Grat that's that's space
Speaker 1: we're talking about, not even processing pay right, absolutely, So, yeah,
Speaker 1: it's it's it's one of those things where the older
Speaker 1: you are, the more incredible today, is right, because you
Speaker 1: start looking at computers and you think, I remember when
Speaker 1: these things came out, and they were essentially the equivalent
Speaker 1: 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.
Speaker 2: Oh right, you know, and people that's why it's it's
Speaker 2: kind of in contention right now, because people are saying that, well,
Speaker 2: there's there's only so much physical space that you can
Speaker 2: fit onto with silicone. There there's there's a physical limitation
Speaker 2: to the material in which there's only so much it
Speaker 2: can do about it. And so does More's law still
Speaker 2: apply if we're talking about other materials and what's you.
Speaker 1: Know, right, and and how small can you get before
Speaker 1: you start to run into quantum effects that are impossible
Speaker 1: to work around. Uh, and then do you change the
Speaker 1: geometry of a chip? Do you go three dimensional instead
Speaker 1: of two dimensional? Would that help? And yeah, there are
Speaker 1: 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 ends to end. It's over,
Speaker 1: it's gone, it's done with. Five years later, you're still
Speaker 1: going strong. Yeah, And then on the six years someone
Speaker 1: else says More's Law is gonna end.
Speaker 2: It's a little bit of a self fulfilling prophecy. I
Speaker 2: think that a lot of companies attempt to.
Speaker 1: Keep it going. To keep it going, oh sure, yeah, yeah, yeah.
Speaker 1: I mean, no 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.
Speaker 2: Also, if I can footnote myself real quick, I'm pretty
Speaker 2: sure that I just pronounced silicon is still a cone,
Speaker 2: and I would like I would like to stay for
Speaker 2: the record that I know that those are two different substances.
Speaker 1: Okay, that's fair. Anyway, I was I was going to
Speaker 1: ask you about it, but by the time 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 hilarious results, excellent. So
Speaker 1: moving on with this whole idea about Moore's law, I mean,
Speaker 1: the reason this plays into the singularity is with the
Speaker 1: technological advances, you start to be able to achieve pretty
Speaker 1: incredible things, and even within one generation of Moore's law,
Speaker 1: which kind of a meaningless term. But let's say you
Speaker 1: arbitrarily pick a date and then two years from that
Speaker 1: date you look and see what's possible with the new technology,
Speaker 1: and getting to twice as much power however you want
Speaker 1: to define 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, grid computing.
Speaker 1: Grid computing is when you are linking computers together to
Speaker 1: work on a problem all at once. Now works really
Speaker 1: well with certain problems parallel problems we call them. These
Speaker 1: are problems where there are lots of potential solutions and
Speaker 1: each 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. And so
Speaker 1: like if you've ever heard of anything like folding at
Speaker 1: Home or the SETI project, where you could dedicate your
Speaker 1: computer's idle time, So the idle processes, the processes that
Speaker 1: are not being used while you're serving the web or
Speaker 1: writing how the singularity works, or I don't know, building
Speaker 1: an architectural program in some sort of CAD application. Anything
Speaker 1: that you're not using can be dedicated to one of
Speaker 1: these projects. Same sort of idea that you don't necessarily
Speaker 1: have to build a supercomputer to solve complex problems if
Speaker 1: you use a whole bunch of computers, whole bunch of
Speaker 1: small ones. Large Hadron Collider does this, although they use
Speaker 1: very nice advanced computers, but they do a lot of
Speaker 1: grid computing as well. So just using those kind of models,
Speaker 1: we see that we're able to do much more sophisticated
Speaker 1: things than we could.
Speaker 2: Otherwise if we were certainly, Yes, networks, as it turns out,
Speaker 2: are pretty cool.
Speaker 1: Yeah, and networks play a part in this idea of
Speaker 1: the singularity. Actually, I guess now is a good time
Speaker 1: we'll kind of transition into Werner Venge's and I honestly,
Speaker 1: I don't know how to say his last name. I
Speaker 1: say Vinge, and it could end up being ringy. But
Speaker 1: I just went with what you said. So that's great,
Speaker 1: that's fine. Let's do it. What we'll say that Venge
Speaker 1: says everything is silicone. So Werner though he vern, I
Speaker 1: call him Vern. He suggested four different potential pathways that
Speaker 1: humans could take, or really that the world could take, yes,
Speaker 1: to arrive at the technological singularity. Okay, what are they?
Speaker 1: The four ways are we could develop a superhuman artificial intelligence,
Speaker 1: So computers suddenly are able to think on a level
Speaker 1: that's analogous to the way humans think and can do
Speaker 1: it better than better. Right whether or not that means
Speaker 1: computers are conscious, that's debatable. We'll get into that too.
Speaker 1: Computer networks could somehow become self aware. That's number two. Okay,
Speaker 1: So yes, skynet, so like the grid computing we were
Speaker 1: just talking about that. Somehow using these grid computers. The
Speaker 1: network itself.
Speaker 2: Having enough cycles and enough pathways and enough loops back around,
Speaker 2: it starts going like, hey, I recognize this, yeah, and
Speaker 2: starts thinking about.
Speaker 1: Like thinking about IBM's Watson. But it's distributed across a network.
Speaker 1: So computers. You can think of computers as all being
Speaker 1: super powerful neurons in a brain, and that the network
Speaker 1: is actually neural pathways. And it's definitely a science fiction
Speaker 1: ye way of looking at things. Doesn't mean it won't happen,
Speaker 1: but strangers, my friends, it feels like a matrix kind
Speaker 1: of thing to me. Then we have the idea that
Speaker 1: computer human interfaces are so advanced and so intrinsically tied
Speaker 1: to who we are, that humans themselves evolve beyond being human,
Speaker 1: we become trans human. Okay, So this is an idea
Speaker 1: that we almost merge with computers at least on some.
Speaker 2: Level via kind of nanobot technology, you know, stuff stuff
Speaker 2: running through our bloodstreams, stuff in our selves yep.
Speaker 1: Or we have just brain in our faces where our consciousness,
Speaker 1: our consciousness is connected to So for example, we might
Speaker 1: have it where instead of connecting to the internet via
Speaker 1: some device like a smartphone or a computer device. Yeah,
Speaker 1: it's right there in our meat brains, so that you know,
Speaker 1: you're sitting there 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 IMDb in my brain. And then you you know,
Speaker 1: depending on how good your connection is, which means, by
Speaker 1: the way, if you are a journalist and you attend CEES,
Speaker 1: you will automatically be dumber because all the all the
Speaker 1: internet connectivity will be taken up, and so you'll be
Speaker 1: sitting there trying to ask good questions and druel will
Speaker 1: come out of your mouth, which to me is a
Speaker 1: typical CEES.
Speaker 2: I can I can only assume that that wireless technology
Speaker 2: would advance also at this point, but one can only
Speaker 2: hope fingers crossed.
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. Yeah. 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 they 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: engineer ourselves to be super smart. Right, So those are
Speaker 1: the four pathways artificial intelligence, computer networks become self aware,
Speaker 1: computer human interfaces become really really awesome, or we have
Speaker 1: biologically engineered human intelligence, and all four of these lead
Speaker 1: to a similar outcome, which is this intelligence explosion. And
Speaker 1: this is the idea that some form of superhuman intelligence
Speaker 1: is created, either artificially or within ourselves, and that at
Speaker 1: that point we will no longer be able to predict
Speaker 1: what our world will will be like, because by definition,
Speaker 1: we will have a superhuman intelligent entity involved. And because
Speaker 1: that's superhuman, it's beyond our ability to predict. Right, which
Speaker 1: is you know which.
Speaker 2: Which makes that experience experiments about it a little bit uh.
Speaker 1: Philosophical. Yeah, that's the kind way of putting it pointless,
Speaker 1: would be another way of putting it, like we could
Speaker 1: we could, you know, sit there and and spitball a
Speaker 1: whole bunch of possible futures. But that's the thing, they're possible.
Speaker 1: We don't know which one could come out. We don't
Speaker 1: even know if these four pathways are inevitable. We have
Speaker 1: futurists who truly believe that this is something that will
Speaker 1: happen at some point. There are other people who are
Speaker 1: more skeptical, but we'll talk about them in a bit.
Speaker 1: So one of the outcomes that Werner was talking about,
Speaker 1: and it's a fairly popular one in futurist circles, is
Speaker 1: the idea of the robo apocalypse. Essentially, right, this is
Speaker 1: where you've got the humans are bad, destroy all humans idea,
Speaker 1: Essentially 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 superhuman intelligence is it besides, we are a problem.
Speaker 2: Yeah, and a lot of futurists are a lot more
Speaker 2: positive about that. They're more looking forward to it than
Speaker 2: being scared of it. It's less of a oh no,
Speaker 2: big scary robots are coming to take over our society
Speaker 2: and more of a robot it's are coming to take
Speaker 2: over our society like free day.
Speaker 1: Yeah, yeah, exactly. Yeah, I don't have to work anymore,
Speaker 1: and and I don't because robots are supplying all the
Speaker 1: things we need. There's no need for anyone to work anymore.
Speaker 1: There's no need for money anymore because the only reason
Speaker 1: you need money is so you can buy stuff. But
Speaker 1: if everything's free, then you don't need you. So it
Speaker 1: becomes Star Trek and we all, you know, run around
Speaker 1: in jumpsuits and right punch people. And if you're Kirk,
Speaker 1: you make out a lot. I mean a lot. That
Speaker 1: dude every week Becrden Riiker. If you add them together,
Speaker 1: make one.
Speaker 2: Kirk and yes in this documentary series.
Speaker 1: Yeah, Star Trek. Yeah, I don't know about our trick
Speaker 1: because I never watched Enterprise, So you guys have to
Speaker 1: get back to me on that. Yeah, sorry, sorry about that. That.
Speaker 2: It's also a gap in my personal understanding.
Speaker 1: I just took one look at that decontamination chamber and
Speaker 1: I said, yep, I'm out anyway. So that's that's Werner Revenge.
Speaker 1: It's he's sort of popularized this idea, but he's there
Speaker 1: are other people have kind of I think their names
Speaker 1: are synonymous with it, and we will talk about them
Speaker 1: in just a minute 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 Kurtsweile.
Speaker 2: Ray Kurtsweil, and this is a fellow who has been
Speaker 2: referred to in various circles as the Thomas Edison of
Speaker 2: modern technology, or or, perhaps more colorfully, the Willy Wonka
Speaker 2: of technology. That was by Jef Duncan of Digital Trends,
Speaker 2: and I just wanted to shout out because that was great, nice.
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 2: We're fans, we might be fans of the Gene Wilder
Speaker 2: Willy Wonka. Everyone, homework assignment, go watch that. It has
Speaker 2: nothing to do with the singularity, the singularity at all.
Speaker 1: I don't know there's some chocolate singularity in there, Chocolate Singularity.
Speaker 1: I want to do an episode on.
Speaker 2: If I were better at cover band names, I totally
Speaker 2: would have said something whitty right there.
Speaker 1: Yeah, all right, well, fair enough, we'll say it's the
Speaker 1: Archies for Sugar Sugar, Oh dear, Oh my goodness.
Speaker 2: Okay, So Ray Kurtzweil, Yeah, Ray Kurtzweil is the kind
Speaker 2: of cat who you know, when he was in high
Speaker 2: school invented a computer program. And this is in the
Speaker 2: mid nineteen sixties. This isn't like last year or something
Speaker 2: in the mid nineteen sixties, created a computer program that
Speaker 2: listened to classical music, found patterns in it, and then
Speaker 2: created new classical music based on that.
Speaker 1: So as a computer that composed classical music, yes, following
Speaker 1: 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, that's dude's got credentials. Yeah.
Speaker 2: He also kind of invented flatbed scanners, has done a
Speaker 2: whole bunch of stuff in speech recognition, and.
Speaker 1: Which that's interesting because we'll and we'll talk about that
Speaker 1: in a second. But one of Kurtzweld's big points is
Speaker 1: that he thinks that by and this all depends upon
Speaker 1: which interview you read of Cartswell, but in various interviews
Speaker 1: he said that essentially, by twenty thirty, we will reach
Speaker 1: a point where we will be able to make an
Speaker 1: artificial brain. We'll have reverse engineered the brain, and we'll
Speaker 1: be able to create an artificial one. And there's a
Speaker 1: lot of debate in smarter circles and the ones I
Speaker 1: move in. That's not a slap against my friends. They're
Speaker 1: pretty bright, but none of us are neu quirologically gifted
Speaker 1: at that point. I include myself in that circle. So,
Speaker 1: but there are some very bright people who debate about
Speaker 1: this point, whether or not we'll be able by the
Speaker 1: year twenty thirty to reverse engineer the brain and design
Speaker 1: an artificial one. And I think the debate is not
Speaker 1: so much on whether or not we'll have the technological
Speaker 1: power necessary to simulate a Sure we can simulate brains
Speaker 1: on a certain superficial level today, well, I.
Speaker 2: Mean hypothetically we could connect enough computers that we could
Speaker 2: 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
Speaker 1: to do so exactly. So that's sort of where the
Speaker 1: debate lies. It's not so much on the technological side
Speaker 1: of things as it is the biological side of things,
Speaker 1: which is kind of interesting. I've read a lot of
Speaker 1: critics who have really jumped on Kurtzweld for this. Particularly PZ.
Speaker 1: Myers has written some pretty yeah strongly worded, strongly worded
Speaker 1: criticisms to Kurtzweil's theories, saying that Kurtzweil simply does not
Speaker 1: understand neurological development and activities, and that you know, the
Speaker 1: nature between the environment and the way our brains develop
Speaker 1: over to versus the you know, nurture versus nature, all
Speaker 1: of this stuff with the hormonal changes, electrochemical reactions.
Speaker 2: Saying that there's there's so many little bits that make
Speaker 2: up our brains, so many hormones, so many processes, and
Speaker 2: we understand such a small fraction of what they do.
Speaker 2: This is why a lot of psychiatric drugs, for example,
Speaker 2: are kind of like, oh, well, we invented this thing,
Speaker 2: and we guess it does this thing right, take it
Speaker 2: and see what happens?
Speaker 1: We do stuff? Yeah, we don't. It tends to make
Speaker 1: you happy. It also makes you perceive the color red
Speaker 1: as having the smell of oranges, like you know that
Speaker 1: that's we don't. We don't understand it fully. And in fact,
Speaker 1: there are other people like Stephen Novella, who is uh
Speaker 1: he's the author of the Neurological Blog, and he also
Speaker 1: is a host on a wonderful podcast called Skeptics Guide
Speaker 1: to the Universe. If you guys haven't listened to that,
Speaker 1: you should try that out if you especially if you
Speaker 1: like skepticism and critical thinking. But he's he's a doctor
Speaker 1: and a proponent of evidence based medicine, and he talks
Speaker 1: about how we don't know how much we don't know
Speaker 1: about the brain. We have no way of knowing where
Speaker 1: the endpoint is as far as the brain is concerned,
Speaker 1: and therefore we cannot guess at how long it will
Speaker 1: take us to reverse engineer. It's simply because we don't
Speaker 1: know where the finish line is.
Speaker 2: Right right, Yeah, Kurt Kurtzwell's Kurtzwell has a new book
Speaker 2: new as of we're recording this in January twenty thirteen.
Speaker 2: It just came out in November of twenty twelve called
Speaker 2: How to Create a Mind. The Secret of Human Thought Revealed.
Speaker 2: And in the book he theorizes that Okay, if you'll
Speaker 2: follow me for a second, adams are tiny bits of data, Okay.
Speaker 2: DNA is a form of a program. The nervous system
Speaker 2: is a computer that coordinates bodily functions, and thought is
Speaker 2: kind of simultaneously a program and the data that that
Speaker 2: program contains.
Speaker 1: Gotcha. See, now, this is another problem that some scientists have, yeah,
Speaker 1: is reducing the human brain to the model of a computer.
Speaker 2: Right, because it's you know, it's it's a very it's
Speaker 2: a very elegant, interesting proposition. Sure, and and it's kind
Speaker 2: of sexy like that because you go like, oh, well
Speaker 2: that's that that sort of makes sense. Man, Like, let's
Speaker 2: go get a pizza and talk about this more.
Speaker 1: Yeah, let me let me get a program that will
Speaker 1: allow me to suddenly know all kung fu.
Speaker 2: Right, and when you're a programmer, that's a great plan. Yeah,
Speaker 2: I mean, yeah, that sounds that sounds terrific. But yeah,
Speaker 2: there's one one specific guy found. Jaren Lanier wrote a
Speaker 2: terrific thing called One Half of a Manifesto, which is
Speaker 2: a really entertaining read if you guys like this kind
Speaker 2: of thing, where he was saying that what futurists are
Speaker 2: talking about when they talk about this the singularity is
Speaker 2: basically a religion. He was calling it cybernetic totalism, you know,
Speaker 2: like like a fanatic ideology. He compares it to Marxism
Speaker 2: at some point. Interesting, Yeah, and he was saying that that,
Speaker 2: you know, it's this, this theory is a terrific theory
Speaker 2: if you want to get into the philosophy of who
Speaker 2: we are and what we do and what technology is.
Speaker 2: But that you know, cybernetic patterns aren't necessarily the best
Speaker 2: way to understand reality, and that they're not necessarily the
Speaker 2: best model for how people work, for how culture works,
Speaker 2: for how intelligence works. And that's saying so is an
Speaker 2: gross over simplification.
Speaker 1: That's a good point, and we should also point out
Speaker 1: that it all depends on how you define intelligence as well,
Speaker 1: because Kurtzwell himself has worded his own predictions in such
Speaker 1: a way that some would argue. Novella argues, for example,
Speaker 1: that he has given himself enough room where he's going
Speaker 1: to be right no matter what, like saying that by
Speaker 1: twenty thirty, we will be able to reverse engineer basic
Speaker 1: brain functions, and Novella says, well, technically you could argue
Speaker 1: that now, So that kind of gives you a lot
Speaker 1: of room, a little bit of a gimme there. Yeah,
Speaker 1: But whether or not it means total brain function, and
Speaker 1: that's that's a totally different question. And so the other
Speaker 1: point is that we could theoretically create an artificial intelligence
Speaker 1: that does not necessarily reverse engineer the brain. It doesn't
Speaker 1: follow the human intelligence model. I mean, that's IBM's Watson again,
Speaker 1: a good example of artificial intelligence that you know, in
Speaker 1: some ways it mimics the brain because it kind of
Speaker 1: has to. You know, we're coming at this human beings
Speaker 1: are the ones creating this technology, and so as human
Speaker 1: beings creating this technology, it's going to follow the rules
Speaker 1: that as we understand them. So there's going to be
Speaker 1: some medocry there. Right. But but IBM's Watson, you know,
Speaker 1: you think about that. It doesn't really understand necessarily the
Speaker 1: data that's passing through it. It's looking for the connections
Speaker 1: and making.
Speaker 2: It really savvy at making connections and recognizing patterns and
Speaker 2: spitting out useful information.
Speaker 1: Yeah, 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 does doesn't reach a certain threshold, it doesn't provide
Speaker 1: the answer. So if arbitrarily speaking, i don't know what
Speaker 1: the threshold is, so I'm just making a number eighty
Speaker 1: five percent. Let's say it has to be eighty five
Speaker 1: percent 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 Jeopardy, right. It would analyze the the
Speaker 1: the answer in jeopardy terms and then come up with
Speaker 1: what it thought was probably the most accurate question for
Speaker 1: 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 2: And I mean the thing about humans is that they're
Speaker 2: they're wrong a lot more than a lot more than
Speaker 2: what that fifteen percent of the time.
Speaker 1: Yeah, it's you know, we've we've got well, we give
Speaker 1: answers even if we're not eighty five percent short a question.
Speaker 1: I certainly do.
Speaker 2: Because we all know from going to trivia nights. Yeah,
Speaker 2: and there's there's a lot of I've read a lot
Speaker 2: on online about arguments of how it's our deficiencies, our memory, biases,
Speaker 2: our rational behavior are weird hormonal stuff going on or
Speaker 2: what make us human, and that you can't teach a
Speaker 2: computer to be irrational.
Speaker 1: That's true, although you can't teach you to swear. You can.
Speaker 1: We just we read a story last week, yeah, where
Speaker 1: IBM allowed Watson to read the Urban Dictionary and then
Speaker 1: I Watson got a little bit of a botty mouth.
Speaker 2: It got it got kind of fresh.
Speaker 1: It did it did it started it started to say that. Uh.
Speaker 1: Oh see what was it? Oh, I'm going to say
Speaker 1: something and it's going to be bleeped 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 bo. So since that
Speaker 1: was bleeped out, you probably don't know what it was,
Speaker 1: so go look it up. It was funny. It was
Speaker 1: really funny.
Speaker 2: Yes, And then and then they basically nuked that part
Speaker 2: of Watson from orbit. They were like, you know what,
Speaker 2: 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. Oh no no judgments here, just saying what
Speaker 1: what IBM said. Anyway, Again, the computer was unable to
Speaker 1: determine when, when there, when it was appropriate and what's
Speaker 1: the appropriate context for dropping a swear word. Yeah, 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. So anyway, that that that's
Speaker 1: an interesting point though. Again you're you're showing how machine
Speaker 1: intelligence and human intelligence are different because the machine intelligence
Speaker 1: doesn't have that context for sure.
Speaker 2: And of course, you know, we're talking about about science
Speaker 2: fiction or science future, however you want to term it
Speaker 2: so that, you know, we might very well come up
Speaker 2: with fancy little program script that lets you that lets
Speaker 2: you introduce that kind of bias. But you know, yeah,
Speaker 2: but again from that documentary Star Trek, I mean, data
Speaker 2: never figured out those contractions.
Speaker 1: That's true, that's true. Touring actually had a great mental exercise,
Speaker 1: really and it's called the Touring test, and this applies
Speaker 1: to artificial intelligence. Touring's point, and we've talked about the
Speaker 1: Touring test in previous episodes of Tech Stuff, but just
Speaker 1: as a refresher, Touring had suggested that you could create
Speaker 1: a test and that if a machine could pass that
Speaker 1: test at the same level as a human, in other words,
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 essentially simulated human intelligence.
Speaker 1: And it usually works as an interview, so you have
Speaker 1: someone who's who's conducting an interview, and you have either
Speaker 1: a machine answering or a human answering, and there's a
Speaker 1: barrier up so that of course the person asking the
Speaker 1: questions cannot see who is responding. And of course they're
Speaker 1: responding through you know, text usually because if they're responding
Speaker 1: through a voice and it's like I think the answer
Speaker 1: as far you know, you'd be like, well, either it's
Speaker 1: a robot or the most boring person in the world.
Speaker 1: The idea being you would ask these questions over a
Speaker 1: computer monitor, get text responses, and if you were unable
Speaker 1: to answer with a certain degree of accuracy whether or
Speaker 1: not it was a machine or a person, then you
Speaker 1: would say the machine passed the Touring the test test.
Speaker 1: And you could argue, well, that could just mean that
Speaker 1: the machine's very good at mimicking human intelligence, it does
Speaker 1: not actually possess human intelligence. Turing's point is, does that matter?
Speaker 1: Because I know that I am intelligent. I speak with
Speaker 1: someone like Lauren, who I assume is also intelligent based
Speaker 1: upon the responses she gives, But she could just be
Speaker 1: simulating intelligence. However, I have already bestowed in my mind
Speaker 1: the feature of intelligence upon Lauren because what she does
Speaker 1: is very much akin to what I do. So Touring said,
Speaker 1: if you extend the courtesy to your fellow human being
Speaker 1: that they are intelligent based on the fact that they
Speaker 1: act like you do. Why would you not do the
Speaker 1: same thing for a machine? Does it matter if the
Speaker 1: machine can actually think, If the machine simulates thought well
Speaker 1: enough for it to pass as human, then you're giving
Speaker 1: it the same benefit of doubt that anyone else.
Speaker 2: You mean, right, this is what a lot of science
Speaker 2: fiction movies are about.
Speaker 1: Actually, yeah, there's a lot of philosophy.
Speaker 2: And yeah, a lot of philosophy, a lot of Isaac Asmo,
Speaker 2: have a lot of Blade Runner and that's not an author.
Speaker 1: Sorry, well no, but you know Philip K. Dick, look
Speaker 1: him up. So anyway, thank you do. Android's dream of
Speaker 1: Electric Sheep. I won't I won't spoil it for you.
Speaker 1: They to kind of wrap this all up, getting back
Speaker 1: into the discussion of philosophy. We had very recently, we
Speaker 1: did a podcast about our we living in a computer simulation, right, right,
Speaker 1: and 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'll be beyond our understanding. Then one thing we
Speaker 1: would expect to do is create simulations of our past
Speaker 1: to kind of study ourselves, sure, right.
Speaker 2: And to see what happens play around variables yams.
Speaker 1: Yeah, and 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: but unable to know that they were a simulation. He
Speaker 1: said that if those things are possible, then there's no
Speaker 1: way of knowing that, you know, the the overwhelming possibility
Speaker 1: is that we are in a computer simulation.
Speaker 2: It's a computer simulation, yeah, right now.
Speaker 1: Because yeah, if that's if that's what's gonna happen, then
Speaker 1: there's no way of saying with certainty that we are
Speaker 1: not in fact the product of that. And so, uh,
Speaker 1: the point being not necessarily that we are in fact
Speaker 1: living in a computer simulation, but that perhaps this singularity,
Speaker 1: this transhumanism thing might not be realistic, It might not
Speaker 1: be the future that we're headed to. Maybe it ends
Speaker 1: up being a pipe dream that's not really possible for
Speaker 1: us to attain. Or maybe we'll wipe ourselves out through
Speaker 1: some terrible war or catastrophic accident. Maybe we create a
Speaker 1: biological entity that wipes us out allah the stand, or
Speaker 1: we create a black hole at the LHC. Which come on,
Speaker 1: people don't write me. I already know about that and
Speaker 1: how tiny and and alm non existent they are because
Speaker 1: it lasts so quickly, it totally happened. Let's say that
Speaker 1: they do that thing where you look at that one
Speaker 1: website where the black hole forms in the parking lot
Speaker 1: outside the LHC and you just see the whole picture
Speaker 1: go which funny video. Anyway, that argument plays back into this.
Speaker 1: So I don't know. I don't know if we're going
Speaker 1: to ever see a future where the singularity becomes a thing.
Speaker 1: Oh and we never really talked about it. But one
Speaker 1: of the big points that Kurtzwell really punches in his
Speaker 1: Singularity talks is the idea of digital immortality, right right.
Speaker 2: And he's been obsessed with this, and obsessed is probably
Speaker 2: a judgmental word. I apologize that's but he's been very
Speaker 2: focused on this concept. His father died when he was
Speaker 2: about twenty four, and he's been exploring theories on life
Speaker 2: extension ever since then, and supposedly takes all kinds of
Speaker 2: supplements and sells them as well to extend life. Has
Speaker 2: all kinds of kinds of health plans.
Speaker 1: Yeah, dietary that he has exercise all the idea that
Speaker 1: the idea being that if he can preserve his own life.
Speaker 2: Last long enough that we hit the singularity, then he
Speaker 2: can become immortal.
Speaker 1: Right, and either that, you know, we attain immortality through
Speaker 1: one of a thousand different ways. For example, we end
Speaker 1: up uploading our own intelligence into the cloud, right, and
Speaker 1: then we become part of a group consciousness, so we
Speaker 1: are no longer really individuals. Or we merge with computers
Speaker 1: in some other way so that we are technically immortal
Speaker 1: that way. Or we just conquer the genes that all
Speaker 1: guide the aging process and we stop it, and we
Speaker 1: stop disease.
Speaker 2: You know, we take like in transmit, you just take
Speaker 2: a cancer pill and then you don't get cancer because
Speaker 2: that's what you do.
Speaker 1: Yeah, So again the singularity. That's kind of why I
Speaker 1: think a lot of critics also point to it as
Speaker 1: being more of a religion because it's kind of this
Speaker 1: sort of utopian pipe dream in their minds.
Speaker 2: There's the former CEO of Lotus, Mitch Kapor Kapper, I'm
Speaker 2: not sure how you say it, once called called it
Speaker 2: the intelligent design for the i Q one forty people.
Speaker 1: Yeah, ouch ouch. Well, meanwhile, Kurtzwild's kind of laughing all
Speaker 1: the way to the bank. I hear that a company
Speaker 1: that rhymes with Shmugel hired him Little little people.
Speaker 2: I mean, we're you probably wouldn't have heard of him, Yeah,
Speaker 2: but yeah, they just tired him on to be uh.
Speaker 2: I have it in my notes the official title. I
Speaker 2: think it's the director of engineering. Yeah, a director of
Speaker 2: engineering over there.
Speaker 1: Yeah, they get they get some big names. I mean
Speaker 1: they had Vince Surf as the chief evangelist, and of
Speaker 1: course he was one of the fathers of the Internet.
Speaker 1: So Google's Google's got a They're known for getting some
Speaker 1: really smart people. 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.
Speaker 2: Now, you know, oh, absolutely so, even if we're even
Speaker 2: if we never reached the point of digital immorte in
Speaker 2: our lifetimes or any other it's I mean, if someone
Speaker 2: wants to think so big that they want to put
Speaker 2: in nanobots to make my body awesomer, I mean, and
Speaker 2: not that that came out. That came out possibly crude.
Speaker 2: It mostly means that I don't get cancer and die
Speaker 2: kind of stuff. That's that's terrific. Can I can't argue
Speaker 2: with any part of that.
Speaker 1: Yeah, I'm going to be on video so much this
Speaker 1: year that I definitely need my body to be awesomer,
Speaker 1: So I'm all for that well either way.
Speaker 2: Yes, And and Google, you know, Google looks forward so
Speaker 2: much to augmented reality. Augmented reality. I'm sorry, I can't
Speaker 2: pronounce anything today. I am on a non roll. It's okay,
Speaker 2: in the Internet of Things and all of that wonderful
Speaker 2: future tech that it seems like a terrific fit.
Speaker 1: Yeah. Yeah, so we'll see 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 thirty and twenty fifty. Yeah, it all
Speaker 1: depends upon which futurist you're asking. And also it's one
Speaker 1: of those kind of I think it's one of those
Speaker 1: rolling goalposts as well. You know how certain technologies are
Speaker 1: always twenty years away, or five years away or ten
Speaker 1: years away. So we'll see. Maybe by twenty twenty we'll
Speaker 1: be saying, all right, we've revised our figures.
Speaker 2: By twenty seventies, definitely, but who knows.
Speaker 1: We'll see. Guys, if you have any suggestions or future
Speaker 1: episodes of tech Stuff, well here's what you can do.
Speaker 1: You can write us an email. And a lot of
Speaker 1: people have been asking about our email address. I do
Speaker 1: say that every episode, but in case you've missed it,
Speaker 1: listen carefully. Our email address is tech Stuff at Discovery
Speaker 1: dot com. Send an email. I'll prove it by writing back,
Speaker 1: or drop us a line on Facebook or Twitter. Our
Speaker 1: handle there at both of those is text Stuff hsw
Speaker 1: and Lauren and I will talk to you again in
Speaker 1: the future. And that was the classic episode tech Stuff
Speaker 1: Enters the Singularity, way back from twenty thirteen, more than
Speaker 1: a decade ago. Holy cats, I have been doing this
Speaker 1: show for so long because Lauren, of course, was my
Speaker 1: second co host. I had already done a couple hundred
Speaker 1: shows with a different co host. Wow really does hit
Speaker 1: me right in the brain. So I hope you all
Speaker 1: enjoyed that. I'm looking forward to seeing what comes next.
Speaker 1: I don't think we're gonna hit the Singularity this year.
Speaker 1: Maybe I should have put that as one of my predictions,
Speaker 1: but who knows. Maybe open Aiye is gonna create the
Speaker 1: next generative chat bot and it'll program the sky Net
Speaker 1: like system that will bring us onto the Singularity kicking
Speaker 1: and screaming, or if you're me, I'm probably already kicking
Speaker 1: and screaming just just because I'm grouchy. Anyway, I hope
Speaker 1: you're all well. I hope you had a happy and
Speaker 1: safe New Year, and I'll talk to you again really soon.
Speaker 1: Tech Stuff is an iHeartRadio production. For more podcasts from iHeartRadio,
Speaker 1: visit the iHeartRadio app, Apple Podcasts, or wherever you listen
Speaker 1: to your favorite shows.