How long will Moore's Law continue boosting computing power? (featuring Dr. Adam Becker)

Daniel and Kelly discuss the future of computing and talk to Adam Becker about what it all means.

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Episode Transcript

Speaker 1 (00:07):
I feel like an old man whenever I buy a
new computer. I mean, why does my laptop need sixty
four gigabytes of memory? When I learned to program on
a PC that had twenty kilobytes? No joke. Kids these
days don't understand how hard we had it back in
the day. Right, But it's also a nice feeling. It
tells me that we're making progress and that's good. It's

(00:29):
creating new worlds and new ways of life. It's literally
saving lives by accelerating science. That's all great stuff, right,
But how long can it go on? What is the
engine of this exponential growth in computing power? And can
we count on it to take us to the stars,
to cure cancer and to develop self driving toothbrushes. Today

(00:51):
we'll dive into the physics underlying this trend and ask
whether there are fundamental limits that could block us from
achieving our dreams. And we'll talk about whether there's danger
and assuming technology will solve all of our problems. Welcome
to Daniel and Kelly's Extraordinary Universe.

Speaker 2 (01:21):
Hello. I am Kelly Wiener Smith. I study parasites and space,
and I realized when we were starting to do this
episode that I wasn't one hundred percent clear on what
mores Law meant exactly.

Speaker 1 (01:31):
Hi, I'm Daniel. I'm a particle physicist and I've been
programming computers for more than forty years. They get faster
and I get slower.

Speaker 2 (01:40):
Oh you're not slowing down yet, Daniel, you stab.

Speaker 1 (01:45):
So my question for you today, Kelly, is what was
your first computer? Let's age Kelly.

Speaker 2 (01:52):
Okay, So later when we talked to Adam Becker in
our interview, he mentions that there was a while there
where folks wouldn't get a computer because you'd wait as
long as you could, because the computers kept getting so
much better so quickly that if you could wait, your
computer would be much better. Yeah, and so my family
waited way too long. We didn't get one until I
was in like high school, and I know, and I

(02:15):
don't even remember what it was. But in the meantime
I had to write my essays on like it was
like a brother typewriter, but it also had a little
electronic screen, and so I could very slowly and laboriously
click through my essays and then I would print it
and something would be wrong. It would take me forever
to find where the error was. It was very annoying.
But what about you, did you have like the first

(02:36):
Apple computer? Ever?

Speaker 3 (02:38):
Oh?

Speaker 1 (02:38):
Apple was way too advanced. I go way before that.
What My first computer was a Commodore VIC twenty, which
I think had twenty kilobytes of RAM, and we stored
stuff on an audio tape, you know, like you write
a little program and then you'd stored on these cassette
tapes that you could later listen to and like, ooh
what does that sound? So yeah, we were very very early.

(03:00):
In fact, I remember hanging out with my dad in
grad school while he was doing his research and he
was literally feeding punch cards into those punch cards machines.
So I feel like I've personally experienced a huge fraction
of the transformation of computers into the basically supercomputers we
have today. I mean, my smartphone is so much more
powerful than anything my dad ever used in his research.

Speaker 2 (03:23):
That is absolutely amazing. I didn't even know that we
were storing data on like cassette tapes. Oh yeah, that's
amazing to me.

Speaker 1 (03:29):
Yeah, before magnetic floppies for sure.

Speaker 2 (03:31):
So when you like are using your are you a
MacBook guy?

Speaker 1 (03:35):
I am? Yeah.

Speaker 2 (03:35):
It's like when you're using your Mac Do you every
day think I am so lucky I'm not doing this
on punch cards or you just do you take it
for granted? Now?

Speaker 1 (03:43):
I think it's awesome. It's incredible. I mean every time
I get a new MacBook, I'm like, while, this drive
is ten times bigger than anything I've ever seen, and
the memory is just shocking. And it's also then incredible
to me how rapidly our computational ambitions grow. You know,
my group does a lot of computation, and we're basically
limited by computation, and so every time we get more

(04:05):
powerful computers, we scale up our ambitions and solve bigger,
harder problems, and so we're always at the edge of
what the computers can do, right, Like, we have an
infinite number of questions we could ask with harder computers.
So yeah, I'm in awe of the MacBook, not just
because it's so much more powerful than anything I've used,
but it's so reliable. I mean, I spend hours and

(04:26):
hours a day in front of this thing. It almost
never gives me problems. So yeah, it's incredible. What engineers
have provided it is incredible.

Speaker 2 (04:34):
And today we're going to talk about one way in
which that incredible ability has been expanded, which has to
do with Moore's Law, which I thought was about how
much data you can store on your computer, and I
think it's much more than that.

Speaker 1 (04:47):
You're right, it's much more than that. It's also about
how things are growing over time and how long that
will continue. And there's this lore about Moore's Law which
is permeated Silicon Valley and broader culture. So in a minute,
we're gonna also talk to Adam Becker about how this
has impacted philosophy and politics and policy and how it
might affect our future. But first we wanted to know

(05:10):
how long people thought Moore's Law might continue to make
all of our computers faster. So I went out there
and I talked to our group of volunteers. Here's what
they had to say about the future of Moore's law.
So I'll give it six years and then I'm gonna
sell my nvidious stock. But quand computing will change the game.

(05:32):
We are restricted by things like housmow.

Speaker 4 (05:36):
We can make stuff, so I think it's not true anymore.
My first thought was to sign no, but I know
very little bit quantuine computing. I would say until the
computer speed, which just be the light maybe ten years,
another good decade or so.

Speaker 3 (05:54):
My understanding is that it's already done.

Speaker 1 (05:56):
I don't think we are doubling in raw processing speed.

Speaker 4 (06:01):
In my understanding, Moore's law kind of slowed down for
laptop desktop chips a number of years back, but has
continued with mobile just because they were a little behind.
But then you also have graphics and neural processing units
that power our AI platforms of today. So can we
go into the future. I think we can go for
a number more years, given the innovations in transistor stacking.

Speaker 2 (06:26):
I thought Moore's law had to do with cost decreasing
as speed increased. We do seem to be close to
a tipping point with electrons being too large for the
tiny circuitry. However, it seems that optical circuitry might be
a good replacement for that.

Speaker 1 (06:41):
They're currently reaching the lower limits of workability before they
start reaching quantum effects. With silicon.

Speaker 3 (06:51):
We are getting closer to the particle level and that
stops us.

Speaker 1 (06:56):
Honestly, I thought it had already stopped. So do you
think these are optimistic or pessimistic?

Speaker 2 (07:02):
I mean I think they're realistic, which seems to be
the option that always gets left out. So I think
there were a lot of people who said, you know,
I thought we've already reached the limits. So we're getting
close to reaching the limits. And I'll admit that I
did not realize we were getting close to reaching the limits.
But it seems like a lot of our listeners are
on top of this trend.

Speaker 1 (07:20):
Yeah, and so we're not giving financial advice. So I
won't tell you whether or not to buy or sell
in Vidia stock. But you know, sometimes I wonder about
these tech companies because their stocks also seem to follow
Moore's law, Like, how can Google just keep getting more valuable?
I keep missing out on buying Google.

Speaker 2 (07:38):
I can tell you that if you can make a
time machine, one of the first things you should do
is go buy in VideA and Google stuff.

Speaker 1 (07:44):
All right, So let's dig into it. What in the
end is Moore's law? So Moore's law was something postulated
by Gordon Moore.

Speaker 2 (07:53):
He has a first name.

Speaker 1 (07:58):
And he was one of the found of Intel, so
a big dude in like, you know, semiconductors and electronics.
And he suggested initially that the number of transistors you
could squeeze onto a chip would double every year. And
it's a little bit more complicated than that. He also
was talking about the power usage and the cost, but

(08:19):
roughly speaking, he was talking about the density of transistors
on chips getting higher every single year, which means the
speed of these computers is growing very quickly.

Speaker 2 (08:29):
So transistors are about speed and not storage, or are
they about both?

Speaker 1 (08:34):
They're about both. The transistor fundamentally is a tiny programmable switch.
And the reason that computers got small and got fast
is because we were able to make transistors small and
make them fast, which allows us to have lots and
lots and lots of switches in a small area, which
is what allows the computer to be complex and to
be fast. And so essentially it's saying we can make

(08:54):
computers denser every year, and that makes computers faster and
more powerful.

Speaker 2 (08:59):
Okay, so this has to do with why we went
from computers that took up entire rooms to something you
can now stick in your bag and take with you.

Speaker 1 (09:06):
Yeah, exactly, And we'll dig into that in a minute.
But the history here is that in nineteen sixty five
More predicted this and then ten years later he revised it.
He was like, well every year, maybe that's too optimistic.
Let's go for every two years. And so that was
the prediction in seventy five, and you'll see that it
mostly held up until fairly recently. It's sort of an

(09:27):
extraordinary prediction in that sense, though. You know, anytime there's
a prediction that holds up, you got to wonder, like, well,
what were the other predictions this person made, Like you
just spew predictions constantly, Eventually you're goind of get one Ris.

Speaker 2 (09:39):
Yeah, yeah, well, especially he gave himself another decade to
like fit the trend line. That was pretty generous to himself.

Speaker 1 (09:45):
But okay, exactly, So let's dick into what a transistor
is and why it allows computers to be faster, because
that's crucial to understand why More's law has worked, how
we've made it work, and whether it's going to work
in the future. Basically, a transistor is a programmable switch
like computers operate on digital logic. I have a number
in the computer, the number four. They store it in binary.

(10:07):
But to store things in binary you need a physical system.
But that can store a zero or a one right
the way you can like write a digit on a
piece of paper. That's like I'm representing the number four
by scratching this graphite onto this sheet of paper. I
want to store things on my computer and zeros and
ones because binary is the code for computers, and physically

(10:28):
that means a switch, you know, as you can imagine
either just like literally like a light switch, but here
we're doing an electronic switch.

Speaker 2 (10:36):
Okay, And so just to if we switched from using
transistors to things like DNA to store data or quantum computing,
could you still apply More's law, like if we switched
to some other method or is More's law specifically about
the transistors that we're talking about now, Yeah.

Speaker 1 (10:55):
Great question. You're talking about fundamental changes in how we
do computing. So currently computing operates on bits, zeros and ones,
and we're saying those are represented by transistors, which is
like a physical implementation of that bit. You switch to
quantum computing, the fundamental element of that is a cubit,
which isn't necessarily a zero one. It has the probability
to be in several different states, and so it requires

(11:16):
a different physical system to model that. We don't use
transistors or not even like quantum transistors. In fact, transistors
are already relying deeply on quantum mechanics, so quantum transistor
is redundant. But yeah, cubit, there's no guarantee that you
can like build cubits and then build them more densely
and more rapidly. There's certainly no More's law for quantum
computing that's a guarantee. And biological computing like DNA is

(11:40):
super awesome as an idea, but there you have like
four possibilities, right, DNA is basically base four, and so
it's a question of like how do you encode numbers
into DNA? Do you use all four bases? Do you
group them into two to make binary? The technology is
fundamentally different, So again you wouldn't expect necessarily further to
be more solved, but you might get some other law

(12:00):
which could be better. So but yeah, Mores law reflects
the details of the technology we're using to represent the
fundamental element of computing, which is a zero or one,
and then crucially the logic that operates on those zeros
and ones.

Speaker 2 (12:14):
Let's get into that logic.

Speaker 1 (12:15):
Yeah, because what you want to do is represent like
numbers in your computer. I want to put the number
four in but also I want to calculate stuff. I
don't just want to write four into my computer. I
want to be able to add four to two. I
want to be able to compare four and seven. Right,
That's what allows you to program a computer for it
to do useful computation. And if you know something about computing,
you know like the basics of computation is a Turing

(12:36):
machine which can like read in numbers and write numbers
onto this infinite tape. And so in order to do logic,
you need to be able to have things that respond
to different inputs. So in logic you have things like gates.
Like a not gate is something which if you give
it to zero, it responds a one. If you give
it a one, it responds to zero. It's like a

(12:56):
logical map from inputs to outputs, or an a gate. Right,
an and gate gives you a one if both inputs
are one and a zero otherwise. Or the converse of
that is a nand gate NA n D, which is
the combination of an N gate and a knot gate.
And the really cool thing is that if you can
build a nand gate, you can build any logical map

(13:19):
nandgates are like the basis function of logic. So if
you have nands, people have shown that you can build
any map from inputs to outputs and essentially any sort
of computer logic. So you can build knot gates and
and gates out of transistors. Transistors are like this digital switch,
and we'll go into the detail of the physics of
how they work, but essentially they're a programmable switch. You

(13:40):
can turn them on or off in response to other stuff.
So from that you can build logic, and from that
you can build nandgates, and from that you can build
literally anything like adders and comparitors and anything you need
in computers. So this is like the basically the smallest
little lego brick of computing is a switch, a programmable
switch that goes from zero to one. And that's what

(14:00):
a transistor is an implementation of. And it didn't have
to be a transistor. It could have been something else.
It could have been DNA, it could have been whatever.
But this is like the best, fastest, smallest thing that
we have invented, and this is what revolutionized our society.

Speaker 2 (14:14):
What does the transistor look like?

Speaker 1 (14:17):
Yeah, what does the transistor look like? It looks like
nothing because it's super duper tiny, right, Like the ones
that we're building these days are order nanometers right, so
like you put one on your finger, you can't see it.
The number of transistors on a typical chip is billions,
so you can't see an individual one. There used to
be able to, like when they were first building them
in the fifties, you would like make one, you know,

(14:39):
on a bench. You could think of it as sort
of like three wires coming together. You have a source,
a drain, and then a gait and the gate basically
decides do I connect the source and the drain Do
I open or close this switch? And so it's sort
of like a wire with a lever in it that
you know you can open or close, and then another
wire that determines what whether or not that's open or closed.

(15:02):
So that's not a physical description of what they look like.
We can get into like the semiconductors in a minute,
but that's sort of the logical construction. And when I
think about more's low, I think, well, what is exactly
is the connection between more transistors and speed? Like it's
cool to have things small because then you can put
a computer in your watch or whatever. But why do

(15:22):
smaller computers operate faster? Because that's really the crucial key.
When you sit down at your laptop, you're not like, wow,
the transistors are super dense. You're like, wow, you know
word opened in a bill a second instead of you know,
spinning my beach ball forever. Yeah, So it's the speed
that's really crucial, and that's really transformed society. Right, it's
computational power and miniaturization means faster operation for a few reasons.

(15:49):
Number one, things just don't have to go as far. Right,
Electronics is limited by the speed of light. It's not instantaneous.
You close a switch, the electrons don't move instantly. Right,
the current doesn't change instantly, and so we are still
limited by the speed of light. And so if the
distances between the transistors are smaller and the transistors themselves
are smaller, things just happen faster because there's a speed

(16:11):
limit to information in the universe.

Speaker 2 (16:14):
That's awesome. I guess I hadn't imagined that as a
limiting factor. Okay, super cool, what's next.

Speaker 1 (16:20):
Yeah, that's one. The other is you can have wider
data paths, like instead of just using thirty two bits
to store your numbers. You can use sixty four bits, right.
Remember bits are this essential element of binary numbers, and
so if you have like a two bit number, you
can only store between zero and four. If you have
an eight bit number, you can store many more numbers.
You have thirty two these days computing a sixty four

(16:42):
one hundred and twenty eight bit If you hear about
these numbers as the sort of the core the computing
of your CPU or your operating system, that's what it describes,
like what size numbers are we operating on? And this
is important because basically it's how much your computer can
do in parallel. Like if you can add two hundred
and twenty eight bit numbers, it's really one hundred and

(17:03):
twenty eight bit wise operations done in parallel instead of
if you're doing sixty four bit numbers, then you're only
doing sixty four operations in parallel, and so you can
do more operations in parallel, You can pass more data
at the same time, and so data flows more quickly.
Another thing that really limits the speed of computers is

(17:23):
how long does it take to get the data into
the actual CPU. Right, Like you have these numbers in memory,
you want to do some calculation on you got to
slurp them from memory and put them into the registers
in your CPU. They're actually doing the comparisons or the
adding or the subtracting or whatever. And so the wider
the data path, the faster the data gets loaded, and
the faster the computation happens.

Speaker 2 (17:45):
And CPU probably means senorebditis pyro wetting underwater. What does
CPU mean?

Speaker 1 (17:54):
CPU means central processing unit. It's a thing on your
computer that does the actual crunching, does the adding or
subtracting or comparing, or loading or unloading or writing to
memorates the closest thing we have to a digital brain. Okay,
but there's another sort of mechanical element to like why
speed means faster computers. And you know, back in the

(18:14):
nineteen fifties, people were doing electronics, and they're doing it
sort of the way you might do it in your garage.
You got resistors, you got capacitors, you solder them together,
you make these big sort of physical circuits. But in
the late nineteen fifties people invented what's called the integrated circuit.
Integrated circuit is just like you know, it's a big
green board and it's got the whole circuit printed onto it.

(18:35):
You don't like solder the components together, and this really
allows for like the embedding of these transistors and other
components inside these protective layers, which enhance their reliability. And
so that means you can make them smaller, you can
make more complex circuits that you didn't have to like
wire together yourself with dripping hot bits of solder, and

(18:55):
so this makes them more reliable, so you don't need
as much error correction, et cetera. And that allows things
to be smaller and to be faster. So you've got
integrated circuits, you got wider data paths, you got shorter
distances to travel, and you have faster switching. All these
things are why more transistors means faster computing.

Speaker 2 (19:13):
Okay, And so when did we get our first transistor?

Speaker 1 (19:16):
Yeah, so the transistor was invented in Bell Labs in
nineteen forty seven, I think it was. And there was
a lot of research in the forties different kinds of
technologies for transistors. Try this, try that, try the other thing.
But the basic concept was invented in the late forties
in Bell Labs and you know, Bell Labs is one
of these like elements of another era, an institution that

(19:37):
I really miss. You know, it's a privately funded research
lab that did basic research. You know, this is an
arm of the telephone company. But they just like gave
nerds money and said, hey, play around, figure stuff out,
and they came up with things like the transistor, which
is I think a trillion dollar idea would be underestimating it, right, Like,

(19:57):
it's literally the foundation of our entire economy. Its transformed
the way we live.

Speaker 2 (20:02):
Wow.

Speaker 1 (20:03):
And so I think even if every other piece of
science was a waste of money, this one brings the
average up like this one idea like means all of
science has been worthwhile just from a purely economical, cynical
point of view. And that's the way science works, right,
like a lot of fuzzes out and occasionally a huge,

(20:26):
huge payoff. Anyway, it was the late nineteen forties people
figured this out. And you know, we've only had quantum
mechanics for a couple of decades.

Speaker 2 (20:34):
Then.

Speaker 1 (20:34):
People had ideas for making transistors before then, but weren't
able to make it work. But at Bell Labs, smart
guys figured this out. One Nobel Prizes. It was really
pretty awesome.

Speaker 2 (20:44):
Awesome, And when we get back, let's talk about how
we went about shrinking these transistors. All right, So in

(21:10):
nineteen forty seven, Bell Labs creates the transistor just in
time for us to use it to get to space,
which is the most important topic that we have to
keep getting to every episode. All right, So now we've
got the transistor, how do we go about shrinking it?

Speaker 1 (21:24):
Yes, the transistors are built out of semiconductors. You know,
you hear the semiconductor industry everywhere, And what does that
really mean? Well, we understand what conductor is, right, It's
something where electricity can flow. An insulator is something where
electricity cannot flow. And to understand that, you have to
take your vision of the atom where you have like
electrons orbiting around the nucleus or being in fuzzy quantum

(21:47):
mechanical states, and think about what happens when you put
a lot of atoms together, Like, what is the energy
level of an electron around an iron atom? Well, it's
a bunch of levels. What happens when you have a
billion iron atoms and a lattice, what happens to those electrons? Well,
they don't really belong to any individual nucleus anymore. They
sort of like move around the iron super highway. They

(22:08):
can flow around from here to there. And what distinguishes
a conductor from an insulator is whether or not there's
a big gap between energy levels, like can the electrons
get up to those energy levels where they can flow
around between all the atoms or not. If they can
get up there, then it's a conductor. If there's a
really big gap so they can't get up there, then

(22:30):
it's an insulator. Semiconductors are things that are sort of
halfway in between. They have a medium sized gap between
the energy levels where the electrons are stuck around individual
atoms and the ones where they're just flowing across the
super highway. And so that's something you can control. If
you tweak it a little bit by like adding them
a little bit of germanium or this other kind of thing,
you can control that gap. And so what you want

(22:53):
when you're building circuits is you want places where things
conduct really well and then places where things conduct really
really terribly. So rather than having to have different kinds
of material, like if I build a circuit in my garage,
I use copper for the wires and then to use
rubber for the insulators. It's better if you can have
a single kind of material and sort of tweak it
and like, okay, I'm going to make this part of
it conductor and that part of it an insulator because

(23:15):
it allows you to print circuits onto your material.

Speaker 2 (23:18):
Okay, And so what is the material you use?

Speaker 1 (23:21):
So we use silicon. Silicon is the semiconductor of choice,
and then you dope it with various things to change
its behavior to make it a conductor. And the way
that we have shrunk transistors from pretty big stuff you
could see on your garage bench to tiny stuff almost
the size of atoms is through a technique called photolithography,
which essentially prints a circuit onto a piece of silicon.

(23:44):
We grow these huge silicon wafers that are like ten
inches and then you want to print a circuit onto it,
and you want to print like billions and billions of transistors,
and you want them to be as small as possible.
For the reason we just point it out, So like,
how do you print this stuff onto a piece of
sar silicon? So this is what photolithography is. Essentially, you
design your circuit on the computer, and then you print

(24:07):
on the surface of the silicon this thing called a
photo mask, and the photomask like protects the silicon from
the next thing you're gonna do to it, which is
blast it with really high energy light. So you shoot
like super high energy light at the silicon which is
partially covered by this mask, and the parts that are
exposed get a little bit chemically changed. Then you dip

(24:28):
the whole thing in like acid, and the parts that
we're exposed get like eaten away, for example, and so
what you're left with is just the pattern that you wanted.
That's like a very hand wavy explanation of how photolithography works.
But the things to understand is that it's limited by
those photons. Like if you use photons that we really

(24:48):
wide wavelengths, then you're going to get a fuzzy picture.
If you use photons with really narrow wavelengths, which means
high energy photons, right, then you're gonna get a much
crisper picture. And so over the decades, we've been trying
to shrink these transistors to get more and more transistors
on these chips and have faster computers. And one way
to do that is to crank up the energy of

(25:10):
those photons, and so now we're in the like extreme
ultraviolet limit where the photons have a wavelength of like
thirteen or fourteen nanometers. Wow, And that's hard because it
requires like special optics. You can't just use normal lenses
to bend this kind of light. It's why it's very
hard to do, like X ray optics. Also, the higher
the energy light, the harder it is to bend it.

Speaker 2 (25:31):
Have we maxed this out?

Speaker 1 (25:32):
We probably have maxed this out, because anything beyond this
requires insane optics. Like already the optics are insane. You know,
making a single mask for these things costs like hundreds
of thousands of dollars, and there's like a few places
in the world you can do this kind of stuff.
The equipment is extremely expensive, the operating conditions are very

(25:53):
very particular. You have to have specialized clean rooms. Like
this is really the pinnacle of technology. It's incredible, and
that's why you know a few of these players in
this field, like the Taiwannee semiconductor industry is so important
for the worldwide computing industry. Like a single company goes
down and like we can't make computers anymore.

Speaker 2 (26:14):
Wow, Oh my gosh. Right, all of the geopolitical tensions
just came into focus exactly.

Speaker 1 (26:19):
That's one reason why Taiwan is so important because a
lot of this stuff is done by Taiwan, these firms.

Speaker 2 (26:25):
All Right, so we figured out photo lithography and we've
kind of reached the limit. Yeah, is that the end
of the story.

Speaker 1 (26:32):
It's not quite the end of the story. And you know,
I'm more to say about like how impressive it is.
Like in the mid nineties, we were doing things at
like three hundred and fifteen nanimeters scale, which sounds pretty awesome,
Like that sounds pretty tiny. And then late nineties it
was like one hundred and eighty animeters, and the two
thousands it was sub one hundred nanimeters. These days we're
getting down to like ten nanimeters single nanometers. It's amazing,

(26:56):
but it's getting harder and harder because we're already beyond
the wave length of the light that we're using, right,
and we're approaching the size of the atom. Right, silk
and atoms are like zero point two nanometers across, so
like you're going to be bild a transistor out of something.
It's like you know, you can't make things out of
legos if you only have a few of the bricks, right,

(27:17):
And so it's challenging to make transistors smaller than about
a nanometer because you're really reaching that fundamental limit of
the size of the silicon atom. And every year it
gets harder. Like it's true that we've increased the transistor
density every two years, we've doubled it, but the amount
of money spent in this research has increased by a

(27:39):
factor of ten or twenty, so it's not like a
constant effort every year to achieve this. We have to
ramp up the energy and the creativity. And that's great,
you know, it's like inspired all sorts of cool things
and spinoffs and whatever. But it gets really really complicated.
And the sort of cutting edge of this is to
now start stacking these transistors, so well, don't just think

(28:01):
of it as a plane. Let's go up in the
third dimension. Let's make the transistors more powerful by shrinking
them further and then allowing them to grow in sort
of the third dimension above this sort of plane. And
the leading edge of technology right now are these transistors
called fin fet so FET, which stands for a field
effet transistor and then a finn meaning like they literally

(28:24):
have this like fin over the gate that controls it
like a physical thing. It looks like a shark fin.
That makes it possible to be efficient while shrinking even further,
so you can make the sort of footprint of it
smaller while keeping its effectiveness because you have this third dimension.
And so that's what stacking is. And really people think
that we've reached the limit of what we can do technologically,

(28:46):
and as some of the listeners have said, we're going
in other directions, like instead of making your CPU more dense,
you just have multiple cores, or you start building other
dedicated stuff like graphics processing units that are really good
at linear algebra, which is needed for graphics and also
for machine learning. And so we're sort of like simultaneously
trying to go in many directions at once to improve

(29:08):
the power of computing. But it's not clear that we
can keep doing this, and a lot of people think
that we really are at the edge of what we
can do to improve computing speed.

Speaker 2 (29:17):
Wow, and so stacking isn't going to be the magic
solution because there's like limits on stacking.

Speaker 1 (29:22):
Yeah, exactly, like stack can get you a little further.
But if we're going to keep doubling, then it's hard.
And you know, I think there's something to be said
about the sociological impact of this doubling. You know, Moore's
law is not something that comes out of like the
fundamental laws of physics. It's something that was predicted and
that we maintained really over decades, which is really incredible.

(29:43):
Like one of Intel's earliest processors, the four thousand and four,
had twenty three hundred transistors in it, right, whereas like
the eighty three eighty six, which I've spent a lot
of time programming on as a teenager, had like hundreds
of thousands of transistors in this MacBook I'm sitting in
front of has billions. It's incredible, but it's sort of
guided the field. I think people because they thought this

(30:04):
was possible and maybe even inevitable, they worked for it.
It's a target, you know, And so if you think
something as possible, then like you stay late and you
push hard and you come up with new ideas, and
so in some sense it's a self fulfilling prophecy.

Speaker 2 (30:19):
Okay, so first of all, have we hit the limit
to More's law? Already, or you just think we're going
to hit it soon, Like when is the first year
you think where we'll be like Moore's law gone.

Speaker 1 (30:30):
I think we're right at that inflection point. You know,
we're still seeing improvements in speed, we're still seeing big
boosts and productivity, but we're sort of running out of
avenues and so I still see that, Like my MacBook
is faster than the one I gave my son, which
is my two year old MacBook, But I don't know
that the one I'm going to get in two years
is going to be as much faster. So I think

(30:53):
we're right at that inflection point.

Speaker 2 (30:54):
So that feels a little scary to me. So, like,
you know, over time, we've gotten computers that are better
and so at least, you know, in my field, almost
every five years you expect, you know, the statistical models
of the systems that we study to get more complicated
so that we can get a better understanding out of
each one of our data sets. Are we not going
to be able to do that anymore? Or do you

(31:15):
think in twenty years our computers are just going to
start getting bigger again until they fill up a room,
Because we're going to want to keep getting more complicated
in our analyses.

Speaker 1 (31:24):
Yeah, well, I think we're already seeing our computing getting bigger.
I mean, think about like the data centers that are
being built by Meta and Microsoft is like trying to
turn back on nuclear reactors because they need the power
for their AI data centers. These things are vast and
they're consuming huge amounts of our resources. So I think, yeah,
our appetite for computing is just growing, and even if

(31:45):
our computers don't get faster, we're just going to keep
building them bigger and bigger. But I also think that
for those of us who do things that are not
directly just computing, that there are other ways to increase speed.
I was talking to Katrina about this, and she was
saying that Moore's law also kind of applies to genomics.
You know, like the first study of a human genome

(32:05):
costs like how many millions for one genome, And then
the NIA had a target like it should cost less
than one thousand dollars to sequence a human genome, and
they hit that target and now it's cheaper than one
thousand dollars. And where does this come from? Part of
it come from computing, but also part of it comes
from like the miniaturization of biology. And I've seen this
just like observing her field. Something that used to be

(32:28):
like a PhD level of work then in a few
years becomes a little box on the lab bench. You
press a button and it's done while you're at lunch, right, Yeah,
and that allows you to now do things that were
impossible ten years earlier. And that kind of transformation of
the scope of the capacity of the field enables broader,
deeper thinking. And that's not just computing, right, that's the

(32:49):
menigtization of like the actual biology, like micro little bits.
It's essentially like what therapnose was tapping into this feeling like, oh,
eventually we should be able to diagnose diseases with tiny
life jobs of blood in this kind of sense. So
I think that there's lots of dimensions that we can
follow for improving our scientific and technological industrial capacity. Is

(33:10):
not just is my computer faster.

Speaker 2 (33:13):
So when someone says, like you just did such and
such follows Moore's law, do they essentially mean we do
it better with smaller stuff, and like we do it
exponentially better in particular.

Speaker 1 (33:27):
Yeah, I think it's about exponential growth that's a crucial
thing because you know, exponential growth builds on itself. You know,
it's like putting a dollar in the bank. Every year
you have more dollars, and those dollars earn more dollars,
and eventually you have all the dollars. Whereas like if
you're just selling lemonade and you're making a dollar every day,
you're making the same amount of dollars every day. It's

(33:48):
not increasing. So it's all about that exponential growth. And
I think that that's what people mean when they refer
to Moore's law sort of more colloquially than just like
the density of transistors on a chip.

Speaker 2 (33:59):
That's kind of interesting because like Moore's law isn't really
a law, like it's an observation. And so it seems
like now anytime we see exponential growth, we say the
words Moore's law instead of just saying exponential growth or
am I being negative?

Speaker 1 (34:14):
No? I think you're right, And I think it says
something about our aspirations. You know, we live in a
time when we expect our children's lives to be very
different from our lives and our grandparent lives, and that's
really unusual, Like most of human history. You could tell
your kids what their life was going to be like,
because it's going to be basically the same as yours
and your grandparents for like the last ten thousand years, right,

(34:37):
because like change was inconceivable because nobody had ever experienced it.
But now we live in a time when, like we
know that's not true, and so I think it leaves
us with this like gap in our wisdom. And then
we project forward, and some of us are optimistic and
we're like, Yay, this is going to change our lives
in a way that solves all of our problems. And

(34:57):
as you'll hear from Adam, some of us are less optimistic,
you know, about what this means and whether it's the
right way to place our bets.

Speaker 2 (35:05):
I do feel like that was a slightly simplified view
of history, But this isn't Daniel and Kelly's historical universe.
So we're moving on.

Speaker 1 (35:12):
Hey, I have to fit it into about one minute,
so I'm not going to do a deep dive. But yeah,
I mean, do you disagree with me about the broader
assessment of the way that human experience has changed.

Speaker 2 (35:22):
I do think human experience was similar for a really
long time. You know, like when our ancestors moved out
of Africa, there was probably a lot that changed in
a couple generations, and the Industrial Revolution and climate. Yeah, yeah,
I think there's probably been a lot of moments where
things were like, oh crud, but usually probably they were
getting worse, whereas now we're hoping that it's getting better.
But anyway, so when I was reading Adam Becker's new

(35:47):
book More Everything Forever, there was a discussion on Moore's
Law where I realized, like, oh my gosh, I fundamentally
didn't understand Moore's Law very well or what like underpinned
Moore's Law, and I didn't realize that we were, you know,
perhaps reaching the end of Moore's Law. And so we
reached out to Adam Becker and asked if he would
talk to us about sort of the implication of, you know,

(36:10):
the death of Moore's Law. I'll be super dramatic about it,
but how this expectation of exponential growth impacts our view
of the future in ways that are not always necessarily realistic.

Speaker 1 (36:22):
Let's say, all right, so then we're very happy to

(36:44):
welcome to the podcast. Adam Becker, who is an astrophysicist
turned author. He wrote the widely acclaimed book What Is Real,
one of my favorite books about quantum chinnings. If you
write me to ask for a book about quantum mechanics
that explain stuff in an accessible way, often recommended. And
he has a new book out called More Everything Forever

(37:06):
about the rise of techno utopiasts and how we can
project our future and the future of technology. Adam, Welcome
back to the podcast. Thanks, it's great to be here.
So let's start just by talking about Moore's law. It's
the foundation of so much of the techno utopian movement.
Why do you think that it has inspired sort of

(37:27):
this broader fanaticism, especially when it's just like an empirical observation,
not like a deep law of the universe.

Speaker 3 (37:34):
Yeah, that's a good question.

Speaker 5 (37:37):
I mean Moore's law. Yeah, it is an empirical observation.
But it's so regular, it's so comforting, and it has
you know, the fact that Moore's law held more or
less accurately for what about fifty years. It did change

(37:58):
a lot of things about the world, and it took
computers from being these large, slow, you know, refrigerator sized
things that live in mainframe rooms at corporations to you know,
tiny little things that live in our pockets, are on
our wrists and have much more power than all of

(38:20):
the main frames that existed, you know in the nineteen
seventies combined, right, caused all sorts of changes in our society,
some for the better, so much for the worse. But
you know, living through that, it seemed like clockwork, right,
you know. I mean I only lived through like the
last part of it, But I remember when I was

(38:42):
a kid, it seemed like, you know, computers were just
always getting smaller and faster and better every single year,
and you could just get you know, the advice was
wait as long as you can to get a new computer,
because the longer you wait, the better it'll be. Right,
And it was this amazing thing, and it made a
lot of people a lot of money, and a few

(39:03):
people truly enormous amounts of money. And so you put
all of that together and it's it kind of makes
some sense that some people would take it extremely seriously
as this general thing, because it seemed to be, you know,
if you lived a comfortable middle or upper class life,
it seemed like the most important thing in the world.

(39:24):
In the late twentieth century, right, and it wasn't really
like anything that you'd seen before. It was easy to think, oh,
this is just going to continue. So Ray Kurzweil is
this inventor and futurist who you know. He made like
real serious contributions to text to speech technology and like

(39:46):
assistive devices for the visually impaired, and I think hearing
impaired as well. You know, he made serious contributions to
the field of electronic instruments, like you know, musical instruments.

Speaker 3 (39:58):
But he is best known as a futurist.

Speaker 5 (40:00):
He is best known as somebody who you know, makes
these forecasts about what the future is going to be like.

Speaker 1 (40:04):
So he's a retired electrical engineer, you're saying, essentially, yeah,
I have a lot of those in my inbox.

Speaker 3 (40:10):
Yeah, me too, man.

Speaker 5 (40:14):
I'm pretty sure that if you put anywhere on the
Internet that you have a PhD in physics, you get
a lot of retired electrical engineers in your inbox.

Speaker 2 (40:22):
Guys, my inbox has pictures of feces from people who
want to note the parasite infections. I'm feeling pretty low
on sympathy right now.

Speaker 5 (40:30):
Oh, but I once got so sorry for you guys.

Speaker 3 (40:34):
Yeah, no, we should.

Speaker 5 (40:35):
We should have a separate episode just talking about what's
in our inboxes, because I have some crazy stuff in
any event.

Speaker 1 (40:42):
All right, So you're telling us how Ray Kurzweild was
thinking about how Moore's law is transforming technology and that's
the engine of transformation of society and predicting the future
of society more broadly exactly.

Speaker 5 (40:55):
Yeah, And like Kurzweil extends Moore's Law in his Forecasts
of the Future and says, oh, this is part of
a more general trend in the history of technology and
the history of you know, even life in the universe.
And he calls it the law of accelerating returns, where
he says, you know, once you have better technology, it's

(41:18):
going to allow you to make the technology that you've
already got even better, and then that'll just be a
self reinforcing cycle that leads to this exponential trend. And
More's law is just one manifestation of that trend, and
it's going to you know, he says, it's something that
you can see if you look back through the entire
history not just of human technology, but evolution of life

(41:39):
on Earth, because you see the same thing with biological
quote unquote technology, and he says, you know, this is
going to continue, and in short order we are going
to reach this point that he calls the singularity, which
is where you've got, you know, technology that has developed
to such an advanced degree that it gives us, you know,
godlike powers of creation and destruction and transform and just

(42:00):
changes the fundamental nature of life on Earth and in
the universe.

Speaker 1 (42:05):
Well, a lot of what you said sounds reasonable. R
There is evolution, and there is transformation, and things are
changing more rapidly. But from reading your book and from
your tone, I'm guessing you don't agree with Cursewil about
singularity and how we're all going to be techno gods
in the future. Why not? Why will Daniel not be
a techno god?

Speaker 3 (42:24):
Yeah?

Speaker 2 (42:24):
I mean, look Daniel in particular, Yes.

Speaker 1 (42:26):
Yeah, I have a personal stake in this question.

Speaker 5 (42:29):
Now, yes, Daniel in particular, Yeah, you are not going
to be a techno god, Daniel, because you know, by
having me on this podcast, Ray Kurzwild is going to
put you on his list, and then you know he
won't allow you to ascend to God.

Speaker 2 (42:44):
I knew this was a mistake.

Speaker 1 (42:46):
Yeah, exactly, worse than trying to fight a land born Asia. Huh, yes, exactly.

Speaker 3 (42:51):
Yeah, No, that's number two.

Speaker 5 (42:52):
Now number one is inviting Adam Becker onto your podcast.
But I mean, look, Curzwild is taking this exponential trend
and just extending it out into the future and saying
it's going to last forever. And the one thing that's
always true about exponential trends is that they end.

Speaker 1 (43:10):
Right.

Speaker 5 (43:11):
If you see any sort of exponential trend in nature
or in you know, technology or whatever, your first thought
should be, oh, that can't last, because it just doesn't.
There are not enough resources, there's not enough space, there's
not enough anything to allow exponential trends in general to

(43:31):
continue forever. One of the examples that Churzwild gives in
his book The Singularity Is Near which is probably his
most famous book from about two thousand and five.

Speaker 1 (43:41):
Doesn't he have a few books like The Singularity is Near,
The Singularity is near Er, the Singularity is near Ish?

Speaker 3 (43:46):
Yeah, yeah, yeah.

Speaker 5 (43:47):
The Singularity is Near Er came out last year, and
when I tell people that that's the title, they usually
don't believe me.

Speaker 3 (43:53):
But that is actually the title. He wrote a book
called the singularity is nearer.

Speaker 1 (43:58):
Next year, the singularity is near your ear.

Speaker 3 (44:01):
Yeah, neariest.

Speaker 5 (44:04):
But the classic example in biology of exponential growth is
something like bacterial growth in a petri dish and yeah,
if you chart the number of bacteria in this you know,
nutrient rich medium over time, Yeah, it grows exponentially until
they fill the dish and eat all of the agar

(44:26):
and then they die.

Speaker 2 (44:29):
To try to play Devil's advocates, so when I was
talking to space settlement folks, they would say something like,
you know, the reason we need to go into space
is because exponential growth does end at some point. But
our species is so amazing that we can see when
we're getting close to the like asymptope and the exponential curve,
and so we can go out to space and get
resources and we can be more proactive about it. What

(44:52):
is wrong about that argument?

Speaker 3 (44:53):
Yeah?

Speaker 2 (44:55):
I mean where to start?

Speaker 3 (44:56):
Ye?

Speaker 2 (44:57):
What you got to pick somewhere?

Speaker 5 (44:58):
Okay, I'm going to pick on you know, I'm going
to do what we should all strive to do, or
what I strive to do, and punch up right, I'm
going to pick on somebody bigger than me.

Speaker 3 (45:06):
Jeff Bezos makes the same argument, right, Yeah.

Speaker 5 (45:09):
Jeff Bezos says that we need to go out into
space because of exactly this. He says, you know, we
are using exponentially more energy as time goes on, and
if that trend continues as it has for decades, if
not centuries, then in about two three hundred years, we're
going to be using all of the energy on Earth

(45:30):
that we get from the Sun and will have used
up all of the non renewable resources. And so at
that point we need to go out into space, if
not before, then otherwise we're going to have what he
calls a civilization of stasis and rationing. And you know,
he's not wrong about the first part. If somehow we
continue that exponential trend in energy usage, then yeah, and
I think it's in about three four hundred years, we'd

(45:52):
be using all of the energy available to us on Earth.
And also we'd be using so much energy that like
the waste heat from our energy usage would like boil
off the oceans.

Speaker 3 (46:03):
We can't we can't do that, right, it's not possible.

Speaker 5 (46:07):
I mean, putting aside that, you know, it's it's implausible
that that trend will continue. The problem is with the
second half, because yeah, Okay, we get like three to
four hundred more years here on Earth if you continue
that trend. So Bezos says, we have to go out
into space, and you know what he doesn't say is
where where resources are unlimited, but you know he implies it.

(46:28):
The problem is that if you really want exponential growth
to continue, going out into space, it doesn't actually help
you that much if you're looking on a timescale of centuries,
because if you do that, like about I think it's
like one thousand years after we hit that point of
using all of the sunlight that hits Earth, we get

(46:48):
to a point where we're just using the entire energy
output of the Sun. And then if we spot Bezos
and company a warp drive so they can go faster
than the line to try to amass even more resources
very very quickly outside of the Solar system, which we
shouldn't spot them a warp drive. There's no reason to

(47:09):
think that you can build a warp drive, and a
lot of reason to think that you can't. But if
we do spot them a warp drive, that only gets
you like about another two thousand years before you're using
all of the energy in the observable universe. Wow, so
you know there are limits, growth ends, and the fact
is that you know, all of that is wildly implausible.

(47:31):
It's not like the lesson that I want people to
take away from all of this is, oh, well, we
better keep in mind that growth has to end at
some point to the next like three thousand days years.
The answer is, oh, no, growth has to end a
lot sooner than that, because you know, going out into
space has lots of problems, even putting aside the lack

(47:51):
of warp drive, just living in the Solar System is
an extraordinarily difficult and dubious proposition. To give Bezos a
little bit of cris after ragging on him just now,
one of the things I like that Jeff Bezos has
said is he makes fun of Elon Musk for wanting
to go to Mars because Mars sucks.

Speaker 3 (48:09):
But Bezos's solution is.

Speaker 5 (48:11):
You know, for going out into space, it's not considerably better,
which is to build like hundreds of thousands or millions
of enormous city size space stations and then have everybody
live inside of them.

Speaker 3 (48:22):
This is also not a great idea for many many reasons.

Speaker 1 (48:26):
All right, So it's reasonable, I think to make these
arguments against like the strongest version of those claims. You know,
exponential growth will last forever. Sure, and you're right, that's
obviously practical because the universe is finite, or the observable
part of it is finite at least.

Speaker 3 (48:41):
Yeah.

Speaker 1 (48:41):
Yeah, But what if we just like water down those
claims a little bit and we just say, you know,
technology is transforming society very rapidly, and even the future
you describe as refuting exponential growth. That sounds pretty awesome.
Like if in two thousand years we're tapping into all
the energy from the Sun and nearby stars and have
an incredible, you know, star spanning civilization a lot of

(49:03):
people out there, and be like, that sounds great. What's
wrong with that?

Speaker 5 (49:07):
The prospect of large numbers of people living and working
in space has an enormous number of technological and social
and political questions tied to it that are very very
difficult to solve and may not be solvable. And some
of those problems are sort of irreducibly time consuming. You

(49:28):
can't solve them without doing like lengthy experiments involving things
like radiation exposure and low gravity exposure.

Speaker 3 (49:35):
And things like that. And I see Kelly nodding.

Speaker 5 (49:38):
And you know, Kelly may know more about this than
I do, because you know, this is one of the
subjects in my book. Kelly and Zach wrote an entire
book about this, an excellent book that I really like.

Speaker 2 (49:49):
I do always find a way to pull the conversation
back to space settlement. So sorry for derailing us, but
you do a great chapter on it in your book.

Speaker 5 (49:56):
Yeah, thank you, and you have nothing to apologize for
it's in my book.

Speaker 1 (50:00):
But let me maybe highlight a difference between the takes
you guys have in your books. Kelly and Zach say
that you know, we're maybe not ready to settle space,
that we haven't done the necessary legwork, and we shouldn't
get over excited and jump too fast and send people
to Mars now, because there's a lot of stuff we
need to figure out, but that it's possible and if
we do it right, maybe you could figure this out.

(50:22):
We just aren't there yet. But I feel like your
book goes a step further and suggests that you know
it's dangerous to make these projections. You know, somebody out
there listening might say, all right, Adam, maybe we won't
get there, you know, to as far as these guys project,
but however far we get will be great. What do
you say to that person? Is there a danger in
this kind of thinking?

Speaker 3 (50:42):
Yeah?

Speaker 5 (50:43):
I mean this This gets back sort of to the
last question that you asked me as well, because we
don't know that it's possible to have large numbers of
humans living off of Earth. Because it's very possible that
that's not, you know, something that we can do. We
need to find a way to live safely and healthily

(51:04):
within the limits imposed by Earth. We can't just assume
that we're going to be able to leave. The danger
is that this rhetoric of oh, it's always going to
be possible to expand out into space and grow forever
can be used, and in fact it's not hypothetical. It
is being used to justify this sort of logic of

(51:27):
rapacious consumption that is not sustainable here on Earth.

Speaker 3 (51:32):
And because there's a very.

Speaker 5 (51:34):
Good chance that we cannot in any meaningful way leave Earth,
we need to stop doing that and find a way
to live here.

Speaker 3 (51:42):
That's not to say that we shouldn't explore space. I
think robots in space are amazing.

Speaker 5 (51:47):
Like the voyager probes make me cry, you know, I'm
a cosmologist by training. I think getting data from space
is really important and interesting. I'm not even saying that
we shouldn't send people into space to you know, the
Apollo missions were amazing and really interesting. They were, of course,
you know, not primarily missions of scientific discovery. It was

(52:08):
about the Cold War. But still like the fact that
we did like a crude sample return mission to the
Moon several times and nobody died is amazing. But the
visions that we have of the future are used to
justify all sorts of things right here and now, and
so we need to be careful about what we think

(52:28):
the future is going to look like and whether that's
remotely plausible. And I really think that the things that
Musk and Bezos and these other tech billionaires are talking
about are sort of like saying, you know, yeah, well
it's okay that we're doing what we're doing right now,
because in the future we're all going to live in
like Hogwarts and have broomsticks and magic wands and like,

(52:49):
it's roughly the same level of plausibility.

Speaker 2 (52:54):
And so to try to get us connecting More's law
back with where we are in the conversation. To me,
I see the connection being that you've got this thinking
that we're going to have exponential growth and our ability
to do everything. So like when I was talking to
space settlement people, they'd be like, I'd talk about a
problem and they'd say, well, AI is going to solve
that everything is expanding. Our ability to do anything related

(53:15):
to technology keeps expanding exponentially, and so you know, we've
talked about how we have limits and so you can't
expect exponential trends to go on forever. Do you connect
then this kind of Moore's law thinking with techno optimism
and this these sort of views of the future. Or
have we just gotten off on a different topic.

Speaker 5 (53:35):
No, No, No, I think these things are connected, right, Like,
there's a reason why all of these different things are.
In my book, one of the things that I like
to remind people about when we're talking about Moore's law
is that More's law. It's not just that it's an
empirical observation rather than a law of nature. More's law
was a decision. More'slaw is a choice that the leaders

(53:57):
of the semiconductor industry made, and then they continued making
it for decades, you know, and there was a road
map and lots and lots of different, you know, plans
made in order to ensure the continuation of Moore's law
for as long as possible. There are massive, massive amounts
of money and corporate resources poured into this, and in fact,

(54:18):
Moore's law is not even an example of accelerating returns,
as as Kurzweil would have, but in a sense it's
an example of diminishing returns because they got, you know,
the semiconductor industry got less bang for their buck over time.
They had to spend more and more money, even adjusting
for inflation, just to get the same doubling of the
number of processors crammed into the same space. The techno

(54:42):
utopian sort of ideas that Kurzweil pushes using Moore's law,
as you know, sort of the justification and this you
know eternal expansion into space stuff that we've just been
talking about, they all sort of traffic in the idea
that the future of technology is not just eternal exponential
growth and expansion, but that it's inevitably that not that

(55:06):
that's you know, something that we could do, but that
it's it's what we have to do. It's what is
going to happen, and the only alternative, if there is one,
is the extinction of the species. And you know, again
Musk is extremely clear about this. Musk has said the
only choice we have is eternal expansion out into cosmos

(55:26):
or extinction. And when he's pushed on this, he, you know,
he brings up the fact that you know, in about
half a billion or a billion years, it's going to
get so hot on Earth because of you know, the
sun getting hotter, that the oceans will boil off. And yeah,
that's not wrong, but you know, a lot's gonna happen
between now and then. Not only is it not a

(55:48):
particularly pressing problem, but it may not even end up
being our problem at all, because there are many other
things that could cause humanity to go extinct between now
and then, like say, civilizational collapse due to global warming,
for example, a problem that tech oligarchs and other billionaires
have done a lot of work to try to prevent

(56:10):
humanity from solving. But instead Musk says that the solution
is to leave Earth. And this is the sort of
rhetoric that I was talking about, you know, in terms
of like, this is what this eternal expansion idea gets you.
But it's also I think part of the connection with
the logic of taking Moore's law as this law of
nature that we can always count on these exponential trends,

(56:33):
and we can always count on human ingenuity and technical
knowledge and know how to get us out of any problem.

Speaker 3 (56:39):
If you believe that.

Speaker 5 (56:41):
Account for all of the problems in the world today, Like,
there's so many problems that we have that are not
amenable to technological solutions that people have tried to solve
for a long time, that are fundamentally social in nature,
or you know, had a technological component but also have
a social component, like climate change. Right, we have a lot,
if not all, of the technology that we need to

(57:03):
address climate change, but we haven't yet as a species,
and that's primarily a social and political issue, not an
issue of technology.

Speaker 1 (57:11):
So, to paraphrase your argument, I think you're saying, it's
not that computers won't get faster and the technology can't
help us in the future. It's just that we can't
rely on it always doing so to magically solve all
of our problems, and doing so distract ourselves from the
real problems we face in the more immediate future.

Speaker 5 (57:28):
Yeah, yeah, I mean, also, more's laws over. I mean,
come on, we have the transistors down about as small
as we can get them. You know, you can't make
a silicon transistor smaller than an atom of silicon.

Speaker 1 (57:44):
But you do see a role for technology in shaping
our future. I mean, it's not that you don't want
chet gpt to cure cancer.

Speaker 5 (57:50):
I definitely hear that there's a role for technology in
shaping our future.

Speaker 3 (57:53):
Technology is a big part of how we shape our future.

Speaker 5 (57:56):
I'm going to just pretend that you didn't say the
thing about chatch ept curing cancer. Though. God, there's this tweet,
like one of my favorite tweet and responses, effor is
where Sam Altman said something like be me, build chatch
ept to cure cancer or whatever, and then people start
criticizing you, and then he like goes on and on
and like has a pity party for himself. And then

(58:17):
somebody just responded with did you cure cancer or whatever?
But you know, there has been actually great progress made
and treating cancer just in the last few years, right,
you know, like these I don't remember the names of
the drugs because like I'm not a cancer guy, but
like these approaches of like getting cancer patient's own immune

(58:39):
systems to properly recognize and attack the cancers in their
own bodies has been like incredibly successful and is really
promising for further developments. It's really amazing, and like there
have been all sorts of really amazing biomedical advances that
are currently being destroyed by RFK Junior and Trump. Like
mRNA vaccines are one of the great success stories of
you know, biomedical science in the last twenty years. And

(59:01):
I think that's important, and I think in general, vaccines
are great. You know, there's all sorts of really wonderful
technology that we've created that has made the world generally
a better place, or has at least enabled.

Speaker 3 (59:13):
People to make the world a better place.

Speaker 1 (59:15):
Right.

Speaker 5 (59:15):
In general, technology is a tool, and there are questions
about how you use it, right. You know, nuclear power
can be used to build nuclear power plants, but it
can also be used to make bombs. YadA, YadA, YadA.
I think I just YadA YadA, nuclear apocalypse.

Speaker 3 (59:27):
But yeah, you did, Yeah whatever. I'm a physicist. Of
course that's what I'm gonna do.

Speaker 5 (59:32):
But the point is, yeah, of course there's a role
for technology to play in shaping our future.

Speaker 3 (59:36):
It's just not two things.

Speaker 5 (59:39):
Technology is not the only thing that shapes our future,
and the development and future direction of technology is not inevitable.
Technology is something that humans make, and the future development
of technology is filled with contingency and human choice. It
is not like we build every single technology that it
is physically possible to build. It's not on rails. It's

(01:00:02):
not like it's you know, the analogy I make in
the book, It's not like a tech tree in civilization, right,
where like the future of technology is just sort of
revealed to us and we have we just make a
choice about which branch we're going to pursue first.

Speaker 3 (01:00:15):
That's not how anything works.

Speaker 1 (01:00:17):
All right. Well, thanks Adam for coming on, and let's
hope that chat GBT desk your cancer before any of
us get it.

Speaker 2 (01:00:23):
Thanks for being on the show, Adam absolutely. Daniel and
Kelly's Extraordinary Universe is produced by iHeartRadio. We would love
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