Speaker 1: I feel like an old man whenever I buy a
Speaker 1: new computer. I mean, why does my laptop need sixty
Speaker 1: four gigabytes of memory? When I learned to program on
Speaker 1: a PC that had twenty kilobytes? No joke. Kids these
Speaker 1: days don't understand how hard we had it back in
Speaker 1: the day. Right, But it's also a nice feeling. It
Speaker 1: tells me that we're making progress and that's good. It's
Speaker 1: creating new worlds and new ways of life. It's literally
Speaker 1: saving lives by accelerating science. That's all great stuff, right,
Speaker 1: But how long can it go on? What is the
Speaker 1: engine of this exponential growth in computing power? And can
Speaker 1: we count on it to take us to the stars,
Speaker 1: to cure cancer and to develop self driving toothbrushes. Today
Speaker 1: we'll dive into the physics underlying this trend and ask
Speaker 1: whether there are fundamental limits that could block us from
Speaker 1: achieving our dreams. And we'll talk about whether there's danger
Speaker 1: and assuming technology will solve all of our problems. Welcome
Speaker 1: to Daniel and Kelly's Extraordinary Universe.
Speaker 2: Hello. I am Kelly Wiener Smith. I study parasites and space,
Speaker 2: and I realized when we were starting to do this
Speaker 2: episode that I wasn't one hundred percent clear on what
Speaker 2: mores Law meant exactly.
Speaker 1: Hi, I'm Daniel. I'm a particle physicist and I've been
Speaker 1: programming computers for more than forty years. They get faster
Speaker 1: and I get slower.
Speaker 2: Oh you're not slowing down yet, Daniel, you stab.
Speaker 1: So my question for you today, Kelly, is what was
Speaker 1: your first computer? Let's age Kelly.
Speaker 2: Okay, So later when we talked to Adam Becker in
Speaker 2: our interview, he mentions that there was a while there
Speaker 2: where folks wouldn't get a computer because you'd wait as
Speaker 2: long as you could, because the computers kept getting so
Speaker 2: much better so quickly that if you could wait, your
Speaker 2: computer would be much better. Yeah, and so my family
Speaker 2: waited way too long. We didn't get one until I
Speaker 2: was in like high school, and I know, and I
Speaker 2: don't even remember what it was. But in the meantime
Speaker 2: I had to write my essays on like it was
Speaker 2: like a brother typewriter, but it also had a little
Speaker 2: electronic screen, and so I could very slowly and laboriously
Speaker 2: click through my essays and then I would print it
Speaker 2: and something would be wrong. It would take me forever
Speaker 2: to find where the error was. It was very annoying.
Speaker 2: But what about you, did you have like the first
Speaker 2: Apple computer? Ever?
Speaker 3: Oh?
Speaker 1: Apple was way too advanced. I go way before that.
Speaker 1: What My first computer was a Commodore VIC twenty, which
Speaker 1: I think had twenty kilobytes of RAM, and we stored
Speaker 1: stuff on an audio tape, you know, like you write
Speaker 1: a little program and then you'd stored on these cassette
Speaker 1: tapes that you could later listen to and like, ooh
Speaker 1: what does that sound? So yeah, we were very very early.
Speaker 1: In fact, I remember hanging out with my dad in
Speaker 1: grad school while he was doing his research and he
Speaker 1: was literally feeding punch cards into those punch cards machines.
Speaker 1: So I feel like I've personally experienced a huge fraction
Speaker 1: of the transformation of computers into the basically supercomputers we
Speaker 1: have today. I mean, my smartphone is so much more
Speaker 1: powerful than anything my dad ever used in his research.
Speaker 2: That is absolutely amazing. I didn't even know that we
Speaker 2: were storing data on like cassette tapes. Oh yeah, that's
Speaker 2: amazing to me.
Speaker 1: Yeah, before magnetic floppies for sure.
Speaker 2: So when you like are using your are you a
Speaker 2: MacBook guy?
Speaker 1: I am? Yeah.
Speaker 2: It's like when you're using your Mac Do you every
Speaker 2: day think I am so lucky I'm not doing this
Speaker 2: on punch cards or you just do you take it
Speaker 2: for granted? Now?
Speaker 1: I think it's awesome. It's incredible. I mean every time
Speaker 1: I get a new MacBook, I'm like, while, this drive
Speaker 1: is ten times bigger than anything I've ever seen, and
Speaker 1: the memory is just shocking. And it's also then incredible
Speaker 1: to me how rapidly our computational ambitions grow. You know,
Speaker 1: my group does a lot of computation, and we're basically
Speaker 1: limited by computation, and so every time we get more
Speaker 1: powerful computers, we scale up our ambitions and solve bigger,
Speaker 1: harder problems, and so we're always at the edge of
Speaker 1: what the computers can do, right, Like, we have an
Speaker 1: infinite number of questions we could ask with harder computers.
Speaker 1: So yeah, I'm in awe of the MacBook, not just
Speaker 1: because it's so much more powerful than anything I've used,
Speaker 1: but it's so reliable. I mean, I spend hours and
Speaker 1: hours a day in front of this thing. It almost
Speaker 1: never gives me problems. So yeah, it's incredible. What engineers
Speaker 1: have provided it is incredible.
Speaker 2: And today we're going to talk about one way in
Speaker 2: which that incredible ability has been expanded, which has to
Speaker 2: do with Moore's Law, which I thought was about how
Speaker 2: much data you can store on your computer, and I
Speaker 2: think it's much more than that.
Speaker 1: You're right, it's much more than that. It's also about
Speaker 1: how things are growing over time and how long that
Speaker 1: will continue. And there's this lore about Moore's Law which
Speaker 1: is permeated Silicon Valley and broader culture. So in a minute,
Speaker 1: we're gonna also talk to Adam Becker about how this
Speaker 1: has impacted philosophy and politics and policy and how it
Speaker 1: might affect our future. But first we wanted to know
Speaker 1: how long people thought Moore's Law might continue to make
Speaker 1: all of our computers faster. So I went out there
Speaker 1: and I talked to our group of volunteers. Here's what
Speaker 1: they had to say about the future of Moore's law.
Speaker 1: So I'll give it six years and then I'm gonna
Speaker 1: sell my nvidious stock. But quand computing will change the game.
Speaker 1: We are restricted by things like housmow.
Speaker 4: We can make stuff, so I think it's not true anymore.
Speaker 4: My first thought was to sign no, but I know
Speaker 4: very little bit quantuine computing. I would say until the
Speaker 4: computer speed, which just be the light maybe ten years,
Speaker 4: another good decade or so.
Speaker 3: My understanding is that it's already done.
Speaker 1: I don't think we are doubling in raw processing speed.
Speaker 4: In my understanding, Moore's law kind of slowed down for
Speaker 4: laptop desktop chips a number of years back, but has
Speaker 4: continued with mobile just because they were a little behind.
Speaker 4: But then you also have graphics and neural processing units
Speaker 4: that power our AI platforms of today. So can we
Speaker 4: go into the future. I think we can go for
Speaker 4: a number more years, given the innovations in transistor stacking.
Speaker 2: I thought Moore's law had to do with cost decreasing
Speaker 2: as speed increased. We do seem to be close to
Speaker 2: a tipping point with electrons being too large for the
Speaker 2: tiny circuitry. However, it seems that optical circuitry might be
Speaker 2: a good replacement for that.
Speaker 1: They're currently reaching the lower limits of workability before they
Speaker 1: start reaching quantum effects. With silicon.
Speaker 3: We are getting closer to the particle level and that
Speaker 3: stops us.
Speaker 1: Honestly, I thought it had already stopped. So do you
Speaker 1: think these are optimistic or pessimistic?
Speaker 2: I mean I think they're realistic, which seems to be
Speaker 2: the option that always gets left out. So I think
Speaker 2: there were a lot of people who said, you know,
Speaker 2: I thought we've already reached the limits. So we're getting
Speaker 2: close to reaching the limits. And I'll admit that I
Speaker 2: did not realize we were getting close to reaching the limits.
Speaker 2: But it seems like a lot of our listeners are
Speaker 2: on top of this trend.
Speaker 1: Yeah, and so we're not giving financial advice. So I
Speaker 1: won't tell you whether or not to buy or sell
Speaker 1: in Vidia stock. But you know, sometimes I wonder about
Speaker 1: these tech companies because their stocks also seem to follow
Speaker 1: Moore's law, Like, how can Google just keep getting more valuable?
Speaker 1: I keep missing out on buying Google.
Speaker 2: I can tell you that if you can make a
Speaker 2: time machine, one of the first things you should do
Speaker 2: is go buy in VideA and Google stuff.
Speaker 1: All right, So let's dig into it. What in the
Speaker 1: end is Moore's law? So Moore's law was something postulated
Speaker 1: by Gordon Moore.
Speaker 2: He has a first name.
Speaker 1: And he was one of the found of Intel, so
Speaker 1: a big dude in like, you know, semiconductors and electronics.
Speaker 1: And he suggested initially that the number of transistors you
Speaker 1: could squeeze onto a chip would double every year. And
Speaker 1: it's a little bit more complicated than that. He also
Speaker 1: was talking about the power usage and the cost, but
Speaker 1: roughly speaking, he was talking about the density of transistors
Speaker 1: on chips getting higher every single year, which means the
Speaker 1: speed of these computers is growing very quickly.
Speaker 2: So transistors are about speed and not storage, or are
Speaker 2: they about both?
Speaker 1: They're about both. The transistor fundamentally is a tiny programmable switch.
Speaker 1: And the reason that computers got small and got fast
Speaker 1: is because we were able to make transistors small and
Speaker 1: make them fast, which allows us to have lots and
Speaker 1: lots and lots of switches in a small area, which
Speaker 1: is what allows the computer to be complex and to
Speaker 1: be fast. And so essentially it's saying we can make
Speaker 1: computers denser every year, and that makes computers faster and
Speaker 1: more powerful.
Speaker 2: Okay, so this has to do with why we went
Speaker 2: from computers that took up entire rooms to something you
Speaker 2: can now stick in your bag and take with you.
Speaker 1: Yeah, exactly, And we'll dig into that in a minute.
Speaker 1: But the history here is that in nineteen sixty five
Speaker 1: More predicted this and then ten years later he revised it.
Speaker 1: He was like, well every year, maybe that's too optimistic.
Speaker 1: Let's go for every two years. And so that was
Speaker 1: the prediction in seventy five, and you'll see that it
Speaker 1: mostly held up until fairly recently. It's sort of an
Speaker 1: extraordinary prediction in that sense, though. You know, anytime there's
Speaker 1: a prediction that holds up, you got to wonder, like, well,
Speaker 1: what were the other predictions this person made, Like you
Speaker 1: just spew predictions constantly, Eventually you're goind of get one Ris.
Speaker 2: Yeah, yeah, well, especially he gave himself another decade to
Speaker 2: like fit the trend line. That was pretty generous to himself.
Speaker 1: But okay, exactly, So let's dick into what a transistor
Speaker 1: is and why it allows computers to be faster, because
Speaker 1: that's crucial to understand why More's law has worked, how
Speaker 1: we've made it work, and whether it's going to work
Speaker 1: in the future. Basically, a transistor is a programmable switch
Speaker 1: like computers operate on digital logic. I have a number
Speaker 1: in the computer, the number four. They store it in binary.
Speaker 1: But to store things in binary you need a physical system.
Speaker 1: But that can store a zero or a one right
Speaker 1: the way you can like write a digit on a
Speaker 1: piece of paper. That's like I'm representing the number four
Speaker 1: by scratching this graphite onto this sheet of paper. I
Speaker 1: want to store things on my computer and zeros and
Speaker 1: ones because binary is the code for computers, and physically
Speaker 1: that means a switch, you know, as you can imagine
Speaker 1: either just like literally like a light switch, but here
Speaker 1: we're doing an electronic switch.
Speaker 2: Okay, And so just to if we switched from using
Speaker 2: transistors to things like DNA to store data or quantum computing,
Speaker 2: could you still apply More's law, like if we switched
Speaker 2: to some other method or is More's law specifically about
Speaker 2: the transistors that we're talking about now, Yeah.
Speaker 1: Great question. You're talking about fundamental changes in how we
Speaker 1: do computing. So currently computing operates on bits, zeros and ones,
Speaker 1: and we're saying those are represented by transistors, which is
Speaker 1: like a physical implementation of that bit. You switch to
Speaker 1: quantum computing, the fundamental element of that is a cubit,
Speaker 1: which isn't necessarily a zero one. It has the probability
Speaker 1: to be in several different states, and so it requires
Speaker 1: a different physical system to model that. We don't use
Speaker 1: transistors or not even like quantum transistors. In fact, transistors
Speaker 1: are already relying deeply on quantum mechanics, so quantum transistor
Speaker 1: is redundant. But yeah, cubit, there's no guarantee that you
Speaker 1: can like build cubits and then build them more densely
Speaker 1: and more rapidly. There's certainly no More's law for quantum
Speaker 1: computing that's a guarantee. And biological computing like DNA is
Speaker 1: super awesome as an idea, but there you have like
Speaker 1: four possibilities, right, DNA is basically base four, and so
Speaker 1: it's a question of like how do you encode numbers
Speaker 1: into DNA? Do you use all four bases? Do you
Speaker 1: group them into two to make binary? The technology is
Speaker 1: fundamentally different, So again you wouldn't expect necessarily further to
Speaker 1: be more solved, but you might get some other law
Speaker 1: which could be better. So but yeah, Mores law reflects
Speaker 1: the details of the technology we're using to represent the
Speaker 1: fundamental element of computing, which is a zero or one,
Speaker 1: and then crucially the logic that operates on those zeros
Speaker 1: and ones.
Speaker 2: Let's get into that logic.
Speaker 1: Yeah, because what you want to do is represent like
Speaker 1: numbers in your computer. I want to put the number
Speaker 1: four in but also I want to calculate stuff. I
Speaker 1: don't just want to write four into my computer. I
Speaker 1: want to be able to add four to two. I
Speaker 1: want to be able to compare four and seven. Right,
Speaker 1: That's what allows you to program a computer for it
Speaker 1: to do useful computation. And if you know something about computing,
Speaker 1: you know like the basics of computation is a Turing
Speaker 1: machine which can like read in numbers and write numbers
Speaker 1: onto this infinite tape. And so in order to do logic,
Speaker 1: you need to be able to have things that respond
Speaker 1: to different inputs. So in logic you have things like gates.
Speaker 1: Like a not gate is something which if you give
Speaker 1: it to zero, it responds a one. If you give
Speaker 1: it a one, it responds to zero. It's like a
Speaker 1: logical map from inputs to outputs, or an a gate. Right,
Speaker 1: an and gate gives you a one if both inputs
Speaker 1: are one and a zero otherwise. Or the converse of
Speaker 1: that is a nand gate NA n D, which is
Speaker 1: the combination of an N gate and a knot gate.
Speaker 1: And the really cool thing is that if you can
Speaker 1: build a nand gate, you can build any logical map
Speaker 1: nandgates are like the basis function of logic. So if
Speaker 1: you have nands, people have shown that you can build
Speaker 1: any map from inputs to outputs and essentially any sort
Speaker 1: of computer logic. So you can build knot gates and
Speaker 1: and gates out of transistors. Transistors are like this digital switch,
Speaker 1: and we'll go into the detail of the physics of
Speaker 1: how they work, but essentially they're a programmable switch. You
Speaker 1: can turn them on or off in response to other stuff.
Speaker 1: So from that you can build logic, and from that
Speaker 1: you can build nandgates, and from that you can build
Speaker 1: literally anything like adders and comparitors and anything you need
Speaker 1: in computers. So this is like the basically the smallest
Speaker 1: little lego brick of computing is a switch, a programmable
Speaker 1: switch that goes from zero to one. And that's what
Speaker 1: a transistor is an implementation of. And it didn't have
Speaker 1: to be a transistor. It could have been something else.
Speaker 1: It could have been DNA, it could have been whatever.
Speaker 1: But this is like the best, fastest, smallest thing that
Speaker 1: we have invented, and this is what revolutionized our society.
Speaker 2: What does the transistor look like?
Speaker 1: Yeah, what does the transistor look like? It looks like
Speaker 1: nothing because it's super duper tiny, right, Like the ones
Speaker 1: that we're building these days are order nanometers right, so
Speaker 1: like you put one on your finger, you can't see it.
Speaker 1: The number of transistors on a typical chip is billions,
Speaker 1: so you can't see an individual one. There used to
Speaker 1: be able to, like when they were first building them
Speaker 1: in the fifties, you would like make one, you know,
Speaker 1: on a bench. You could think of it as sort
Speaker 1: of like three wires coming together. You have a source,
Speaker 1: a drain, and then a gait and the gate basically
Speaker 1: decides do I connect the source and the drain Do
Speaker 1: I open or close this switch? And so it's sort
Speaker 1: of like a wire with a lever in it that
Speaker 1: you know you can open or close, and then another
Speaker 1: wire that determines what whether or not that's open or closed.
Speaker 1: So that's not a physical description of what they look like.
Speaker 1: We can get into like the semiconductors in a minute,
Speaker 1: but that's sort of the logical construction. And when I
Speaker 1: think about more's low, I think, well, what is exactly
Speaker 1: is the connection between more transistors and speed? Like it's
Speaker 1: cool to have things small because then you can put
Speaker 1: a computer in your watch or whatever. But why do
Speaker 1: smaller computers operate faster? Because that's really the crucial key.
Speaker 1: When you sit down at your laptop, you're not like, wow,
Speaker 1: the transistors are super dense. You're like, wow, you know
Speaker 1: word opened in a bill a second instead of you know,
Speaker 1: spinning my beach ball forever. Yeah, So it's the speed
Speaker 1: that's really crucial, and that's really transformed society. Right, it's
Speaker 1: computational power and miniaturization means faster operation for a few reasons.
Speaker 1: Number one, things just don't have to go as far. Right,
Speaker 1: Electronics is limited by the speed of light. It's not instantaneous.
Speaker 1: You close a switch, the electrons don't move instantly. Right,
Speaker 1: the current doesn't change instantly, and so we are still
Speaker 1: limited by the speed of light. And so if the
Speaker 1: distances between the transistors are smaller and the transistors themselves
Speaker 1: are smaller, things just happen faster because there's a speed
Speaker 1: limit to information in the universe.
Speaker 2: That's awesome. I guess I hadn't imagined that as a
Speaker 2: limiting factor. Okay, super cool, what's next.
Speaker 1: Yeah, that's one. The other is you can have wider
Speaker 1: data paths, like instead of just using thirty two bits
Speaker 1: to store your numbers. You can use sixty four bits, right.
Speaker 1: Remember bits are this essential element of binary numbers, and
Speaker 1: so if you have like a two bit number, you
Speaker 1: can only store between zero and four. If you have
Speaker 1: an eight bit number, you can store many more numbers.
Speaker 1: You have thirty two these days computing a sixty four
Speaker 1: one hundred and twenty eight bit If you hear about
Speaker 1: these numbers as the sort of the core the computing
Speaker 1: of your CPU or your operating system, that's what it describes,
Speaker 1: like what size numbers are we operating on? And this
Speaker 1: is important because basically it's how much your computer can
Speaker 1: do in parallel. Like if you can add two hundred
Speaker 1: and twenty eight bit numbers, it's really one hundred and
Speaker 1: twenty eight bit wise operations done in parallel instead of
Speaker 1: if you're doing sixty four bit numbers, then you're only
Speaker 1: doing sixty four operations in parallel, and so you can
Speaker 1: do more operations in parallel, You can pass more data
Speaker 1: at the same time, and so data flows more quickly.
Speaker 1: Another thing that really limits the speed of computers is
Speaker 1: how long does it take to get the data into
Speaker 1: the actual CPU. Right, Like you have these numbers in memory,
Speaker 1: you want to do some calculation on you got to
Speaker 1: slurp them from memory and put them into the registers
Speaker 1: in your CPU. They're actually doing the comparisons or the
Speaker 1: adding or the subtracting or whatever. And so the wider
Speaker 1: the data path, the faster the data gets loaded, and
Speaker 1: the faster the computation happens.
Speaker 2: And CPU probably means senorebditis pyro wetting underwater. What does
Speaker 2: CPU mean?
Speaker 1: CPU means central processing unit. It's a thing on your
Speaker 1: computer that does the actual crunching, does the adding or
Speaker 1: subtracting or comparing, or loading or unloading or writing to
Speaker 1: memorates the closest thing we have to a digital brain. Okay,
Speaker 1: but there's another sort of mechanical element to like why
Speaker 1: speed means faster computers. And you know, back in the
Speaker 1: nineteen fifties, people were doing electronics, and they're doing it
Speaker 1: sort of the way you might do it in your garage.
Speaker 1: You got resistors, you got capacitors, you solder them together,
Speaker 1: you make these big sort of physical circuits. But in
Speaker 1: the late nineteen fifties people invented what's called the integrated circuit.
Speaker 1: Integrated circuit is just like you know, it's a big
Speaker 1: green board and it's got the whole circuit printed onto it.
Speaker 1: You don't like solder the components together, and this really
Speaker 1: allows for like the embedding of these transistors and other
Speaker 1: components inside these protective layers, which enhance their reliability. And
Speaker 1: so that means you can make them smaller, you can
Speaker 1: make more complex circuits that you didn't have to like
Speaker 1: wire together yourself with dripping hot bits of solder, and
Speaker 1: so this makes them more reliable, so you don't need
Speaker 1: as much error correction, et cetera. And that allows things
Speaker 1: to be smaller and to be faster. So you've got
Speaker 1: integrated circuits, you got wider data paths, you got shorter
Speaker 1: distances to travel, and you have faster switching. All these
Speaker 1: things are why more transistors means faster computing.
Speaker 2: Okay, And so when did we get our first transistor?
Speaker 1: Yeah, so the transistor was invented in Bell Labs in
Speaker 1: nineteen forty seven, I think it was. And there was
Speaker 1: a lot of research in the forties different kinds of
Speaker 1: technologies for transistors. Try this, try that, try the other thing.
Speaker 1: But the basic concept was invented in the late forties
Speaker 1: in Bell Labs and you know, Bell Labs is one
Speaker 1: of these like elements of another era, an institution that
Speaker 1: I really miss. You know, it's a privately funded research
Speaker 1: lab that did basic research. You know, this is an
Speaker 1: arm of the telephone company. But they just like gave
Speaker 1: nerds money and said, hey, play around, figure stuff out,
Speaker 1: and they came up with things like the transistor, which
Speaker 1: is I think a trillion dollar idea would be underestimating it, right, Like,
Speaker 1: it's literally the foundation of our entire economy. Its transformed
Speaker 1: the way we live.
Speaker 2: Wow.
Speaker 1: And so I think even if every other piece of
Speaker 1: science was a waste of money, this one brings the
Speaker 1: average up like this one idea like means all of
Speaker 1: science has been worthwhile just from a purely economical, cynical
Speaker 1: point of view. And that's the way science works, right,
Speaker 1: like a lot of fuzzes out and occasionally a huge,
Speaker 1: huge payoff. Anyway, it was the late nineteen forties people
Speaker 1: figured this out. And you know, we've only had quantum
Speaker 1: mechanics for a couple of decades.
Speaker 2: Then.
Speaker 1: People had ideas for making transistors before then, but weren't
Speaker 1: able to make it work. But at Bell Labs, smart
Speaker 1: guys figured this out. One Nobel Prizes. It was really
Speaker 1: pretty awesome.
Speaker 2: Awesome, And when we get back, let's talk about how
Speaker 2: we went about shrinking these transistors. All right, So in
Speaker 2: nineteen forty seven, Bell Labs creates the transistor just in
Speaker 2: time for us to use it to get to space,
Speaker 2: which is the most important topic that we have to
Speaker 2: keep getting to every episode. All right, So now we've
Speaker 2: got the transistor, how do we go about shrinking it?
Speaker 1: Yes, the transistors are built out of semiconductors. You know,
Speaker 1: you hear the semiconductor industry everywhere, And what does that
Speaker 1: really mean? Well, we understand what conductor is, right, It's
Speaker 1: something where electricity can flow. An insulator is something where
Speaker 1: electricity cannot flow. And to understand that, you have to
Speaker 1: take your vision of the atom where you have like
Speaker 1: electrons orbiting around the nucleus or being in fuzzy quantum
Speaker 1: mechanical states, and think about what happens when you put
Speaker 1: a lot of atoms together, Like, what is the energy
Speaker 1: level of an electron around an iron atom? Well, it's
Speaker 1: a bunch of levels. What happens when you have a
Speaker 1: billion iron atoms and a lattice, what happens to those electrons? Well,
Speaker 1: they don't really belong to any individual nucleus anymore. They
Speaker 1: sort of like move around the iron super highway. They
Speaker 1: can flow around from here to there. And what distinguishes
Speaker 1: a conductor from an insulator is whether or not there's
Speaker 1: a big gap between energy levels, like can the electrons
Speaker 1: get up to those energy levels where they can flow
Speaker 1: around between all the atoms or not. If they can
Speaker 1: get up there, then it's a conductor. If there's a
Speaker 1: really big gap so they can't get up there, then
Speaker 1: it's an insulator. Semiconductors are things that are sort of
Speaker 1: halfway in between. They have a medium sized gap between
Speaker 1: the energy levels where the electrons are stuck around individual
Speaker 1: atoms and the ones where they're just flowing across the
Speaker 1: super highway. And so that's something you can control. If
Speaker 1: you tweak it a little bit by like adding them
Speaker 1: a little bit of germanium or this other kind of thing,
Speaker 1: you can control that gap. And so what you want
Speaker 1: when you're building circuits is you want places where things
Speaker 1: conduct really well and then places where things conduct really
Speaker 1: really terribly. So rather than having to have different kinds
Speaker 1: of material, like if I build a circuit in my garage,
Speaker 1: I use copper for the wires and then to use
Speaker 1: rubber for the insulators. It's better if you can have
Speaker 1: a single kind of material and sort of tweak it
Speaker 1: and like, okay, I'm going to make this part of
Speaker 1: it conductor and that part of it an insulator because
Speaker 1: it allows you to print circuits onto your material.
Speaker 2: Okay, And so what is the material you use?
Speaker 1: So we use silicon. Silicon is the semiconductor of choice,
Speaker 1: and then you dope it with various things to change
Speaker 1: its behavior to make it a conductor. And the way
Speaker 1: that we have shrunk transistors from pretty big stuff you
Speaker 1: could see on your garage bench to tiny stuff almost
Speaker 1: the size of atoms is through a technique called photolithography,
Speaker 1: which essentially prints a circuit onto a piece of silicon.
Speaker 1: We grow these huge silicon wafers that are like ten
Speaker 1: inches and then you want to print a circuit onto it,
Speaker 1: and you want to print like billions and billions of transistors,
Speaker 1: and you want them to be as small as possible.
Speaker 1: For the reason we just point it out, So like,
Speaker 1: how do you print this stuff onto a piece of
Speaker 1: sar silicon? So this is what photolithography is. Essentially, you
Speaker 1: design your circuit on the computer, and then you print
Speaker 1: on the surface of the silicon this thing called a
Speaker 1: photo mask, and the photomask like protects the silicon from
Speaker 1: the next thing you're gonna do to it, which is
Speaker 1: blast it with really high energy light. So you shoot
Speaker 1: like super high energy light at the silicon which is
Speaker 1: partially covered by this mask, and the parts that are
Speaker 1: exposed get a little bit chemically changed. Then you dip
Speaker 1: the whole thing in like acid, and the parts that
Speaker 1: we're exposed get like eaten away, for example, and so
Speaker 1: what you're left with is just the pattern that you wanted.
Speaker 1: That's like a very hand wavy explanation of how photolithography works.
Speaker 1: But the things to understand is that it's limited by
Speaker 1: those photons. Like if you use photons that we really
Speaker 1: wide wavelengths, then you're going to get a fuzzy picture.
Speaker 1: If you use photons with really narrow wavelengths, which means
Speaker 1: high energy photons, right, then you're gonna get a much
Speaker 1: crisper picture. And so over the decades, we've been trying
Speaker 1: to shrink these transistors to get more and more transistors
Speaker 1: on these chips and have faster computers. And one way
Speaker 1: to do that is to crank up the energy of
Speaker 1: those photons, and so now we're in the like extreme
Speaker 1: ultraviolet limit where the photons have a wavelength of like
Speaker 1: thirteen or fourteen nanometers. Wow, And that's hard because it
Speaker 1: requires like special optics. You can't just use normal lenses
Speaker 1: to bend this kind of light. It's why it's very
Speaker 1: hard to do, like X ray optics. Also, the higher
Speaker 1: the energy light, the harder it is to bend it.
Speaker 2: Have we maxed this out?
Speaker 1: We probably have maxed this out, because anything beyond this
Speaker 1: requires insane optics. Like already the optics are insane. You know,
Speaker 1: making a single mask for these things costs like hundreds
Speaker 1: of thousands of dollars, and there's like a few places
Speaker 1: in the world you can do this kind of stuff.
Speaker 1: The equipment is extremely expensive, the operating conditions are very
Speaker 1: very particular. You have to have specialized clean rooms. Like
Speaker 1: this is really the pinnacle of technology. It's incredible, and
Speaker 1: that's why you know a few of these players in
Speaker 1: this field, like the Taiwannee semiconductor industry is so important
Speaker 1: for the worldwide computing industry. Like a single company goes
Speaker 1: down and like we can't make computers anymore.
Speaker 2: Wow, Oh my gosh. Right, all of the geopolitical tensions
Speaker 2: just came into focus exactly.
Speaker 1: That's one reason why Taiwan is so important because a
Speaker 1: lot of this stuff is done by Taiwan, these firms.
Speaker 2: All Right, so we figured out photo lithography and we've
Speaker 2: kind of reached the limit. Yeah, is that the end
Speaker 2: of the story.
Speaker 1: It's not quite the end of the story. And you know,
Speaker 1: I'm more to say about like how impressive it is.
Speaker 1: Like in the mid nineties, we were doing things at
Speaker 1: like three hundred and fifteen nanimeters scale, which sounds pretty awesome,
Speaker 1: Like that sounds pretty tiny. And then late nineties it
Speaker 1: was like one hundred and eighty animeters, and the two
Speaker 1: thousands it was sub one hundred nanimeters. These days we're
Speaker 1: getting down to like ten nanimeters single nanometers. It's amazing,
Speaker 1: but it's getting harder and harder because we're already beyond
Speaker 1: the wave length of the light that we're using, right,
Speaker 1: and we're approaching the size of the atom. Right, silk
Speaker 1: and atoms are like zero point two nanometers across, so
Speaker 1: like you're going to be bild a transistor out of something.
Speaker 1: It's like you know, you can't make things out of
Speaker 1: legos if you only have a few of the bricks, right,
Speaker 1: And so it's challenging to make transistors smaller than about
Speaker 1: a nanometer because you're really reaching that fundamental limit of
Speaker 1: the size of the silicon atom. And every year it
Speaker 1: gets harder. Like it's true that we've increased the transistor
Speaker 1: density every two years, we've doubled it, but the amount
Speaker 1: of money spent in this research has increased by a
Speaker 1: factor of ten or twenty, so it's not like a
Speaker 1: constant effort every year to achieve this. We have to
Speaker 1: ramp up the energy and the creativity. And that's great,
Speaker 1: you know, it's like inspired all sorts of cool things
Speaker 1: and spinoffs and whatever. But it gets really really complicated.
Speaker 1: And the sort of cutting edge of this is to
Speaker 1: now start stacking these transistors, so well, don't just think
Speaker 1: of it as a plane. Let's go up in the
Speaker 1: third dimension. Let's make the transistors more powerful by shrinking
Speaker 1: them further and then allowing them to grow in sort
Speaker 1: of the third dimension above this sort of plane. And
Speaker 1: the leading edge of technology right now are these transistors
Speaker 1: called fin fet so FET, which stands for a field
Speaker 1: effet transistor and then a finn meaning like they literally
Speaker 1: have this like fin over the gate that controls it
Speaker 1: like a physical thing. It looks like a shark fin.
Speaker 1: That makes it possible to be efficient while shrinking even further,
Speaker 1: so you can make the sort of footprint of it
Speaker 1: smaller while keeping its effectiveness because you have this third dimension.
Speaker 1: And so that's what stacking is. And really people think
Speaker 1: that we've reached the limit of what we can do technologically,
Speaker 1: and as some of the listeners have said, we're going
Speaker 1: in other directions, like instead of making your CPU more dense,
Speaker 1: you just have multiple cores, or you start building other
Speaker 1: dedicated stuff like graphics processing units that are really good
Speaker 1: at linear algebra, which is needed for graphics and also
Speaker 1: for machine learning. And so we're sort of like simultaneously
Speaker 1: trying to go in many directions at once to improve
Speaker 1: the power of computing. But it's not clear that we
Speaker 1: can keep doing this, and a lot of people think
Speaker 1: that we really are at the edge of what we
Speaker 1: can do to improve computing speed.
Speaker 2: Wow, and so stacking isn't going to be the magic
Speaker 2: solution because there's like limits on stacking.
Speaker 1: Yeah, exactly, like stack can get you a little further.
Speaker 1: But if we're going to keep doubling, then it's hard.
Speaker 1: And you know, I think there's something to be said
Speaker 1: about the sociological impact of this doubling. You know, Moore's
Speaker 1: law is not something that comes out of like the
Speaker 1: fundamental laws of physics. It's something that was predicted and
Speaker 1: that we maintained really over decades, which is really incredible.
Speaker 1: Like one of Intel's earliest processors, the four thousand and four,
Speaker 1: had twenty three hundred transistors in it, right, whereas like
Speaker 1: the eighty three eighty six, which I've spent a lot
Speaker 1: of time programming on as a teenager, had like hundreds
Speaker 1: of thousands of transistors in this MacBook I'm sitting in
Speaker 1: front of has billions. It's incredible, but it's sort of
Speaker 1: guided the field. I think people because they thought this
Speaker 1: was possible and maybe even inevitable, they worked for it.
Speaker 1: It's a target, you know, And so if you think
Speaker 1: something as possible, then like you stay late and you
Speaker 1: push hard and you come up with new ideas, and
Speaker 1: so in some sense it's a self fulfilling prophecy.
Speaker 2: Okay, so first of all, have we hit the limit
Speaker 2: to More's law? Already, or you just think we're going
Speaker 2: to hit it soon, Like when is the first year
Speaker 2: you think where we'll be like Moore's law gone.
Speaker 1: I think we're right at that inflection point. You know,
Speaker 1: we're still seeing improvements in speed, we're still seeing big
Speaker 1: boosts and productivity, but we're sort of running out of
Speaker 1: avenues and so I still see that, Like my MacBook
Speaker 1: is faster than the one I gave my son, which
Speaker 1: is my two year old MacBook, But I don't know
Speaker 1: that the one I'm going to get in two years
Speaker 1: is going to be as much faster. So I think
Speaker 1: we're right at that inflection point.
Speaker 2: So that feels a little scary to me. So, like,
Speaker 2: you know, over time, we've gotten computers that are better
Speaker 2: and so at least, you know, in my field, almost
Speaker 2: every five years you expect, you know, the statistical models
Speaker 2: of the systems that we study to get more complicated
Speaker 2: so that we can get a better understanding out of
Speaker 2: each one of our data sets. Are we not going
Speaker 2: to be able to do that anymore? Or do you
Speaker 2: think in twenty years our computers are just going to
Speaker 2: start getting bigger again until they fill up a room,
Speaker 2: Because we're going to want to keep getting more complicated
Speaker 2: in our analyses.
Speaker 1: Yeah, well, I think we're already seeing our computing getting bigger.
Speaker 1: I mean, think about like the data centers that are
Speaker 1: being built by Meta and Microsoft is like trying to
Speaker 1: turn back on nuclear reactors because they need the power
Speaker 1: for their AI data centers. These things are vast and
Speaker 1: they're consuming huge amounts of our resources. So I think, yeah,
Speaker 1: our appetite for computing is just growing, and even if
Speaker 1: our computers don't get faster, we're just going to keep
Speaker 1: building them bigger and bigger. But I also think that
Speaker 1: for those of us who do things that are not
Speaker 1: directly just computing, that there are other ways to increase speed.
Speaker 1: I was talking to Katrina about this, and she was
Speaker 1: saying that Moore's law also kind of applies to genomics.
Speaker 1: You know, like the first study of a human genome
Speaker 1: costs like how many millions for one genome, And then
Speaker 1: the NIA had a target like it should cost less
Speaker 1: than one thousand dollars to sequence a human genome, and
Speaker 1: they hit that target and now it's cheaper than one
Speaker 1: thousand dollars. And where does this come from? Part of
Speaker 1: it come from computing, but also part of it comes
Speaker 1: from like the miniaturization of biology. And I've seen this
Speaker 1: just like observing her field. Something that used to be
Speaker 1: like a PhD level of work then in a few
Speaker 1: years becomes a little box on the lab bench. You
Speaker 1: press a button and it's done while you're at lunch, right, Yeah,
Speaker 1: and that allows you to now do things that were
Speaker 1: impossible ten years earlier. And that kind of transformation of
Speaker 1: the scope of the capacity of the field enables broader,
Speaker 1: deeper thinking. And that's not just computing, right, that's the
Speaker 1: menigtization of like the actual biology, like micro little bits.
Speaker 1: It's essentially like what therapnose was tapping into this feeling like, oh,
Speaker 1: eventually we should be able to diagnose diseases with tiny
Speaker 1: life jobs of blood in this kind of sense. So
Speaker 1: I think that there's lots of dimensions that we can
Speaker 1: follow for improving our scientific and technological industrial capacity. Is
Speaker 1: not just is my computer faster.
Speaker 2: So when someone says, like you just did such and
Speaker 2: such follows Moore's law, do they essentially mean we do
Speaker 2: it better with smaller stuff, and like we do it
Speaker 2: exponentially better in particular.
Speaker 1: Yeah, I think it's about exponential growth that's a crucial
Speaker 1: thing because you know, exponential growth builds on itself. You know,
Speaker 1: it's like putting a dollar in the bank. Every year
Speaker 1: you have more dollars, and those dollars earn more dollars,
Speaker 1: and eventually you have all the dollars. Whereas like if
Speaker 1: you're just selling lemonade and you're making a dollar every day,
Speaker 1: you're making the same amount of dollars every day. It's
Speaker 1: not increasing. So it's all about that exponential growth. And
Speaker 1: I think that that's what people mean when they refer
Speaker 1: to Moore's law sort of more colloquially than just like
Speaker 1: the density of transistors on a chip.
Speaker 2: That's kind of interesting because like Moore's law isn't really
Speaker 2: a law, like it's an observation. And so it seems
Speaker 2: like now anytime we see exponential growth, we say the
Speaker 2: words Moore's law instead of just saying exponential growth or
Speaker 2: am I being negative?
Speaker 1: No? I think you're right, And I think it says
Speaker 1: something about our aspirations. You know, we live in a
Speaker 1: time when we expect our children's lives to be very
Speaker 1: different from our lives and our grandparent lives, and that's
Speaker 1: really unusual, Like most of human history. You could tell
Speaker 1: your kids what their life was going to be like,
Speaker 1: because it's going to be basically the same as yours
Speaker 1: and your grandparents for like the last ten thousand years, right,
Speaker 1: because like change was inconceivable because nobody had ever experienced it.
Speaker 1: But now we live in a time when, like we
Speaker 1: know that's not true, and so I think it leaves
Speaker 1: us with this like gap in our wisdom. And then
Speaker 1: we project forward, and some of us are optimistic and
Speaker 1: we're like, Yay, this is going to change our lives
Speaker 1: in a way that solves all of our problems. And
Speaker 1: as you'll hear from Adam, some of us are less optimistic,
Speaker 1: you know, about what this means and whether it's the
Speaker 1: right way to place our bets.
Speaker 2: I do feel like that was a slightly simplified view
Speaker 2: of history, But this isn't Daniel and Kelly's historical universe.
Speaker 2: So we're moving on.
Speaker 1: Hey, I have to fit it into about one minute,
Speaker 1: so I'm not going to do a deep dive. But yeah,
Speaker 1: I mean, do you disagree with me about the broader
Speaker 1: assessment of the way that human experience has changed.
Speaker 2: I do think human experience was similar for a really
Speaker 2: long time. You know, like when our ancestors moved out
Speaker 2: of Africa, there was probably a lot that changed in
Speaker 2: a couple generations, and the Industrial Revolution and climate. Yeah, yeah,
Speaker 2: I think there's probably been a lot of moments where
Speaker 2: things were like, oh crud, but usually probably they were
Speaker 2: getting worse, whereas now we're hoping that it's getting better.
Speaker 2: But anyway, so when I was reading Adam Becker's new
Speaker 2: book More Everything Forever, there was a discussion on Moore's
Speaker 2: Law where I realized, like, oh my gosh, I fundamentally
Speaker 2: didn't understand Moore's Law very well or what like underpinned
Speaker 2: Moore's Law, and I didn't realize that we were, you know,
Speaker 2: perhaps reaching the end of Moore's Law. And so we
Speaker 2: reached out to Adam Becker and asked if he would
Speaker 2: talk to us about sort of the implication of, you know,
Speaker 2: the death of Moore's Law. I'll be super dramatic about it,
Speaker 2: but how this expectation of exponential growth impacts our view
Speaker 2: of the future in ways that are not always necessarily realistic.
Speaker 1: Let's say, all right, so then we're very happy to
Speaker 1: welcome to the podcast. Adam Becker, who is an astrophysicist
Speaker 1: turned author. He wrote the widely acclaimed book What Is Real,
Speaker 1: one of my favorite books about quantum chinnings. If you
Speaker 1: write me to ask for a book about quantum mechanics
Speaker 1: that explain stuff in an accessible way, often recommended. And
Speaker 1: he has a new book out called More Everything Forever
Speaker 1: about the rise of techno utopiasts and how we can
Speaker 1: project our future and the future of technology. Adam, Welcome
Speaker 1: back to the podcast. Thanks, it's great to be here.
Speaker 1: So let's start just by talking about Moore's law. It's
Speaker 1: the foundation of so much of the techno utopian movement.
Speaker 1: Why do you think that it has inspired sort of
Speaker 1: this broader fanaticism, especially when it's just like an empirical observation,
Speaker 1: not like a deep law of the universe.
Speaker 3: Yeah, that's a good question.
Speaker 5: I mean Moore's law. Yeah, it is an empirical observation.
Speaker 5: But it's so regular, it's so comforting, and it has
Speaker 5: you know, the fact that Moore's law held more or
Speaker 5: less accurately for what about fifty years. It did change
Speaker 5: a lot of things about the world, and it took
Speaker 5: computers from being these large, slow, you know, refrigerator sized
Speaker 5: things that live in mainframe rooms at corporations to you know,
Speaker 5: tiny little things that live in our pockets, are on
Speaker 5: our wrists and have much more power than all of
Speaker 5: the main frames that existed, you know in the nineteen
Speaker 5: seventies combined, right, caused all sorts of changes in our society,
Speaker 5: some for the better, so much for the worse. But
Speaker 5: you know, living through that, it seemed like clockwork, right,
Speaker 5: you know. I mean I only lived through like the
Speaker 5: last part of it, But I remember when I was
Speaker 5: a kid, it seemed like, you know, computers were just
Speaker 5: always getting smaller and faster and better every single year,
Speaker 5: and you could just get you know, the advice was
Speaker 5: wait as long as you can to get a new computer,
Speaker 5: because the longer you wait, the better it'll be. Right,
Speaker 5: And it was this amazing thing, and it made a
Speaker 5: lot of people a lot of money, and a few
Speaker 5: people truly enormous amounts of money. And so you put
Speaker 5: all of that together and it's it kind of makes
Speaker 5: some sense that some people would take it extremely seriously
Speaker 5: as this general thing, because it seemed to be, you know,
Speaker 5: if you lived a comfortable middle or upper class life,
Speaker 5: it seemed like the most important thing in the world.
Speaker 5: In the late twentieth century, right, and it wasn't really
Speaker 5: like anything that you'd seen before. It was easy to think, oh,
Speaker 5: this is just going to continue. So Ray Kurzweil is
Speaker 5: this inventor and futurist who you know. He made like
Speaker 5: real serious contributions to text to speech technology and like
Speaker 5: assistive devices for the visually impaired, and I think hearing
Speaker 5: impaired as well. You know, he made serious contributions to
Speaker 5: the field of electronic instruments, like you know, musical instruments.
Speaker 3: But he is best known as a futurist.
Speaker 5: He is best known as somebody who you know, makes
Speaker 5: these forecasts about what the future is going to be like.
Speaker 1: So he's a retired electrical engineer, you're saying, essentially, yeah,
Speaker 1: I have a lot of those in my inbox.
Speaker 3: Yeah, me too, man.
Speaker 5: I'm pretty sure that if you put anywhere on the
Speaker 5: Internet that you have a PhD in physics, you get
Speaker 5: a lot of retired electrical engineers in your inbox.
Speaker 2: Guys, my inbox has pictures of feces from people who
Speaker 2: want to note the parasite infections. I'm feeling pretty low
Speaker 2: on sympathy right now.
Speaker 5: Oh, but I once got so sorry for you guys.
Speaker 3: Yeah, no, we should.
Speaker 5: We should have a separate episode just talking about what's
Speaker 5: in our inboxes, because I have some crazy stuff in
Speaker 5: any event.
Speaker 1: All right, So you're telling us how Ray Kurzweild was
Speaker 1: thinking about how Moore's law is transforming technology and that's
Speaker 1: the engine of transformation of society and predicting the future
Speaker 1: of society more broadly exactly.
Speaker 5: Yeah, And like Kurzweil extends Moore's Law in his Forecasts
Speaker 5: of the Future and says, oh, this is part of
Speaker 5: a more general trend in the history of technology and
Speaker 5: the history of you know, even life in the universe.
Speaker 5: And he calls it the law of accelerating returns, where
Speaker 5: he says, you know, once you have better technology, it's
Speaker 5: going to allow you to make the technology that you've
Speaker 5: already got even better, and then that'll just be a
Speaker 5: self reinforcing cycle that leads to this exponential trend. And
Speaker 5: More's law is just one manifestation of that trend, and
Speaker 5: it's going to you know, he says, it's something that
Speaker 5: you can see if you look back through the entire
Speaker 5: history not just of human technology, but evolution of life
Speaker 5: on Earth, because you see the same thing with biological
Speaker 5: quote unquote technology, and he says, you know, this is
Speaker 5: going to continue, and in short order we are going
Speaker 5: to reach this point that he calls the singularity, which
Speaker 5: is where you've got, you know, technology that has developed
Speaker 5: to such an advanced degree that it gives us, you know,
Speaker 5: godlike powers of creation and destruction and transform and just
Speaker 5: changes the fundamental nature of life on Earth and in
Speaker 5: the universe.
Speaker 1: Well, a lot of what you said sounds reasonable. R
Speaker 1: There is evolution, and there is transformation, and things are
Speaker 1: changing more rapidly. But from reading your book and from
Speaker 1: your tone, I'm guessing you don't agree with Cursewil about
Speaker 1: singularity and how we're all going to be techno gods
Speaker 1: in the future. Why not? Why will Daniel not be
Speaker 1: a techno god?
Speaker 3: Yeah?
Speaker 2: I mean, look Daniel in particular, Yes.
Speaker 1: Yeah, I have a personal stake in this question.
Speaker 5: Now, yes, Daniel in particular, Yeah, you are not going
Speaker 5: to be a techno god, Daniel, because you know, by
Speaker 5: having me on this podcast, Ray Kurzwild is going to
Speaker 5: put you on his list, and then you know he
Speaker 5: won't allow you to ascend to God.
Speaker 2: I knew this was a mistake.
Speaker 1: Yeah, exactly, worse than trying to fight a land born Asia. Huh, yes, exactly.
Speaker 3: Yeah, No, that's number two.
Speaker 5: Now number one is inviting Adam Becker onto your podcast.
Speaker 5: But I mean, look, Curzwild is taking this exponential trend
Speaker 5: and just extending it out into the future and saying
Speaker 5: it's going to last forever. And the one thing that's
Speaker 5: always true about exponential trends is that they end.
Speaker 1: Right.
Speaker 5: If you see any sort of exponential trend in nature
Speaker 5: or in you know, technology or whatever, your first thought
Speaker 5: should be, oh, that can't last, because it just doesn't.
Speaker 5: There are not enough resources, there's not enough space, there's
Speaker 5: not enough anything to allow exponential trends in general to
Speaker 5: continue forever. One of the examples that Churzwild gives in
Speaker 5: his book The Singularity Is Near which is probably his
Speaker 5: most famous book from about two thousand and five.
Speaker 1: Doesn't he have a few books like The Singularity is Near,
Speaker 1: The Singularity is near Er, the Singularity is near Ish?
Speaker 3: Yeah, yeah, yeah.
Speaker 5: The Singularity is Near Er came out last year, and
Speaker 5: when I tell people that that's the title, they usually
Speaker 5: don't believe me.
Speaker 3: But that is actually the title. He wrote a book
Speaker 3: called the singularity is nearer.
Speaker 1: Next year, the singularity is near your ear.
Speaker 3: Yeah, neariest.
Speaker 5: But the classic example in biology of exponential growth is
Speaker 5: something like bacterial growth in a petri dish and yeah,
Speaker 5: if you chart the number of bacteria in this you know,
Speaker 5: nutrient rich medium over time, Yeah, it grows exponentially until
Speaker 5: they fill the dish and eat all of the agar
Speaker 5: and then they die.
Speaker 2: To try to play Devil's advocates, so when I was
Speaker 2: talking to space settlement folks, they would say something like,
Speaker 2: you know, the reason we need to go into space
Speaker 2: is because exponential growth does end at some point. But
Speaker 2: our species is so amazing that we can see when
Speaker 2: we're getting close to the like asymptope and the exponential curve,
Speaker 2: and so we can go out to space and get
Speaker 2: resources and we can be more proactive about it. What
Speaker 2: is wrong about that argument?
Speaker 3: Yeah?
Speaker 2: I mean where to start?
Speaker 3: Ye?
Speaker 2: What you got to pick somewhere?
Speaker 5: Okay, I'm going to pick on you know, I'm going
Speaker 5: to do what we should all strive to do, or
Speaker 5: what I strive to do, and punch up right, I'm
Speaker 5: going to pick on somebody bigger than me.
Speaker 3: Jeff Bezos makes the same argument, right, Yeah.
Speaker 5: Jeff Bezos says that we need to go out into
Speaker 5: space because of exactly this. He says, you know, we
Speaker 5: are using exponentially more energy as time goes on, and
Speaker 5: if that trend continues as it has for decades, if
Speaker 5: not centuries, then in about two three hundred years, we're
Speaker 5: going to be using all of the energy on Earth
Speaker 5: that we get from the Sun and will have used
Speaker 5: up all of the non renewable resources. And so at
Speaker 5: that point we need to go out into space, if
Speaker 5: not before, then otherwise we're going to have what he
Speaker 5: calls a civilization of stasis and rationing. And you know,
Speaker 5: he's not wrong about the first part. If somehow we
Speaker 5: continue that exponential trend in energy usage, then yeah, and
Speaker 5: I think it's in about three four hundred years, we'd
Speaker 5: be using all of the energy available to us on Earth.
Speaker 5: And also we'd be using so much energy that like
Speaker 5: the waste heat from our energy usage would like boil
Speaker 5: off the oceans.
Speaker 3: We can't we can't do that, right, it's not possible.
Speaker 5: I mean, putting aside that, you know, it's it's implausible
Speaker 5: that that trend will continue. The problem is with the
Speaker 5: second half, because yeah, Okay, we get like three to
Speaker 5: four hundred more years here on Earth if you continue
Speaker 5: that trend. So Bezos says, we have to go out
Speaker 5: into space, and you know what he doesn't say is
Speaker 5: where where resources are unlimited, but you know he implies it.
Speaker 5: The problem is that if you really want exponential growth
Speaker 5: to continue, going out into space, it doesn't actually help
Speaker 5: you that much if you're looking on a timescale of centuries,
Speaker 5: because if you do that, like about I think it's
Speaker 5: like one thousand years after we hit that point of
Speaker 5: using all of the sunlight that hits Earth, we get
Speaker 5: to a point where we're just using the entire energy
Speaker 5: output of the Sun. And then if we spot Bezos
Speaker 5: and company a warp drive so they can go faster
Speaker 5: than the line to try to amass even more resources
Speaker 5: very very quickly outside of the Solar system, which we
Speaker 5: shouldn't spot them a warp drive. There's no reason to
Speaker 5: think that you can build a warp drive, and a
Speaker 5: lot of reason to think that you can't. But if
Speaker 5: we do spot them a warp drive, that only gets
Speaker 5: you like about another two thousand years before you're using
Speaker 5: all of the energy in the observable universe. Wow, so
Speaker 5: you know there are limits, growth ends, and the fact
Speaker 5: is that you know, all of that is wildly implausible.
Speaker 5: It's not like the lesson that I want people to
Speaker 5: take away from all of this is, oh, well, we
Speaker 5: better keep in mind that growth has to end at
Speaker 5: some point to the next like three thousand days years.
Speaker 5: The answer is, oh, no, growth has to end a
Speaker 5: lot sooner than that, because you know, going out into
Speaker 5: space has lots of problems, even putting aside the lack
Speaker 5: of warp drive, just living in the Solar System is
Speaker 5: an extraordinarily difficult and dubious proposition. To give Bezos a
Speaker 5: little bit of cris after ragging on him just now,
Speaker 5: one of the things I like that Jeff Bezos has
Speaker 5: said is he makes fun of Elon Musk for wanting
Speaker 5: to go to Mars because Mars sucks.
Speaker 3: But Bezos's solution is.
Speaker 5: You know, for going out into space, it's not considerably better,
Speaker 5: which is to build like hundreds of thousands or millions
Speaker 5: of enormous city size space stations and then have everybody
Speaker 5: live inside of them.
Speaker 3: This is also not a great idea for many many reasons.
Speaker 1: All right, So it's reasonable, I think to make these
Speaker 1: arguments against like the strongest version of those claims. You know,
Speaker 1: exponential growth will last forever. Sure, and you're right, that's
Speaker 1: obviously practical because the universe is finite, or the observable
Speaker 1: part of it is finite at least.
Speaker 3: Yeah.
Speaker 1: Yeah, But what if we just like water down those
Speaker 1: claims a little bit and we just say, you know,
Speaker 1: technology is transforming society very rapidly, and even the future
Speaker 1: you describe as refuting exponential growth. That sounds pretty awesome.
Speaker 1: Like if in two thousand years we're tapping into all
Speaker 1: the energy from the Sun and nearby stars and have
Speaker 1: an incredible, you know, star spanning civilization a lot of
Speaker 1: people out there, and be like, that sounds great. What's
Speaker 1: wrong with that?
Speaker 5: The prospect of large numbers of people living and working
Speaker 5: in space has an enormous number of technological and social
Speaker 5: and political questions tied to it that are very very
Speaker 5: difficult to solve and may not be solvable. And some
Speaker 5: of those problems are sort of irreducibly time consuming. You
Speaker 5: can't solve them without doing like lengthy experiments involving things
Speaker 5: like radiation exposure and low gravity exposure.
Speaker 3: And things like that. And I see Kelly nodding.
Speaker 5: And you know, Kelly may know more about this than
Speaker 5: I do, because you know, this is one of the
Speaker 5: subjects in my book. Kelly and Zach wrote an entire
Speaker 5: book about this, an excellent book that I really like.
Speaker 2: I do always find a way to pull the conversation
Speaker 2: back to space settlement. So sorry for derailing us, but
Speaker 2: you do a great chapter on it in your book.
Speaker 5: Yeah, thank you, and you have nothing to apologize for
Speaker 5: it's in my book.
Speaker 1: But let me maybe highlight a difference between the takes
Speaker 1: you guys have in your books. Kelly and Zach say
Speaker 1: that you know, we're maybe not ready to settle space,
Speaker 1: that we haven't done the necessary legwork, and we shouldn't
Speaker 1: get over excited and jump too fast and send people
Speaker 1: to Mars now, because there's a lot of stuff we
Speaker 1: need to figure out, but that it's possible and if
Speaker 1: we do it right, maybe you could figure this out.
Speaker 1: We just aren't there yet. But I feel like your
Speaker 1: book goes a step further and suggests that you know
Speaker 1: it's dangerous to make these projections. You know, somebody out
Speaker 1: there listening might say, all right, Adam, maybe we won't
Speaker 1: get there, you know, to as far as these guys project,
Speaker 1: but however far we get will be great. What do
Speaker 1: you say to that person? Is there a danger in
Speaker 1: this kind of thinking?
Speaker 3: Yeah?
Speaker 5: I mean this This gets back sort of to the
Speaker 5: last question that you asked me as well, because we
Speaker 5: don't know that it's possible to have large numbers of
Speaker 5: humans living off of Earth. Because it's very possible that
Speaker 5: that's not, you know, something that we can do. We
Speaker 5: need to find a way to live safely and healthily
Speaker 5: within the limits imposed by Earth. We can't just assume
Speaker 5: that we're going to be able to leave. The danger
Speaker 5: is that this rhetoric of oh, it's always going to
Speaker 5: be possible to expand out into space and grow forever
Speaker 5: can be used, and in fact it's not hypothetical. It
Speaker 5: is being used to justify this sort of logic of
Speaker 5: rapacious consumption that is not sustainable here on Earth.
Speaker 3: And because there's a very.
Speaker 5: Good chance that we cannot in any meaningful way leave Earth,
Speaker 5: we need to stop doing that and find a way
Speaker 5: to live here.
Speaker 3: That's not to say that we shouldn't explore space. I
Speaker 3: think robots in space are amazing.
Speaker 5: Like the voyager probes make me cry, you know, I'm
Speaker 5: a cosmologist by training. I think getting data from space
Speaker 5: is really important and interesting. I'm not even saying that
Speaker 5: we shouldn't send people into space to you know, the
Speaker 5: Apollo missions were amazing and really interesting. They were, of course,
Speaker 5: you know, not primarily missions of scientific discovery. It was
Speaker 5: about the Cold War. But still like the fact that
Speaker 5: we did like a crude sample return mission to the
Speaker 5: Moon several times and nobody died is amazing. But the
Speaker 5: visions that we have of the future are used to
Speaker 5: justify all sorts of things right here and now, and
Speaker 5: so we need to be careful about what we think
Speaker 5: the future is going to look like and whether that's
Speaker 5: remotely plausible. And I really think that the things that
Speaker 5: Musk and Bezos and these other tech billionaires are talking
Speaker 5: about are sort of like saying, you know, yeah, well
Speaker 5: it's okay that we're doing what we're doing right now,
Speaker 5: because in the future we're all going to live in
Speaker 5: like Hogwarts and have broomsticks and magic wands and like,
Speaker 5: it's roughly the same level of plausibility.
Speaker 2: And so to try to get us connecting More's law
Speaker 2: back with where we are in the conversation. To me,
Speaker 2: I see the connection being that you've got this thinking
Speaker 2: that we're going to have exponential growth and our ability
Speaker 2: to do everything. So like when I was talking to
Speaker 2: space settlement people, they'd be like, I'd talk about a
Speaker 2: problem and they'd say, well, AI is going to solve
Speaker 2: that everything is expanding. Our ability to do anything related
Speaker 2: to technology keeps expanding exponentially, and so you know, we've
Speaker 2: talked about how we have limits and so you can't
Speaker 2: expect exponential trends to go on forever. Do you connect
Speaker 2: then this kind of Moore's law thinking with techno optimism
Speaker 2: and this these sort of views of the future. Or
Speaker 2: have we just gotten off on a different topic.
Speaker 5: No, No, No, I think these things are connected, right, Like,
Speaker 5: there's a reason why all of these different things are.
Speaker 5: In my book, one of the things that I like
Speaker 5: to remind people about when we're talking about Moore's law
Speaker 5: is that More's law. It's not just that it's an
Speaker 5: empirical observation rather than a law of nature. More's law
Speaker 5: was a decision. More'slaw is a choice that the leaders
Speaker 5: of the semiconductor industry made, and then they continued making
Speaker 5: it for decades, you know, and there was a road
Speaker 5: map and lots and lots of different, you know, plans
Speaker 5: made in order to ensure the continuation of Moore's law
Speaker 5: for as long as possible. There are massive, massive amounts
Speaker 5: of money and corporate resources poured into this, and in fact,
Speaker 5: Moore's law is not even an example of accelerating returns,
Speaker 5: as as Kurzweil would have, but in a sense it's
Speaker 5: an example of diminishing returns because they got, you know,
Speaker 5: the semiconductor industry got less bang for their buck over time.
Speaker 5: They had to spend more and more money, even adjusting
Speaker 5: for inflation, just to get the same doubling of the
Speaker 5: number of processors crammed into the same space. The techno
Speaker 5: utopian sort of ideas that Kurzweil pushes using Moore's law,
Speaker 5: as you know, sort of the justification and this you
Speaker 5: know eternal expansion into space stuff that we've just been
Speaker 5: talking about, they all sort of traffic in the idea
Speaker 5: that the future of technology is not just eternal exponential
Speaker 5: growth and expansion, but that it's inevitably that not that
Speaker 5: that's you know, something that we could do, but that
Speaker 5: it's it's what we have to do. It's what is
Speaker 5: going to happen, and the only alternative, if there is one,
Speaker 5: is the extinction of the species. And you know, again
Speaker 5: Musk is extremely clear about this. Musk has said the
Speaker 5: only choice we have is eternal expansion out into cosmos
Speaker 5: or extinction. And when he's pushed on this, he, you know,
Speaker 5: he brings up the fact that you know, in about
Speaker 5: half a billion or a billion years, it's going to
Speaker 5: get so hot on Earth because of you know, the
Speaker 5: sun getting hotter, that the oceans will boil off. And yeah,
Speaker 5: that's not wrong, but you know, a lot's gonna happen
Speaker 5: between now and then. Not only is it not a
Speaker 5: particularly pressing problem, but it may not even end up
Speaker 5: being our problem at all, because there are many other
Speaker 5: things that could cause humanity to go extinct between now
Speaker 5: and then, like say, civilizational collapse due to global warming,
Speaker 5: for example, a problem that tech oligarchs and other billionaires
Speaker 5: have done a lot of work to try to prevent
Speaker 5: humanity from solving. But instead Musk says that the solution
Speaker 5: is to leave Earth. And this is the sort of
Speaker 5: rhetoric that I was talking about, you know, in terms
Speaker 5: of like, this is what this eternal expansion idea gets you.
Speaker 5: But it's also I think part of the connection with
Speaker 5: the logic of taking Moore's law as this law of
Speaker 5: nature that we can always count on these exponential trends,
Speaker 5: and we can always count on human ingenuity and technical
Speaker 5: knowledge and know how to get us out of any problem.
Speaker 3: If you believe that.
Speaker 5: Account for all of the problems in the world today, Like,
Speaker 5: there's so many problems that we have that are not
Speaker 5: amenable to technological solutions that people have tried to solve
Speaker 5: for a long time, that are fundamentally social in nature,
Speaker 5: or you know, had a technological component but also have
Speaker 5: a social component, like climate change. Right, we have a lot,
Speaker 5: if not all, of the technology that we need to
Speaker 5: address climate change, but we haven't yet as a species,
Speaker 5: and that's primarily a social and political issue, not an
Speaker 5: issue of technology.
Speaker 1: So, to paraphrase your argument, I think you're saying, it's
Speaker 1: not that computers won't get faster and the technology can't
Speaker 1: help us in the future. It's just that we can't
Speaker 1: rely on it always doing so to magically solve all
Speaker 1: of our problems, and doing so distract ourselves from the
Speaker 1: real problems we face in the more immediate future.
Speaker 5: Yeah, yeah, I mean, also, more's laws over. I mean,
Speaker 5: come on, we have the transistors down about as small
Speaker 5: as we can get them. You know, you can't make
Speaker 5: a silicon transistor smaller than an atom of silicon.
Speaker 1: But you do see a role for technology in shaping
Speaker 1: our future. I mean, it's not that you don't want
Speaker 1: chet gpt to cure cancer.
Speaker 5: I definitely hear that there's a role for technology in
Speaker 5: shaping our future.
Speaker 3: Technology is a big part of how we shape our future.
Speaker 5: I'm going to just pretend that you didn't say the
Speaker 5: thing about chatch ept curing cancer. Though. God, there's this tweet,
Speaker 5: like one of my favorite tweet and responses, effor is
Speaker 5: where Sam Altman said something like be me, build chatch
Speaker 5: ept to cure cancer or whatever, and then people start
Speaker 5: criticizing you, and then he like goes on and on
Speaker 5: and like has a pity party for himself. And then
Speaker 5: somebody just responded with did you cure cancer or whatever?
Speaker 5: But you know, there has been actually great progress made
Speaker 5: and treating cancer just in the last few years, right,
Speaker 5: you know, like these I don't remember the names of
Speaker 5: the drugs because like I'm not a cancer guy, but
Speaker 5: like these approaches of like getting cancer patient's own immune
Speaker 5: systems to properly recognize and attack the cancers in their
Speaker 5: own bodies has been like incredibly successful and is really
Speaker 5: promising for further developments. It's really amazing, and like there
Speaker 5: have been all sorts of really amazing biomedical advances that
Speaker 5: are currently being destroyed by RFK Junior and Trump. Like
Speaker 5: mRNA vaccines are one of the great success stories of
Speaker 5: you know, biomedical science in the last twenty years. And
Speaker 5: I think that's important, and I think in general, vaccines
Speaker 5: are great. You know, there's all sorts of really wonderful
Speaker 5: technology that we've created that has made the world generally
Speaker 5: a better place, or has at least enabled.
Speaker 3: People to make the world a better place.
Speaker 1: Right.
Speaker 5: In general, technology is a tool, and there are questions
Speaker 5: about how you use it, right. You know, nuclear power
Speaker 5: can be used to build nuclear power plants, but it
Speaker 5: can also be used to make bombs. YadA, YadA, YadA.
Speaker 5: I think I just YadA YadA, nuclear apocalypse.
Speaker 3: But yeah, you did, Yeah whatever. I'm a physicist. Of
Speaker 3: course that's what I'm gonna do.
Speaker 5: But the point is, yeah, of course there's a role
Speaker 5: for technology to play in shaping our future.
Speaker 3: It's just not two things.
Speaker 5: Technology is not the only thing that shapes our future,
Speaker 5: and the development and future direction of technology is not inevitable.
Speaker 5: Technology is something that humans make, and the future development
Speaker 5: of technology is filled with contingency and human choice. It
Speaker 5: is not like we build every single technology that it
Speaker 5: is physically possible to build. It's not on rails. It's
Speaker 5: not like it's you know, the analogy I make in
Speaker 5: the book, It's not like a tech tree in civilization, right,
Speaker 5: where like the future of technology is just sort of
Speaker 5: revealed to us and we have we just make a
Speaker 5: choice about which branch we're going to pursue first.
Speaker 3: That's not how anything works.
Speaker 1: All right. Well, thanks Adam for coming on, and let's
Speaker 1: hope that chat GBT desk your cancer before any of
Speaker 1: us get it.
Speaker 2: Thanks for being on the show, Adam absolutely. Daniel and
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