Speaker 1: Brought to you by Toyota. Let's go places. Welcome to
Speaker 1: Forward Thinking. Hey there, and welcome to another episode of
Speaker 1: Forward Thinking, the podcast that looks at the future and
Speaker 1: says one singular sensation. I'm Jonathan Strickland, I'm Lauren Pola,
Speaker 1: and I'm Joe McCormick. So, you, guys, how is it
Speaker 1: possible that we've gone this long with a forward thinking
Speaker 1: futuristic podcast and not really touched upon the singularity. I
Speaker 1: mean we we've joked about it a couple of times,
Speaker 1: were slacking. They say it's near. Well, yeah, depending upon
Speaker 1: whom you ask, it's gonna be um like any day now.
Speaker 1: So we thought it's high time we actually take a
Speaker 1: look at the singularity, talk about what is this idea
Speaker 1: of the singularity, What does it mean? What do people
Speaker 1: who are super duper small aren't have to say about
Speaker 1: it on one side or the other, And kind of,
Speaker 1: I guess, ultimately kind of give our own opinions about
Speaker 1: what we think. Keeping in mind that we are not
Speaker 1: futurists in the strictest sense of the word. This is
Speaker 1: more about how we kind of feel about things because
Speaker 1: we're not computer scientists. Were futuri ins or future ologists
Speaker 1: is what we are future rangers. So um, yeah, so
Speaker 1: let's let's get started. Let's let's talk about what the
Speaker 1: singularity is. So, what the heck is it? You know?
Speaker 1: I think in the popular consciousness when you mentioned the singularity,
Speaker 1: they're aware that it has something to do with technology
Speaker 1: and something to do with the future. But other than that,
Speaker 1: it's just kind of this vague mental piece of stock
Speaker 1: art where there's some wavy lines and a picture of
Speaker 1: like a brain and some electricity. Right, yeah, maybe maybe
Speaker 1: brains suddenly going up into disappearing into ones and zeros
Speaker 1: and joining a giant cloud of them or something. Yeah.
Speaker 1: So I think the general understanding of it is fairly vague,
Speaker 1: and so I'd like to narrow that down and focus
Speaker 1: it on what does this mean in the most basic
Speaker 1: technological sense, And what I'd say is that it's usually
Speaker 1: used to mean a time when humans develop superhuman intelligence
Speaker 1: through some means, whether by creating artificial intelligence or by
Speaker 1: amplifying their own intelligence, or somehow or other stumbling on
Speaker 1: an intelligence greater than that of what humans are normally capable.
Speaker 1: And often they also go further into saying that in
Speaker 1: this world where we have developed superhuman intelligence. We will
Speaker 1: we we in the present right now, will be unable
Speaker 1: to kind of predict what that future is going to
Speaker 1: look like because we won't even be able to recognize it. Yeah,
Speaker 1: by our very nature, by our limited human intelligence, we
Speaker 1: cannot conceive of what that future will be. It's impossible.
Speaker 1: It's beyond our our what our limitations are are around us.
Speaker 1: The idea also tends to involve not just a stasis,
Speaker 1: like we reach a point of plateau of very high intelligence,
Speaker 1: but it involves this idea of a vast acceleration in
Speaker 1: learning and improvement, right, so educational specotification, Yeah, or a
Speaker 1: Moore's law that applies directly to how smart we are,
Speaker 1: so that we're constantly getting smarter than we were earlier.
Speaker 1: And it just keeps except that instead of Moore's law,
Speaker 1: which is steady you have you know, you have this
Speaker 1: this uh, this doubling growth, but it's a steady doubling
Speaker 1: growth in the singularity, and at least some versions of it,
Speaker 1: it's an exponential or or lager eithmic growth to the
Speaker 1: point where, uh, you know, it's you're not only getting smarter,
Speaker 1: but you're getting smarter faster, right, and in that sense,
Speaker 1: it's sort of a double impossibility for us to understand
Speaker 1: what it will be like. It's not only smarter than
Speaker 1: we can imagine now, but it's getting smarter faster than
Speaker 1: we can imagine now. Right, So, there are generally speaking
Speaker 1: four different agreed upon ways that this singularity could come about.
Speaker 1: These are are proposed by a science fiction writer and
Speaker 1: mathematician and mathematician Verne Buddy Verne, I don't I don't
Speaker 1: actually know Verner of into it anyway. He's a he's
Speaker 1: got this idea. He had this idea where he kind
Speaker 1: of proposed four ways that we could reach this superhuman
Speaker 1: intelligent future. And these are four pathways that are not
Speaker 1: necessarily completely um isolated from each other or compartmentalized. We
Speaker 1: may see some weird um combination of different paths that
Speaker 1: lead us to this, assuming that the singularity is indeed
Speaker 1: something we are going to hit at some point time
Speaker 1: or another. Okay, what are they? So you've got superhuman
Speaker 1: intelligent machines. This is the artificial intelligence route. I think
Speaker 1: this is like the most classic sense that people would
Speaker 1: imagine the most it's just saying, like developing computers that
Speaker 1: are beyond human capabilities. Yeah, the idea of being that
Speaker 1: you would be able to build a computer so sophisticated
Speaker 1: that it could design the next generation of computers much
Speaker 1: better than any human could, and that next generation of
Speaker 1: computers could design the next generation of computers better than
Speaker 1: the predecessor could, and so on and so forth, and
Speaker 1: then creating a level way beyond anything that we can
Speaker 1: even understand. Right, and faster too, so that you know,
Speaker 1: the time between generations gets to a point where there's
Speaker 1: no longer you can no longer say this is generation one,
Speaker 1: this is generation too. They'll just be meaningless to ask
Speaker 1: the question because it's constantly changing. Yeah, That rapid optimization
Speaker 1: is often called the intelligence explosion. Yes, uh. And so
Speaker 1: next we have the idea about computer networks themselves gaining
Speaker 1: some form of sentience or intelligence. Now, this is one
Speaker 1: that I've heard a few different philosophers and computer scientists
Speaker 1: talk about the kind of idea that with any uh,
Speaker 1: network of information exchanging nodes that's complex enough, you could
Speaker 1: have consciousness arise. So, in other words, if you had
Speaker 1: enough information exchanging nodes in a complex enough system, then
Speaker 1: it would end up mirroring what our brains do with
Speaker 1: our neural pathways. And because uh, in the argument of
Speaker 1: these people, consciousness is itself a manifestation of these physical
Speaker 1: connections that our brain emergent manifestation, Yes, that that would
Speaker 1: in fact emerge in these synthetic networks. One of the
Speaker 1: things here would be to consider whether or not a
Speaker 1: system like this could have executive control of some kind.
Speaker 1: Like if you imagine the Internet today as a brain,
Speaker 1: well that is a brain or a mind, whatever you
Speaker 1: want to call it, that is both has more intellectual
Speaker 1: capability and has more knowledge than any other thing that exists,
Speaker 1: but it has no executive at the top of it.
Speaker 1: There's nobody controlling the Internet. To say, now, think about this, well,
Speaker 1: if you consider that the Internet is a crazy cat lady,
Speaker 1: it makes perfect sense. It's the question of whether a
Speaker 1: flock of birds really knows where it's going, or just
Speaker 1: if each individual bird is uh doing what it does.
Speaker 1: Are a school of fish, this kind of thing where
Speaker 1: you see these behaviors that are are fascinating, uh, and
Speaker 1: on the surface they start to really perplex people. It's
Speaker 1: what you have to really dig down to understand how
Speaker 1: they work. Well, next, we've got the idea of computers
Speaker 1: and humans getting all buddy buddy. Okay, so this is
Speaker 1: this is also ties into the stock art, right, it's
Speaker 1: like a human brain with like a computer chip on
Speaker 1: it and electricity shooting now a giant wind up key
Speaker 1: sticking out of the humans back come from a different
Speaker 1: school than you guys, So uh yeah, this is the
Speaker 1: idea that we have computer and human intelligence merging into
Speaker 1: some form of new entity. So a lot of not all,
Speaker 1: but a lot of the singularity models that will talk
Speaker 1: about include this idea of trans humanism, where humans evolve
Speaker 1: beyond what we are now. We become a new species,
Speaker 1: either because we've merged with machines in this way where
Speaker 1: where we've incorporated machine intelligence into our human intelligence in
Speaker 1: a in a very organic way. I guess it's kind
Speaker 1: of weird to say organic, but that's kind of what
Speaker 1: they're talking about. Or we create something that's uh like
Speaker 1: a superhuman intelligent machine that then changes us so that
Speaker 1: we're no longer human in the way we would think
Speaker 1: of now. And in that way, it's easy to see
Speaker 1: how some of these different pathways could overlap. Like first,
Speaker 1: you design say just a classical AI, like a super
Speaker 1: intelligent machine that's a computer, but that machine that's a
Speaker 1: computer tells you exactly how to modify your body with
Speaker 1: cybernetics that allow you to go in this hybrid state
Speaker 1: to the singularity exactly. And this this is also the
Speaker 1: option I think where a lot of nanobots tend to
Speaker 1: come in our good old buddies nano bots. Yeah, the
Speaker 1: idea of like, uh, sort of fortifying your body. I'll
Speaker 1: make sure you have your vitamins, your minerals in your
Speaker 1: nanobots because the nanobots will continuously upgrade you. That isn't
Speaker 1: one of those popular ideas in science fiction. It's also
Speaker 1: one that you know, we've talked a little bit about
Speaker 1: nanotechnology in the past. We'll talk a lot more about
Speaker 1: it in future episodes, but it's complicated stuff. Question, all
Speaker 1: these involved computers. Is there a way we could achieve
Speaker 1: super intelligence without computer? This is the Frankenstein method. So yes,
Speaker 1: through through pure application of medicine and science, we can
Speaker 1: create a superhuman. This is starting to sound a little
Speaker 1: scary in a way, but yeah, we're telling bioengineering as
Speaker 1: opposed to the rest of them. It's sky nets was
Speaker 1: totally fine with you. Look, this one is scary. I'd
Speaker 1: like to say that I, for one, welcome our robot overlords,
Speaker 1: and I'm okay with them, all right. I have always
Speaker 1: treated my room bow with respect. This is just as
Speaker 1: a recorded account of my philosophy. M That's all I'm
Speaker 1: gonna say now. So, the bioengineering approach is the idea
Speaker 1: that we find out ways to maybe genetically modify humans.
Speaker 1: It involves changing us on a biological level, where we
Speaker 1: attain this sort of superhuman intelligence through that pathway, as
Speaker 1: opposed through some form of machine intelligence. Okay, so before
Speaker 1: this was a cliche on the internet, what was it?
Speaker 1: Where did this idea come from? Well, you know, it's
Speaker 1: it's an old idea like we've had. We've had people
Speaker 1: talking about machines giving us the capability to to think
Speaker 1: better for more than a century. So if you go
Speaker 1: all the way back to the Industrial Revolution, there were
Speaker 1: people who were saying, as machines were becoming more important
Speaker 1: in human activities, they were saying, look, this is allowing
Speaker 1: us to extend our ability to do to complete tasks,
Speaker 1: and just imagine a time where those tasks aren't just
Speaker 1: physical but also mental. And so it was pretty early
Speaker 1: on that people were starting to have the very seeds
Speaker 1: of this idea. It wasn't so formalized as the idea
Speaker 1: of a singularity that would come later, but it was
Speaker 1: already starting to kind of trickle into the minds of
Speaker 1: people at the time. The actual term singularity, as it
Speaker 1: relates to a point beyond which humanity as we know
Speaker 1: it will change um was coined a nineteen fifty eight
Speaker 1: by John von Neuman. Okay, oh, that's kind of interesting,
Speaker 1: like a singularity as in like a black hole, or
Speaker 1: as in like at the beginning of the universe, like
Speaker 1: you can't point right right. That's that's where. Yeah, I'm
Speaker 1: just thankful they didn't call it event horizon that that
Speaker 1: shows that movies had enough references on the show. So
Speaker 1: but yeah, so singularity as a point that we are
Speaker 1: not able to see beyond simply because it's it's beyond
Speaker 1: what we are able to conceive of. You don't get
Speaker 1: into technological singularity until about thirty years later, and that's
Speaker 1: when our our good buddy Verne came up with this idea.
Speaker 1: He wrote an essay for Omni magazine, and he predicted
Speaker 1: we would quote unquote soon create superhuman intelligences that would
Speaker 1: transform our world in ways we can't anticipate because again,
Speaker 1: we have human intelligence. So if you're talking superhuman by definition,
Speaker 1: we cannot conceive of that. It's it's beyond our ken. Okay,
Speaker 1: where does Ray come in? Oh, you're talking Kurtswhile great
Speaker 1: kurts Will. I mean, he's the big name in the singularity,
Speaker 1: at least as far as I can tell. He When
Speaker 1: you say singularity, who do you think of? Kurtswild, Like
Speaker 1: to the point that a lot of people on some
Speaker 1: futurists on the Internet are kind of derisive and go like,
Speaker 1: you know, other people aside from Ray Kurtzwile are working
Speaker 1: in this field, Thank you very much. Churtswild published a
Speaker 1: very popular book about it in two thousand five. He
Speaker 1: wrote The Singularity is New, or rather he got it published,
Speaker 1: and that book was extremely popular. It it really brought
Speaker 1: this idea of the singularity beyond a kind of niche audience.
Speaker 1: I mean, uh, my dad subscribed to Omni magazine, but
Speaker 1: I'm not sure that that many other people outside of
Speaker 1: the science fiction world really read that much of Omni.
Speaker 1: So suddenly getting this into more of a kind of
Speaker 1: a mainstream mindset made the whole concept explode. Yeah, this
Speaker 1: took this weird nerd concept and in and had TV
Speaker 1: interviews and stuff about it. He's also so charismatic. Yeah, yeah,
Speaker 1: he's I mean, he travels the world giving talks about,
Speaker 1: you know, futurism as well as other topics. And of
Speaker 1: course he's had his own incredible career. I've talked about
Speaker 1: him in the past on another show. We do text stuff,
Speaker 1: and Kurt Swile has had a very long career in
Speaker 1: uh everything from voice recognition to computer AI and it's
Speaker 1: pretty cool stuff. So when he talked, people listened. And
Speaker 1: his prediction, which as far as I know, he has
Speaker 1: not amended any time recently, was that we would have
Speaker 1: the singularity by twenty five. So, in other words, when
Speaker 1: the year gets here, we will reach a time and
Speaker 1: human history where it will no longer be something we recognize. Yeah.
Speaker 1: The unfortunate thing about predictions and dates in the future
Speaker 1: is you can't really know whether they're right until you
Speaker 1: get there. And that's a long way off, isn't it.
Speaker 1: That's deep Joe, Yes, that is true. Both of those
Speaker 1: things you said are true. Uh. Yeah. He actually also
Speaker 1: said that we would have computers that are as intelligent
Speaker 1: as humans. As to me, that's that's a really tricky prediction, because,
Speaker 1: of course, you can argue that there are many ways
Speaker 1: that computers are much better at performing certain types of
Speaker 1: tasks than humans are. I mean, it's it's undeniable. Yeah,
Speaker 1: Like sorting through an incredibly long list incredibly quickly. Computers
Speaker 1: tend to be much better than people are sequencing a genome. Yeah.
Speaker 1: There are other things that humans are great at that
Speaker 1: computers are not so great at, like natural language. Natural
Speaker 1: language is a great example, or just being able to see.
Speaker 1: Like if I show you a cup and I teach
Speaker 1: you what a cup is, and then I show you
Speaker 1: a totally different cup, that's not that's not the same design.
Speaker 1: It's different colors, different shape, different size. You still know
Speaker 1: what a cup is? You still oh, that's a cup.
Speaker 1: Computers don't necessarily know that. You have to really start
Speaker 1: building in this software. It doesn't matter how powerful the
Speaker 1: computer is unless the software itself is able to also
Speaker 1: give the computer that that processing ability. Right. This is
Speaker 1: actually one reason that scientists and engineers are trying to
Speaker 1: teach computers to work like brains in terms of the
Speaker 1: hardware itself, because you can take a normal computer and
Speaker 1: with good facial recognition software. Like the computer being taught
Speaker 1: how to recognize faces and what faces are. It can
Speaker 1: sort of, it can do a good job. It can
Speaker 1: look at your face and say okay, but that's after
Speaker 1: you've taught it. What's a lot harder is to release
Speaker 1: a normal computer onto the Internet and say, learn what
Speaker 1: these images are. I'm not giving you any help, right,
Speaker 1: Associations which are something that that humans do very naturally,
Speaker 1: are not something it's you have to program that, and
Speaker 1: programming that is one of the more difficult tasks. Very
Speaker 1: even even if you build the structure, it takes a
Speaker 1: lot of time. This is why you know, we've talked
Speaker 1: about the semantic web and this idea of meta data
Speaker 1: and tagging this data and building ontologies. I mean, these
Speaker 1: are very important so that a computer can understand how
Speaker 1: to navigate a world that we can navigate naturally. YEA.
Speaker 1: So even though we have agreement that computers are good
Speaker 1: at some things and that humans are better at other things,
Speaker 1: the thought of the people who who propose this technological
Speaker 1: singularity is that computers are rapidly going to catch up
Speaker 1: to the areas where humans are better at at those tasks,
Speaker 1: and they're still going to be much better at the
Speaker 1: other task that computers are already ideally suited to. Yeah,
Speaker 1: perhaps the the things that the computers are good at
Speaker 1: will allow them to rapidly become better at the things
Speaker 1: they're not good at. Sure, but not everyone agrees with
Speaker 1: the idea of the singularity. No, that We've got actually
Speaker 1: a bunch of people on on both sides of the issue, right, right,
Speaker 1: Let's talk about some of these main figures in in
Speaker 1: sort of singularity thought or singularity studies and what they've
Speaker 1: had to say about this idea because it's actually somewhat
Speaker 1: controversial these days. So we've got Kurtswile we've already mentioned him,
Speaker 1: he's probably one of the most visible UH thinkers and
Speaker 1: speakers about the singularity. Yeah, and we should make clear
Speaker 1: when we talk about these people that being sort of
Speaker 1: on the pro singularity side doesn't necessarily mean you think
Speaker 1: it's a good thing. Oh right. A lot of these
Speaker 1: people actually think that it will be very negative and
Speaker 1: are looking at ways of mitigating that potential. Yeah, right,
Speaker 1: But we're talking about people who sort of think that
Speaker 1: it's gonna happen, and think that it's going to happen
Speaker 1: pretty soon, like within our lifetimes, or if not our lifetimes,
Speaker 1: the next generation's lifetime. Okay, what about Hans Hans more
Speaker 1: of It. Well, Hans more of Ek is a Carnegie
Speaker 1: Mellon Robotics Institute adjunct professor used to be anyway, and
Speaker 1: uh he says, of course that the mind is the
Speaker 1: product of physical processes in the brain. So uh, you
Speaker 1: know this is this is again something that's argued among
Speaker 1: philosophers and uh neuro specialists as well. But his his
Speaker 1: premise is that if you have enough power, enough computing power,
Speaker 1: and enough sophistication with software, that you would be able
Speaker 1: to replicate what happens in our our brains and thus
Speaker 1: give rise to a synthetic mind. Okay, this would sort
Speaker 1: of make sense if you're saying that you're starting position
Speaker 1: is that the brain doesn't have anything magic in it,
Speaker 1: then why should it be that difficult to replicate what
Speaker 1: it does or even do better? And on one level,
Speaker 1: a lot of people say, yeah, that makes sense, but
Speaker 1: but on another level, you may be trivializing exactly how
Speaker 1: complicated the brain and neurological processes actually are. Well, that's
Speaker 1: exactly why it seems like there might be something magic
Speaker 1: in the brain. Right, imagine that there's not something magic
Speaker 1: in it. Well, it's so complex physically that it seems
Speaker 1: to lots of people like there is. Well, it's just
Speaker 1: like just like the idea of any technology sophistical enough
Speaker 1: will appear as magic. Exactly, same sort of thing here,
Speaker 1: any science that's complex enough and really really and that's
Speaker 1: sort of a testament to the fact that the brain
Speaker 1: may be a lot harder to replicate than we're giving
Speaker 1: it credit for. Right, And it's and it's really big.
Speaker 1: I mean, don't don't let the relatively small sides of
Speaker 1: our skulls fool you. There's a lot going on in there. Yeah,
Speaker 1: when you're looking at how many neurons the typical brain has,
Speaker 1: how many neural pathways, the fact that neural pathways will
Speaker 1: form and then start to kind of every time you
Speaker 1: think back on that memory, the same sort of pathway
Speaker 1: starts lighting up, and then sometimes the pathway changes a
Speaker 1: little bit, which means that our memories are not entirely reliable,
Speaker 1: something that a lot of people depend heavily upon, Like lawyers, Um, So,
Speaker 1: I mean, it's it's true, it's true. So, but it's
Speaker 1: it's an incredibly complex system, and it works in a
Speaker 1: very different way than your classic computer system. Now, one
Speaker 1: thing I want to say in defensive this idea is
Speaker 1: that even if the brain is very complex, if we
Speaker 1: can simulate the brain, I can't really see any reason
Speaker 1: why a machine shouldn't go way beyond the brain. Yes,
Speaker 1: the brain is limited by all kinds of external factors
Speaker 1: like you know, the size of the head when you
Speaker 1: need to give birth and things like that, and competing
Speaker 1: with other organs for developing resources. I think a lot
Speaker 1: of objections to this are not based on it's impossible.
Speaker 1: I think most people who object to the idea of
Speaker 1: of simulating the brain aren't saying this is something that's
Speaker 1: never going to happen. They're saying this is something that
Speaker 1: if it happens, it's going to happen a really long
Speaker 1: time from now. Yeah, the more optimistic neuroscience people that
Speaker 1: I've seen talk about this have estimated at least a
Speaker 1: hundred years, like absolutely crazy, minimum of I don't even
Speaker 1: understand what's happening anymore, is a hundred years. Because if
Speaker 1: you even look at IBM S Watson, which is one
Speaker 1: of the great examples of artificial intelligence, that we can
Speaker 1: talk about today. You know, that's the IBM computer that
Speaker 1: went on Jeopardy defeated the two former Jeopardy champions. Seem
Speaker 1: to be really, really smart. It was relying on thousands
Speaker 1: of processors running at an incre dorble speed in order
Speaker 1: for it to even compete at that level. And it
Speaker 1: was it was a fairly specific, uh kind of task.
Speaker 1: I mean, yeah, you had you had the wonderful idea
Speaker 1: of this is going to encompass all human knowledge because
Speaker 1: you never know what the the categories are going to be.
Speaker 1: But it still was specifically to compete at Jeopardy, not
Speaker 1: to hold a conversation and try and pass the Turing
Speaker 1: test for example. Um, if for us to have a
Speaker 1: fully functioning mind, not just a brain, but a mind,
Speaker 1: and looks like it's going to have to be even
Speaker 1: more complicated than what Watson was. And it's not just
Speaker 1: the hardware that we have to worry about again, it's
Speaker 1: the software. If the software isn't sophisticate enough in uh,
Speaker 1: in the job of simulating the pathways that are in
Speaker 1: the brain, you can't really hope to simulate an organic mind.
Speaker 1: You might be able to come across and create some
Speaker 1: other form of mind that we have never encountered. I mean,
Speaker 1: that's still a possibility, and it's it's fascinating and scary
Speaker 1: all at the same time. But it's not going to
Speaker 1: be the same as an organic mind unless you're able
Speaker 1: to really create an insanely sophisticated piece of software running
Speaker 1: on an equally insane sophisticated piece of hardware. So anyway,
Speaker 1: that's my own personal objection. So I think you already
Speaker 1: see where my mind goes. But next we have a
Speaker 1: we have Verned again. We have our science fiction author
Speaker 1: and mathematician um and he said that he would be
Speaker 1: surprised if the Singularity doesn't show its head around twenty thirty.
Speaker 1: So he's even more aggressive in his timeline than Kurtswile is.
Speaker 1: That is sixteen years away. It's hard to imagine it
Speaker 1: was only a couple of years ago that someone talked
Speaker 1: to him and asked him again, like do you want
Speaker 1: to revise that? And he says, I stand by it.
Speaker 1: I guess as well. At a certain yeah, you know,
Speaker 1: you're like, either it happens or it doesn't. I mean,
Speaker 1: so it's I guess it's at some point you just say, well, well,
Speaker 1: we'll just wait and see. Although I do want to
Speaker 1: say that his concepts of the singularity were largely inspired
Speaker 1: by a mathematician by the name of I Jake good Um,
Speaker 1: who is writing a lot about the intelligence explosion back
Speaker 1: in the nineteen sixties. So so you know, Verner. Verner
Speaker 1: might be a little bit on the fantastical side. The
Speaker 1: arguments say aggressive, but as singularity is concerned, but his
Speaker 1: but his concepts are certainly based on mathematical concepts. Right though.
Speaker 1: He's great fun to listen to. There's an interview that
Speaker 1: Wired did with him a few years back. If you
Speaker 1: go and read that, he's just, uh, he seems to
Speaker 1: have this great fluidity talking about issues like this. A
Speaker 1: published science fiction writer. I mean, all the people I
Speaker 1: know who are published science fiction writers are the most
Speaker 1: amazing people in the world. High dad. Uh. Then we've
Speaker 1: got Alizar yet Kalski. Yeah, he's um someone that was is.
Speaker 1: I always found it fascinating because of his thought experiment,
Speaker 1: which we'll talk about in another episode. Maybe we've already
Speaker 1: talked about it. It's our friendly AI episode. Right. He's
Speaker 1: known in this field of of AI and sort of
Speaker 1: cautioning in the future of AI and discussing how to
Speaker 1: make it safe. Yeah. Yeah, he's particularly concerned that the singularity,
Speaker 1: I mean A will occur, but but B will be
Speaker 1: a species extinction level event and uh, and so he's yeah,
Speaker 1: working towards creating strategies for a sustainable singularity, right, which again,
Speaker 1: very hard to imagine if you're talking about in a
Speaker 1: point where you can't really predict what happens next, I mean,
Speaker 1: just alone, how do you prepare for something that's unpredictable.
Speaker 1: Also interested in creating the idea of friendly artificial intelligence
Speaker 1: is Nick Bostrom. Yeah. He also again, anyone who wants
Speaker 1: to prepare for a friendly kind of approach to this,
Speaker 1: you know, you kind of have to say this person
Speaker 1: is at least somewhat convinced that it's actually gonna happen.
Speaker 1: I mean, you wouldn't have a conversation about preparing for it.
Speaker 1: I mean, we're it's always better to prepare for something
Speaker 1: and not have it happened than to not prepare and
Speaker 1: it happens anyway. Yeah, I'd agree with that last part.
Speaker 1: I could say that you could be very interested in
Speaker 1: preparing for safety in the case of the singularity without
Speaker 1: being especially concerned that it's very likely. I'm just not
Speaker 1: sure how many people would actually put forth the effort,
Speaker 1: you know, I just knowing just knowing humans the way
Speaker 1: I do. But well, anyway, he's given a prediction, right, Yeah,
Speaker 1: he's a director of the Future of Humanity Institute. Boy,
Speaker 1: that's a heavy burden in it if you're the director
Speaker 1: for the Future of Humanity Institute, Like, so, what's the
Speaker 1: future of humanity? Look, I'm working on it, Okay, back off,
Speaker 1: all right, but he was quoted as saying that there's
Speaker 1: less than a fifty percent probability that will develop some
Speaker 1: sort of super intelligence by twenty thirty three. So this
Speaker 1: sort of contradicts what Werner's prediction was. Assuming that the
Speaker 1: singularity also necessitates some sort of super intelligence, most of
Speaker 1: our definitions do involve super intelligence, intelligence explosion. That tends
Speaker 1: to be the way we think about the singularity. I
Speaker 1: guess you could argue that if you could find some
Speaker 1: other means to constantly have the entire world changing so
Speaker 1: quickly that's impossible to define it without using superintelligence, that
Speaker 1: would also be a singularity. Yeah, and so there have
Speaker 1: been some people who have been sort of pro singularity
Speaker 1: in terms of thinking, it's very likely to happen, but
Speaker 1: at the same time very against it in terms of
Speaker 1: what should happen. Like Bill Joy, co founder of Sun Microsystems.
Speaker 1: He got famous in this line of thinking when he
Speaker 1: published an article in two thousand and Wired magazine called
Speaker 1: why the Future Doesn't Need Us, and it was very
Speaker 1: pessimistic about the role of technology in the future of humanity. Yeah,
Speaker 1: he specifically was worried that we would develop technology that
Speaker 1: would be incredibly destructive and yet really easy to use.
Speaker 1: So imagine the equivalent of the button, right, the whole
Speaker 1: idea of that, the button that you press and it
Speaker 1: launches a nuclear strike against another country. Now imagine that
Speaker 1: essentially a sizeable percentage of the human population has access
Speaker 1: to something that's it's equivalent in being dangerous. Does necessarily
Speaker 1: have to be nuclear, it could be whatever. Saying that,
Speaker 1: you know, as technology gets more advanced, it's giving more
Speaker 1: power to people, and with that, with great power becomes
Speaker 1: great responsibility, and so we have to be very cautious.
Speaker 1: And so he's he's advocated, let's not build those technologies.
Speaker 1: Let's back off and just build the stuff that's going
Speaker 1: to help people, and not the stuff that's gonna white
Speaker 1: people out, which is easy to say exactly. I mean,
Speaker 1: a lot of the stuff that you build with the
Speaker 1: goal of helping people could eventually be used by accident
Speaker 1: to cause problems. I've built this death scorpion too health
Speaker 1: humanity and not destroy it or you know. I mean,
Speaker 1: if if you create an AI that wants to make
Speaker 1: people happy, um, but as it turns out, what makes
Speaker 1: a lot of people happy is exploding other people's skulls. Uh,
Speaker 1: got problems. That would be a bad example of technology
Speaker 1: you want to push. Let's just say you create an
Speaker 1: AI that's designed to maximize the output of penicillin, but accidentally,
Speaker 1: what it does by maximizing the output of penicillin is
Speaker 1: it harvests people's bodies in order to turn them into
Speaker 1: the constituents it needs to make penicilla. So this is
Speaker 1: like Outbreak plus the matrix. I got it. Okay, Well,
Speaker 1: those are the folks, they're they're more obviously, there are
Speaker 1: a lot of people who fall on the side of
Speaker 1: the Singularity is a thing. It's definitely gonna happen. It
Speaker 1: may be good, it may be bad, but it's coming.
Speaker 1: But they're not the only ones in this discussion. Oh yeah,
Speaker 1: there's a whole list of critics who say that either
Speaker 1: it's not possible at all or that it's very, very
Speaker 1: not near. Let's talk about the skeptics. So so, we
Speaker 1: had the co founder of Sun Microsystems in one corner.
Speaker 1: In the other corner, we got a co founder of Microsoft,
Speaker 1: Steve Balmer. No, not that Steve Bomber was not a
Speaker 1: co founder. He was an early employee, but he was
Speaker 1: the in the sales department. I can talk all about
Speaker 1: Steve Bomber if you really want me to know what
Speaker 1: we're talking about. Paul Allen, Now I want to know
Speaker 1: what Steve Bomber. What about Bomber is a robot? Come on,
Speaker 1: we know this. Developers, developers, developers. He was on that
Speaker 1: loop for a long time. Took a while to get
Speaker 1: him out of that. Okay, what about Paul Paul Alan
Speaker 1: his argument which he made with along with another computer
Speaker 1: scientists expert, He posted a an article that was kind
Speaker 1: of a rebuttal of of Kurtzwild. Yeah, and he said that, Yeah,
Speaker 1: Kurtswell ended up having a rebuttal of the rebuttal. But
Speaker 1: Kurtswall strikes me as someone who who rarely um rarely
Speaker 1: resists the urge to have the last word. But uh,
Speaker 1: maybe we'll find out for sure podcast His Life. No,
Speaker 1: but Alan said that that if such a thing as
Speaker 1: the Singularity is going to happen, it's a long, long,
Speaker 1: long way off, And he made a lot of the
Speaker 1: arguments that I had kind of alluded to earlier. This
Speaker 1: idea that creating any kind of of machine intelligence that
Speaker 1: has intelligence in the way we think of intelligence, like
Speaker 1: on human level or beyond, is so far in the
Speaker 1: future as to be kind of a meaningless discussion at
Speaker 1: the moment. Yeah, one thing that it brings up to
Speaker 1: think about the software limitations is that it's not just computers,
Speaker 1: Like you can make the most powerful computer that you
Speaker 1: could ever have, and if it didn't have some kind
Speaker 1: of guidance, if it didn't have instructions on how to
Speaker 1: create intelligence, I don't know how you would achieve intelligence.
Speaker 1: Could just run Tetris way better than the other computers
Speaker 1: could run Tetris. Yeah, now that that's kind of Paul
Speaker 1: Allen's argument, And in fact, there's the goofy, snarky fake
Speaker 1: law saying Moore's law. You know you have right right,
Speaker 1: Moore's law says that technology will increase, it will double
Speaker 1: in power, right every two years, every two years or so,
Speaker 1: and pages Law in in contrast says that software will
Speaker 1: bloat twice as much, twice as much every two years. So,
Speaker 1: in other words, your performance from one computer to flash
Speaker 1: forward two years in the future, the next computer ends
Speaker 1: up looking the same because the software ends up expanding
Speaker 1: to take advantage of all those up all those those
Speaker 1: capabilities of your computer has, but not in a way
Speaker 1: that would necessarily strike you as uh as as noticeable.
Speaker 1: Like we just think, well, this, this computer runs this
Speaker 1: program just fine, but it's not software. It gets twice
Speaker 1: as slow for every unit of uh yeah, computer getting fasterware.
Speaker 1: So yeah, you preserve the stats quo. It doesn't you
Speaker 1: don't end up with this world of magical computers that
Speaker 1: can suddenly do everything. Although you know that's clearly a
Speaker 1: very tongue in cheek approach, because if you do look
Speaker 1: around us the it's it's undeniable to say that the
Speaker 1: computers of today can run programs that are far more
Speaker 1: sophisticated than what like I mean, I think back to
Speaker 1: my very first computer, which was an Apple to E,
Speaker 1: and it would just fizzle and explode if I were
Speaker 1: to show it some of the stuff I can run
Speaker 1: on my phone these days. But the point is kind
Speaker 1: of is kind of made where the software sophistication isn't
Speaker 1: increasing at the same uh space as More's law and
Speaker 1: I and I do have to say that sometimes web
Speaker 1: page is load not quite as slow as they did
Speaker 1: when I was on dial up, but but approaching that
Speaker 1: do to say ad software? Okay, So we had a
Speaker 1: sci fi author in the pro corner, do we have
Speaker 1: any sci fi authors in the anti corner? Charles Stross.
Speaker 1: He believes that the development in a I will be
Speaker 1: focused on creating reactive technologies and environments that respond to
Speaker 1: our needs, rather than intelligent environments that anticipate things make
Speaker 1: decisions on its own. I mean, even these reactive environments
Speaker 1: could anticipate our needs, but they're doing so in a
Speaker 1: quote unquote dumb way, not a smart way, right. I think?
Speaker 1: Is this sort of an argument against what's called a
Speaker 1: generalized artificial intelligence or artificial general intelligence, meaning simulating the
Speaker 1: whole way a human brain works, with the total freedom
Speaker 1: and range of thought, as opposed to a limited AI
Speaker 1: that's really good at being like a human brain at
Speaker 1: one thing. Yeah, sure, Sure, it's the difference between a
Speaker 1: video game character that can competently follow you around and
Speaker 1: shoot your enemies versus a video game character, you know,
Speaker 1: taking that same grunt and having it cookie breakfast. It's right.
Speaker 1: Or to put it in in terms of like a
Speaker 1: smart home. You know, you might have a smart thermostat
Speaker 1: which can, based upon a certain algorithm, anticipate what temperature
Speaker 1: you're gonna want your house, but it's not going to
Speaker 1: be able to do everything else that you need to do.
Speaker 1: You have all these other little elements, and together they
Speaker 1: can create an entire environment that seems really reactive and intelligent,
Speaker 1: but ultimately it's not really smart. It's just all following
Speaker 1: very specific sets of rules and not necessarily in a
Speaker 1: coordinated way. Just integrated stupidity. Yeah, which I think that
Speaker 1: that should be the new industry buzz term. I think
Speaker 1: that they should be calling, like nest to the integrated stupidity.
Speaker 1: Pretty sure. I pledged to a frat that had that
Speaker 1: as motto. At any rate, Uh, go dogs at any rate.
Speaker 1: Next we have Ernest Davis, who's a computer scientist with
Speaker 1: New York University, and Davis's argument is that the human
Speaker 1: brain and intelligence is far more complex than computer scientists
Speaker 1: tend to give it credit, that it is something that
Speaker 1: is non trivial, that we have barely even scratched the surface.
Speaker 1: That even to have a conversation about intelligence usually requires
Speaker 1: you to focus in on a specific aspect of intelligence
Speaker 1: rather than just talking about general intelligence, because it's just
Speaker 1: too broad a topic. Right, So this is sort of
Speaker 1: the other side of the coin that we already talked
Speaker 1: about with respect to Hans more Evc. Right, So maybe
Speaker 1: there's nothing magic in the brain. It's not we're not
Speaker 1: unable in principle to reproduce it. It's just so hard, yeah, right, right.
Speaker 1: And and the fact that some a lot of futurists
Speaker 1: have really good understanding of how computers work, but a
Speaker 1: really poor understanding of biology is is kind of an
Speaker 1: issue here. One. I don't think it was this guy,
Speaker 1: but but I did read one neuroscientist who was talking
Speaker 1: about the genome. I mean, because you know, people have said, like,
Speaker 1: so we've uncoded the genome, so we know how to
Speaker 1: build a brain, so therefore we can build an intelligent
Speaker 1: and it's like, no, no, no, that's not what that does.
Speaker 1: If I gave that same person just a list of
Speaker 1: ingredients and say Lucky Charms cereal, and so you now
Speaker 1: have the ingredients needed to make Lucky Charm cereal, go
Speaker 1: and make it for me. I doubt that they would
Speaker 1: come back with a bowl that looks anything like Lucky
Speaker 1: Charm cereal. It wouldn't even be ingredients. You'd be I
Speaker 1: guess giving them a list of atomic ratios. That's true,
Speaker 1: I could go. I was, I was oversimplifying, just to
Speaker 1: show the the how absurd the argument is. But true,
Speaker 1: it's even more absurd than that you need to make
Speaker 1: some carbohydrates out of them, and and and even if
Speaker 1: you build, even if you build that wet where Again,
Speaker 1: like we said earlier, the emergence of intelligence from that
Speaker 1: wet where is a whole other question. Now, Joe, I
Speaker 1: know you spent some time looking over our next our
Speaker 1: next critic Lanier here who uh as, as you pointed out,
Speaker 1: looks like the villain and iron Man two. Yeah, he
Speaker 1: does from certain angles. The computer scientist and and vr
Speaker 1: iluminary jarn Linear looks like Mickey Rourke in Iron Man two.
Speaker 1: This is true. It's a white guy with dreads. I mean,
Speaker 1: he's he's definitely got to look going. Uh he's and
Speaker 1: also really intelligent dude. Uh you know again vr illuminary
Speaker 1: like this is basically the guy who popularized the term
Speaker 1: virtual reality. He's had a lot to do in the
Speaker 1: industry down ever since. But he has some really interesting
Speaker 1: things to say also about the singularity. He he calls
Speaker 1: the entire concept of it cybernetic totalism. He refers to
Speaker 1: it as a fanatic ideology and compares it to Marxism
Speaker 1: his His arguments here are that the idea of the
Speaker 1: singularity is flawed because brains and bodies and culture are
Speaker 1: actually pretty unlike computers. Um. Also because Darwin's theories of
Speaker 1: evolution don't apply perfectly to culture the way that a
Speaker 1: lot of futurists tend to speak of them as um.
Speaker 1: And then also that whole thing with Moore's law that
Speaker 1: we were talking about before. He He furthermore goes on
Speaker 1: to say that the very concept of the singularity is dangerous.
Speaker 1: This goes back to his comparison to Marxism um, because
Speaker 1: he says that that the concept of the singularity denies
Speaker 1: scientific skepticism, strokes the the the ego of the general
Speaker 1: computer scientists and um, furthermore encourages and kind of unrealistically
Speaker 1: rosy sense of predestination, which which all of which he
Speaker 1: thinks could lead to like possibly apocalyptic separation of the
Speaker 1: haves and have not the technological and economic Yeah. Sure,
Speaker 1: I mean that that's one of those ideas about trans humanism,
Speaker 1: is that if this ever does come to pass, we
Speaker 1: can easily imagine that if such a thing or is possible,
Speaker 1: a very elite few are going to have access to
Speaker 1: it initially. So assuming we've gotten past those testing stages
Speaker 1: where we've had the people stop exploding when we put
Speaker 1: computers in them and now they're fine, Um, then you
Speaker 1: could imagine that really it's just going to be the
Speaker 1: super duper rich people who are going to have access
Speaker 1: to this, which makes them even more further distanced from
Speaker 1: the rest of us. And uh, yeah, there there are
Speaker 1: a lot of science fiction stories that are predicated upon this.
Speaker 1: In fact, there are several that movies that came out
Speaker 1: over the last like twenty four months that have the
Speaker 1: same premise. And I love his quote that arrogance is
Speaker 1: always a bad strategy and science and philosophy, I suppose
Speaker 1: it's fine kind of again, a little backhanded diss saying
Speaker 1: that you know this, this whole concept of the singularity
Speaker 1: is more in the world of philosophy than science. Okay,
Speaker 1: speaking of philosophy, we've talked about the philosophical question before.
Speaker 1: Then this is slightly separated from the idea of the
Speaker 1: super intelligence in terms of behavior and capabilities. But is
Speaker 1: it possible that this machine or this set of machines
Speaker 1: or what where it is the super intelligent framework could
Speaker 1: achieve consciousness or the experience of mind and the way
Speaker 1: we think of it. So this is the idea of
Speaker 1: a machine knowing that it can think, knowing that it
Speaker 1: is what it is, and it is able to make
Speaker 1: uh decisions based upon this information. And we have John
Speaker 1: Searle who's another critic of the singularity. This name might
Speaker 1: sound familiar to you guys. We talked about him about
Speaker 1: the in the Chinese room experiment discussion we had in
Speaker 1: a previous podcast. So this is the experiment where you say,
Speaker 1: imagine that you're sitting inside a room. Uh, there's a
Speaker 1: single door and it's got a little slot and it
Speaker 1: occasionally someone shoves a piece of paper through the slot
Speaker 1: and when you pick it up, it's got a Chinese
Speaker 1: character written on it, but you don't speak or read
Speaker 1: or understand Chinese at all. What you do is you
Speaker 1: then you didn't consult an enormous book that gives instructions
Speaker 1: on what to do. When you get a sheet of
Speaker 1: paper that has any particular Chinese character on and you
Speaker 1: find the one that corresponds to the sheet of paper
Speaker 1: that was sent through the door, you end up scribbling
Speaker 1: something else down a sheet of paper. You push that
Speaker 1: back through the slot. Then the question is do you,
Speaker 1: as the person inside the room, actually understand Chinese? And
Speaker 1: people would say, well, no, you don't understand it. You're
Speaker 1: following these instructions, but you don't have any comprehension of
Speaker 1: what it is you're doing apart from when this happens,
Speaker 1: do this other thing. And so his argument is that
Speaker 1: you have to extend the same thing to machines that
Speaker 1: they don't understand what they're doing. They're they're carrying out
Speaker 1: instructions and that's it. The idea is that instruction based
Speaker 1: computation can't by itself account for the idea of understanding
Speaker 1: right now. Of course, we've also talked about criticisms of
Speaker 1: that particular thought experiment. The idea that if you take
Speaker 1: the system as a whole, as opposed to just the
Speaker 1: person inside the room, then would you say it understands Chinese. So,
Speaker 1: in other words, you're taking into consideration the book of
Speaker 1: instructions and the entire apparatus that's involved. Maybe then you
Speaker 1: would have a more questionable approach, like could you say
Speaker 1: that that understands Chinese. Maybe not in the same way
Speaker 1: as a native speaker would, but maybe in a way
Speaker 1: that is semi analogous perhaps, uh, as opposed to the
Speaker 1: person in sight, because you could say, well, just think
Speaker 1: of the person is a microchip. That's not the full system,
Speaker 1: that's just one part of the system. Okay. Anybody else
Speaker 1: critical of this consciousness question? No, everyone else loves it. Well,
Speaker 1: Roger Penrose doesn't. He's a physicist and professor of mathematics
Speaker 1: at Oxford, and he's thinking that we can't duplicate consciousness
Speaker 1: and machines because it depends upon non computational physical processes
Speaker 1: which we don't yet fully understand. So again, this is
Speaker 1: another approach of saying the human brain is so complex
Speaker 1: and we only barely know anything about it that we
Speaker 1: can't hope to simulate it or or even create another
Speaker 1: mind based upon that little bit of information we have.
Speaker 1: We're just miles and miles away, so that if there
Speaker 1: ever does come a time where we can do this,
Speaker 1: it's going to require a new understanding of physics that
Speaker 1: we do not currently possess. And because it's going to
Speaker 1: require that and we don't, you know, you can't say like, oh,
Speaker 1: we've got a timeline in eight months, we're going to
Speaker 1: understand this. You can't say that. So he says, it's
Speaker 1: it's impossible to predict. It's probably not going to be
Speaker 1: in the near future. Yeah. So I think something's interesting,
Speaker 1: which is that despite the fact that we've got lots
Speaker 1: of really really smart people on both sides of this debate,
Speaker 1: people say the singularity, it's both possible and near, and
Speaker 1: people who say possible, but not anytime soon, and then
Speaker 1: people who say not possible. Despite all that, you can
Speaker 1: see very clearly people are very quick to jump into
Speaker 1: one camp or the other on whether or not this
Speaker 1: is a good thing. Have you noticed this that you
Speaker 1: just dive right in, Oh, yeah, utopia, you know, just
Speaker 1: this kind of Curtsewile kind of it's great vision. Probably
Speaker 1: even more common is the dystopian idea that oh yeah, okay,
Speaker 1: it means we will be destroyed. Yeah, I I mean
Speaker 1: my actual responses, there's no assuming that we really do
Speaker 1: in our world where we cannot predict what's going to
Speaker 1: happen next, then you can't predict whether it's going to
Speaker 1: be good or bad exactly. That That's my point. What
Speaker 1: I was trying to point out there was it's it's
Speaker 1: such a hard question about whether or not it will
Speaker 1: happen and what form it will take. How could you
Speaker 1: possibly predict without knowing those things, the kinds of effects
Speaker 1: it will have. Now, I would say that it's very
Speaker 1: smart to be cautious. Sure, oh sure, sure, Well, and
Speaker 1: it's sort of like the old joke of of you
Speaker 1: don't know, like that comma that you could get in
Speaker 1: from a terrible accident might be the happiest time of
Speaker 1: your life. Uh. And and so you should open up
Speaker 1: door number three because I got door number one is
Speaker 1: a goat behind it. Okay, So no one else is
Speaker 1: a big fan of let's make a deal? All right, Fine,
Speaker 1: that's fine. I know about the let's make a deal problem, yes,
Speaker 1: which we should probably do a podcast on at some
Speaker 1: point because it's an interesting problem future of it. It's
Speaker 1: it's a it's an awesome it's an awesome thought experiment.
Speaker 1: But the uh, you know what I was going to
Speaker 1: say is that, yeah, you can't predict it. I I
Speaker 1: think one safe prediction you could make, assuming again, that
Speaker 1: would go to the The more fantastical version of the
Speaker 1: singularity is that human beings would ultimately cease to exist
Speaker 1: as we understand them today. It doesn't mean that the
Speaker 1: species would be wiped out and that no, no, uh,
Speaker 1: other kind of remains of humans would ever know exist.
Speaker 1: It would just be machines from there on out. But
Speaker 1: they might be transformed in some fundamental way where we
Speaker 1: wouldn't really refer to them as human beings anymore. Human
Speaker 1: beings would be something we would use as a term
Speaker 1: to talk about those guys who lived before the singularity
Speaker 1: A right, that whole trans human space baby, super advanced
Speaker 1: X men kind of concept. Yeah, yeah, well yeah. People
Speaker 1: take the idea of the singularity and then they attribute
Speaker 1: all different kinds of effects. You know, it'll mean immortality
Speaker 1: or near immortality. Oh, we'll be able to live forever.
Speaker 1: And then the next big engineering problem will be how
Speaker 1: do we stop the heat death at the universe so
Speaker 1: that we don't have to die then, or there will
Speaker 1: be people who talk about how it means the end
Speaker 1: of work, say, it's going to lead to this this
Speaker 1: post scarcity world where there's absolutely nothing we need, right,
Speaker 1: this idea of going into sort of a Star Trek
Speaker 1: future where everything's idea like and no one has to
Speaker 1: no one has to work, they can pursue whatever whatever
Speaker 1: they want to do. Not saying that it wouldn't mean
Speaker 1: those things. But I do think it's interesting that people
Speaker 1: are using this as as almost kind of a fantasy fulfillment.
Speaker 1: Oh sure, and I do I don't think that we
Speaker 1: said earlier. But but kurtswhile UM seems very personally motivated
Speaker 1: from a really intense fear of mortality, of its own mortality, UM,
Speaker 1: I think I think that's not hidden. He's fairly explicit
Speaker 1: about the fact that he wants to extend his life,
Speaker 1: Oh absolutely, and and that that comes from the death
Speaker 1: of I think his father at a relatively young age. Yeah,
Speaker 1: he has UM. He has spoken many times on his
Speaker 1: hope that in within his lifetime obviously that we will
Speaker 1: have UH either conquered death or if not conquered it
Speaker 1: at least extended lie indefinitely. Uh, And that he thinks
Speaker 1: that that sort of breakthrough is like the Singularity right
Speaker 1: around the corner. Now, obviously, if that breakthrough does happen,
Speaker 1: or if it comes part and parcel with the Singularity,
Speaker 1: then we will live to see this eventually come to pass.
Speaker 1: I mean, ultimately, I would say that if the Singularity
Speaker 1: is indeed a possibility, it will happen. So if it
Speaker 1: is possible, it will happen, because there's going to be
Speaker 1: someone who's going to do that next step that pushes
Speaker 1: it into that world. It's only if it's not possible
Speaker 1: that we won't see it happen. I don't think there's
Speaker 1: gonna be a future we might not humans, humans not
Speaker 1: not we as in the three people in this room.
Speaker 1: I'm not gonna see it happen because I'll be washing
Speaker 1: my hair that day. I keep it in in a box.
Speaker 1: It's in my desk at home, take it out occasionally,
Speaker 1: try and wiggle out of it. I know exactly what
Speaker 1: you had in mind. You're like Kurts of all. You
Speaker 1: think that the Singularity is going to give you hair,
Speaker 1: you know, a long, beautiful hair, shining streaming. Yeah, although
Speaker 1: actually that that brings up a good point. I mean,
Speaker 1: it's not like any of us are not personally motivated
Speaker 1: to see this kind of thing happen. It's I mean,
Speaker 1: it's a beautiful idea, and I totally understand that the
Speaker 1: seduction of that idea. Sure. Yeah, now, it's just when
Speaker 1: you start looking at you know, it is amazing the
Speaker 1: stuff we can do today compared to the stuff that
Speaker 1: we could do twenty years ago. But I don't know
Speaker 1: that it's so amazing that it has us on track
Speaker 1: for this incredibly aggressive timeline that people like Werner and
Speaker 1: Kurtswile have in mind of. You know, by twenty we're
Speaker 1: going to have this uh, this this world that we
Speaker 1: can't even begin to describe right now. Certainly, although if
Speaker 1: those kind of aggressive timelines are leading to people putting
Speaker 1: real thought into it and and real caution into it,
Speaker 1: then I think that it's completely worthwhile to have these
Speaker 1: kind of blowhard standing at the front of the stage.
Speaker 1: Of course, the caution is what we're want you to
Speaker 1: talk about in our next podcast. Yeah, yeah, nice lead in. Yeah,
Speaker 1: So guys, stay tuned because we're going to talk all
Speaker 1: about superhuman intelligent artificial intelligence and how it will try
Speaker 1: to kill you. That will be our next episode. And
Speaker 1: if you guys have suggestions for future episodes of Forward Thinking,
Speaker 1: you should get in touch with us. Let us know
Speaker 1: what you think, tell us what you love about the show,
Speaker 1: tell us what excites you about the future. You can
Speaker 1: email us our addresses f W Thinking at Discovery dot com,
Speaker 1: or drop us a line on Google Plus, Twitter or Facebook.
Speaker 1: Our handle is f W Thinking and we will talk
Speaker 1: to you again really soon. For more on this topic
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