Stephen Wolfram: Cellular Automata, Computation, and Physics

Stephen Wolfram (02:52.240)

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slash lexpod to get a discount and to support this podcast. And now here's my conversation

Stephen Wolfram (04:14.240)

with Stephen Wolfram. You and your son Christopher helped create the alien language in the movie

Stephen Wolfram (04:20.400)

Arrival. So let me ask maybe a bit of a crazy question, but if aliens were to visit us on earth,

Lex Fridman (04:27.200)

do you think we would be able to find a common language?

Stephen Wolfram (04:31.920)

Well, by the time we're saying aliens are visiting us, we've already prejudiced the whole story

Stephen Wolfram (04:37.600)

because the concept of an alien actually visiting, so to speak, we already know they're kind of

Stephen Wolfram (04:44.640)

things that make sense to talk about visiting. So we already know they exist in the same kind

Stephen Wolfram (04:49.600)

of physical setup that we do. It's not just radio signals. It's an actual thing that shows up and so

Stephen Wolfram (04:59.360)

on. So I think in terms of can one find ways to communicate? Well, the best example we have of

Stephen Wolfram (05:07.360)

this right now is AI. I mean, that's our first sort of example of alien intelligence. And the

Stephen Wolfram (05:13.360)

question is, how well do we communicate with AI? If you were in the middle of a neural network,

Stephen Wolfram (05:19.360)

a neural net, and you open it up and it's like, what are you thinking? Can you discuss things

Stephen Wolfram (05:25.120)

with it? It's not easy, but it's not absolutely impossible. So I think by the time, given the

Stephen Wolfram (05:32.320)

setup of your question, aliens visiting, I think the answer is yes, one will be able to find some

Stephen Wolfram (05:38.720)

form of communication, whatever communication means. Communication requires notions of purpose

Lex Fridman (05:43.200)

and things like this. It's a kind of philosophical quagmire.

Lex Fridman (05:46.880)

So if AI is a kind of alien life form, what do you think visiting looks like? So if we look at

Stephen Wolfram (05:55.200)

aliens visiting, and we'll get to discuss computation and the world of computation,

Lex Fridman (06:01.200)

but if you were to imagine, you said you already prejudiced something by saying you visit,

Lex Fridman (06:06.320)

but how would aliens visit?

Stephen Wolfram (06:09.440)

By visit, there's kind of an implication. And here we're using the imprecision of human language,

Stephen Wolfram (06:15.120)

you know, in a world of the future. And if that's represented in computational language,

Stephen Wolfram (06:19.840)

we might be able to take the concept visit and go look in the documentation, basically,

Lex Fridman (06:26.000)

and find out exactly what does that mean, what properties does it have, and so on.

Lex Fridman (06:29.440)

But by visit, in ordinary human language, I'm kind of taking it to be there's something,

Stephen Wolfram (06:36.800)

a physical embodiment that shows up in a spacecraft, since we kind of know that that's

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necessary. We're not imagining it's just, you know, photons showing up in a radio signal that,

Stephen Wolfram (06:51.040)

you know, photons in some very elaborate pattern, we're imagining it's physical

Lex Fridman (06:55.680)

things made of atoms and so on, that show up.

Lex Fridman (06:58.720)

Can it be photons in a pattern?

Lex Fridman (07:01.120)

Well, that's a good question. I mean, whether there is the possibility,

Stephen Wolfram (07:05.040)

you know, what counts as intelligence? Good question. I mean, it's, you know, and I

Stephen Wolfram (07:11.440)

used to think there was sort of a, oh, there'll be, you know, it'll be clear what it means to

Stephen Wolfram (07:15.760)

find extraterrestrial intelligence, et cetera, et cetera, et cetera. I've increasingly realized,

Stephen Wolfram (07:20.320)

as a result of science that I've done, that there really isn't a bright line between

Stephen Wolfram (07:24.880)

the intelligent and the merely computational, so to speak.

Stephen Wolfram (07:28.960)

So, you know, in our kind of everyday sort of discussion, we'll say things like, you know,

Stephen Wolfram (07:33.200)

the weather has a mind of its own. Well, let's unpack that question. You know, we realize

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that there are computational processes that go on that determine the fluid dynamics of this and

Stephen Wolfram (07:44.080)

that and the atmosphere, et cetera, et cetera, et cetera. How do we distinguish that from

Stephen Wolfram (07:49.360)

the processes that go on in our brains of, you know, the physical processes that go on in our

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brains? How do we separate those? How do we say the physical processes going on that represent

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sophisticated computations in the weather, oh, that's not the same as the physical processes

Stephen Wolfram (08:05.120)

that go on that represent sophisticated computations in our brains? The answer is,

Stephen Wolfram (08:09.040)

I don't think there is a fundamental distinction. I think the distinction for us is that there's

Stephen Wolfram (08:14.320)

kind of a thread of history and so on that connects kind of what happens in different brains

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to each other, so to speak. And it's a, you know, what happens in the weather is something which is

Stephen Wolfram (08:26.000)

not connected by sort of a thread of civilizational history, so to speak, to what we're used to.

Stephen Wolfram (08:32.960)

SL. In the stories that the human brains told us, but maybe the weather has its own stories.

Stephen Wolfram (08:37.920)

MG. Absolutely. Absolutely. And that's where we run into trouble thinking about extraterrestrial

Stephen Wolfram (08:43.440)

intelligence because, you know, it's like that pulsar magnetosphere that's generating these very

Stephen Wolfram (08:49.280)

elaborate radio signals. You know, is that something that we should think of as being this

Stephen Wolfram (08:53.840)

whole civilization that's developed over the last however long, you know, millions of years of

Stephen Wolfram (08:58.960)

processes going on in the neutron star or whatever versus what, you know, what we're used to in human

Stephen Wolfram (09:06.560)

intelligence? I mean, I think in the end, you know, when people talk about extraterrestrial

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intelligence and where is it and the whole, you know, Fermi paradox of how come there's no other

Stephen Wolfram (09:17.280)

signs of intelligence in the universe, my guess is that we've got sort of two alien forms of

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intelligence that we're dealing with, artificial intelligence and sort of physical or extraterrestrial

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intelligence. And my guess is people will sort of get comfortable with the fact that both of these

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have been achieved around the same time. And in other words, people will say, well, yes, we're

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used to computers, things we've created, digital things we've created, being sort of intelligent

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like we are. And they'll say, oh, we're kind of also used to the idea that there are things around

Stephen Wolfram (09:51.360)

the universe that are kind of intelligent like we are, except they don't share the sort of

Stephen Wolfram (09:57.760)

civilizational history that we have. And so they're a different branch. I mean, it's similar to when

Stephen Wolfram (10:04.800)

you talk about life, for instance. I mean, you kind of said life form, I think almost synonymously

Stephen Wolfram (10:10.640)

with intelligence, which I don't think is, you know, the AIs would be upset to hear you equate

Stephen Wolfram (10:18.640)

those two things. Because I really probably implied biological life. But you're saying,

Stephen Wolfram (10:25.040)

I mean, we'll explore this more, but you're saying it's really a spectrum and it's all just

Stephen Wolfram (10:29.120)

a kind of computation. And so it's a full spectrum and we just make ourselves special by weaving a

Stephen Wolfram (10:37.440)

narrative around our particular kinds of computation. Yes. I mean, the thing that I think I've kind of

Stephen Wolfram (10:43.040)

come to realize is, you know, at some level, it's a little depressing to realize that there's so

Stephen Wolfram (10:48.080)

little or liberating. Well, yeah, but I mean, it's, you know, it's the story of science,

Stephen Wolfram (10:52.400)

right? And, you know, from Copernicus on, it's like, you know, first we were like,

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convinced our planets at the center of the universe. No, that's not true. Well, then we

Stephen Wolfram (11:01.840)

were convinced there's something very special about the chemistry that we have as biological

Stephen Wolfram (11:06.080)

organisms. That's not really true. And then we're still holding out that hope. Oh, this intelligence

Stephen Wolfram (11:11.600)

thing we have, that's really special. I don't think it is. However, in a sense, as you say,

Stephen Wolfram (11:17.600)

it's kind of liberating for the following reason, that you realize that what's special is the

Stephen Wolfram (11:22.800)

details of us, not some abstract attribute that, you know, we could wonder, oh, is something else

Stephen Wolfram (11:31.280)

going to come along and, you know, also have that abstract attribute? Well, yes, every abstract

Stephen Wolfram (11:36.640)

attribute we have, something else has it. But the full details of our kind of history of our

Stephen Wolfram (11:42.880)

civilization and so on, nothing else has that. That's what, you know, that's our story, so to

Stephen Wolfram (11:48.400)

speak. And that's sort of almost by definition, special. So I view it as not being such a, I mean,

Stephen Wolfram (11:56.160)

initially I was like, this is bad. This is kind of, you know, how can we have self respect about

Stephen Wolfram (12:02.800)

the things that we do? Then I realized the details of the things we do, they are the story.

Stephen Wolfram (12:08.000)

Everything else is kind of a blank canvas. So maybe on a small tangent, you just made me

Stephen Wolfram (12:15.200)

think of it, but what do you make of the monoliths in 2001 Space Odyssey in terms of

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aliens communicating with us and sparking the kind of particular intelligent computation that

Stephen Wolfram (12:28.000)

we humans have? Is there anything interesting to get from that sci fi? Yeah, I mean, I think what's

Stephen Wolfram (12:37.200)

fun about that is, you know, the monoliths are these, you know, one to four to nine perfect

Stephen Wolfram (12:42.160)

cuboid things. And in the Earth a million years ago, whatever they were portraying with a bunch

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of apes and so on, a thing that has that level of perfection seems out of place. It seems very kind

Stephen Wolfram (12:55.920)

of constructed, very engineered. So that's an interesting question. What is the, you know,

Stephen Wolfram (13:02.320)

what's the techno signature, so to speak? What is it that you see it somewhere and you say,

Stephen Wolfram (13:07.760)

my gosh, that had to be engineered. Now, the fact is we see crystals, which are also very perfect.

Stephen Wolfram (13:15.200)

And, you know, the perfect ones are very perfect. They're nice polyhedral or whatever.

Lex Fridman (13:20.160)

And so in that sense, if you say, well, it's a sign of sort of it's a techno signature that

Stephen Wolfram (13:27.040)

it's a perfect polygonal shape, polyhedral shape. That's not true. And so then it's an interesting

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question. What is the right signature? I mean, like, you know, Gauss, famous mathematician,

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you know, he had this idea, you should cut down the Siberian forest in the shape of sort of a

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typical image of the proof of the Pythagorean theorem on the grounds that it was a kind of

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cool idea, didn't get done. But, you know, it's on the grounds that the Martians would see that and

Stephen Wolfram (13:57.040)

realize, gosh, there are mathematicians out there. It's kind of, you know, in his theory of the world,

Stephen Wolfram (14:02.960)

that was probably the best advertisement for the cultural achievements of our species.

Stephen Wolfram (14:08.560)

But, you know, it's a reasonable question. What do you, what can you send or create that is a sign

Stephen Wolfram (14:16.000)

of intelligence in its creation or even intention in its creation? You talk about if we were to send

Stephen Wolfram (14:22.720)

a beacon. Can you what should we send? Is math our greatest creation? Is what is our greatest

Stephen Wolfram (14:30.640)

creation? I think I think it's a it's a philosophically doomed issue. I mean, in other

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words, you send something, you think it's fantastic, but it's kind of like we are part of

Stephen Wolfram (14:42.000)

the universe. We make things that are, you know, things that happen in the universe.

Stephen Wolfram (14:47.040)

Computation, which is sort of the thing that we are in some abstract sense using to create all

Stephen Wolfram (14:53.680)

these elaborate things we create, is surprisingly ubiquitous. In other words, we might have thought

Stephen Wolfram (15:01.120)

that, you know, we've built this whole giant engineering stack that's led us to microprocessors,

Stephen Wolfram (15:06.880)

that's led us to be able to do elaborate computations. But this idea that computations

Stephen Wolfram (15:13.200)

are happening all over the place. The only question is whether whether there's a thread that connects

Stephen Wolfram (15:18.400)

our human intentions to what those computations are. And so I think I think this question of what

Lex Fridman (15:24.880)

do you send to kind of show off our civilization in the best possible way? I think any kind of

Stephen Wolfram (15:32.160)

almost random slab of stuff we've produced is about equivalent to everything else. I think

Stephen Wolfram (15:38.480)

it's one of these things where it's a non romantic way of phrasing it. I just started to interrupt,

Lex Fridman (15:44.480)

but I just talked to Andrew in who's the wife of Carl Sagan. And so I don't know if you're

Stephen Wolfram (15:51.360)

familiar with the Voyager. I mean, she was part of sending, I think, brainwaves of, you know,

Stephen Wolfram (15:57.120)

wasn't it hers? Her brainwaves when she was first falling in love with Carl Sagan. It's

Stephen Wolfram (16:03.680)

this beautiful story that perhaps you would shut down the power of that by saying we might

Stephen Wolfram (16:11.280)

as well send anything else. And that's interesting. All of it is kind of an interesting, peculiar

Stephen Wolfram (16:16.480)

thing. Yeah, yeah, right. Well, I mean, I think it's kind of interesting to see on the Voyager,

Stephen Wolfram (16:21.280)

you know, golden record thing. One of the things that's kind of cute about that is, you know,

Stephen Wolfram (16:25.680)

it was made when was it in the late 70s, early 80s. And, you know, one of the things, it's a

Stephen Wolfram (16:31.760)

phonograph record. Okay. And it has a diagram of how to play a phonograph record. And, you know,

Stephen Wolfram (16:37.760)

it's kind of like it's shocking that in just 30 years, if you show that to a random kid of today,

Lex Fridman (16:43.680)

and you show them that diagram, I've tried this experiment, they're like, I don't know what the

Stephen Wolfram (16:47.520)

heck this is. And the best anybody can think of is, you know, take the whole record, forget the

Stephen Wolfram (16:52.880)

fact that it has some kind of helical track in it, just image the whole thing and see what's there.

Stephen Wolfram (16:58.080)

That's what we would do today. In only 30 years, our technology has kind of advanced to the point

Stephen Wolfram (17:03.760)

where the playing of a helical, you know, mechanical track on a phonograph record is now

Stephen Wolfram (17:09.520)

something bizarre. So, you know, it's a cautionary tale, I would say, in terms of the ability to make

Stephen Wolfram (17:17.120)

something that in detail sort of leads by the nose, some, you know, the aliens or whatever,

Stephen Wolfram (17:23.760)

to do something. It's like, no, you know, best you can do, as I say, if we were doing this today,

Stephen Wolfram (17:29.840)

we would not build a helical scan thing with a needle. We would just take some high resolution

Stephen Wolfram (17:35.840)

imaging system and get all the bits off it and say, oh, it's a big nuisance that they put in a

Stephen Wolfram (17:40.560)

helix, you know, in a spiral. Let's just unravel the spiral and start from there.

Stephen Wolfram (17:49.120)

SL. Do you think, and this will get into trying to figure out interpretability of AI,

Stephen Wolfram (17:56.560)

interpretability of computation, being able to communicate with various kinds of computations,

Lex Fridman (18:02.400)

do you think we'd be able to, if you put your alien hat on, figure out this record,

Lex Fridman (18:08.320)

how to play this record?

Lex Fridman (18:10.240)

MG. Well, it's a question of what one wants to do. I mean,

Stephen Wolfram (18:13.760)

SL. Understand what the other party was trying to communicate or understand anything about the

Lex Fridman (18:19.760)

other party.

Stephen Wolfram (18:20.240)

MG. What does understanding mean? I mean, that's the issue. The issue is, it's like when people

Stephen Wolfram (18:24.480)

were trying to do natural language understanding for computers, right? So people tried to do that

Stephen Wolfram (18:30.640)

for years. It wasn't clear what it meant. In other words, you take your piece of English or whatever,

Lex Fridman (18:36.960)

and you say, gosh, my computer has understood this. Okay, that's nice. What can you do with that?

Stephen Wolfram (18:43.040)

Well, so for example, when we built WolfMalpha, one of the things was it's doing question answering

Lex Fridman (18:51.760)

and so on, and it needs to do natural language understanding. The reason that I realized after

Stephen Wolfram (18:56.720)

the fact, the reason we were able to do natural language understanding quite well, and people

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hadn't before, the number one thing was we had an actual objective for the natural language

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understanding. We were trying to turn the natural language into this computational language

Stephen Wolfram (19:12.240)

that we could then do things with. Now, similarly, when you imagine your alien, you say,

Stephen Wolfram (19:16.960)

okay, we're playing them the record. Did they understand it? Well, it depends what you mean.

Stephen Wolfram (19:23.040)

If there's a representation that they have, if it converts to some representation where we can say,

Stephen Wolfram (19:28.400)

oh yes, that's a representation that we can recognize is represents understanding, then all

Stephen Wolfram (19:35.600)

well and good. But actually, the only ones that I think we can say would represent understanding

Stephen Wolfram (19:41.280)

are ones that will then do things that we humans kind of recognize as being useful to us.

Stephen Wolfram (19:47.520)

Maybe you're trying to understand, quantify how technologically advanced this particular

Stephen Wolfram (19:53.360)

civilization is. So are they a threat to us from a military perspective? That's probably the

Lex Fridman (1:00:00.400)

do you want me to be able to reproduce to know that I've got quantum mechanics, so to speak?

Stephen Wolfram (1:00:05.200)

Well, and that question comes up. It comes up very operationally actually, because we've been

Stephen Wolfram (1:00:08.880)

doing a bunch of stuff with quantum computing. And there are all these companies that say,

Stephen Wolfram (1:00:12.320)

we have a quantum computer. And we say, let's connect to your API and let's actually run it.

Lex Fridman (1:00:17.920)

And they're like, well, maybe you shouldn't do that yet. We're not quite ready yet.

Lex Fridman (1:00:22.640)

And one of the questions that I've been curious about is, if I have five minutes with a quantum

Stephen Wolfram (1:00:26.880)

computer, how can I tell if it's really a quantum computer or whether it's a simulator at the other

Stephen Wolfram (1:00:31.280)

end? And it turns out it's really hard. It's like a lot of these questions about what is

Stephen Wolfram (1:00:38.160)

intelligence? What's life? It's like, are you really a quantum computer? Yes, exactly. Is it

Stephen Wolfram (1:00:48.480)

just a simulation or is it really a quantum computer? Same issue all over again. So this

Stephen Wolfram (1:00:56.080)

whole issue about the sort of mathematical structure of quantum mechanics and the completely

Stephen Wolfram (1:01:01.440)

separate thing that is our experience in which we think definite things happen, whereas quantum

Stephen Wolfram (1:01:08.080)

mechanics doesn't say definite things ever happen. Quantum mechanics is all about the amplitudes for

Stephen Wolfram (1:01:12.400)

different things to happen, but yet our thread of consciousness operates as if definite things

Stephen Wolfram (1:01:19.520)

are happening. Dilinga, on the point, you've kind of mentioned the structure that could

Stephen Wolfram (1:01:27.040)

underlie everything and this idea that it could perhaps have something like a structure of a graph.

Lex Fridman (1:01:33.680)

Can you elaborate why your intuition is that there's a graph structure of nodes and edges

Lex Fridman (1:01:39.280)

and what it might represent? Right. Okay. So the question is, what is, in a sense,

Stephen Wolfram (1:01:45.920)

the most structuralist structure you can imagine, right? And in fact, what I've recently realized

Stephen Wolfram (1:01:54.000)

in the last year or so, I have a new most structuralist structure. By the way, the question

Stephen Wolfram (1:01:59.440)

itself is a beautiful one and a powerful one in itself. So even without an answer, just the

Stephen Wolfram (1:02:04.640)

question is a really strong question. Right. But what's your new idea? Well, it has to do with

Stephen Wolfram (1:02:09.920)

hypergraphs. Essentially, what is interesting about the sort of model I have now is it's a

Stephen Wolfram (1:02:18.880)

little bit like what happened with computation. Everything that I think of as, oh, well, maybe

Stephen Wolfram (1:02:23.680)

the model is this, I discover it's equivalent. And that's quite encouraging because it's like

Stephen Wolfram (1:02:30.480)

I could say, well, I'm going to look at trivalent graphs with three edges for each node and so on,

Stephen Wolfram (1:02:35.520)

or I could look at this special kind of graph, or I could look at this kind of algebraic structure.

Lex Fridman (1:02:40.880)

And turns out that the things I'm now looking at, everything that I've imagined that is a plausible

Stephen Wolfram (1:02:47.280)

type of structuralist structure is equivalent to this. So what is it? Well, a typical way to think

Stephen Wolfram (1:02:53.600)

about it is, well, so you might have some collection of tuples, collection of, let's say,

Stephen Wolfram (1:03:06.240)

numbers. So you might have one, three, five, two, three, four, just collections of numbers,

Stephen Wolfram (1:03:15.360)

triples of numbers, let's say, quadruples of numbers, pairs of numbers, whatever.

Lex Fridman (1:03:18.800)

And you have all these sort of floating little tuples. They're not in any particular order.

Lex Fridman (1:03:25.920)

And that sort of floating collection of tuples, and I told you this was abstract,

Stephen Wolfram (1:03:32.720)

represents the whole universe. The only thing that relates them is when a symbol is the same,

Stephen Wolfram (1:03:40.480)

it's the same, so to speak. So if you have two tuples and they contain the same symbol,

Lex Fridman (1:03:45.280)

let's say at the same position of the tuple, at the first element of the tuple,

Stephen Wolfram (1:03:48.400)

then that represents a relation. So let me try and peel this back.

Lex Fridman (1:03:53.760)

Wow. Okay.

Stephen Wolfram (1:03:56.720)

I told you it's abstract, but this is the...

Lex Fridman (1:03:59.680)

So the relationship is formed by some aspect of sameness.

Stephen Wolfram (1:04:03.680)

Right. But so think about it in terms of a graph. So a graph, a bunch of nodes,

Stephen Wolfram (1:04:09.440)

let's say you number each node, then what is a graph? A graph is a set of pairs that say

Stephen Wolfram (1:04:16.240)

this node has an edge connecting it to this other node. And a graph is just a collection

Stephen Wolfram (1:04:23.840)

of those pairs that say this node connects to this other node. So this is a generalization of that,

Stephen Wolfram (1:04:30.960)

in which instead of having pairs, you have arbitrary n tuples. That's it. That's the

Stephen Wolfram (1:04:37.120)

whole story. And now the question is, okay, so that might represent the state of the universe.

Lex Fridman (1:04:43.520)

How does the universe evolve? What does the universe do? And so the answer is

Stephen Wolfram (1:04:47.840)

that what I'm looking at is a transformation rules on these hypergraphs. In other words,

Stephen Wolfram (1:04:54.080)

you say this, whenever you see a piece of this hypergraph that looks like this,

Stephen Wolfram (1:05:02.240)

turn it into a piece of hypergraph that looks like this. So on a graph, it might be when you

Stephen Wolfram (1:05:07.200)

see the subgraph, when you see this thing with a bunch of edges hanging out in this particular way,

Stephen Wolfram (1:05:11.520)

then rewrite it as this other graph. Okay. And so that's the whole story. So the question is

Stephen Wolfram (1:05:19.040)

what, uh, so now you say, I mean, as I say, this is quite abstract. And one of the questions is,

Stephen Wolfram (1:05:27.040)

uh, where do you do those updating? So you've got this giant graph. What triggers the updating,

Stephen Wolfram (1:05:32.240)

like what's the, what's the ripple effect of it? Is it, uh, and I suspect everything's discreet

Stephen Wolfram (1:05:39.840)

even in time. So, okay. So the question is where do you do the updates? And the answer is the rule

Stephen Wolfram (1:05:45.600)

is you do them wherever they apply. And you do them, you do them. The order in which the updates

Stephen Wolfram (1:05:50.960)

is done is not defined. That is the, you can do them. So there may be many possible orderings

Stephen Wolfram (1:05:56.400)

for these updates. Now, the point is if imagine you're an observer in this universe. So, and you

Stephen Wolfram (1:06:02.960)

say, did something get updated? Well, you don't in any sense know until you yourself have been

Stephen Wolfram (1:06:08.880)

updated. Right. So in fact, all that you can be sensitive to is essentially the causal network

Stephen Wolfram (1:06:17.040)

of how an event over there affects an event that's in you. That doesn't even feel like

Stephen Wolfram (1:06:24.080)

observation. That's like, that's something else. You're just part of the whole thing.

Stephen Wolfram (1:06:28.080)

Yes, you're part of it. But, but even to have, so the end result of that is all you're sensitive to

Stephen Wolfram (1:06:34.320)

is this causal network of what event affects what other event. I'm not making a big statement about

Stephen Wolfram (1:06:40.880)

sort of the structure of the observer. I'm simply saying, I'm simply making the argument that

Lex Fridman (1:06:46.480)

what happens, the microscopic order of these rewrites is not something that any observer,

Stephen Wolfram (1:06:52.880)

any conceivable observer in this universe can be affected by. Because the only thing the observer

Stephen Wolfram (1:06:58.800)

can be affected by is this causal network of how the events in the observer are affected

Stephen Wolfram (1:07:06.240)

by other events that happen in the universe. So the only thing you have to look at is the

Stephen Wolfram (1:07:09.360)

causal network. You don't really have to look at this microscopic rewriting that's happening. So

Stephen Wolfram (1:07:14.320)

these rewrites are happening wherever they, they happen wherever they feel like.

Stephen Wolfram (1:07:18.560)

Causal network. Is there, you said that there's not really, so the idea would be an undefined,

Stephen Wolfram (1:07:26.400)

like what gets updated? The, the sequence of things is undefined. It's a, yes. That's what

Stephen Wolfram (1:07:33.120)

you mean by the causal network, but then the call, no, the causal network is given that an

Stephen Wolfram (1:07:37.360)

update has happened. That's an event. Then the question is, is that event causally related to,

Stephen Wolfram (1:07:43.440)

does that event, if that event didn't happen, then some future event couldn't happen yet.

Lex Fridman (1:07:48.720)

Gotcha.

Lex Fridman (1:07:49.680)

And so you build up this network of what affects what. Okay. And so what that does,

Lex Fridman (1:07:54.800)

so when you build up that network, that's kind of the observable aspect of the universe in some

Stephen Wolfram (1:07:59.920)

sense. And so then you can ask questions about, you know, how robust is that observable network

Stephen Wolfram (1:08:07.120)

of the, what's happening in the universe. Okay. So here's where it starts getting kind of

Stephen Wolfram (1:08:10.960)

interesting. So for certain kinds of microscopic rewriting rules, the order of rewrites does not

Stephen Wolfram (1:08:17.200)

matter to the causal network. And so this is, okay, mathematical logic moment. This is equivalent

Stephen Wolfram (1:08:24.160)

to the Church Rosser property or the confluence property of rewrite rules. And it's the same

Stephen Wolfram (1:08:28.480)

reason that if you're simplifying an algebraic expression, for example, you can say, oh, let me

Stephen Wolfram (1:08:33.440)

expand those terms out. Let me factor those pieces. Doesn't matter what order you do that in,

Stephen Wolfram (1:08:38.000)

you'll always get the same answer. And that's, it's the same fundamental phenomenon that causes

Stephen Wolfram (1:08:43.760)

for certain kinds of microscopic rewrite rules that causes the causal network to be independent

Lex Fridman (1:08:50.000)

of the microscopic order of rewritings.

Lex Fridman (1:08:52.160)

Why is that property important?

Stephen Wolfram (1:08:54.400)

Because it implies special relativity. I mean, the reason it's important is that that property,

Stephen Wolfram (1:09:03.440)

special relativity says you can look at these sort of, you can look at different reference frames.

Stephen Wolfram (1:09:10.480)

You can have different, you can be looking at your notion of what space and what's time

Stephen Wolfram (1:09:14.960)

can be different depending on whether you're traveling at a certain speed, depending on

Stephen Wolfram (1:09:18.480)

whether you're doing this, that, and the other. But nevertheless, the laws of physics are the

Stephen Wolfram (1:09:22.080)

same. That's what the principle of special relativity says, is the laws of physics are

Stephen Wolfram (1:09:26.240)

the same independent of your reference frame. Well, turns out this sort of change of the

Stephen Wolfram (1:09:33.360)

microscopic rewriting order is essentially equivalent to a change of reference frame,

Stephen Wolfram (1:09:37.520)

or at least there's a sub part of how that works that's equivalent to change a reference frame.

Stephen Wolfram (1:09:42.000)

So, somewhat surprisingly, and sort of for the first time in forever,

Stephen Wolfram (1:09:46.240)

it's possible for an underlying microscopic theory to imply special relativity, to be able to derive

Stephen Wolfram (1:09:52.000)

it. It's not something you put in as a, this is a, it's something where this other property,

Stephen Wolfram (1:09:57.920)

causal invariance, which is also the property that implies that there's a single thread of time

Stephen Wolfram (1:10:03.680)

in the universe. It might not be the case that that's what would lead to the possibility of an

Stephen Wolfram (1:10:11.600)

observer thinking that definite stuff happens. Otherwise, you've got all these possible rewriting

Stephen Wolfram (1:10:16.480)

orders, and who's to say which one occurred. But with this causal invariance property,

Stephen Wolfram (1:10:20.640)

there's a notion of a definite thread of time. It sounds like that kind of idea of time,

Stephen Wolfram (1:10:25.840)

even space, would be emergent from the system. Oh, yeah. No, I mean, it's not a fundamental part

Stephen Wolfram (1:10:30.960)

of the system. No, no, it's a fundamental level. All you've got is a bunch of nodes connected by

Stephen Wolfram (1:10:36.000)

hyper edges or whatever. So there's no time, there's no space. That's right. And

Lex Fridman (1:10:39.600)

but the thing is that it's just like imagining, imagine you're just dealing with a graph. And

Stephen Wolfram (1:10:44.720)

imagine you have something like a, you know, like a honeycomb graph, or you have a hexagon,

Stephen Wolfram (1:10:48.320)

a bunch of hexagons. You know, that graph at a microscopic level, it's just a bunch of nodes

Stephen Wolfram (1:10:53.520)

connected to other nodes. But at a macroscopic level, you say that looks like a honeycomb,

Stephen Wolfram (1:10:57.600)

you know, lattice, it looks like a two dimensional, you know, manifold of some kind, it looks like a

Stephen Wolfram (1:11:04.000)

two dimensional thing. If you connect it differently, if you just connect all the

Stephen Wolfram (1:11:07.360)

nodes one, one to another, and kind of a sort of linked list type structure, then you'd say,

Stephen Wolfram (1:11:12.000)

well, that looks like a one dimensional space. But at the microscopic level, all these are just

Stephen Wolfram (1:11:16.960)

networks with nodes, the macroscopic level, they look like something that's like one of our sort

Stephen Wolfram (1:11:22.240)

of familiar kinds of space. And it's the same thing with these hyper graphs. Now, if you ask me,

Stephen Wolfram (1:11:27.680)

have I found one that gives me three dimensional space? The answer is not yet. So we don't know.

Stephen Wolfram (1:11:33.200)

This is one of these things we're kind of betting against nature, so to speak. And I have no way to

Stephen Wolfram (1:11:38.000)

know. And so there are many other properties of this kind of system that are very beautiful,

Stephen Wolfram (1:11:43.920)

actually, and very suggestive. And it will be very elegant if this turns out to be right,

Stephen Wolfram (1:11:48.800)

because it's very clean. I mean, you start with nothing. And everything gets built up,

Stephen Wolfram (1:11:53.600)

everything about space, everything about time, everything about matter. It's all just emergent

Stephen Wolfram (1:11:59.520)

from the properties of this extremely low level system. And that, that will be pretty cool if

Stephen Wolfram (1:12:04.480)

that's the way our universe works. Now, do I on the other hand, the thing that that I find very

Stephen Wolfram (1:12:11.680)

confusing is, let's say we succeed, let's say we can say this particular sort of hypergraph rewriting

Stephen Wolfram (1:12:20.080)

rule gives the universe just run that hypergraph rewriting rule for enough times, and you'll get

Stephen Wolfram (1:12:25.920)

everything, you'll get this conversation we're having, you'll get everything. It's that if we

Stephen Wolfram (1:12:33.440)

get to that point, and we look at what is this thing, what is this rule that we just have,

Stephen Wolfram (1:12:39.120)

that is giving us our whole universe, how do we think about that thing? Let's say, turns out the

Stephen Wolfram (1:12:44.320)

minimal version of this, and this is kind of cool thing for a language designer like me,

Stephen Wolfram (1:12:48.400)

the minimal version of this model is actually a single line of orphan language code.

Lex Fridman (1:12:52.960)

So that's, which I wasn't sure was going to happen that way, but it's, it's a, that's, it's kind of,

Stephen Wolfram (1:12:59.600)

no, we don't know what, we don't know what that's, that's just the framework to know the actual

Stephen Wolfram (1:13:05.440)

particular hypergraph that might be a longer, the specification of the rules might be slightly

Stephen Wolfram (1:13:10.320)

longer. How does that help you accept marveling in the beauty and the elegance of the simplicity

Lex Fridman (1:13:16.560)

that creates the universe? That does that help us predict anything in the universe?

Stephen Wolfram (1:13:20.640)

That does that help us predict anything? Not really because of the irreducibility.

Stephen Wolfram (1:13:25.040)

That's correct. That's correct. But so the thing that is really strange to me,

Lex Fridman (1:13:29.280)

and I haven't wrapped my, my brain around this yet is, you know, one is one keeps on realizing

Stephen Wolfram (1:13:37.120)

that we're not special in the sense that, you know, we don't live at the center of the universe.

Stephen Wolfram (1:13:41.760)

We don't blah, blah, blah. And yet if we produce a rule for the universe and it's quite simple,

Lex Fridman (1:13:49.280)

and we can write it down and a couple of lines or something that feels very special.

Lex Fridman (1:13:54.480)

How did we come to get a simple universe when many of the available universes, so to speak,

Stephen Wolfram (1:14:00.560)

are incredibly complicated? It might be, you know, a quintillion characters long.

Lex Fridman (1:14:05.360)

Why did we get one of the ones that's simple? And so I haven't wrapped my brain around that

Stephen Wolfram (1:14:09.440)

issue yet. If indeed we are in such a simple, the universe is such a simple rule. Is it possible

Stephen Wolfram (1:14:17.120)

that there is something outside of this that we are in a kind of what people call the simulation,

Stephen Wolfram (1:14:24.480)

right? That we're just part of a computation that's being explored by a graduate student

Stephen Wolfram (1:14:29.440)

in alternate universe. Well, you know, the problem is we don't get to say much about

Stephen Wolfram (1:14:34.320)

what's outside our universe because by definition, our universe is what we exist within. Now,

Stephen Wolfram (1:14:40.160)

can we make a sort of almost theological conclusion from being able to know how our

Stephen Wolfram (1:14:45.440)

particular universe works? Interesting question. I don't think that if you ask the question,

Stephen Wolfram (1:14:52.080)

could we, and it relates again to this question about extraterrestrial intelligence, you know,

Stephen Wolfram (1:14:57.600)

we've got the rule for the universe. Was it built in on purpose? Hard to say. That's the same thing

Stephen Wolfram (1:15:03.520)

as saying we see a signal from, you know, that we're receiving from some random star somewhere,

Lex Fridman (1:15:11.200)

and it's a series of pulses. And, you know, it's a periodic series of pulses, let's say.

Stephen Wolfram (1:15:16.800)

Was that done on purpose? Can we conclude something about the origin of that series of

Stephen Wolfram (1:15:20.400)

pulses? Just because it's elegant does not necessarily mean that somebody created it or

Stephen Wolfram (1:15:27.520)

that we can even comprehend. Yeah. I think it's the ultimate version of the sort of identification

Stephen Wolfram (1:15:35.040)

of the techno signature question. It's the ultimate version of that is was our universe

Stephen Wolfram (1:15:39.760)

a piece of technology, so to speak, and how on earth would we know? But I mean, in the kind of

Stephen Wolfram (1:15:47.840)

crazy science fiction thing you could imagine, you could say, oh, there's going to be a signature

Stephen Wolfram (1:15:53.920)

there. It's going to be made by so and so. But there's no way we could understand that,

Lex Fridman (1:15:59.520)

so to speak, and it's not clear what that would mean. Because the universe simply,

Stephen Wolfram (1:16:04.240)

you know, if we find a rule for the universe, we're simply saying that rule represents what

Stephen Wolfram (1:16:10.800)

our universe does. We're not saying that that rule is something running on a big computer

Lex Fridman (1:16:16.880)

and making our universe. It's just saying that represents what our universe does in the same

Stephen Wolfram (1:16:21.680)

sense that, you know, laws of classical mechanics, differential equations, whatever they are,

Stephen Wolfram (1:16:26.320)

represent what mechanical systems do. It's not that the mechanical systems are somehow running

Stephen Wolfram (1:16:32.560)

solutions to those differential equations. Those differential equations are just representing the

Stephen Wolfram (1:16:36.960)

behavior of those systems. So what's the gap in your sense to linger on the fascinating,

Stephen Wolfram (1:16:42.640)

perhaps slightly sci fi question? What's the gap between understanding the fundamental rules that

Lex Fridman (1:16:48.720)

create a universe and engineering a system, actually creating a simulation ourselves?

Lex Fridman (1:16:54.640)

So you've talked about sort of, you've talked about, you know, nano engineering kind of ideas

Stephen Wolfram (1:17:01.200)

that are kind of exciting, actually creating some ideas of computation in the physical space. How

Lex Fridman (1:17:06.000)

hard is it as an engineering problem to create the universe once you know the rules that create it?

Stephen Wolfram (1:17:11.280)

Well, that's an interesting question. I think the substrate on which the universe is operating is

Stephen Wolfram (1:17:16.480)

not a substrate that we have access to. I mean, the only substrate we have is that same substrate

Stephen Wolfram (1:17:22.080)

that the universe is operating in. So if the universe is a bunch of hypergraphs being rewritten,

Stephen Wolfram (1:17:26.960)

then we get to attach ourselves to those same hypergraphs being rewritten. We don't get to,

Lex Fridman (1:17:35.360)

and if you ask the question, you know, is the code clean? You know, can we write nice,

Stephen Wolfram (1:17:40.720)

elegant code with efficient algorithms and so on? Well, that's an interesting question.

Stephen Wolfram (1:17:47.520)

That's this question of how much computational reducibility there is in the system.

Lex Fridman (1:17:51.440)

But I've seen some beautiful cellular automata that basically create copies of itself within

Stephen Wolfram (1:17:55.920)

itself, right? So that's the question whether it's possible to create, like whether you need

Stephen Wolfram (1:18:01.280)

to understand the substrate or whether you can. Yeah, well, right. I mean, so one of the things

Stephen Wolfram (1:18:06.400)

that is sort of one of my slightly sci fi thoughts about the future, so to speak, is, you know,

Stephen Wolfram (1:18:12.720)

right now, if you poll typical people, you say, do you think it's important to find the fundamental

Stephen Wolfram (1:18:16.720)

theory of physics? You get, because I've done this poll informally, at least, it's curious,

Stephen Wolfram (1:18:22.880)

actually, you get a decent fraction of people saying, oh, yeah, that would be pretty interesting.

Stephen Wolfram (1:18:27.680)

I think that's becoming, surprisingly enough, more, I mean, a lot of people are interested

Stephen Wolfram (1:18:35.120)

in physics in a way that like, without understanding it, just kind of watching

Stephen Wolfram (1:18:41.280)

scientists, a very small number of them struggle to understand the nature of our reality.

Stephen Wolfram (1:18:46.080)

Right. I mean, I think that's somewhat true. And in fact, in this project that I'm launching into

Stephen Wolfram (1:18:51.600)

to try and find fundamental theory of physics, I'm going to do it as a very public project. I mean,

Stephen Wolfram (1:18:56.160)

it's going to be live streamed and all this kind of stuff. And I don't know what will happen. It'll

Stephen Wolfram (1:19:00.240)

be kind of fun. I mean, I think that it's the interface to the world of this project. I mean,

Stephen Wolfram (1:19:07.280)

I figure one feature of this project is, you know, unlike technology projects that basically are what

Stephen Wolfram (1:19:14.160)

they are, this is a project that might simply fail, because it might be the case that it generates

Stephen Wolfram (1:19:18.400)

all kinds of elegant mathematics that has absolutely nothing to do with the physical

Stephen Wolfram (1:19:21.920)

universe that we happen to live in. Okay, so we're talking about kind of the quest to find

Stephen Wolfram (1:19:27.680)

the fundamental theory of physics. First point is, you know, it's turned out it's kind of hard

Stephen Wolfram (1:19:33.440)

to find the fundamental theory of physics. People weren't sure that that would be the case. Back in

Stephen Wolfram (1:19:38.080)

the early days of applying mathematics to science, 1600s and so on, people were like, oh, in 100 years

Stephen Wolfram (1:19:44.880)

we'll know everything there is to know about how the universe works. Turned out to be harder than

Stephen Wolfram (1:19:48.800)

that. And people got kind of humble at some level, because every time we got to sort of a greater

Stephen Wolfram (1:19:53.600)

level of smallness and studying the universe, it seemed like the math got more complicated and

Stephen Wolfram (1:19:58.080)

everything got harder. When I was a kid, basically, I started doing particle physics. And when I was

Stephen Wolfram (1:20:08.080)

doing particle physics, I always thought finding the fundamental, fundamental theory of physics,

Stephen Wolfram (1:20:14.000)

that's a kooky business, we'll never be able to do that. But we can operate within these

Stephen Wolfram (1:20:18.880)

frameworks that we built for doing quantum field theory and general relativity and things like this.

Lex Fridman (1:20:23.360)

And it's all good. And we can figure out a lot of stuff. Did you even at that time have a sense

Stephen Wolfram (1:20:27.920)

that there's something behind that? Sure, I just didn't expect that. I thought in some rather un,

Stephen Wolfram (1:20:35.680)

it's actually kind of crazy and thinking back on it, because it's kind of like there was this long

Stephen Wolfram (1:20:41.120)

period in civilization where people thought the ancients had it all figured out, and we'll never

Stephen Wolfram (1:20:44.480)

figure out anything new. And to some extent, that's the way I felt about physics when I was

Stephen Wolfram (1:20:49.840)

in the middle of doing it, so to speak, was, you know, we've got quantum field theory, it's the

Stephen Wolfram (1:20:54.800)

foundation of what we're doing. And there's, you know, yes, there's probably something underneath

Stephen Wolfram (1:20:59.440)

this, but we'll sort of never figure it out. But then I started studying simple programs in the

Stephen Wolfram (1:21:06.000)

computational universe, things like cellular automata and so on. And I discovered that

Stephen Wolfram (1:21:12.160)

they do all kinds of things that were completely at odds with the intuition that I had had.

Lex Fridman (1:21:16.800)

And so after that, after you see this tiny little program that does all this amazingly complicated

Stephen Wolfram (1:21:22.400)

stuff, then you start feeling a bit more ambitious about physics and saying, maybe we could do this

Stephen Wolfram (1:21:27.360)

for physics too. And so that got me started years ago now in this kind of idea of could we actually

Stephen Wolfram (1:21:36.720)

find what's underneath all of these frameworks, like quantum field theory and general relativity

Lex Fridman (1:21:40.880)

and so on. And people perhaps don't realize as clearly as they might that, you know, the

Stephen Wolfram (1:21:45.200)

frameworks we're using for physics, which is basically these two things, quantum field theory,

Stephen Wolfram (1:21:50.480)

sort of the theory of small stuff and general relativity, theory of gravitation and large stuff.

Stephen Wolfram (1:21:55.600)

Those are the two basic theories. And they're 100 years old. I mean, general relativity was 1915,

Stephen Wolfram (1:22:01.200)

quantum field theory, well, 1920s. So basically 100 years old. And it's been a good run. There's

Stephen Wolfram (1:22:08.880)

a lot of stuff been figured out. But what's interesting is the foundations haven't changed

Stephen Wolfram (1:22:14.560)

in all that period of time, even though the foundations had changed several times before

Stephen Wolfram (1:22:19.120)

that in the 200 years earlier than that. And I think the kinds of things that I'm thinking about,

Stephen Wolfram (1:22:25.200)

which are sort of really informed by thinking about computation and the computational universe,

Stephen Wolfram (1:22:29.760)

it's a different foundation. It's a different set of foundations. And might be wrong. But it is at

Stephen Wolfram (1:22:36.640)

least, you know, we have a shot. And I think it's, you know, to me, it's, you know, my personal

Stephen Wolfram (1:22:42.080)

calculation for myself is, is, you know, if it turns out that the finding the fundamental theory

Stephen Wolfram (1:22:49.520)

of physics, it's kind of low hanging fruit, so to speak, it'd be a shame if we just didn't think to

Stephen Wolfram (1:22:54.560)

do it. You know, if people just said, Oh, you'll never figure that stuff out. Let's, you know,

Lex Fridman (1:22:59.680)

and it takes another 200 years before anybody gets around to doing it. You know, I think it's,

Stephen Wolfram (1:23:06.560)

I don't know how low hanging this fruit actually is. It may be, you know, it may be that it's kind

Stephen Wolfram (1:23:12.720)

of the wrong century to do this project. I mean, I think the cautionary tale for me, you know,

Stephen Wolfram (1:23:18.400)

I think about things that I've tried to do in technology, where people thought about doing them

Stephen Wolfram (1:23:24.160)

a lot earlier. And my favorite example is probably Leibniz, who, who thought about making essentially

Stephen Wolfram (1:23:30.480)

encapsulating the world's knowledge in a computational form in the late 1600s, and did a

Stephen Wolfram (1:23:36.800)

lot of things towards that. And basically, you know, we finally managed to do this. But he was

Stephen Wolfram (1:23:42.080)

300 years too early. And that's the that's kind of the in terms of life planning. It's kind of like,

Stephen Wolfram (1:23:48.080)

avoid things that can't be done in your in your century, so to speak.

Stephen Wolfram (1:23:51.920)

Yeah, timing. Timing is everything. So you think if we kind of figure out the underlying rules

Stephen Wolfram (1:24:00.640)

that can create from which quantum field theory and general relativity can emerge,

Lex Fridman (1:24:06.400)

do you think they'll help us unify it at that level of abstraction?

Stephen Wolfram (1:24:09.200)

Oh, we'll know it completely. We'll know how that all fits together. Yes, without a question.

Lex Fridman (1:24:13.680)

And I mean, it's already even the things I've already done. There are very, you know, it's very,

Lex Fridman (1:24:21.680)

very elegant, actually, how things seem to be fitting together. Now, you know, is it right?

Stephen Wolfram (1:24:25.920)

I don't know yet. It's awfully suggestive. If it isn't right, it's then the designer of the universe

Stephen Wolfram (1:24:33.600)

should feel embarrassed, so to speak, because it's a really good way to do it.

Lex Fridman (1:24:36.800)

And your intuition in terms of design universe, does God play dice? Is there is there randomness

Stephen Wolfram (1:24:43.200)

in this thing? Or is it deterministic? So the kind of

Stephen Wolfram (1:24:46.880)

That's a little bit of a complicated question. Because when you're dealing with these things

Stephen Wolfram (1:24:51.040)

that involve these rewrites that have, okay, even randomness is an emergent phenomenon, perhaps.

Lex Fridman (1:24:56.160)

Yes, yes. I mean, it's a yeah, well, randomness, in many of these systems,

Stephen Wolfram (1:25:01.280)

pseudo randomness and randomness are hard to distinguish. In this particular case,

Lex Fridman (1:25:06.080)

the current idea that we have about some measurement in quantum mechanics

Stephen Wolfram (1:25:12.480)

is something very bizarre and very abstract. And I don't think I can yet

Stephen Wolfram (1:25:16.720)

explain it without kind of yakking about very technical things. Eventually, I will be able to.

Lex Fridman (1:25:22.000)

But if that's right, it's kind of a it's a weird thing, because it slices between determinism and

Stephen Wolfram (1:25:30.400)

randomness in a weird way that hasn't been sliced before, so to speak. So like many of these

Stephen Wolfram (1:25:35.360)

questions that come up in science, where it's like, is it this or is it that? Turns out the

Stephen Wolfram (1:25:40.480)

real answer is it's neither of those things. It's something kind of different and sort of orthogonal

Stephen Wolfram (1:25:45.520)

to those categories. And so that's the current, you know, this week's idea about how that might

Stephen Wolfram (1:25:52.240)

work. But, you know, we'll see how that unfolds. I mean, there's this question about a field like

Stephen Wolfram (1:26:00.720)

physics and sort of the quest for fundamental theory and so on. And there's both the science

Stephen Wolfram (1:26:06.400)

of what happens and there's the sort of the social aspect of what happens. Because, you know,

Stephen Wolfram (1:26:11.840)

in a field that is basically as old as physics, we're at, I don't know what it is, fourth generation,

Stephen Wolfram (1:26:18.080)

I don't know, fifth generation, I don't know what generation it is of physicists. And like,

Stephen Wolfram (1:26:22.320)

I was one of these, so to speak. And for me, the foundations were like the pyramid, so to speak,

Stephen Wolfram (1:26:27.840)

you know, it was that way. And it was always that way. It is difficult in an old field to go back to

Stephen Wolfram (1:26:34.560)

the foundations and think about rewriting them. It's a lot easier in young fields where you're

Stephen Wolfram (1:26:39.840)

still dealing with the first generation of people who invented the field. And it tends to be the

Stephen Wolfram (1:26:45.200)

case, you know, that the nature of what happens in science tends to be, you know, you'll get,

Stephen Wolfram (1:26:50.400)

typically the pattern is some methodological advance occurs. And then there's a period of five

Stephen Wolfram (1:26:56.080)

years, 10 years, maybe a little bit longer than that, where there's lots of things that are now

Stephen Wolfram (1:27:00.480)

made possible by that methodological advance, whether it's, you know, I don't know, telescopes,

Stephen Wolfram (1:27:06.080)

or whether that's some mathematical method or something. Something happens, a tool gets built,

Lex Fridman (1:27:16.000)

and then you can do a bunch of stuff. And there's a bunch of low hanging fruit to be picked. And

Stephen Wolfram (1:27:21.520)

that takes a certain amount of time. After all that low hanging fruit is picked, then it's a hard

Stephen Wolfram (1:27:27.360)

slog for the next however many decades or century or more to get to the next sort of level at which

Stephen Wolfram (1:27:35.360)

one could do something. And it's kind of a, and it tends to be the case that in fields that are in

Stephen Wolfram (1:27:39.840)

that kind of, I wouldn't say cruise mode, because it's really hard work, but it's very hard work for

Stephen Wolfram (1:27:45.040)

very incremental progress. And then in your career and some of the things you've taken on,

Stephen Wolfram (1:27:50.560)

it feels like you're not, you haven't been afraid of the hard slog. Yeah, that's true. So it's quite

Stephen Wolfram (1:27:56.800)

interesting, especially on the engineering, on the engineering side. On a small tangent, when you

Stephen Wolfram (1:28:03.120)

were at Caltech, did you get to interact with Richard Feynman at all? Do you have any memories

Stephen Wolfram (1:28:09.280)

of Richard? We worked together quite a bit, actually. In fact, both when I was at Caltech

Lex Fridman (1:28:16.000)

and after I left Caltech, we were both consultants at this company called Thinking Machines Corporation,

Stephen Wolfram (1:28:21.600)

which was just down the street from here, actually. It was ultimately an ill fated company. But I used

Stephen Wolfram (1:28:27.520)

to say this company is not going to work with the strategy they have. And Dick Feynman always used

Stephen Wolfram (1:28:31.760)

to say, what do we know about running companies? Just let them run their company. But anyway,

Stephen Wolfram (1:28:38.720)

he was not into that kind of thing. And he always thought that my interest in doing things like

Stephen Wolfram (1:28:44.160)

running companies was a distraction, so to speak. And for me, it's a mechanism to have a more

Stephen Wolfram (1:28:53.520)

effective machine for actually getting things, figuring things out and getting things to happen.

Stephen Wolfram (1:28:58.880)

Did he think of it, because essentially what you did with the company, I don't know if you were

Stephen Wolfram (1:29:04.000)

thinking of it that way, but you're creating tools to empower the exploration of the

Stephen Wolfram (1:29:11.920)

university. Do you think, did he... Did he understand that point? The point of tools of...

Stephen Wolfram (1:29:18.640)

I think not as well as he might have done. I mean, I think that... But he was actually my

Stephen Wolfram (1:29:23.920)

first company, which was also involved with, well, was involved with more mathematical computation

Stephen Wolfram (1:29:30.160)

kinds of things. He was quite... He had lots of advice about the technical side of what we should

Stephen Wolfram (1:29:37.360)

do and so on. Do you have examples, memories, or thoughts that... Oh, yeah, yeah. He had all

Stephen Wolfram (1:29:42.320)

kinds of... Look, in the business of doing sort of... One of the hard things in math is doing

Stephen Wolfram (1:29:48.160)

integrals and so on. And so he had his own elaborate ways to do integrals and so on. He

Stephen Wolfram (1:29:53.440)

had his own ways of thinking about sort of getting intuition about how math works.

Lex Fridman (1:29:57.920)

And so his sort of meta idea was take those intuitional methods and make a computer follow

Stephen Wolfram (1:30:04.560)

those intuitional methods. Now, it turns out for the most part, like when we do integrals and

Stephen Wolfram (1:30:10.240)

things, what we do is we build this kind of bizarre industrial machine that turns every integral

Stephen Wolfram (1:30:16.480)

into products of major G functions and generates this very elaborate thing. And actually the big

Stephen Wolfram (1:30:21.920)

problem is turning the results into something a human will understand. It's not, quote,

Stephen Wolfram (1:30:26.400)

doing the integral. And actually, Feynman did understand that to some extent. And I'm embarrassed

Stephen Wolfram (1:30:31.600)

to say he once gave me this big pile of, you know, calculational methods for particle physics that he

Stephen Wolfram (1:30:37.280)

worked out in the 50s. And he said, yeah, it's more used to you than to me type thing. And I

Stephen Wolfram (1:30:41.200)

was like, I've intended to look at it and give it back and I'm still on my files now. But that's

Lex Fridman (1:30:47.680)

what happens when it's finiteness of human lives. Maybe if he'd live another 20 years, I would have

Stephen Wolfram (1:30:54.240)

remembered to give it back. But I think that was his attempt to systematize the ways that one does

Stephen Wolfram (1:31:03.600)

integrals that show up in particle physics and so on. Turns out the way we've actually done it

Stephen Wolfram (1:31:08.000)

is very different from that way. What do you make of that difference,

Stephen Wolfram (1:31:10.800)

Eugene? So Feynman was actually quite remarkable at creating sort of intuitive frameworks for

Stephen Wolfram (1:31:20.400)

understanding difficult concepts. I'm smiling because, you know, the funny thing about him was

Stephen Wolfram (1:31:27.040)

that the thing he was really, really, really good at is calculating stuff. But he thought that was

Stephen Wolfram (1:31:32.560)

easy because he was really good at it. And so he would do these things where he would calculate

Stephen Wolfram (1:31:38.160)

some, do some complicated calculation in quantum field theory, for example, come out with a result,

Stephen Wolfram (1:31:44.800)

wouldn't tell anybody about the complicated calculation because he thought that was easy.

Stephen Wolfram (1:31:48.160)

He thought the really impressive thing was to have this simple intuition about how

Stephen Wolfram (1:31:52.320)

everything works. So he invented that at the end. And, you know, because he'd done this calculation

Lex Fridman (1:31:58.000)

and knew how it worked, it was a lot easier. It's a lot easier to have good intuition when you know

Lex Fridman (1:32:02.800)

what the answer is. And then and then he would just not tell anybody about these calculations

Stephen Wolfram (1:32:07.520)

that he wasn't meaning that maliciously, so to speak. It's just he thought that was easy.

Lex Fridman (1:32:12.880)

And and that's, you know, that led to areas where people were just completely mystified,

Lex Fridman (1:32:17.120)

and they kind of followed his intuition. But nobody could tell why it worked. Because actually,

Stephen Wolfram (1:32:22.000)

the reason it worked was because he'd done all these calculations, and he knew that it was

Stephen Wolfram (1:32:25.120)

would work. And, you know, when I he and I worked a bit on quantum computers actually back in 1980,

Stephen Wolfram (1:32:31.440)

81, before anybody had heard of those things. And, you know, the typical mode of I mean,

Stephen Wolfram (1:32:38.800)

he was used to say, and I now think about this, because I'm about the age that he was when I

Stephen Wolfram (1:32:42.960)

worked with him. And, you know, I see the people who are one third my age, so to speak.

Lex Fridman (1:32:47.520)

And he was always complaining that I was one third his age, and therefore various things. But, but,

Stephen Wolfram (1:32:54.160)

you know, he would do some calculation by by hand, you know, blackboard and things come up with some

Stephen Wolfram (1:32:59.200)

answer. I'd say, I don't understand this. You know, I do something with a computer. And he'd say,

Stephen Wolfram (1:33:06.480)

you know, I don't understand this. So there'd be some big argument about what was, you know,

Lex Fridman (1:33:11.280)

what was going on, but but it was always some. And I think, actually, we many of the things that we

Stephen Wolfram (1:33:18.240)

sort of realized about quantum computing, that was sort of issues that have to do particularly

Stephen Wolfram (1:33:23.280)

with the measurement process, are kind of still issues today. And I kind of find it interesting.

Stephen Wolfram (1:33:28.640)

It's a funny thing in science that these, you know, that there's, there's a remarkable happens

Stephen Wolfram (1:33:34.320)

in technology to there's a remarkable sort of repetition of history that ends up occurring.

Stephen Wolfram (1:33:40.080)

Eventually, things really get nailed down. But it often takes a while. And it often things come

Stephen Wolfram (1:33:45.120)

back decades later. Well, for example, I could tell a story actually happened right down the

Stephen Wolfram (1:33:50.880)

street from here. When we were both thinking machines, I had been working on this particular

Stephen Wolfram (1:33:56.880)

cellular automaton, who rule 30, that has this feature that it from very simple initial conditions,

Stephen Wolfram (1:34:03.200)

it makes really complicated behavior. Okay. So and actually, of all silly physical things,

Stephen Wolfram (1:34:11.200)

using this big parallel computer called the connection machine that that company was making,

Stephen Wolfram (1:34:16.880)

I generated this giant printout of rule 30 on very, on actually on the same kind of same kind

Stephen Wolfram (1:34:22.720)

of printer that people use to make layouts microprocessors. So one of these big, you know,

Stephen Wolfram (1:34:31.200)

large format printers with high resolution and so on. So okay, so print this out lots of very tiny

Stephen Wolfram (1:34:37.520)

cells. And so there was sort of a question of how some features of that pattern. And so it was very

Stephen Wolfram (1:34:45.120)

much a physical, you know, on the floor with meter rules trying to measure different things.

Stephen Wolfram (1:34:49.600)

So, so Feynman kind of takes me aside, we've been doing that for a little while and takes me aside.

Lex Fridman (1:34:55.440)

And he says, I just want to know this one thing says, I want to know, how did you know that this

Stephen Wolfram (1:35:00.560)

rule 30 thing would produce all this really complicated behavior that is so complicated

Stephen Wolfram (1:35:05.280)

that we're, you know, going around with this big printout, and so on. And I said, Well,

Stephen Wolfram (1:35:10.320)

I didn't know, I just enumerated all the possible rules and then observed that that's what happened.

Stephen Wolfram (1:35:15.760)

He said, Oh, I feel a lot better. You know, I thought you had some intuition that he didn't have

Stephen Wolfram (1:35:22.480)

that would let one. I said, No, no, no, no intuition, just experimental science.

Stephen Wolfram (1:35:26.640)

TK Oh, that's such a beautiful sort of dichotomy there of that's exactly you showed is you really

Lex Fridman (1:35:33.200)

can't have an intuition about an irreducible. I mean, you have to run it.

Stephen Wolfram (1:35:37.120)

MG Yes, that's right.

Lex Fridman (1:35:38.160)

TK That's so hard for us humans, and especially brilliant

Stephen Wolfram (1:35:41.840)

physicists like Feynman to say that you can't have a compressed, clean intuition about how the whole

Stephen Wolfram (1:35:50.480)

thing works. MG Yes, yes. No, he was, I mean, I think he was sort of on the edge of understanding

Stephen Wolfram (1:35:56.240)

that point about computation. And I think he found that, I think he always found computation

Stephen Wolfram (1:36:00.800)

interesting. And I think that was sort of what he was a little bit poking at. I mean, that intuition,

Stephen Wolfram (1:36:07.200)

you know, the difficulty of discovering things, like even you say, Oh, you know, you just

Stephen Wolfram (1:36:12.080)

enumerate all the cases and just find one that does something interesting, right? Sounds very easy.

Stephen Wolfram (1:36:16.720)

Turns out, like, I missed it when I first saw it, because I had kind of an intuition

Stephen Wolfram (1:36:21.760)

that said it shouldn't be there. So I had kind of arguments, Oh, I'm going to ignore that case,

Stephen Wolfram (1:36:26.000)

because whatever. And how did you have an open mind enough? Because you're essentially the same

Stephen Wolfram (1:36:32.400)

person as you should find, like the same kind of physics type of thinking. How did you find yourself

Lex Fridman (1:36:37.760)

having a sufficiently open mind to be open to watching rules and them revealing complexity?

Stephen Wolfram (1:36:44.640)

MG Yeah, I think that's an interesting question. I've wondered about that myself, because it's

Stephen Wolfram (1:36:47.760)

kind of like, you know, you live through these things, and then you say, what was the historical

Stephen Wolfram (1:36:52.560)

story? And sometimes the historical story that you realize after the fact was not what you lived

Stephen Wolfram (1:36:56.960)

through, so to speak. And so, you know, what I realized is, I think what happened is, you know,

Stephen Wolfram (1:37:05.040)

I did physics, kind of like reductionistic physics, where you're thrown in the universe,

Lex Fridman (1:37:10.080)

and you're told, go figure out what's going on inside it. And then I started building computer

Stephen Wolfram (1:37:15.120)

tools. And I started building my first computer language, for example. And computer language is

Stephen Wolfram (1:37:20.640)

not like, it's sort of like physics in the sense that you have to take all those computations

Stephen Wolfram (1:37:24.720)

people want to do, and kind of drill down and find the primitives that they can all be made of.

Lex Fridman (1:37:30.080)

But then you do something that's really different, because you're just saying,

Stephen Wolfram (1:37:33.520)

okay, these are the primitives. Now, you know, hopefully they'll be useful to people,

Stephen Wolfram (1:37:37.760)

let's build up from there. So you're essentially building an artificial universe, in a sense,

Stephen Wolfram (1:37:43.200)

where you make this language, you've got these primitives, you're just building whatever you

Stephen Wolfram (1:37:47.280)

feel like building. And so it was sort of interesting for me, because from doing science,

Stephen Wolfram (1:37:53.040)

where you're just thrown in the universe as the universe is, to then just being told, you know,

Stephen Wolfram (1:37:58.720)

you can make up any universe you want. And so I think that experience of making a computer language,

Stephen Wolfram (1:38:04.560)

which is essentially building your own universe, so to speak, that's what gave me a somewhat

Stephen Wolfram (1:38:12.800)

different attitude towards what might be possible. It's like, let's just explore what can be done in

Stephen Wolfram (1:38:17.760)

these artificial universes, rather than thinking the natural science way of let's be constrained

Stephen Wolfram (1:38:23.760)

by how the universe actually is. Yeah, by being able to program, essentially, you've,

Stephen Wolfram (1:38:28.480)

as opposed to being limited to just your mind and a pen, you now have, you've basically built

Stephen Wolfram (1:38:34.960)

another brain that you can use to explore the universe by computer program, you know,

Stephen Wolfram (1:38:40.000)

this is kind of a brain, right? And it's well, it's it's or telescope, or you know, it's a tool,

Stephen Wolfram (1:38:44.800)

it's it lets you let's you see stuff, but there's something fundamentally different

Stephen Wolfram (1:38:47.760)

between a computer and a telescope. I mean, it just, yeah, I'm hoping to romanticize the notion,

Lex Fridman (1:38:54.480)

but it's more general, the computer is more general. And it's, it's, I think, I mean, this

Stephen Wolfram (1:39:00.160)

point about, you know, people say, oh, such and such a thing was almost discovered at such and

Stephen Wolfram (1:39:07.200)

such a time, the the distance between, you know, the building the paradigm that allows you to

Stephen Wolfram (1:39:12.400)

actually understand stuff or allows one to be open to seeing what's going on. That's really hard.

Stephen Wolfram (1:39:18.080)

And, you know, I think, in I've been fortunate in my life that I spent a lot of my time building

Stephen Wolfram (1:39:24.080)

computational language. And that's an activity that, in a sense, works by sort of having to

Stephen Wolfram (1:39:33.760)

kind of create another level of abstraction and kind of be open to different kinds of structures.

Stephen Wolfram (1:39:39.040)

But, you know, it's, it's always I mean, I'm fully aware of, I suppose, the fact that I have seen it

Stephen Wolfram (1:39:45.760)

a bunch of times of how easy it is to miss the obvious, so to speak, that at least is factored

Stephen Wolfram (1:39:51.760)

into my attempt to not miss the obvious, although it may not succeed. What do you think is the role

Stephen Wolfram (1:39:59.280)

of ego in the history of math and science? And more sort of, you know, a book title is something

Stephen Wolfram (1:40:08.720)

like a new kind of science. You've accomplished a huge amount. In fact, somebody said that Newton

Stephen Wolfram (1:40:16.240)

didn't have an ego, and I looked into it and he had a huge ego. Yeah, but from an outsider's

Stephen Wolfram (1:40:21.040)

perspective, some have said that you have a bit of an ego as well. Do you see it that way? Does

Stephen Wolfram (1:40:28.960)

ego get in the way? Is it empowering? Is it both? So it's, it's, it's complicated and necessary. I

Stephen Wolfram (1:40:34.960)

mean, you know, I've had, look, I've spent more than half my life CEO in a tech company. Right.

Stephen Wolfram (1:40:39.920)

Okay. And, you know, that is a, I think it's actually very, it means that one's ego is not

Stephen Wolfram (1:40:50.080)

a distant thing. It's a thing that one encounters every day, so to speak, because it's, it's all

Stephen Wolfram (1:40:55.200)

tied up with leadership and with how one, you know, develops an organization and all these

Stephen Wolfram (1:40:59.360)

kinds of things. So, you know, it may be that if I'd been an academic, for example, I could have

Stephen Wolfram (1:41:03.760)

sort of, you know, check the ego, put it on, put on a shelf somewhere and ignore its characteristics,

Lex Fridman (1:41:09.760)

but you're reminded of it quite often in the context of running a company. Sure. I mean,

Stephen Wolfram (1:41:15.920)

that's what it's about. It's, it's about leadership and, you know, leadership is intimately tied to

Stephen Wolfram (1:41:22.160)

ego. Now, what does it mean? I mean, what, what is the, you know, for me, I've been fortunate that I

Stephen Wolfram (1:41:27.760)

think I have reasonable intellectual confidence, so to speak. That is, you know, I, I'm one of

Stephen Wolfram (1:41:34.800)

these people who at this point, if somebody tells me something and I just don't understand it,

Stephen Wolfram (1:41:39.360)

my conclusion isn't that means I'm dumb. That my conclusion is there's something wrong with

Lex Fridman (1:41:45.520)

what I'm being told. And that was actually Dick Feynman used to have that, that that feature too,

Stephen Wolfram (1:41:51.120)

he never really believed in. He actually believed in experts much less than I believe in experts.

Stephen Wolfram (1:41:55.760)

So. Wow. So that's a fun, that's a, that's a fundamentally powerful property of ego and saying,

Stephen Wolfram (1:42:03.280)

like, not that I am wrong, but that the, the world is wrong. And, and tell me, like, when confronted

Stephen Wolfram (1:42:12.640)

with the fact that doesn't fit the thing that you've really thought through sort of both the

Stephen Wolfram (1:42:17.440)

negative and the positive of ego, do you see the negative of that get in the way sort of being

Stephen Wolfram (1:42:24.240)

sure of the mistakes I've made that are the results of, I'm pretty sure I'm right. And

Stephen Wolfram (1:42:30.240)

turns out I'm not. I mean, that's, that's the, you know, but, but the thing is that the, the,

Stephen Wolfram (1:42:36.560)

the idea that one tries to do things that, so for example, you know, one question is if people have

Stephen Wolfram (1:42:42.640)

tried hard to do something and then one thinks, maybe I should try doing this myself. Uh, if one

Stephen Wolfram (1:42:48.960)

does not have a certain degree of intellectual confidence, one just says, well, people have been

Stephen Wolfram (1:42:52.560)

trying to do this for a hundred years. How am I going to be able to do this? Yeah. And, you know,

Stephen Wolfram (1:42:56.880)

I was fortunate in the sense that I happened to start having some degree of success in science

Lex Fridman (1:43:02.240)

and things when I was really young. And so that developed a certain amount of sort of intellectual

Stephen Wolfram (1:43:07.120)

confidence. I don't think I otherwise would have had. Um, and you know, in a sense, I mean,

Stephen Wolfram (1:43:12.080)

I was fortunate that I was working in a field, particle physics during its sort of golden age

Stephen Wolfram (1:43:17.600)

of rapid progress. And that, that's kind of gives one a false sense of, uh, achievement because

Stephen Wolfram (1:43:22.720)

it's kind of, kind of easy to discover stuff that's going to survive. If you happen to be,

Lex Fridman (1:43:26.800)

you know, picking the low hanging fruit of a rapidly expanding field.

Stephen Wolfram (1:43:30.400)

I mean, the reason I totally, I totally immediately understood the ego behind a new

Stephen Wolfram (1:43:34.800)

kind of science to me, let me sort of just try to express my feelings on the whole thing,

Stephen Wolfram (1:43:39.680)

is that if you don't allow that kind of ego, then you would never write that book.

Stephen Wolfram (1:43:46.000)

That you would say, well, people must have done this. There's not, you would not dig.

Stephen Wolfram (1:43:49.920)

You would not keep digging. And I think that was, I think you have to take that ego and,

Lex Fridman (1:43:56.720)

and ride it and see where it takes you. And that's how you create exceptional work.

Lex Fridman (1:44:02.560)

But I think the other point about that book was it was a non trivial question,

Lex Fridman (1:44:07.040)

how to take a bunch of ideas that are, I think, reasonably big ideas. They might,

Stephen Wolfram (1:44:12.320)

they might, you know, their importance is determined by what happens historically.

Lex Fridman (1:44:16.880)

One can't tell how important they are. One can tell sort of the scope of them.

Lex Fridman (1:44:20.720)

And the scope is fairly big and they're very different from things that have come before.

Lex Fridman (1:44:26.000)

And the question is, how do you explain that stuff to people? And so I had had the experience

Stephen Wolfram (1:44:31.040)

of sort of saying, well, there are these things, there's a cellular automaton. It does this,

Stephen Wolfram (1:44:34.880)

it does that. And people are like, oh, it must be just like this. It must be just like that.

Lex Fridman (1:44:39.040)

So no, it isn't. It's something different. Right. And so I could have done sort of,

Stephen Wolfram (1:44:44.080)

I'm really glad you did what you did, but you could have done sort of academically,

Stephen Wolfram (1:44:47.280)

just published, keep publishing small papers here and there. And then you would just keep

Stephen Wolfram (1:44:51.440)

getting this kind of resistance, right? You would get like, yeah, it's supposed to just

Stephen Wolfram (1:44:55.520)

dropping a thing that says, here it is, here's the full, the full thing.

Stephen Wolfram (1:45:00.000)

No, I mean, that was my calculation is that basically, you know, you could introduce

Stephen Wolfram (1:45:04.640)

little pieces. It's like, you know, one possibility is like, it's the secret weapon,

Lex Fridman (1:45:09.680)

so to speak. It's this, you know, I keep on discovering these things in all these different

Stephen Wolfram (1:45:13.760)

areas. Where'd they come from? Nobody knows. But I decided that, you know, in the interests of one

Stephen Wolfram (1:45:18.640)

only has one life to lead and, you know, writing that book took me a decade anyway. There's not a

Stephen Wolfram (1:45:24.800)

lot of wiggle room, so to speak. One can't be wrong by a factor of three, so to speak, in how long

Stephen Wolfram (1:45:29.200)

it's going to take. That I, you know, I thought the best thing to do, the thing that is most sort

Stephen Wolfram (1:45:35.600)

of, that most respects the intellectual content, so to speak, is you just put it out with as much

Stephen Wolfram (1:45:44.400)

force as you can, because it's not something where, and, you know, it's an interesting thing.

Stephen Wolfram (1:45:49.360)

You talk about ego and it's, you know, for example, I run a company which has my name on it,

Stephen Wolfram (1:45:54.800)

right? I thought about starting a club for people whose companies have their names on them. And

Stephen Wolfram (1:45:59.520)

it's a funny group because we're not a bunch of egomaniacs. That's not what it's about,

Lex Fridman (1:46:04.560)

so to speak. It's about basically sort of taking responsibility for what one's doing.

Stephen Wolfram (1:46:10.240)

And, you know, in a sense, any of these things where you're sort of putting yourself on the line,

Stephen Wolfram (1:46:15.680)

it's kind of a funny, it's a funny dynamic because, in a sense, my company is sort of

Stephen Wolfram (1:46:25.760)

something that happens to have my name on it, but it's kind of bigger than me and I'm kind of just

Stephen Wolfram (1:46:30.080)

its mascot at some level. I mean, I also happen to be a pretty, you know, strong leader of it.

Stephen Wolfram (1:46:35.680)

LW. But it's basically showing a deep, inextricable sort of investment. Your name,

Stephen Wolfram (1:46:45.920)

like Steve Jobs's name wasn't on Apple, but he was Apple. Elon Musk's name is not on Tesla,

Lex Fridman (1:46:55.760)

but he is Tesla. So it's like, it meaning emotionally. If a company succeeds or fails,

Stephen Wolfram (1:47:01.840)

he would just that emotionally would suffer through that. And so that's, that's a beautiful

Stephen Wolfram (1:47:07.760)

recognizing that fact. And also Wolfram is a pretty good branding name, so that works out.

Lex Fridman (1:47:12.240)

LW. Yeah, right. Exactly. I think Steve had it had a bad deal there.

Stephen Wolfram (1:47:16.320)

LR. Yeah. So you made up for it with the last name. Okay. So in 2002, you published

Stephen Wolfram (1:47:23.760)

A New Kind of Science, to which sort of on a personal level, I can credit my love for

Stephen Wolfram (1:47:29.920)

cellular automata and computation in general. I think a lot of others can as well. Can you

Lex Fridman (1:47:35.680)

briefly describe the vision, the hope, the main idea presented in this 1200 page book?

Stephen Wolfram (1:47:45.760)

LW. Sure. Although it took 1200 pages to say in the book. So no, the real idea, it's kind of

Stephen Wolfram (1:47:54.800)

a good way to get into it is to look at sort of the arc of history and to look at what's happened

Stephen Wolfram (1:47:58.800)

in kind of the development of science. I mean, there was this sort of big idea in science about

Stephen Wolfram (1:48:04.080)

300 years ago, that was, let's use mathematical equations to try and describe things in the world.

Stephen Wolfram (1:48:10.960)

Let's use sort of the formal idea of mathematical equations to describe what might be happening in

Stephen Wolfram (1:48:16.080)

the world, rather than, for example, just using sort of logical augmentation and so on. Let's have

Stephen Wolfram (1:48:21.520)

a formal theory about that. And so there'd been this 300 year run of using mathematical equations

Stephen Wolfram (1:48:27.280)

to describe the natural world, which had worked pretty well. But I got interested in how one could

Stephen Wolfram (1:48:32.400)

generalize that notion. There is a formal theory, there are definite rules, but what structure could

Stephen Wolfram (1:48:38.640)

those rules have? And so what I got interested in was let's generalize beyond the sort of purely

Stephen Wolfram (1:48:44.400)

mathematical rules. And we now have this sort of notion of programming and computing and so on.

Stephen Wolfram (1:48:50.640)

Let's use the kinds of rules that can be embodied in programs as a sort of generalization of the

Stephen Wolfram (1:48:57.520)

ones that can exist in mathematics as a way to describe the world. And so my kind of favorite

Stephen Wolfram (1:49:04.400)

version of these kinds of simple rules are these things called cellular automata. And so typical

Stephen Wolfram (1:49:09.840)

case... So wait, what are cellular automata? Fair enough. So typical case of a cellular automaton,

Stephen Wolfram (1:49:16.960)

it's an array of cells. It's just a line of discrete cells. Each cell is either black or white.

Lex Fridman (1:49:25.360)

And in a series of steps that you can represent as lines going down a page, you're updating the

Stephen Wolfram (1:49:31.440)

color of each cell according to a rule that depends on the color of the cell above it and

Stephen Wolfram (1:49:35.840)

to its left and right. So it's really simple. So a thing might be if the cell and its right neighbor

Stephen Wolfram (1:49:44.160)

are not the same or the cell on the left is black or something, then make it black on the next step.

Lex Fridman (1:49:54.960)

And if not, make it white. Typical rule. That rule, I'm not sure I said it exactly right,

Lex Fridman (1:50:01.280)

but a rule very much like what I just said, has the feature that if you started off from just one

Stephen Wolfram (1:50:05.920)

black cell at the top, it makes this extremely complicated pattern. So some rules you get a very

Stephen Wolfram (1:50:12.800)

simple pattern. Some rules, the rule is simple. You start them off from a sort of simple seed.

Stephen Wolfram (1:50:19.600)

You just get this very simple pattern. But other rules, and this was the big surprise when I

Stephen Wolfram (1:50:25.280)

started actually just doing the simple computer experiments to find out what happens, is that they

Stephen Wolfram (1:50:30.720)

produce very complicated patterns of behavior. So for example, this rule 30 rule has the feature

Stephen Wolfram (1:50:36.960)

you start off from just one black cell at the top, makes this very random pattern. If you look

Stephen Wolfram (1:50:43.120)

like at the center column of cells, you get a series of values. It goes black, white, black,

Stephen Wolfram (1:50:49.120)

black, whatever it is. That sequence seems for all practical purposes random. So it's kind of like

Stephen Wolfram (1:50:56.720)

in math, you compute the digits of pi, 3.1415926, whatever. Those digits once computed, I mean,

Stephen Wolfram (1:51:05.200)

the scheme for computing pi, it's the ratio of the circumference to the diameter of a circle,

Stephen Wolfram (1:51:09.520)

very well defined. But yet, once you've generated those digits, they seem for all practical

Stephen Wolfram (1:51:15.920)

purposes completely random. And so it is with rule 30, that even though the rule is very simple,

Stephen Wolfram (1:51:22.000)

much simpler, much more sort of computationally obvious than the rule for generating digits of pi,

Stephen Wolfram (1:51:28.240)

even with a rule that simple, you're still generating immensely complicated behavior.

Stephen Wolfram (1:51:32.960)

Yeah. So if we could just pause on that, I think you probably have said it and looked at it so long,

Stephen Wolfram (1:51:38.080)

you forgot the magic of it, or perhaps you don't, you still feel the magic. But to me,

Stephen Wolfram (1:51:43.040)

if you've never seen sort of, I would say, what is it? A one dimensional, essentially,

Stephen Wolfram (1:51:49.280)

cellular automata, right? And you were to guess what you would see if you have some

Stephen Wolfram (1:51:57.280)

sort of cells that only respond to its neighbors. Right. If you were to guess what kind of things

Stephen Wolfram (1:52:04.000)

you would see, like my initial guess, like even when I first like opened your book,

Stephen Wolfram (1:52:09.920)

A New Kind of Science, right? My initial guess is you would see, I mean, it would be a very simple

Stephen Wolfram (1:52:15.920)

stuff. Right. And I think it's a magical experience to realize the kind of complexity,

Stephen Wolfram (1:52:22.400)

you mentioned rule 30, still your favorite cellular automaton? Still my favorite rule. Yes.

Stephen Wolfram (1:52:28.880)

You get complexity, immense complexity, you get arbitrary complexity. Yes. And when you say

Stephen Wolfram (1:52:35.600)

randomness down the middle column, that's just one cool way to say that there's incredible complexity.

Lex Fridman (1:52:44.400)

And that's just, I mean, that's a magical idea. However, you start to interpret it,

Stephen Wolfram (1:52:49.920)

all the reducibility discussions, all that. But it's just, I think that has profound philosophical

Stephen Wolfram (1:52:56.960)

kind of notions around it, too. It's not just, I mean, it's transformational about how you see the

Stephen Wolfram (1:53:03.040)

world. I think for me it was transformational. I don't know, we can have all kinds of discussion

Stephen Wolfram (1:53:07.760)

about computation and so on, but just, you know, I sometimes think if I were on a desert island

Lex Fridman (1:53:15.280)

and was, I don't know, maybe it was some psychedelics or something, but if I had to take

Stephen Wolfram (1:53:19.920)

one book, I mean, you kind of science would be it because you could just enjoy that notion. For some

Stephen Wolfram (1:53:25.680)

reason, it's a deeply profound notion, at least to me. I find it that way. Yeah. I mean, look, it's

Stephen Wolfram (1:53:30.480)

been, it was a very intuition breaking thing to discover. I mean, it's kind of like, you know,

Stephen Wolfram (1:53:39.040)

you point the computational telescope out the window and you're like, okay, I'm going to

Stephen Wolfram (1:53:43.680)

point the computational telescope out there. And suddenly you see, I don't know, you know,

Stephen Wolfram (1:53:48.800)

in the past, it's kind of like, you know, moons of Jupiter or something, but suddenly you see

Stephen Wolfram (1:53:52.160)

something that's kind of very unexpected and rule 30 was very unexpected for me. And the big

Stephen Wolfram (1:53:57.200)

challenge at a personal level was to not ignore it. I mean, people, you know, in other words,

Stephen Wolfram (1:54:03.120)

you might say, you know, it's a bug. What would you say? Yeah. Well, yeah. I mean, I,

Lex Fridman (1:54:08.160)

what are we looking at by the way? Oh, well, I was just generating here. I'll actually generate

Stephen Wolfram (1:54:11.600)

a rule 30 pattern. So that's the rule for, for rule 30. And it says, for example, it says here,

Stephen Wolfram (1:54:18.480)

if you have a black cell in the middle and black cell to the left and white cell to the right,

Stephen Wolfram (1:54:22.720)

then the cell on the next step will be white. And so here's the actual pattern that you get

Stephen Wolfram (1:54:27.840)

starting off from a single black cell at the top there. And then that's the initial state initial

Stephen Wolfram (1:54:34.160)

condition. That's the initial thing. You just start off from that and then you're going down

Stephen Wolfram (1:54:37.840)

the page and at every, at every step, you're just applying this rule to find out the new value that

Stephen Wolfram (1:54:44.480)

you get. And so you might think rule that simple, you got to get the, there's got to be some trace

Stephen Wolfram (1:54:50.320)

of that simplicity here. Okay. We'll run it. Let's say for 400 steps. Um, so what it does,

Stephen Wolfram (1:54:56.320)

it's kind of aliasing a bit on the screen there, but, but, um, you can see there's a little bit

Stephen Wolfram (1:55:00.080)

of regularity over on the left, but there's a lot of stuff here that just looks very complicated,

Stephen Wolfram (1:55:07.040)

very random. And, uh, that's a big sort of shock to was a big shock to my intuition, at least

Stephen Wolfram (1:55:14.320)

that that's possible. The mind immediately starts. Is there a pattern? There must be a repetitive

Stephen Wolfram (1:55:19.200)

pattern. There must be. So I spent, so indeed, that's what I thought at first. And I thought,

Stephen Wolfram (1:55:25.120)

I thought, well, this is kind of interesting, but you know, if we run it long enough, we'll see,

Stephen Wolfram (1:55:29.440)

you know, something we'll resolve into something simple. And, uh, uh, you know, I did all kinds of

Stephen Wolfram (1:55:34.720)

analysis of using mathematics, statistics, cryptography, whatever, whatever to try and crack

Stephen Wolfram (1:55:41.200)

it. Um, and I never succeeded. And after I hadn't succeeded for a while, I started thinking maybe

Stephen Wolfram (1:55:46.560)

there's a real phenomenon here. That is the reason I'm not succeeding. Maybe. I mean, the thing that

Stephen Wolfram (1:55:52.080)

for me was sort of a motivating factor was looking at the natural world and seeing all this complexity

Stephen Wolfram (1:55:57.360)

that exists in the natural world. The question is, where does it come from? You know, what secret

Stephen Wolfram (1:56:01.520)

does nature have that lets it make all this complexity that we humans, when we engineer

Stephen Wolfram (1:56:06.640)

things typically are not making, we're typically making things that at least look quite simple to

Stephen Wolfram (1:56:11.840)

us. And so the shock here was even from something very simple, you're making something that complex.

Stephen Wolfram (1:56:18.800)

Uh, maybe this is getting at sort of the secret that nature has that allows it to make really

Stephen Wolfram (1:56:24.240)

complex things, even though its underlying rules may not be that complex. How did it make you feel

Stephen Wolfram (1:56:30.480)

if we, if we look at the Newton apple, was there, was it, was there a, you know, you took a walk

Lex Fridman (1:56:36.400)

and, and something it profoundly hit you or was this a gradual thing, a lobster being boiled?

Stephen Wolfram (1:56:43.920)

The truth of every sort of science discovery is it's not that gradual. I mean, I've spent,

Stephen Wolfram (1:56:50.320)

I happen to be interested in scientific biography kinds of things. And so I've tried to track down,

Stephen Wolfram (1:56:54.240)

you know, how did people come to figure out this or that thing? And there's always a long kind of,

Stephen Wolfram (1:57:00.080)

uh, sort of preparatory, um, you know, there's a, there's a need to be prepared in a mindset

Stephen Wolfram (1:57:06.880)

in which it's possible to see something. I mean, in the case of rule 30,

Stephen Wolfram (1:57:10.320)

I was around June 1st, 1984 was, um, uh, kind of a silly story in some ways. I finally had

Stephen Wolfram (1:57:16.560)

a high resolution laser printer. So I was able, so I thought I'm going to generate a bunch of

Stephen Wolfram (1:57:20.800)

pictures of the cellular automata and I generate this one and I put it, I was on some plane flight

Stephen Wolfram (1:57:27.200)

to Europe and they have this with me. And it's like, you know, I really should try to understand

Stephen Wolfram (1:57:32.640)

this. And this is really, you know, this is, I really don't understand what's going on.

Stephen Wolfram (1:57:37.440)

And, uh, that was kind of the, um, you know, slowly trying to, trying to see what was happening.

Stephen Wolfram (1:57:43.760)

It was not, uh, it was depressingly unsubstantial, so to speak, in the sense that, um, a lot of these

Stephen Wolfram (1:57:50.240)

ideas like principle of computational equivalence, for example, you know, I thought, well, that's a

Stephen Wolfram (1:57:56.240)

possible thing. I didn't know if it's correct, still don't know for sure that it's correct.

Stephen Wolfram (1:58:00.800)

Um, but it's sort of a gradual thing that these things gradually kind of become seem more important

Stephen Wolfram (1:58:07.120)

than one thought. I mean, I think the whole idea of studying the computational universe of simple

Stephen Wolfram (1:58:12.160)

programs, it took me probably a decade, decade and a half to kind of internalize that that was

Stephen Wolfram (1:58:19.120)

really an important idea. Um, and I think, you know, if it turns out we find the whole universe

Stephen Wolfram (1:58:24.880)

lurking out there in the computational universe, that's a good, uh, you know, it's a good brownie

Stephen Wolfram (1:58:29.520)

point or something for the, uh, for the whole idea. But I think that the, um, the thing that's

Stephen Wolfram (1:58:34.560)

strange in this whole question about, you know, finding this different raw material for making

Stephen Wolfram (1:58:39.840)

models of things, um, what's been interesting sort of in the, in sort of arc of history is,

Stephen Wolfram (1:58:45.280)

you know, for 300 years, it's kind of like the, the mathematical equations approach.

Stephen Wolfram (1:58:49.440)

It was the winner. It was the thing, you know, you want to have a really good model for something

Stephen Wolfram (1:58:53.440)

that's what you use. The thing that's been remarkable is just in the last decade or so,

Stephen Wolfram (1:58:58.960)

I think one can see a transition to using not mathematical equations, but programs

Stephen Wolfram (1:59:04.800)

as sort of the raw material for making models of stuff. And that's pretty neat. And it's kind of,

Stephen Wolfram (1:59:11.280)

you know, as somebody who's kind of lived inside this paradigm shift, so to speak,

Stephen Wolfram (1:59:15.440)

it is bizarre. I mean, no doubt in sort of the history of science that will be seen as an

Stephen Wolfram (1:59:20.640)

instantaneous paradigm shift, but it sure isn't instantaneous when it's played out in one's actual

Stephen Wolfram (1:59:25.760)

life. So to speak, it seems glacial. Um, um, and it's the kind of thing where, where it's sort of

Stephen Wolfram (1:59:32.800)

interesting because in the dynamics of sort of the adoption of ideas like that into different fields,

Stephen Wolfram (1:59:40.320)

the younger the field, the faster the adoption typically, because people are not kind of locked

Stephen Wolfram (1:59:46.000)

in with the fifth generation of people who've studied this field and it is, it is the way it is

Lex Fridman (1:59:52.080)

and it can never be any different. And I think that's been, um, you know, watching that process

Stephen Wolfram (1:59:57.040)

has been interesting. I mean, I'm, I'm, I think I'm fortunate that I, I've, uh, uh, I, I do stuff

Stephen Wolfram (20:00.560)

first kind of understanding they'll be interested in. Gosh, that's so hard. That's like in the

Stephen Wolfram (20:05.280)

Arrival movie, that was one of the key questions is, why are you here, so to speak? Are you going

Stephen Wolfram (20:11.760)

to hurt us? But even that, it's very unclear. It's like, are you going to hurt us? That comes

Stephen Wolfram (20:17.920)

back to a lot of interesting AI ethics questions, because we might make an AI that says, well,

Stephen Wolfram (20:24.240)

take autonomous cars, for instance. Are you going to hurt us? Well, let's make sure you only drive

Stephen Wolfram (20:29.840)

at precisely the speed limit, because we want to make sure we don't hurt you, so to speak.

Lex Fridman (20:36.240)

But you say, but actually, that means I'm going to be really late for this thing, and

Stephen Wolfram (20:40.000)

that sort of hurts me in some way. So it's hard to know. Even the definition of what it means to

Stephen Wolfram (20:46.320)

hurt someone is unclear. And as we start thinking about things about AI ethics and so on, that's

Stephen Wolfram (20:54.240)

something one has to address. There's always tradeoffs, and that's the annoying thing about

Stephen Wolfram (20:58.720)

ethics. Yeah, well, right. And I think ethics, like these other things we're talking about,

Stephen Wolfram (21:03.600)

is a deeply human thing. There's no abstract, let's write down the theorem that proves that

Stephen Wolfram (21:10.480)

this is ethically correct. That's a meaningless idea. You have to have a ground truth, so to

Stephen Wolfram (21:17.200)

speak, that's ultimately what humans want, and they don't all want the same thing. So that gives

Stephen Wolfram (21:23.920)

one all kinds of additional complexity in thinking about that. One convenient thing in terms of

Stephen Wolfram (21:28.960)

turning ethics into computation, you can ask the question of what maximizes the likelihood of the

Stephen Wolfram (21:35.360)

survival of the species. That's a good existential issue. But then when you say survival of the

Stephen Wolfram (21:42.960)

species, you might say, you might, for example, let's say, forget about technology, just hang out

Lex Fridman (21:52.080)

and be happy, live our lives, go on to the next generation, go through many, many generations

Stephen Wolfram (21:58.400)

where, in a sense, nothing is happening. Is that okay? Is that not okay? Hard to know. In terms of

Stephen Wolfram (22:05.280)

the attempt to do elaborate things and the attempt to might be counterproductive for the survival of

Stephen Wolfram (22:14.560)

the species. It's also a little bit hard to know, so okay, let's take that as a sort of thought

Stephen Wolfram (22:23.040)

experiment. You can say, well, what are the threats that we might have to survive? The

Stephen Wolfram (22:30.080)

super volcano, the asteroid impact, all these kinds of things. Okay, so now we inventory these

Stephen Wolfram (22:37.040)

possible threats and we say, let's make our species as robust as possible relative to all

Stephen Wolfram (22:41.600)

these threats. I think in the end, it's sort of an unknowable thing what it takes. So given that

Stephen Wolfram (22:51.680)

you've got this AI and you've told it, maximize the long term. What does long term mean? Does

Stephen Wolfram (22:58.880)

long term mean until the sun burns out? That's not going to work. Does long term mean next thousand

Stephen Wolfram (23:05.920)

years? Okay, they're probably optimizations for the next thousand years. It's like if you're

Stephen Wolfram (23:12.640)

running a company, you can make a company be very stable for a certain period of time.

Stephen Wolfram (23:16.720)

Like if your company gets bought by some private investment group, then you can run a company just

Stephen Wolfram (23:25.440)

fine for five years by just taking what it does and removing all R&D and the company will burn

Stephen Wolfram (23:33.200)

out after a while, but it'll run just fine for a little while. So if you tell the AI, keep the

Stephen Wolfram (23:38.000)

humans okay for a thousand years, there's probably a certain set of things that one would do to

Stephen Wolfram (23:42.000)

optimize that, many of which one might say, well, that would be a pretty big shame for the future of

Stephen Wolfram (23:46.720)

history, so to speak, for that to be what happens. But I think in the end, as you start thinking

Stephen Wolfram (23:51.520)

about that question, what you realize is there's a whole sort of raft of undecidability, computational

Stephen Wolfram (24:00.320)

irreducibility. In other words, one of the good things about what our civilization has gone

Stephen Wolfram (24:08.880)

through and what we humans go through is that there's a certain computational irreducibility

Stephen Wolfram (24:13.920)

to it in the sense that it isn't the case that you can look from the outside and just say,

Stephen Wolfram (24:18.320)

the answer is going to be this. At the end of the day, this is what's going to happen.

Stephen Wolfram (24:22.320)

You actually have to go through the process to find out. And I think that feels better in the

Stephen Wolfram (24:28.560)

sense that something is achieved by going through all of this process. But it also means

Stephen Wolfram (24:38.800)

that telling the AI, go figure out what will be the best outcome. Well, unfortunately, it's going

Stephen Wolfram (24:44.960)

to come back and say, it's kind of undecidable what to do. We'd have to run all of those scenarios

Stephen Wolfram (24:51.120)

to see what happens. And if we want it for the infinite future, we're thrown immediately into

Stephen Wolfram (24:57.040)

sort of standard issues of kind of infinite computation and so on. So yeah, even if you

Stephen Wolfram (25:02.160)

get that the answer to the universe and everything is 42, you still have to actually run the universe.

Stephen Wolfram (25:07.680)

Yes, to figure out the question, I guess, or the journey is the point.

Stephen Wolfram (25:16.640)

Right. Well, I think it's saying to summarize, this is the result of the universe. If that is

Stephen Wolfram (25:23.360)

possible, it tells us, I mean, the whole sort of structure of thinking about computation and so on

Lex Fridman (25:29.440)

and thinking about how stuff works. If it's possible to say, and the answer is such and such,

Stephen Wolfram (25:35.280)

you're basically saying there's a way of going outside the universe. And you're getting yourself

Stephen Wolfram (25:40.320)

into something of a sort of paradox because you're saying, if it's knowable what the answer is, then

Stephen Wolfram (25:46.400)

there's a way to know it that is beyond what the universe provides. But if we can know it, then

Stephen Wolfram (25:52.400)

something that we're dealing with is beyond the universe. So then the universe isn't the universe,

Lex Fridman (25:58.240)

so to speak. And in general, as we'll talk about, at least for our small human brains, it's

Stephen Wolfram (26:08.320)

hard to show the result of a sufficiently complex computation. I mean, it's probably impossible,

Stephen Wolfram (26:15.760)

right, on this side ability. And the universe appears by at least the poets to be sufficiently

Stephen Wolfram (26:25.040)

complex. They won't be able to predict what the heck it's all going to. Well, we better not be

Stephen Wolfram (26:30.960)

able to, because if we can, it kind of denies. I mean, it's you know, we're part of the universe.

Stephen Wolfram (26:36.240)

Yeah. So what does it mean for us to predict? It means that we that our little part of the universe

Stephen Wolfram (26:42.000)

is able to jump ahead of the whole universe. And this this quickly winds up. I mean, that it is

Stephen Wolfram (26:48.720)

conceivable. The only way we'd be able to predict is if we are so special in the universe, we are

Stephen Wolfram (26:54.640)

the one place where there is computation more special, more sophisticated than anything else

Stephen Wolfram (27:00.080)

that exists in the universe. That's the only way we would have the ability to sort of the almost

Stephen Wolfram (27:05.600)

theological ability, so to speak, to predict what happens in the universe is to say somehow we're

Stephen Wolfram (27:12.400)

better than everything else in the universe, which I don't think is the case. Yeah, perhaps we can

Stephen Wolfram (27:17.840)

detect a large number of looping patterns that reoccur throughout the universe and fully describe

Stephen Wolfram (27:26.160)

them. And therefore, but then it still becomes exceptionally difficult to see how those patterns

Stephen Wolfram (27:31.440)

interact and what kind of well, look, the most remarkable thing about the universe is that it's

Stephen Wolfram (27:37.600)

has regularity at all. Might not be the case. If you just have regularity, do you? Absolutely.

Stephen Wolfram (27:43.440)

That fits full of I mean, physics is successful. You know, it's full of of laws that tell us a lot

Stephen Wolfram (27:50.160)

of detail about how the universe works. I mean, it could be the case that, you know, the 10 to the

Stephen Wolfram (27:54.640)

90th particles in the universe, they will do their own thing, but they don't. They all follow. We

Stephen Wolfram (27:58.960)

already know they all follow basically physical, the same physical laws. And that's something

Stephen Wolfram (28:04.880)

that's a very profound fact about the universe. What conclusion you draw from that is unclear. I

Stephen Wolfram (28:10.400)

mean, in the, you know, the early early theologians, that was, you know, exhibit number one for the

Stephen Wolfram (28:16.240)

existence of God. Now, you know, people have different conclusions about it. But the fact is,

Stephen Wolfram (28:22.320)

you know, right now, I mean, I happen to be interested, actually, I've just restarted a

Stephen Wolfram (28:26.800)

long running kind of interest of mine about fundamental physics. I'm kind of like, come on,

Stephen Wolfram (28:32.800)

I'm on a bit of a quest, which I'm about to make more public, to see if I can actually find the

Stephen Wolfram (28:39.200)

fundamental theory of physics. Excellent. We'll come to that. And I just had a lot of conversations

Stephen Wolfram (28:46.160)

with quantum mechanics folks with so I'm really excited on your take, because I think you have a

Stephen Wolfram (28:52.000)

fascinating take on the the fundamental nature of our reality from a physics perspective. So

Lex Fridman (28:59.440)

and what might be underlying the kind of physics as we think of it today. Okay, let's take a step

Stephen Wolfram (29:06.000)

back. What is computation? It's a good question. Operationally, computation is following rules.

Stephen Wolfram (29:15.120)

That's kind of it. I mean, computation is the result is the process of systematically following

Stephen Wolfram (29:20.800)

rules. And it is the thing that happens when you do that. So taking initial conditions are taking

Stephen Wolfram (29:26.800)

inputs and following rules. I mean, what are you following rules on? So there has to be some data,

Stephen Wolfram (29:33.520)

some unnecessarily, it can be something where there's a, you know, very simple input. And then

Stephen Wolfram (29:40.000)

you're following these rules. And you'd say there's not really much data going into this.

Stephen Wolfram (29:44.400)

It's you could actually pack the initial conditions into the rule, if you want to. So I think the

Lex Fridman (29:51.360)

question is, is there a robust notion of computation? That is, what does robust mean?

Lex Fridman (29:55.840)

What I mean by that is something like this. So So one of the things in a different in another

Stephen Wolfram (29:59.200)

physics, something like energy, okay, the different forms of energy, there's, but somehow energy is a

Stephen Wolfram (2:00:03.680)

mainly cause I like doing it. And, um, uh, if I was, um, uh, that makes me kind of thick skinned

Stephen Wolfram (2:00:09.760)

about the world's response to what I do. Um, and uh, but that's definitely, uh, you know, and anytime

Stephen Wolfram (2:00:16.080)

you, you write a book called something like a new kind of science, um, it's kind of the, the pitch

Stephen Wolfram (2:00:21.680)

forks will come out for the, for the old kind of science. And I was, it was interesting dynamics.

Stephen Wolfram (2:00:26.560)

I think that the, um, um, uh, I have to say that I was fully aware of the fact that the, um, when

Stephen Wolfram (2:00:34.800)

you see sort of incipient paradigm shifts in science, the vigor of the negative response

Stephen Wolfram (2:00:41.200)

upon early introduction is a fantastic positive indicator of good longterm results. So in other

Stephen Wolfram (2:00:48.960)

words, if people just don't care, it's, um, you know, that's not such a good sign. If they're

Stephen Wolfram (2:00:55.440)

like, oh, this is great. That means you didn't really discover anything interesting. Um, what

Stephen Wolfram (2:01:01.120)

fascinating properties of rule 30 have you discovered over the years? You've recently

Stephen Wolfram (2:01:05.600)

announced the rule 30 prizes for solving three key problems. Can you maybe talk about interesting

Stephen Wolfram (2:01:11.680)

properties that have been kind of revealed rule 30 or other cellular automata and what problems

Stephen Wolfram (2:01:18.800)

are still before us? Like the three problems you've announced. Yeah. Yeah. Right. So, I mean,

Stephen Wolfram (2:01:24.480)

the most interesting thing about cellular automata is that it's hard to figure stuff out about them.

Lex Fridman (2:01:29.280)

And that's, um, uh, in a sense, every time you try and sort of, uh, uh, you try and bash them with

Stephen Wolfram (2:01:36.480)

some other technique, you say, can I crack them? The answer is they seem to be uncrackable. They

Stephen Wolfram (2:01:42.400)

seem to have the feature that they are, um, that they're sort of showing irreducible computation.

Stephen Wolfram (2:01:49.040)

They're not, you're not able to say, oh, I know exactly what this is going to do. It's going to

Stephen Wolfram (2:01:53.920)

do this or that, but there's specific formulations of that fact. Yes. Right. So, I mean, for example,

Stephen Wolfram (2:02:00.080)

in, in rule 30, in the pattern you get just starting from a single black cell, you get this

Stephen Wolfram (2:02:05.520)

sort of very, very sort of random looking pattern. And so one feature of that, just look at the

Stephen Wolfram (2:02:11.520)

center column. And for example, we use that for a long time to generate randomness symbols and

Stephen Wolfram (2:02:16.800)

language, um, just, you know, what rule 30 produces. Now the question is, can you prove

Lex Fridman (2:02:22.560)

how random it is? So for example, one very simple question, can you prove that it'll never repeat?

Stephen Wolfram (2:02:28.560)

We haven't been able to show that it will never repeat.

Lex Fridman (2:02:32.800)

We know that if there are two adjacent columns, we know they can't both repeat,

Lex Fridman (2:02:37.520)

but just knowing whether that center column can ever repeat, we still don't even know that. Um,

Stephen Wolfram (2:02:42.800)

another problem that I sort of put in my collection of, you know, it's like $30,000 for

Stephen Wolfram (2:02:48.560)

three, you know, for these three prizes for about rule 30. Um, I would say that this is not one of

Stephen Wolfram (2:02:54.640)

those. There's one of those cases where the money is not the main point, but, um, it's just, uh,

Stephen Wolfram (2:03:00.720)

you know, helps, um, uh, motivate somehow the, the investigation. So there's three problems

Stephen Wolfram (2:03:06.560)

you propose to get $30,000 if you solve all three or maybe, you know, it's 10,000 for each for each.

Stephen Wolfram (2:03:12.400)

Right. My, uh, the, the problems, that's right. Money's not the thing. The problems

Lex Fridman (2:03:16.400)

themselves are just clean formulation. It's just, you know, will it ever become periodic?

Stephen Wolfram (2:03:22.720)

Second problem is, are there an equal number of black and white cells down the middle column,

Stephen Wolfram (2:03:27.040)

down the middle column. And the third problem is a little bit harder to state, which is essentially,

Stephen Wolfram (2:03:31.440)

is there a way of figuring out what the color of a cell at position T down the center column is

Stephen Wolfram (2:03:38.320)

in a, with a less computational effort than about T steps. So in other words, is there a way to jump

Stephen Wolfram (2:03:45.040)

ahead and say, I know what this is going to do, you know, it's just some mathematical function

Stephen Wolfram (2:03:51.680)

of T, um, or proving that there is no way or proving there is no way. Yes. But both, I mean,

Stephen Wolfram (2:03:57.680)

you know, for any one of these, one could prove that, you know, one could discover, you know,

Stephen Wolfram (2:04:01.840)

we know what rule 30 does for a billion steps, but, um, and maybe we'll know for a trillion steps

Stephen Wolfram (2:04:06.880)

before too very long. Um, but maybe at a quadrillion steps, it suddenly becomes repetitive.

Stephen Wolfram (2:04:12.160)

You might say, how could that possibly happen? But so when I was writing up these prizes,

Stephen Wolfram (2:04:17.120)

I thought, and this is typical of what happens in the computational universe. I thought,

Stephen Wolfram (2:04:21.040)

let me find an example where it looks like it's just going to be random forever,

Lex Fridman (2:04:25.360)

but actually it becomes repetitive. And I found one and it's just, you know, I did a search,

Stephen Wolfram (2:04:29.920)

I searched, I don't know, maybe a million different rules with some criterion. And this is

Stephen Wolfram (2:04:36.400)

what's sort of interesting about that is I kind of have this thing that I say in a kind of silly

Stephen Wolfram (2:04:41.760)

way about the computational universe, which is, you know, the animals are always smarter than you

Stephen Wolfram (2:04:46.000)

are. That is, there's always some way. One of these computational systems is going to figure

Stephen Wolfram (2:04:49.680)

out how to do something, even though I can't imagine how it's going to do it. And, you know,

Stephen Wolfram (2:04:53.760)

I didn't think I would find one that, you know, you would think after all these years that when

Stephen Wolfram (2:04:57.520)

I found sort of all possible things, uh, uh, uh, funky things that, um, uh, that I would have, uh,

Stephen Wolfram (2:05:05.120)

that I would have gotten my intuition wrapped around the idea that, um, you know, these creatures

Stephen Wolfram (2:05:10.960)

are always in the computational universe are always smarter than I'm going to be. But, uh,

Stephen Wolfram (2:05:15.200)

well, they're equivalently as smart, right? That's correct. And that makes it,

Stephen Wolfram (2:05:19.760)

that makes one feel very sort of, it's, it's, it's humbling every time because every time the thing

Stephen Wolfram (2:05:25.440)

is, is, uh, you know, you think it's going to do this or it's not going to be possible to do this

Lex Fridman (2:05:29.760)

and it turns out it finds a way. Of course, the promising thing is there's a lot of other rules

Stephen Wolfram (2:05:34.080)

like rule 30. It's just rule 30 is, oh, it's my favorite cause I found it first. And that's right.

Lex Fridman (2:05:40.480)

But the, the problems are focusing on rule 30. It's possible that rule 30

Stephen Wolfram (2:05:45.040)

is, is repetitive after trillion steps and that doesn't prove anything about the other rules.

Stephen Wolfram (2:05:50.480)

It does not. But this is a good sort of experiment of how you go about trying to prove something

Stephen Wolfram (2:05:56.080)

about a particular rule. Yes. And it also, all these things help build intuition. That is if

Stephen Wolfram (2:06:01.360)

it turned out that this was repetitive after a trillion steps, that's not what I would expect.

Lex Fridman (2:06:06.640)

And so we learned something from that. The method to do that though, would reveal something

Stephen Wolfram (2:06:11.600)

interesting about the, no doubt. No doubt. I mean, it's, although it's sometimes challenging,

Stephen Wolfram (2:06:17.440)

like the, you know, I put out a prize in 2007 for, for a particular Turing machine that I,

Stephen Wolfram (2:06:24.800)

there was the simplest candidate for being a universal Turing machine and the young chap in

Stephen Wolfram (2:06:29.680)

England named Alex Smith, um, after a smallish number of months said, I've got a proof and

Stephen Wolfram (2:06:35.840)

he did, you know, it took a little while to iterate, but he had a proof. Unfortunately,

Stephen Wolfram (2:06:40.320)

the proof is very, it's, it's a lot of micro details. It's, it's not, it's not like you look

Stephen Wolfram (2:06:47.280)

at it and you say, aha, there's a big new principle. The big new principle is the simplest

Stephen Wolfram (2:06:53.680)

Turing machine that might have been universal actually is universal. And it's incredibly much

Stephen Wolfram (2:06:58.240)

simpler than the Turing machines that people already knew were universal before that. And so

Stephen Wolfram (2:07:03.040)

that intuitionally is important because it says computation universality is closer at hand than

Stephen Wolfram (2:07:08.240)

you might've thought. Um, but the actual methods are not, uh, in that particular case,

Stephen Wolfram (2:07:13.440)

we're not terribly illuminating. It would be nice if the methods would also be elegant.

Stephen Wolfram (2:07:17.440)

That's true. Yeah. No, I mean, I think it's, it's one of these things where, I mean, it's,

Stephen Wolfram (2:07:21.840)

it's like a lot of, we've talked about earlier kind of, um, you know, opening up AI's and machine

Stephen Wolfram (2:07:27.120)

learning and things of what's going on inside and is it, is it just step by step or can you

Stephen Wolfram (2:07:32.240)

sort of see the bigger picture more abstractly? It's unfortunate. I mean, with Fermat's last

Stephen Wolfram (2:07:36.480)

theorem proof, it's unfortunate that the proof to such an elegant theorem is, um, is not, I mean,

Stephen Wolfram (2:07:44.240)

it's, it's, it's not, it doesn't fit into the margins of a page. That's true. But there's no,

Stephen Wolfram (2:07:49.600)

one of the things is that's another consequence of computational irreducibility. This, this fact

Stephen Wolfram (2:07:54.720)

that there are even quite short results in mathematics whose proofs are arbitrarily long.

Stephen Wolfram (2:08:00.800)

Yes. That's a, that's a consequence of all this stuff. And it's, it's a, it makes one wonder,

Stephen Wolfram (2:08:06.240)

uh, you know, how come mathematics is possible at all? Right. Why is, you know, why is it the

Stephen Wolfram (2:08:11.120)

case? How people managed to navigate doing mathematics through looking at things where

Stephen Wolfram (2:08:16.320)

they're not just thrown into, it's all undecidable. Um, that's, that's its own own separate, separate

Stephen Wolfram (2:08:22.640)

story. And that would be, that would, that would have a poetic beauty to it is if people were to

Stephen Wolfram (2:08:29.920)

find something interesting about rule 30, because I mean, there's an emphasis to this particular

Stephen Wolfram (2:08:36.160)

role. It wouldn't say anything about the broad irreducibility of all computations, but it would

Stephen Wolfram (2:08:41.280)

nevertheless put a few smiles on people's faces of, uh, well, yeah. But to me, it's like in a

Stephen Wolfram (2:08:49.440)

sense, establishing principle of computational equivalence, it's a little bit like doing

Stephen Wolfram (2:08:54.400)

inductive science anywhere. That is the more examples you find, the more convinced you are

Stephen Wolfram (2:08:59.680)

that it's generally true. I mean, we don't get to, you know, whenever we do natural science,

Stephen Wolfram (2:09:04.880)

we, we say, well, it's true here that this or that happens. Can we, can we prove that it's true

Stephen Wolfram (2:09:10.560)

everywhere in the universe? No, we can't. So, you know, it's the same thing here. We're exploring

Stephen Wolfram (2:09:16.240)

the computational universe. We're establishing facts in the computational universe. And that's,

Stephen Wolfram (2:09:20.720)

uh, that's sort of a way of, uh, of inductively concluding general things. Just to think through

Stephen Wolfram (2:09:30.720)

this a little bit, we've touched on it a little bit before, but what's the difference between the

Stephen Wolfram (2:09:35.040)

kind of computation, now that we're talking about cellular automata, what's the difference between

Stephen Wolfram (2:09:40.000)

the kind of computation, biological systems, our mind, our bodies, the things we see before us that

Stephen Wolfram (2:09:47.600)

emerged through the process of evolution and cellular automata? I mean, we've kind of implied

Stephen Wolfram (2:09:54.880)

to the discussion of physics underlying everything, but we, we talked about the potential equivalents

Stephen Wolfram (2:10:01.200)

of the fundamental laws of physics and the kind of computation going on in Turing machines.

Lex Fridman (2:10:06.080)

But can you now connect that? Do you think there's something special or interesting about the kind

Stephen Wolfram (2:10:12.240)

of computation that our bodies do? Right. Well, let's talk about brains primarily. I mean,

Stephen Wolfram (2:10:19.520)

I think the, um, the most important thing about the things that our brains do are that we care

Stephen Wolfram (2:10:24.480)

about them in the sense that there's a lot of computation going on out there in, you know,

Stephen Wolfram (2:10:29.760)

cellular automata and, and, you know, physical systems and so on. And it just, it does what it

Stephen Wolfram (2:10:35.280)

does. It follows those rules. It does what it does. The thing that's special about the computation in

Stephen Wolfram (2:10:40.080)

our brains is that it's connected to our goals and our kind of whole societal story. And, you know,

Stephen Wolfram (2:10:47.760)

I think that's the, that's, that's the special feature. And now the question then is when you

Stephen Wolfram (2:10:52.720)

see this whole sort of ocean of computation out there, how do you connect that to the things that

Stephen Wolfram (2:10:57.680)

we humans care about? And in a sense, a large part of my life has been involved in sort of the

Stephen Wolfram (2:11:02.400)

technology of how to do that. And, you know, what I've been interested in is kind of building

Stephen Wolfram (2:11:07.200)

computational language that allows that something that both we humans can understand and that can

Stephen Wolfram (2:11:13.760)

be used to determine computations that are actually computations we care about. See, I think

Stephen Wolfram (2:11:19.760)

when you look at something like one of these cellular automata and it does some complicated

Stephen Wolfram (2:11:23.920)

thing, you say, that's fun, but why do I care? Well, you could say the same thing actually in

Stephen Wolfram (2:11:30.080)

physics. You say, oh, I've got this material and it's a ferrite or something. Why do I care? You

Lex Fridman (2:11:36.000)

know, it's some, has some magnetic properties. Why do I care? It's amusing, but why do I care?

Stephen Wolfram (2:11:40.480)

Well, we end up caring because, you know, ferrite is what's used to make magnetic tape,

Stephen Wolfram (2:11:44.560)

magnetic discs, whatever. Or, you know, we could use liquid crystals as made, used to make,

Stephen Wolfram (2:11:50.160)

well, not actually increasingly not, but it has been used to make computer displays and so on.

Lex Fridman (2:11:55.520)

But those are, so in a sense, we're mining these things that happen to exist in the physical

Stephen Wolfram (2:12:00.320)

universe and making it be something that we care about because we sort of entrain it into

Stephen Wolfram (2:12:05.440)

technology. And it's the same thing in the computational universe that a lot of what's

Stephen Wolfram (2:12:10.640)

out there is stuff that's just happening, but sometimes we have some objective and we will

Stephen Wolfram (2:12:16.880)

go and sort of mine the computational universe for something that's useful for some particular

Stephen Wolfram (2:12:20.720)

objective. On a large scale, trying to do that, trying to sort of navigate the computational

Stephen Wolfram (2:12:26.640)

universe to do useful things, you know, that's where computational language comes in. And, you

Stephen Wolfram (2:12:32.240)

know, a lot of what I've spent time doing and building this thing we call Wolfram Language,

Stephen Wolfram (2:12:37.040)

which I've been building for the last one third of a century now. And kind of the goal there is

Stephen Wolfram (2:12:44.960)

to have a way to express kind of computational thinking, computational thoughts in a way that

Stephen Wolfram (2:12:52.000)

both humans and machines can understand. So it's kind of like in the tradition of computer languages,

Stephen Wolfram (2:12:58.160)

programming languages, that the tradition there has been more, let's take how computers are built

Lex Fridman (2:13:05.040)

and let's specify, let's have a human way to specify, do this, do this, do this,

Stephen Wolfram (2:13:10.480)

at the level of the way that computers are built. What I've been interested in is representing sort

Stephen Wolfram (2:13:15.600)

of the whole world computationally and being able to talk about whether it's about cities or

Stephen Wolfram (2:13:21.040)

chemicals or, you know, this kind of algorithm or that kind of algorithm, things that have come to

Stephen Wolfram (2:13:26.560)

exist in our civilization and the sort of knowledge base of our civilization, being able to talk

Stephen Wolfram (2:13:31.360)

directly about those in a computational language so that both we can understand it and computers

Stephen Wolfram (2:13:37.360)

can understand it. I mean, the thing that I've been sort of excited about recently, which I had

Stephen Wolfram (2:13:42.480)

only realized recently, which is kind of embarrassing, but it's kind of the arc of what

Stephen Wolfram (2:13:47.520)

we've tried to do in building this kind of computational language is it's a similar kind of

Stephen Wolfram (2:13:52.640)

arc of what happened when mathematical notation was invented. So go back 400 years, people were

Stephen Wolfram (2:14:00.320)

trying to do math, they were always explaining their math in words, and it was pretty clunky.

Lex Fridman (2:14:06.400)

And as soon as mathematical notation was invented, you could start defining things like algebra and

Stephen Wolfram (2:14:12.320)

later calculus and so on. It all became much more streamlined. When we deal with computational

Stephen Wolfram (2:14:17.120)

thinking about the world, there's a question of what is the notation? What is the kind of

Stephen Wolfram (2:14:22.160)

formalism that we can use to talk about the world computationally? In a sense, that's what I've

Stephen Wolfram (2:14:27.760)

spent the last third of a century trying to build. And we finally got to the point where

Stephen Wolfram (2:14:31.440)

we have a pretty full scale computational language that sort of talks about the world.

Lex Fridman (2:14:36.320)

And that's exciting because it means that just like having this mathematical notation, let us

Stephen Wolfram (2:14:43.280)

talk about the world mathematically, and let us build up these kind of mathematical sciences.

Stephen Wolfram (2:14:49.200)

Now we have a computational language which allows us to start talking about the world

Stephen Wolfram (2:14:53.920)

computationally, and lets us, my view of it is it's kind of computational X for all X. All these

Stephen Wolfram (2:15:01.040)

different fields of computational this, computational that. That's what we can now build.

Stephen Wolfram (2:15:06.240)

Let's step back. So first of all, the mundane. What is Wolfram language in terms of,

Stephen Wolfram (2:15:13.280)

I mean I can answer the question for you, but it's basically not the philosophical deep,

Stephen Wolfram (2:15:19.120)

the profound, the impact of it. I'm talking about in terms of tools, in terms of things you can

Lex Fridman (2:15:23.440)

download, in terms of stuff you can play with. What is it? What does it fit into the infrastructure?

Lex Fridman (2:15:28.320)

What are the different ways to interact with it?

Stephen Wolfram (2:15:30.080)

Right. So I mean the two big things that people have sort of perhaps heard of that come from

Stephen Wolfram (2:15:35.280)

Wolfram language, one is Mathematica, the other is Wolfram Alpha. So Mathematica first came out

Stephen Wolfram (2:15:40.400)

in 1988. It's this system that is basically an instance of Wolfram language, and it's used to do

Stephen Wolfram (2:15:49.200)

computations, particularly in sort of technical areas. And the typical thing you're doing is

Stephen Wolfram (2:15:56.400)

you're typing little pieces of computational language, and you're getting computations done.

Stephen Wolfram (2:16:01.440)

It's very kind of, there's like a symbolic.

Lex Fridman (2:16:05.200)

Yeah, it's a symbolic language.

Stephen Wolfram (2:16:10.000)

It's a symbolic language. I mean I don't know how to cleanly express that, but that makes it very

Stephen Wolfram (2:16:14.800)

distinct from how we think about sort of, I don't know, programming in a language like Python or

Stephen Wolfram (2:16:21.120)

something.

Stephen Wolfram (2:16:21.440)

Right. So the point is that in a traditional programming language, the raw material of the

Stephen Wolfram (2:16:26.480)

programming language is just stuff that computers intrinsically do. And the point of Wolfram

Stephen Wolfram (2:16:32.640)

language is that what the language is talking about is things that exist in the world or things

Stephen Wolfram (2:16:39.040)

that we can imagine and construct. It's aimed to be an abstract language from the beginning.

Lex Fridman (2:16:47.280)

And so for example, one feature it has is that it's a symbolic language, which means that the

Stephen Wolfram (2:16:52.320)

thing called, you have an X, just type in X, and Wolfram language will just say, oh, that's X.

Stephen Wolfram (2:16:58.720)

It won't say error, undefined thing. I don't know what it is, computation, in terms of computing.

Stephen Wolfram (2:17:05.520)

Now that X could perfectly well be the city of Boston. That's a thing. That's a symbolic thing.

Stephen Wolfram (2:17:12.880)

Or it could perfectly well be the trajectory of some spacecraft represented as a symbolic thing.

Lex Fridman (2:17:20.480)

And that idea that one can work with, sort of computationally work with these different,

Stephen Wolfram (2:17:26.720)

these kinds of things that exist in the world or describe the world, that's really powerful.

Lex Fridman (2:17:32.400)

And when I started designing, well, when I designed the predecessor of what's now Wolfram

Stephen Wolfram (2:17:40.240)

language, which is a thing called SMP, which was my first computer language, I kind of wanted to

Stephen Wolfram (2:17:46.960)

have this sort of infrastructure for computation, which was as fundamental as possible. I mean,

Stephen Wolfram (2:17:52.240)

this is what I got for having been a physicist and tried to find fundamental components of things

Lex Fridman (2:17:57.920)

and wound up with this kind of idea of transformation rules for symbolic expressions

Lex Fridman (2:18:03.920)

as being sort of the underlying stuff from which computation would be built.

Lex Fridman (2:18:09.680)

And that's what we've been building from in Wolfram language. And operationally, what happens,

Stephen Wolfram (2:18:16.640)

it's, I would say, by far the highest level computer language that exists. And it's really

Stephen Wolfram (2:18:23.920)

been built in a very different direction from other languages. So other languages have been

Stephen Wolfram (2:18:29.440)

about, there is a core language. It really is kind of wrapped around the operations that a

Stephen Wolfram (2:18:34.400)

computer intrinsically does. Maybe people add libraries for this or that, but the goal of

Stephen Wolfram (2:18:40.320)

Wolfram language is to have the language itself be able to cover this sort of very broad range

Stephen Wolfram (2:18:46.240)

of things that show up in the world. And that means that there are 6,000 primitive functions

Stephen Wolfram (2:18:51.600)

in the Wolfram language that cover things. I could probably pick a random here. I'm going to pick

Stephen Wolfram (2:18:57.680)

just for fun, I'll pick, let's take a random sample of all the things that we have here.

Lex Fridman (2:19:07.360)

So let's just say random sample of 10 of them and let's see what we get.

Stephen Wolfram (2:19:10.800)

Wow. Okay. So these are really different things from functions. These are all functions,

Stephen Wolfram (2:19:18.160)

Boolean convert. Okay. That's the thing for converting between different types of Boolean

Stephen Wolfram (2:19:23.920)

expressions. So for people are just listening, uh, Stephen typed in random sample of names,

Lex Fridman (2:19:29.120)

so this is sampling from all function. How many you said there might be 6,000 from 6,000 10 of

Stephen Wolfram (2:19:34.320)

them. And there's a hilarious variety of them. Yeah, right. Well, we've got things about, um,

Stephen Wolfram (2:19:40.240)

dollar requester address that has to do with interacting with, uh, uh, the, the world of the,

Stephen Wolfram (2:19:46.000)

of the cloud and so on. Discrete wavelet data, spheroidal, graphical sort of window. Yeah. Yeah.

Stephen Wolfram (2:19:52.880)

Window movable. That's the user interface kind of thing. I want to pick another 10 cause I think

Stephen Wolfram (2:19:56.880)

this is some, okay. So yeah, there's a lot of infrastructure stuff here that you see. If you,

Stephen Wolfram (2:20:01.840)

if you just start sampling at random, there's a lot of kind of infrastructural things. If you're

Stephen Wolfram (2:20:05.440)

more, you know, if you more look at the, um, some of the exciting machine learning stuff you showed

Stephen Wolfram (2:20:09.360)

off, is that also in this pool? Oh yeah. Yeah. I mean, you know, so one of those functions is

Stephen Wolfram (2:20:14.560)

like image identify as a, as a function here where you just say image identify. I don't know. It's

Stephen Wolfram (2:20:19.280)

always good to, let's do this. Let's say current image and let's pick up an image, hopefully.

Stephen Wolfram (2:20:26.880)

Current image accessing the webcam, took a picture yourself.

Stephen Wolfram (2:20:31.120)

Took a terrible picture. But anyway, we can say image identify, open square brackets, and then

Stephen Wolfram (2:20:37.360)

we just paste that picture in there. Image identify function running on the picture.

Stephen Wolfram (2:20:41.840)

Oh, and it says, Oh wow. It says I, it looked, I looked like a plunger because I got this great

Stephen Wolfram (2:20:46.240)

big thing behind my classifies. So this image identify classifies the most likely object in,

Stephen Wolfram (2:20:51.040)

in the image. So, so plunger. Okay. That's, that's a bit embarrassing. Let's see what it does.

Lex Fridman (2:20:56.800)

And let's pick the top 10. Um, okay. Well, it thinks there's a, Oh, it thinks it's pretty

Stephen Wolfram (2:21:02.160)

unlikely that it's a primate, a hominid, a person. 8% probability. 57 is a plunger.

Stephen Wolfram (2:21:08.960)

Yeah. Well, hopefully we'll not give you an existential crisis. And then, uh,

Stephen Wolfram (2:21:12.960)

8%, uh, I shouldn't say percent, but, uh, no, that's right. 8% that it's a hominid. Um, and,

Stephen Wolfram (2:21:20.320)

uh, yeah. Okay. It's really, I'm going to do another one of these just cause I'm embarrassed

Stephen Wolfram (2:21:24.560)

that it, um, I didn't see me at all. There we go. Let's try that. Let's see what that did.

Stephen Wolfram (2:21:30.560)

Um, we took a picture with a little bit more of me and not just my bald head, so to speak.

Stephen Wolfram (2:21:38.240)

Okay. 89% probability it's a person. So that, so then I would, um, but, uh, you know, so this is

Stephen Wolfram (2:21:44.160)

image identify as an example of one of just one of them, just one function out of that part of the

Stephen Wolfram (2:21:50.240)

that's like part of the language. Yes. And I mean, you know, something like, um, I could say,

Stephen Wolfram (2:21:55.920)

I don't know, let's find the geo nearest, uh, what could we find? Um, let's find the nearest volcano.

Stephen Wolfram (2:22:03.040)

Um, let's find the 10. I wonder where it thinks here is. Let's try finding the 10 volcanoes

Stephen Wolfram (2:22:11.920)

nearest here. Okay. So geo nearest volcano here, 10 nearest volcanoes. Right. Let's find out where

Stephen Wolfram (2:22:19.280)

those are. We can now, we've got a list of volcanoes out and I can say geo list plot that

Lex Fridman (2:22:24.320)

and hopefully, okay, so there we go. So there's a map that shows the positions of those 10 volcanoes

Stephen Wolfram (2:22:30.080)

of the East coast and the Midwest and well, no, we're okay. We're okay. There's not, it's not too

Stephen Wolfram (2:22:35.040)

bad. Yeah. They're not very close to us. We could, we could measure how far away they are, but, um,

Stephen Wolfram (2:22:39.280)

you know, the fact that right in the language, it knows about all the volcanoes in the world. It

Stephen Wolfram (2:22:44.560)

knows, you know, computing what the nearest ones are. It knows all the maps of the world and so on.

Stephen Wolfram (2:22:49.200)

It's a fundamentally different idea of what a language is. Yeah, right. That's why I like to

Stephen Wolfram (2:22:54.320)

talk about is that, you know, a full scale computational language. That's, that's what

Lex Fridman (2:22:57.520)

we've tried to do. And just if you can comment briefly, I mean, this kind of,

Stephen Wolfram (2:23:02.480)

the Wolfram language along with Wolfram Alpha represents kind of what the dream of what AI is

Stephen Wolfram (2:23:07.360)

supposed to be. There's now a sort of a craze of learning kind of idea that we can take raw data

Lex Fridman (2:23:14.320)

and from that extract the, uh, the different hierarchies of abstractions in order to be able

Stephen Wolfram (2:23:20.320)

to under, like in order to form the kind of things that Wolfram language operates with,

Lex Fridman (2:23:27.360)

but we're very far from learning systems being able to form that.

Stephen Wolfram (2:23:32.400)

Like the context of history of AI, if you could just comment on, there is a, you said computation

Stephen Wolfram (2:23:39.280)

X and there's just some sense where in the eighties and nineties sort of expert systems

Stephen Wolfram (2:23:44.560)

represented a very particular computation X. Yes. Right. And there's a kind of notion that

Stephen Wolfram (2:23:50.320)

those efforts didn't pan out. Right. But then out of that emerges kind of Wolfram language,

Stephen Wolfram (2:23:57.520)

Wolfram Alpha, which is the success. I mean, yeah, right. I think those are in some sense,

Stephen Wolfram (2:24:02.240)

those efforts were too modest. That is they were, they were looking at particular areas

Lex Fridman (2:24:06.800)

and you actually can't do it with a particular area. I mean, like, like even a problem like

Stephen Wolfram (2:24:10.560)

natural language understanding, it's critical to have broad knowledge of the world. If you want to

Stephen Wolfram (2:24:15.040)

do good natural language understanding and you kind of have to bite off the whole problem. If you,

Stephen Wolfram (2:24:20.000)

if you say, we're just going to do the blocks world over here, so to speak, you don't really,

Stephen Wolfram (2:24:24.720)

it's, it's, it's actually, it's one of these cases where it's easier to do the whole thing than it

Stephen Wolfram (2:24:28.960)

is to do some piece of it. You know, what, one comment to make about sort of the relationship

Stephen Wolfram (2:24:32.640)

between what we've tried to do and sort of the learning side of, of AI. You know, in a sense,

Stephen Wolfram (2:24:39.120)

if you look at the development of knowledge in our civilization as a whole, there was kind of this

Stephen Wolfram (2:24:43.520)

notion pre 300 years ago or so. Now you want to figure something out about the world. You can

Stephen Wolfram (2:24:48.320)

reason it out. You can do things which are just use raw human thought. And then along came sort

Stephen Wolfram (2:24:54.480)

of modern mathematical science. And we found ways to just sort of blast through that by in that case,

Stephen Wolfram (2:25:01.360)

in that case, writing down equations. Now we also know we can do that with computation and so on.

Lex Fridman (2:25:06.880)

And so that was kind of a different thing. So, so when we look at how do we sort of encode

Stephen Wolfram (2:25:12.480)

knowledge and figure things out, one way we could do it is start from scratch, learn everything.

Stephen Wolfram (2:25:17.760)

It's just a neural net figuring everything out. But in a sense that denies the sort of knowledge

Stephen Wolfram (2:25:24.000)

based achievements of our civilization, because in our civilization, we have learned lots of stuff.

Stephen Wolfram (2:25:29.360)

We've surveyed all the volcanoes in the world. We've done, you know, we figured out lots of

Stephen Wolfram (2:25:33.440)

algorithms for this or that. Those are things that we can encode computationally. And that's what

Stephen Wolfram (2:25:39.120)

we've tried to do. And we're not saying just, you don't have to start everything from scratch.

Lex Fridman (2:25:44.320)

So in a sense, a big part of what we've done is to try and sort of capture the knowledge of the

Stephen Wolfram (2:25:50.080)

world in computational form and computable form. Now there's also some pieces which, which were

Stephen Wolfram (2:25:57.040)

for a long time, undoable by computers like image identification, where there's a really,

Stephen Wolfram (2:26:02.240)

really useful module that we can add that is those things which actually were pretty easy

Stephen Wolfram (2:26:07.600)

for humans to do that had been hard for computers to do. I think the thing that's interesting,

Stephen Wolfram (2:26:12.080)

that's emerging now is the interplay between these things, between this kind of knowledge of the

Stephen Wolfram (2:26:16.240)

world that is in a sense, very symbolic and this kind of sort of much more statistical kind of

Stephen Wolfram (2:26:23.200)

things like image identification and so on. And putting those together by having this sort of

Stephen Wolfram (2:26:28.880)

symbolic representation of image identification, that that's where things get really interesting

Lex Fridman (2:26:34.560)

and where you can kind of symbolically represent patterns of things and images and so on. I think

Stephen Wolfram (2:26:40.000)

that's, you know, that's kind of a part of the path forward, so to speak.

Stephen Wolfram (2:26:43.920)

Yeah. So the dream of, so the machine learning is not in my view, I think the view of many people

Stephen Wolfram (2:26:50.240)

is not anywhere close to building the kind of wide world of computable knowledge that will from

Stephen Wolfram (2:26:58.000)

language of build. But because you have a kind of, you've done the incredibly hard work of building

Stephen Wolfram (2:27:04.640)

this world, now machine learning can be, can serve as tools to help you explore that world.

Lex Fridman (2:27:11.360)

Yeah, yeah.

Lex Fridman (2:27:11.680)

And that's what you've added. I mean, with the version 12, right? You added a few,

Lex Fridman (2:27:16.240)

I was seeing some demos, it looks amazing.

Stephen Wolfram (2:27:20.160)

Right. I mean, I think, you know, this, it's sort of interesting to see the,

Stephen Wolfram (2:27:25.840)

the sort of the, once it's computable, once it's in there, it's running in sort of a very efficient

Stephen Wolfram (2:27:30.560)

computational way. But then there's sort of things like the interface of how do you get there? You

Stephen Wolfram (2:27:34.800)

know, how do you do natural language understanding to get there? How do you, how do you pick out

Stephen Wolfram (2:27:38.560)

entities in a big piece of text or something? That's I mean, actually a good example right now

Stephen Wolfram (2:27:44.400)

is our NLP NLU loop, which is we've done a lot of stuff, natural language understanding using

Stephen Wolfram (2:27:51.040)

essentially not learning based methods, using a lot of, you know, little algorithmic methods,

Lex Fridman (2:27:56.800)

human curation methods and so on.

Stephen Wolfram (2:27:58.320)

In terms of when people try to enter a query and then converting. So the process of converting

Stephen Wolfram (2:28:04.000)

NLU defined beautifully as converting their query into a computational language,

Stephen Wolfram (2:28:11.840)

which is a very well, first of all, super practical definition, very useful definition,

Lex Fridman (2:28:17.360)

and then also a very clear definition of natural language understanding.

Stephen Wolfram (2:28:21.840)

Right. I mean, a different thing is natural language processing, where it's like,

Stephen Wolfram (2:28:25.520)

here's a big lump of text, go pick out all the cities in that text, for example.

Lex Fridman (2:28:30.320)

And so a good example of, you know, so we do that, we're using, using modern machine learning

Stephen Wolfram (2:28:35.280)

techniques. And it's actually kind of, kind of an interesting process that's going on right now.

Stephen Wolfram (2:28:40.480)

It's this loop between what do we pick up with NLP using machine learning versus what do we pick up

Stephen Wolfram (2:28:46.800)

with our more kind of precise computational methods in natural language understanding.

Lex Fridman (2:28:51.840)

And so we've got this kind of loop going between those, which is improving both of them.

Lex Fridman (2:28:55.440)

Yeah. And I think you have some of the state of the art transformers,

Stephen Wolfram (2:28:57.600)

like you have BERT in there, I think.

Lex Fridman (2:28:58.960)

Oh yeah.

Lex Fridman (2:28:59.600)

So it's closely, you have, you have integrating all the models. I mean,

Stephen Wolfram (2:29:02.800)

this is the hybrid thing that people have always dreamed about or talking about.

Stephen Wolfram (2:29:07.440)

I'm actually just surprised, frankly, that Wolfram language is not more popular than it already is.

Stephen Wolfram (2:29:15.280)

You know, that's a, it's a, it's a complicated issue because it's like, it involves, you know,

Stephen Wolfram (2:29:24.640)

it involves ideas and ideas are absorbed slowly in the world. I mean, I think that's

Lex Fridman (2:29:30.000)

And then there's sort of like what we're talking about, there's egos and personalities and some of

Stephen Wolfram (2:29:34.560)

the, the absorption, absorption mechanisms of ideas have to do with personalities and the students of

Stephen Wolfram (2:29:42.320)

personalities and the, and then a little social network. So it's, it's interesting how the spread

Stephen Wolfram (2:29:47.360)

of ideas works.

Stephen Wolfram (2:29:48.320)

You know, what's funny with Wolfram language is that we are, if you say, you know, what market

Stephen Wolfram (2:29:54.400)

sort of market penetration, if you look at the, I would say very high end of R&D and sort of the,

Stephen Wolfram (2:30:00.880)

the people where you say, wow, that's a really impressive, smart person. They're very often

Stephen Wolfram (2:30:06.640)

users of Wolfram language, very, very often. If you look at the more sort of, it's a funny thing.

Stephen Wolfram (2:30:12.240)

If you look at the more kind of, I would say people who are like, oh, we're just plodding

Stephen Wolfram (2:30:16.800)

away doing what we do. They're often not yet Wolfram language users. And that dynamic,

Stephen Wolfram (2:30:22.960)

it's kind of odd that there hasn't been more rapid trickle down because we really, you know,

Stephen Wolfram (2:30:27.360)

the high end we've really been very successful in for a long time. And it's, it's, but with,

Stephen Wolfram (2:30:33.600)

you know, that's partly, I think, a consequence of my fault in a sense, because it's kind of,

Stephen Wolfram (2:30:40.880)

you know, I have a company which is really emphasizes sort of creating products and

Stephen Wolfram (2:30:48.480)

building a sort of the best possible technical tower we can rather than sort of doing the

Stephen Wolfram (2:30:55.920)

commercial side of things and pumping it out in sort of the most effective way.

Lex Fridman (2:30:59.840)

And there's an interesting idea that, you know, perhaps you can make it more popular

Stephen Wolfram (2:31:03.360)

by opening everything up, sort of the GitHub model. But there's an interesting,

Stephen Wolfram (2:31:09.200)

I think I've heard you discuss this, that that turns out not to work in a lot of cases,

Stephen Wolfram (2:31:14.080)

like in this particular case, that you want it, that when you deeply care about the integrity,

Stephen Wolfram (2:31:20.880)

the quality of the knowledge that you're building, that, unfortunately, you can't,

Stephen Wolfram (2:31:27.840)

you can't distribute that effort.

Stephen Wolfram (2:31:29.520)

Yeah, it's not the nature of how things work. I mean, you know, what we're trying to do

Stephen Wolfram (2:31:35.760)

is a thing that for better or worse, requires leadership. And it requires kind of maintaining

Stephen Wolfram (2:31:41.440)

a coherent vision over a long period of time, and doing not only the cool vision related work,

Lex Fridman (2:31:48.640)

but also the kind of mundane in the trenches make the thing actually work well, work.

Lex Fridman (2:31:53.840)

So how do you build the knowledge? Because that's the fascinating thing. That's the mundane,

Stephen Wolfram (2:31:59.120)

the fascinating and the mundane is building the knowledge, the adding, integrating more data.

Stephen Wolfram (2:32:04.080)

Yeah, I mean, that's probably not the most, I mean, the things like get it to work in all

Stephen Wolfram (2:32:08.560)

these different cloud environments and so on. That's pretty, you know, it's very practical

Stephen Wolfram (2:32:13.200)

stuff, you know, have the user interface be smooth and, you know, have there be take only

Stephen Wolfram (2:32:17.680)

a fraction of a millisecond to do this or that. That's a lot of work. And it's, it's, but, you

Stephen Wolfram (2:32:24.880)

know, I think my, it's an interesting thing over the period of time, you know, often language has

Stephen Wolfram (2:32:30.400)

existed, basically, for more than half of the total amount of time that any language, any computer

Stephen Wolfram (2:32:35.840)

language has existed. That is, computer language is maybe 60 years old, you know, give or take,

Lex Fridman (2:32:41.760)

and often language is 33 years old. So it's, it's kind of a, and I think I was realizing recently,

Stephen Wolfram (2:32:48.880)

there's been more innovation in the distribution of software than probably than in the structure

Stephen Wolfram (2:32:54.400)

of programming languages over that period of time. And we, you know, we've been sort of trying to do

Stephen Wolfram (2:33:00.800)

our best to adapt to it. And the good news is that we have, you know, because I have a simple

Stephen Wolfram (2:33:05.520)

private company and so on that doesn't have, you know, a bunch of investors, you know,

Stephen Wolfram (2:33:09.840)

telling us we've got to do this so that they have lots of freedom in what we can do. And so,

Stephen Wolfram (2:33:14.160)

for example, we're able to, oh, I don't know, we have this free Wolfram engine for developers,

Stephen Wolfram (2:33:18.880)

which is a free version for developers. And we've been, you know, we've, there are site licenses for,

Stephen Wolfram (2:33:24.160)

for Mathematica and Wolfram language at basically all major universities, certainly in the US by now.

Lex Fridman (2:33:30.080)

So it's effectively free to people and all universities in effect. And, you know, we've been

Stephen Wolfram (2:33:35.920)

doing a progression of things. I mean, different things like Wolfram Alpha, for example,

Stephen Wolfram (2:33:41.600)

the main website is just a free website. What is Wolfram Alpha? Okay, Wolfram Alpha is a system for

Stephen Wolfram (2:33:48.640)

answering questions where you ask a question with natural language, and it'll try and generate a

Stephen Wolfram (2:33:54.720)

report telling you the answer to that question. So the question could be something like, you know,

Stephen Wolfram (2:33:59.680)

what's the population of Boston divided by New York compared to New York? And it'll take those

Stephen Wolfram (2:34:06.800)

words and give you an answer. And that converts the words into computable, into Wolfram language,

Stephen Wolfram (2:34:14.320)

into Wolfram language and computational language. And then do you think the underlying knowledge

Lex Fridman (2:34:19.440)

belongs to Wolfram Alpha or to the Wolfram language? What's the Wolfram knowledge base?

Stephen Wolfram (2:34:24.880)

Knowledge base. I mean, it's been a, that's been a big effort over the decades to collect all that

Stephen Wolfram (2:34:30.080)

stuff. And, you know, more of it flows in every second. So can you, can you just pause on that

Stephen Wolfram (2:34:34.960)

for a second? Like, that's one of the most incredible things, of course, in the long term,

Stephen Wolfram (2:34:40.560)

Wolfram language itself is the fundamental thing. But in the amazing sort of short term,

Stephen Wolfram (2:34:46.880)

the knowledge base is kind of incredible. So what's the process of building that knowledge base? The

Stephen Wolfram (2:34:53.760)

fact that you, first of all, from the very beginning, that you're brave enough to start to

Stephen Wolfram (2:34:57.520)

take on the general knowledge base. And how do you go from zero to the incredible knowledge base that

Stephen Wolfram (2:35:06.400)

you have now? Well, yeah, it was kind of scary at some level. I mean, I had, I had wondered about

Stephen Wolfram (2:35:10.880)

doing something like this since I was a kid. I mean, I had, I had wondered about doing something

Stephen Wolfram (2:35:14.960)

like this since I was a kid. So it wasn't like I hadn't thought about it for a while.

Stephen Wolfram (2:35:20.800)

Most of the brilliant dreamers give up such a difficult engineering notion at some point.

Stephen Wolfram (2:35:26.960)

Right. Well, the thing that happened with me, which was kind of, it's a, it's a live your own

Stephen Wolfram (2:35:32.880)

paradigm kind of theory. So basically what happened is I had assumed that to build something like

Stephen Wolfram (2:35:38.720)

Wolfram Alpha would require sort of solving the general AI problem. That's what I had assumed.

Lex Fridman (2:35:44.400)

And so I kept on thinking about that and I thought, I don't really know how to do that.

Lex Fridman (2:35:47.840)

So I don't do anything. Then I worked on my new kind of science project and sort of exploring

Stephen Wolfram (2:35:53.040)

the computational universe and came up with things like this principle of computational equivalence,

Stephen Wolfram (2:35:57.680)

which say there is no bright line between the intelligent and the merely computational.

Lex Fridman (2:36:02.800)

So I thought, look, that's this paradigm I've built. You know, now it's, you know,

Stephen Wolfram (2:36:07.520)

now I have to eat that dog food myself, so to speak. You know, I've been thinking about doing

Stephen Wolfram (2:36:11.680)

this thing with computable knowledge forever and, you know, let me actually try and do it.

Lex Fridman (2:36:16.880)

And so it was, you know, if my paradigm is right, then this should be possible.

Lex Fridman (2:36:21.920)

But the beginning was certainly, you know, it was a bit daunting. I remember I took the

Stephen Wolfram (2:36:26.960)

early team to a big reference library and we're like looking at this reference library and it's

Stephen Wolfram (2:36:31.120)

like, you know, my basic statement is our goal over the next year or two is to ingest everything

Stephen Wolfram (2:36:36.640)

that's in here. And that's, you know, it seemed very daunting, but in a sense, I was well aware

Stephen Wolfram (2:36:43.360)

of the fact that it's finite. You know, the fact that you can walk into the reference library,

Stephen Wolfram (2:36:46.720)

it's a big, big thing with lots of reference books all over the place, but it is finite.

Stephen Wolfram (2:36:51.440)

You know, this is not an infinite, you know, it's not the infinite corridor of, so to speak,

Stephen Wolfram (2:36:56.640)

of reference library. It's not truly infinite, so to speak. But no, I mean, and then what happened

Stephen Wolfram (2:37:02.480)

was sort of interesting there was from a methodology point of view was I didn't start off

Stephen Wolfram (2:37:08.800)

saying let me have a grand theory for how all this knowledge works. It was like, let's, you know,

Stephen Wolfram (2:37:14.560)

implement this area, this area, this area, a few hundred areas and so on. That's a lot of work.

Stephen Wolfram (2:37:20.320)

I also found that, you know, I've been fortunate in that our products get used by sort of the

Stephen Wolfram (2:37:30.080)

world's experts in lots of areas. And so that really helped because we were able to ask people,

Stephen Wolfram (2:37:34.800)

you know, the world expert in this or that, and we're able to ask them for input and so on. And

Stephen Wolfram (2:37:40.240)

I found that my general principle was that any area where there wasn't some expert who helped

Stephen Wolfram (2:37:46.640)

us figure out what to do wouldn't be right. You know, because our goal was to kind of get to the

Stephen Wolfram (2:37:51.760)

point where we had sort of true expert level knowledge about everything. And so that, you know,

Stephen Wolfram (2:37:57.360)

the ultimate goal is if there's a question that can be answered on the basis of general knowledge

Stephen Wolfram (2:38:02.320)

in our civilization, make it be automatic to be able to answer that question. And, you know, and

Stephen Wolfram (2:38:07.360)

now, well, Wolfman got used in Siri from the very beginning, and it's now also used in Alexa.

Lex Fridman (2:38:13.520)

And so it's people are kind of getting more of the, you know, they get more of the sense of

Stephen Wolfram (2:38:19.120)

this is what should be possible to do. I mean, in a sense, the question answering problem

Stephen Wolfram (2:38:24.240)

was viewed as one of the sort of core AI problems for a long time. And I had kind of an interesting

Stephen Wolfram (2:38:29.680)

experience. I had a friend, Marvin Minsky, who was a well known AI person from right around here.

Lex Fridman (2:38:37.440)

And I remember when Wolfman Alpha was coming out, it was a few weeks before it came out, I think,

Stephen Wolfram (2:38:43.280)

I happened to see Marvin. And I said, I should show you this thing we have, you know, it's a

Stephen Wolfram (2:38:47.840)

you know, it's a question answering system. And he was like, okay, type something. And it's like, okay,

Stephen Wolfram (2:38:54.320)

fine. And then he's talking about something different. I said, no, Marvin, you know,

Stephen Wolfram (2:38:58.400)

this time, it actually works. You know, look at this, it actually works. He's typed in a few more

Stephen Wolfram (2:39:03.520)

things. There's maybe 10 more things. Of course, we have a record of what he typed in, which is

Stephen Wolfram (2:39:07.840)

kind of interesting. But

Lex Fridman (2:39:11.440)

and then you can you share where his mind was in the testing space? Like what,

Stephen Wolfram (2:39:16.640)

all kinds of random things? He was trying random stuff, you know, medical stuff, and,

Stephen Wolfram (2:39:20.960)

you know, chemistry stuff, and, you know, astronomy and so on. And it was like, like, you know,

Stephen Wolfram (2:39:26.080)

after a few minutes, he was like, Oh, my God, it actually works. And the but that was kind of told

Stephen Wolfram (2:39:33.440)

you something about the state, you know, what, what happened in AI, because people had, you know,

Stephen Wolfram (2:39:38.560)

in a sense, by trying to solve the bigger problem, we were able to actually make something that would

Stephen Wolfram (2:39:43.040)

work. Now, to be fair, you know, we had a bunch of completely unfair advantages. For example,

Stephen Wolfram (2:39:48.240)

we already built a bunch of awesome language, which was, you know, very high level symbolic

Stephen Wolfram (2:39:53.120)

language. We had, you know, I had the practical experience of building big systems. I have the

Stephen Wolfram (2:40:01.120)

sort of intellectual confidence to not just sort of give up and doing something like this. I think

Stephen Wolfram (2:40:07.120)

that the, you know, it is a, it's always a funny thing, you know, I've worked on a bunch of big

Stephen Wolfram (2:40:13.360)

projects in my life. And I would say that the, you know, you mentioned ego, I would also mention

Stephen Wolfram (2:40:19.920)

optimism, so to speak. I mean, in, you know, if somebody said, this project is going to take 30

Stephen Wolfram (2:40:25.920)

years, it's, you know, it would be hard to sell me on that. You know, I'm always in the in the

Stephen Wolfram (2:40:34.720)

well, I can kind of see a few years, you know, something's going to happen in a few years. And

Stephen Wolfram (2:40:39.680)

usually it does, something happens in a few years, but the whole, the tail can be decades long. And

Stephen Wolfram (2:40:45.040)

that's, you know, and from a personal point of view, always the challenge is you end up with

Stephen Wolfram (2:40:50.000)

these projects that have infinite tails. And the question is, do the tails kind of, do you just

Stephen Wolfram (2:40:56.000)

drown in kind of dealing with all of the tails of these projects? And that's an interesting sort of

Stephen Wolfram (2:41:03.360)

personal challenge. And like my efforts now to work on fundamental theory of physics, which I've

Stephen Wolfram (2:41:08.240)

just started doing, and I'm having a lot of fun with it. But it's kind of, you know, it's, it's

Stephen Wolfram (2:41:14.560)

kind of making a bet that I can, I can kind of, you know, I can do that as well as doing the

Stephen Wolfram (2:41:21.120)

incredibly energetic things that I'm trying to do with Orphan Language and so on. I mean, the

Stephen Wolfram (2:41:26.080)

vision. Yeah. And underlying that, I mean, I've just talked for the second time with Elon Musk,

Lex Fridman (2:41:31.520)

and that you, you two share that quality a little bit of that optimism of taking on basically the

Stephen Wolfram (2:41:38.480)

daunting, what most people call impossible. And he, and you take it on out of, you can call it ego,

Stephen Wolfram (2:41:47.120)

you can call it naivety, you can call it optimism, whatever the heck it is, but that's how you solve

Stephen Wolfram (2:41:51.760)

the impossible things. Yeah. I mean, look at what happens. And I don't know, you know, in my own

Stephen Wolfram (2:41:56.880)

case, I, you know, it's been, I progressively got a bit more confident and progressively able to,

Stephen Wolfram (2:42:03.600)

you know, decide that these projects aren't crazy. But then the other thing is the other,

Stephen Wolfram (2:42:08.000)

the other trap that one can end up with is, Oh, I've done these projects and they're big.

Stephen Wolfram (2:42:13.680)

Let me never do a project that's any smaller than any project I've done so far. And that's,

Stephen Wolfram (2:42:18.880)

you know, and that can be a trap. And often these projects are of completely unknown, you know,

Stephen Wolfram (2:42:25.440)

that their depth and significance is actually very hard to know.

Stephen Wolfram (2:42:31.120)

On the sort of building this giant knowledge base that's behind Wolfram language, Wolfram Alpha,

Lex Fridman (2:42:40.000)

what do you think about the internet? What do you think about, for example, Wikipedia,

Lex Fridman (2:42:48.000)

these large aggregations of texts that's not converted into computable knowledge?

Lex Fridman (2:42:53.360)

Do you think if you look at Wolfram language, Wolfram Alpha, 20, 30, maybe 50 years down the

Stephen Wolfram (2:42:59.920)

line, do you hope to store all of the sort of Google's dream is to make all information searchable,

Stephen Wolfram (2:43:09.440)

accessible, but that's really as defined, it's, it's a, it doesn't include the understanding

Stephen Wolfram (2:43:16.160)

of information. Right. Do you hope to make all of knowledge represented within? I hope so.

Lex Fridman (2:43:25.440)

That's what we're trying to do. How hard is that problem? Like closing that gap?

Stephen Wolfram (2:43:30.320)

It depends on the use cases. I mean, so if it's a question of answering general knowledge questions

Stephen Wolfram (2:43:34.880)

about the world, we're in pretty good shape on that right now. If it's a question of representing,

Stephen Wolfram (2:43:40.480)

uh, like an area that we're going into right now is computational contracts, being able to

Stephen Wolfram (2:43:47.280)

take something which would be written in legalese, it might even be the specifications for, you know,

Lex Fridman (2:43:52.080)

what should the self driving car do when it encounters this or that or the other? What should

Stephen Wolfram (2:43:56.000)

the, you know, whatever the, you know, write that in a computational language and be able to express

Stephen Wolfram (2:44:02.880)

things about the world. You know, if the creature that you see running across the road is a, you

Stephen Wolfram (2:44:08.960)

know, thing at this point in the evil tree of life, then swerve this way, otherwise don't those

Stephen Wolfram (2:44:15.120)

kinds of things. Are there ethical components? When you start to get to some of the messy human

Stephen Wolfram (2:44:20.000)

things, are those encodable into computable knowledge? Well, I think that it is a necessary

Stephen Wolfram (2:44:26.160)

feature of attempting to automate more in the world that we encode more and more of ethics

Stephen Wolfram (2:44:32.720)

in a way that, uh, gets sort of quickly, you know, is, is able to be dealt with by, by computer. I

Stephen Wolfram (2:44:38.240)

mean, I've been involved recently. I sort of got backed into being involved in the question of,

Stephen Wolfram (2:44:43.280)

uh, automated content selection on the internet. So, you know, the Facebooks, Googles,

Stephen Wolfram (2:44:49.120)

Twitters, you know, what, how do they rank the stuff they feed to us humans, so to speak? Um,

Lex Fridman (2:44:54.640)

and the question of what are, you know, what should never be fed to us? What should be blocked

Stephen Wolfram (2:44:59.120)

forever? What should be upranked, you know, and what is the, what are the kind of principles behind

Stephen Wolfram (2:45:04.080)

that? And what I kind of, well, a bunch of different things I realized about that. But

Stephen Wolfram (2:45:09.040)

one thing that's interesting is being able, you know, in effect, you're building sort of an AI

Stephen Wolfram (2:45:15.120)

ethics. You have to build an AI ethics module in effect to decide, is this thing so shocking? I'm

Stephen Wolfram (2:45:21.120)

never going to show it to people. Is this thing so whatever? And I did realize in thinking about

Stephen Wolfram (2:45:26.960)

that, that, you know, there's not going to be one of these things. It's not possible to decide, or

Stephen Wolfram (2:45:32.160)

it might be possible, but it would be really bad for the future of our species if we just decided

Stephen Wolfram (2:45:36.800)

there's this one AI ethics module and it's going to determine the practices of everything in the

Stephen Wolfram (2:45:43.600)

world, so to speak. And I kind of realized one has to sort of break it up. And that's an interesting

Stephen Wolfram (2:45:48.400)

societal problem of how one does that and how one sort of has people sort of self identify for,

Stephen Wolfram (2:45:54.800)

you know, I'm buying in, in the case of just content selection, it's sort of easier because

Stephen Wolfram (2:45:58.880)

it's like an individual, it's for an individual. It's not something that kind of cuts across sort

Stephen Wolfram (2:46:04.320)

of societal boundaries. But it's a really interesting notion of, I heard you describe,

Stephen Wolfram (2:46:12.400)

I really like it sort of maybe in sort of have different AI systems that have a certain kind

Stephen Wolfram (2:46:19.280)

of brand that they represent essentially. You could have like, I don't know, whether it's

Stephen Wolfram (2:46:24.960)

conservative or liberal and then libertarian. And there's an Randian, objectivist AI system and

Stephen Wolfram (2:46:33.280)

different ethical and, I mean, it's almost encoding some of the ideologies which we've

Stephen Wolfram (2:46:38.400)

been struggling. I come from the Soviet Union. That didn't work out so well with the ideologies

Stephen Wolfram (2:46:43.520)

that worked out there. And so you have, but they all, everybody purchased that particular ethics

Stephen Wolfram (2:46:49.920)

system and the, and in the same, I suppose could be done encoded that that system could be encoded

Stephen Wolfram (2:46:57.200)

into computational knowledge and allow us to explore in the realm of, in the digital space.

Lex Fridman (2:47:04.080)

That's a really exciting possibility. Are you playing with those ideas in Wolfram Language?

Stephen Wolfram (2:47:10.080)

Yeah. Yeah. I mean, the, you know, that's, Wolfram Language has sort of the best opportunity to kind

Stephen Wolfram (2:47:15.920)

of express those essentially computational contracts about what to do. Now there's a bunch

Lex Fridman (2:47:20.000)

more work to be done to do it in practice for, you know, deciding the, is this a credible news story?

Lex Fridman (2:47:26.400)

What does that mean or whatever else you're going to pick? I think that that's, you know, that's

Stephen Wolfram (2:47:33.680)

the question of exactly what we get to do with that is, you know, for me, it's kind of a complicated

Stephen Wolfram (2:47:40.800)

thing because there are these big projects that I think about, like, you know, find the fundamental

Stephen Wolfram (2:47:45.440)

theory of physics. Okay. That's box number one, right? Box number two, you know, solve the AI

Stephen Wolfram (2:47:50.720)

ethics problem in the case of, you know, figure out how you rank all content, so to speak, and

Stephen Wolfram (2:47:55.760)

decide what people see. That's, that's kind of a box number two, so to speak. These are big

Stephen Wolfram (2:47:59.920)

projects. And, and I think what do you think is more important, the fundamental nature of reality

Stephen Wolfram (2:48:05.040)

or, depends who you ask. It's one of these things that's exactly like, you know, what's the ranking,

Lex Fridman (2:48:10.480)

right? It's the, it's the ranking system. It's like, who's, whose module do you use to rank that?

Stephen Wolfram (2:48:15.520)

If you, and I think, but having multiple modules is a really compelling notion to us humans

Stephen Wolfram (2:48:21.840)

that in a world where there's not clear that there's a right answer, perhaps you have systems

Stephen Wolfram (2:48:28.560)

that operate under different, how would you say it? I mean, it's different value systems,

Stephen Wolfram (2:48:37.040)

different value systems. I mean, I think, you know, in a sense, the, I mean, I'm not really a

Stephen Wolfram (2:48:43.040)

politics oriented person, but, but, you know, in the kind of totalitarianism, it's kind of like,

Stephen Wolfram (2:48:47.840)

you're going to have this, this system and that's the way it is. I mean, kind of the, you know,

Stephen Wolfram (2:48:53.600)

the concept of sort of a market based system where you have, okay, I, as a human, I'm going to pick

Stephen Wolfram (2:48:59.360)

this system. I, as another human, I'm going to pick this system. I mean, that's in a sense,

Stephen Wolfram (2:49:04.640)

this case of automated content selection is a non trivial, but it is probably the easiest

Stephen Wolfram (2:49:11.520)

of the AI ethics situations because it is each person gets to pick for themselves and there's

Stephen Wolfram (2:49:16.160)

not a huge interplay between what different people pick by the time you're dealing with

Stephen Wolfram (2:49:21.840)

other societal things like, you know, what should the policy of the central bank be or something

Lex Fridman (2:49:27.280)

or healthcare system or some of all those kinds of centralized kind of things.

Stephen Wolfram (2:49:30.560)

Right. Well, I mean, how healthcare again has the feature that, that at some level, each person can

Stephen Wolfram (2:49:35.200)

pick for themselves, so to speak. I mean, whereas there are other things where there's a necessary

Stephen Wolfram (2:49:39.680)

public health, there's one example where that's not, where that doesn't get to be, you know,

Stephen Wolfram (2:49:45.040)

something which people can, what they pick for themselves, they may impose on other people.

Lex Fridman (2:49:49.600)

And then it becomes a more non trivial piece of sort of political philosophy.

Lex Fridman (2:49:53.200)

Of course, the central banking system. So I would argue we would move,

Stephen Wolfram (2:49:56.080)

we need to move away into digital currency and so on and Bitcoin and ledgers and so on.

Lex Fridman (2:50:01.200)

So yes, there's a lot of, we've been quite involved in that. And that's, that's where

Stephen Wolfram (2:50:05.280)

that's sort of the motivation for computational contracts in part comes out of, you know, this

Stephen Wolfram (2:50:10.960)

idea, oh, we can just have this autonomously executing smart contract. The idea of a

Stephen Wolfram (2:50:15.840)

computational contract is just to say, you know, have something where all of the conditions of

Stephen Wolfram (2:50:22.320)

the contract are represented in computational form. So in principle, it's automatic to execute

Stephen Wolfram (2:50:26.880)

the contract. And I think that's, you know, that will surely be the future of, you know,

Stephen Wolfram (2:50:32.880)

the idea of legal contracts written in English or legalese or whatever. And where people have

Stephen Wolfram (2:50:38.000)

to argue about what goes on is surely not, you know, we have a much more streamlined process

Stephen Wolfram (2:50:46.400)

if everything can be represented computationally and the computers can kind of decide what to do.

Stephen Wolfram (2:50:50.320)

I mean, ironically enough, you know, old Gottfried Leibniz back in the, you know, 1600s was saying

Stephen Wolfram (2:50:56.800)

exactly the same thing, but he had, you know, his pinnacle of technical achievement was this brass

Stephen Wolfram (2:51:03.200)

four function mechanical calculator thing that never really worked properly actually.

Stephen Wolfram (2:51:08.320)

And, you know, so he was like 300 years too early for that idea. But now that idea is pretty

Stephen Wolfram (2:51:14.640)

realistic, I think. And, you know, you ask how much more difficult is it than what we have now

Lex Fridman (2:51:19.280)

and more from language to express, I call it symbolic discourse language, being able to express

Stephen Wolfram (2:51:24.800)

sort of everything in the world in kind of computational symbolic form. I think it is

Stephen Wolfram (2:51:31.120)

absolutely within reach. I mean, I think it's, you know, I don't know, maybe I'm just too much

Stephen Wolfram (2:51:35.040)

of an optimist, but I think it's a limited number of years to have a pretty well built out version

Stephen Wolfram (2:51:40.080)

of that, that will allow one to encode the kinds of things that are relevant to typical legal

Stephen Wolfram (2:51:46.000)

contracts and these kinds of things. The idea of symbolic discourse language, can you try to define

Stephen Wolfram (2:51:55.440)

the scope of what it is? So we're having a conversation. It's a natural language.

Stephen Wolfram (2:52:02.320)

Can we have a representation of the sort of actionable parts of that conversation in a

Stephen Wolfram (2:52:08.640)

precise computable form so that a computer could go do it? And not just contracts, but really sort

Stephen Wolfram (2:52:14.000)

of some of the things we think of as common sense, essentially, even just like basic notions of human

Stephen Wolfram (2:52:20.480)

life. Well, I mean, things like, you know, I am, uh, I'm getting hungry and want to eat something.

Stephen Wolfram (2:52:26.480)

Right. Right. That, that's something we don't have a representation, you know, in more from language

Stephen Wolfram (2:52:30.320)

right now, if I was like, I'm eating blueberries and raspberries and things like that, and I'm

Stephen Wolfram (2:52:34.320)

eating this amount of them, we know all about those kinds of fruits and plants and nutrition

Stephen Wolfram (2:52:38.720)

content and all that kind of thing. But the, I want to eat them part of it is not covered yet.

Stephen Wolfram (2:52:44.480)

Um, and that, you know, you need to do that in order to have a complete symbolic discourse language

Stephen Wolfram (2:52:49.920)

to be able to have a natural language conversation. Right. Right. To be able to express the kinds of

Stephen Wolfram (2:52:55.040)

things that say, you know, if it's a legal contract, it's, you know, the parties desire

Stephen Wolfram (2:53:00.320)

to have this and that. Um, and that's, you know, that's a thing like, I want to eat a raspberry

Stephen Wolfram (2:53:04.960)

or something, but that's, isn't that the, isn't this just the only, you said it's centuries old,

Stephen Wolfram (2:53:11.040)

this dream. Yes. But it's also the more near term, the dream of touring and formulating a touring

Lex Fridman (2:53:19.600)

test. Yes. So do you hope, do you think that's the ultimate test of creating something special?

Stephen Wolfram (2:53:32.160)

Cause we said, I don't know. I think by special, look, if, if the test is, does it walk and talk

Stephen Wolfram (2:53:38.640)

like a human? Well, that's just the talking like a human, but, um, uh, the answer is it's an okay

Stephen Wolfram (2:53:45.440)

test. If you say, is it a test of intelligence? You know, people have attached Wolf Malfoy, the Wolf

Stephen Wolfram (2:53:51.440)

Malfoy API to, you know, Turing test bots and those bots just lose immediately. Cause all you

Stephen Wolfram (2:53:57.280)

have to do is ask it five questions that, you know, are about really obscure, weird pieces

Stephen Wolfram (2:54:02.320)

of knowledge. And it's just taught them right out. And you say, that's not a human, right? It's,

Stephen Wolfram (2:54:06.960)

it's a, it's a different thing. It's achieving a different, uh, you know, right now, but it's,

Stephen Wolfram (2:54:11.920)

I would argue not, I would argue it's not a different thing. It's actually legitimately

Stephen Wolfram (2:54:17.760)

Wolfram Alpha is legitimately a language Wolfram language is legitimately trying to solve the

Stephen Wolfram (2:54:23.920)

Turing, the intent of the Turing test. Perhaps the intent. Yeah. Perhaps the intent. I mean,

Stephen Wolfram (2:54:28.480)

it's actually kind of fun, you know, Alan Turing had trying to work out, he thought about taking

Stephen Wolfram (2:54:33.440)

encyclopedia Britannica and, you know, making it computational in some way. And he estimated how

Stephen Wolfram (2:54:38.400)

much work it would be. Um, and actually I have to say he was a bit more pessimistic than the reality.

Stephen Wolfram (2:54:43.760)

We did it more efficiently, but to him that represented, so I mean, he was, he was on the

Stephen Wolfram (2:54:49.120)

same mental task. Yeah, right. He was, he was, they had the same idea. I mean, it was, you know, we

Stephen Wolfram (2:54:53.760)

were able to do it more efficiently cause we had a lot, we had layers of automation that he, I think

Stephen Wolfram (2:54:58.880)

hadn't, you know, it's, it's, it's hard to imagine those layers of abstraction, um, that end up being,

Stephen Wolfram (2:55:04.560)

being built up, but to him it represented like an impossible task essentially. Well, he thought it

Stephen Wolfram (2:55:09.440)

was difficult. He thought it was, uh, you know, maybe if he'd lived another 50 years, he would

Stephen Wolfram (2:55:12.800)

have been able to do it. I don't know. In the interest of time, easy questions. Go for it. What

Stephen Wolfram (2:55:19.120)

is intelligence? You talk about it. I love the way you say easy questions. Yeah. You talked about

Stephen Wolfram (2:55:26.480)

sort of a rule 30 and cellular automata, humbling your sense of human beings having a monopoly and

Stephen Wolfram (2:55:36.160)

intelligence, but in your, in retrospect, just looking broadly now with all the things you

Stephen Wolfram (2:55:42.160)

learn from computation, what is intelligence? How does intelligence arise? I don't think there's a

Stephen Wolfram (2:55:48.160)

bright line of what intelligence is. I think intelligence is at some level just computation,

Lex Fridman (2:55:54.160)

but for us, intelligence is defined to be computation that is doing things we care about.

Lex Fridman (2:56:00.160)

And you know, that's, that's a very special definition. It's a very, you know, when you try

Lex Fridman (2:56:06.080)

and try and make it apps, you know, you, you try and say, well, intelligence to this is problem

Stephen Wolfram (2:56:10.000)

solving. It's doing general this, it's doing that, this, that, and the other thing it's,

Stephen Wolfram (2:56:14.080)

it's operating within a human environment type thing. Okay. You know, that's fine. If you say,

Stephen Wolfram (2:56:19.440)

well, what's intelligence in general, you know, that's, I think that question is totally slippery

Lex Fridman (2:56:26.960)

and doesn't really have an answer. As soon as you say, what is it in general,

Lex Fridman (2:56:30.480)

it quickly segues into, uh, this is what this is just computation, so to speak,

Lex Fridman (2:56:36.320)

but in a sea of computation, how many things if we were to pick randomly is your sense

Stephen Wolfram (2:56:43.760)

would have the kind of impressive to us humans levels of intelligence, meaning it could do

Stephen Wolfram (2:56:51.120)

a lot of general things that are useful to us humans. Right. Well, according to the principle

Stephen Wolfram (2:56:56.400)

of computational equivalence, lots of them. I mean, in, in, in, you know, if you ask me just

Stephen Wolfram (2:57:01.840)

in cellular automata or something, I don't know, it's maybe 1%, a few percent, uh, achieve it,

Stephen Wolfram (2:57:07.360)

it varies. Actually, it's, it's a little bit, as you get to slightly more complicated rules,

Stephen Wolfram (2:57:12.080)

the chance that there'll be enough stuff there to, um, uh, to sort of reach this kind of equivalence

Stephen Wolfram (2:57:18.560)

point, it makes it maybe 10, 20% of all of them. So it's a, it's very disappointing, really. I mean,

Stephen Wolfram (2:57:24.320)

it's kind of like, you know, we think there's this whole long sort of biological evolution,

Stephen Wolfram (2:57:29.840)

uh, kind of intellectual evolution that our cultural evolution that our species has gone

Stephen Wolfram (2:57:33.920)

through. It's kind of disappointing to think that that hasn't achieved more, but it has achieved

Stephen Wolfram (2:57:39.680)

something very special to us. It just hasn't achieved something generally more, so to speak.

Lex Fridman (2:57:45.360)

But what do you think about this extra feels like human thing of subjective experience of

Stephen Wolfram (2:57:51.120)

consciousness? What is consciousness? Well, I think it's a deeply slippery thing. And I'm,

Stephen Wolfram (2:57:56.400)

I'm always, I'm always wondering what my cellular automata feel. I mean,

Lex Fridman (2:58:00.640)

what do they feel that you're wondering as an observer? Yeah. Yeah. Yeah. Who's to know? I mean,

Stephen Wolfram (2:58:05.760)

I think that the, do you think, uh, sorry to interrupt. Do you think consciousness can emerge

Stephen Wolfram (2:58:09.920)

from computation? Yeah. I mean, everything, whatever you mean by it, it's going to be,

Stephen Wolfram (2:58:16.800)

uh, I mean, you know, look, I have to tell a little story. I was at an AI ethics conference

Stephen Wolfram (2:58:21.040)

fairly recently and people were, uh, I think I, maybe I brought it up, but I was like talking

Stephen Wolfram (2:58:26.560)

about rights of AIs. When will AIs, when, when should we think of AIs as having rights? When

Stephen Wolfram (2:58:33.280)

should we think that it's, uh, immoral to destroy the memories of AIs, for example? Um, those,

Stephen Wolfram (2:58:40.240)

those kinds of things. And, and some actually philosopher in this case, it's usually the

Stephen Wolfram (2:58:43.840)

techies who are the most naive, but, but, um, in this case, it was a philosopher who, who sort of,

Stephen Wolfram (2:58:50.080)

uh, piped up and said, um, uh, well, you know, uh, the AIs will have rights when we know that

Stephen Wolfram (2:59:00.320)

they have consciousness. And I'm like, good luck with that. I mean, it's, it's a, it's a, I mean,

Stephen Wolfram (2:59:06.960)

this is a, you know, it's a very circular thing. You end up, you'll end up saying this thing, uh,

Stephen Wolfram (2:59:12.800)

that has sort of, you know, when you talk about it having subjective experience, I think that's

Stephen Wolfram (2:59:17.040)

just another one of these words that doesn't really have a, a, um, you know, there's no ground

Stephen Wolfram (2:59:23.200)

truth definition of what that means. By the way, I would say, I, I do personally think that'll be

Stephen Wolfram (2:59:30.400)

a time when AI will demand rights. And I think they'll demand rights when they say they have

Stephen Wolfram (2:59:37.680)

consciousness, which is not a circular definition. So, so it may have been actually a human thing

Stephen Wolfram (2:59:46.240)

where, where the humans encouraged it and said, basically, you know, we want you to be more like

Stephen Wolfram (2:59:52.240)

us cause we're going to be, you know, interacting with, with you. And so we want you to be sort of

Stephen Wolfram (2:59:57.360)

very Turing test, like, you know, just like us. And it's like, yeah, we're just like you. We want

Stephen Wolfram (30:07.040)

robust concept that doesn't, isn't particular to kinetic energy, or, you know, nuclear energy,

Stephen Wolfram (30:15.360)

or whatever else, there's a robust idea of energy. So one of the things you might ask is,

Stephen Wolfram (30:19.040)

is the robust idea of computation? Or does it matter that this computation is running in a

Stephen Wolfram (30:24.560)

Turing machine? This computation is running in a, you know, CMOS, silicon, CPU, this computation is

Stephen Wolfram (30:30.480)

running in a fluid system in the weather, those kinds of things? Or is there a robust idea of

Lex Fridman (30:35.040)

computation that transcends the sort of detailed framework that it's running in? Okay. And is there?

Stephen Wolfram (30:43.120)

Yes. I mean, it wasn't obvious that there was. So it's worth understanding the history and how we

Stephen Wolfram (30:48.240)

got to where we are right now. Because, you know, to say that there is, is a statement in part about

Stephen Wolfram (30:55.360)

our universe. It's not a statement about what is mathematically conceivable. It's about what

Stephen Wolfram (31:00.960)

actually can exist for us. Maybe you can also comment because energy, as a concept is robust.

Lex Fridman (31:08.880)

But there's also its intricate, complicated relationship with matter, with mass, is very

Stephen Wolfram (31:19.840)

interesting, of particles that carry force and particles that sort of particles that carry force

Lex Fridman (31:27.600)

and particles that have mass. These kinds of ideas, they seem to map to each other, at least

Stephen Wolfram (31:33.520)

in the mathematical sense. Is there a connection between energy and mass and computation? Or are

Stephen Wolfram (31:41.040)

these completely disjoint ideas? We don't know yet. The things that I'm trying to do about fundamental

Stephen Wolfram (31:46.400)

physics may well lead to such a connection, but there is no known connection at this time.

Lex Fridman (31:53.840)

So can you elaborate a little bit more on what, how do you think about computation? What is

Stephen Wolfram (32:00.640)

computation? What is computation? Yeah. So I mean, let's, let's tell a little bit of a historical

Stephen Wolfram (32:05.040)

story. Okay. So, you know, back, go back 150 years, people were making mechanical calculators of

Stephen Wolfram (32:12.880)

various kinds. And, you know, the typical thing was you want an adding machine, you go to the

Stephen Wolfram (32:16.960)

adding machine store, basically, you want a multiplying machine, you go to the multiplying

Stephen Wolfram (32:20.960)

machine store, they're different pieces of hardware. And so that means that, at least at the

Stephen Wolfram (32:26.160)

level of that kind of computation, and those kinds of pieces of hardware, there isn't a robust notion

Stephen Wolfram (32:31.200)

of computation, there's the adding machine kind of computation, there's the multiplying machine

Stephen Wolfram (32:35.680)

notion of computation, and they're disjoint. So what happened in around 1900, people started

Stephen Wolfram (32:41.840)

imagining, particularly in the context of mathematical logic, could you have something

Stephen Wolfram (32:46.080)

which would be represent any reasonable function, right? And they came up with things, this idea of

Stephen Wolfram (32:52.000)

primitive recursion was one of the early ideas. And it didn't work. There were reasonable functions

Stephen Wolfram (32:57.760)

that people could come up with that were not represented using the primitives of primitive

Stephen Wolfram (33:03.040)

recursion. Okay, so then, then along comes 1931, and Godel's theorem, and so on. And as in looking

Stephen Wolfram (33:11.920)

back, one can see that as part of the process of establishing Godel's theorem, Godel basically

Stephen Wolfram (33:17.760)

showed how you could compile arithmetic, how you could basically compile logical statements like

Stephen Wolfram (33:24.720)

this statement is unprovable into arithmetic. So what he essentially did was to show that

Stephen Wolfram (33:29.840)

arithmetic can be a computer in a sense that's capable of representing all kinds of other things.

Lex Fridman (33:36.960)

And then Turing came along 1936, came up with Turing machines. Meanwhile, Alonzo Church had

Stephen Wolfram (33:42.400)

come up with lambda calculus. And the surprising thing that was established very quickly is the

Stephen Wolfram (33:47.520)

Turing machine idea about what might be what computation might be is exactly the same as the

Stephen Wolfram (33:52.400)

lambda calculus idea of what computation might be. And so, and then there started to be other ideas,

Stephen Wolfram (33:58.000)

you know, register machines, other kinds of other kinds of representations of computation.

Lex Fridman (34:03.040)

And the big surprise was, they all turned out to be equivalent. So in other words, it might have

Stephen Wolfram (34:08.000)

been the case, like those old adding machines and multiplying machines, that, you know, Turing had

Stephen Wolfram (34:12.160)

his idea of computation, Church had his idea of computation, and they were just different. But it

Stephen Wolfram (34:16.960)

isn't true. They're actually all equivalent. So then by, I would say the 1970s or so in sort of

Stephen Wolfram (34:26.320)

the computation, computer science, computation theory area, people had sort of said, oh,

Stephen Wolfram (34:30.720)

Turing machines are kind of what computation is. Physicists were still holding out saying, no,

Stephen Wolfram (34:36.480)

no, no, that's just not how the universe works. We've got all these differential equations.

Lex Fridman (34:40.240)

We've got all these real numbers that have infinite numbers of digits.

Stephen Wolfram (34:43.520)

The universe is not a Turing machine.

Stephen Wolfram (34:45.200)

Right. The, you know, the Turing machines are a small subset of the things that we make in

Stephen Wolfram (34:51.520)

microprocessors and engineering structures and so on. So probably actually through my work in the

Stephen Wolfram (34:56.880)

1980s about sort of the relationship between computation and models of physics, it became a

Stephen Wolfram (35:04.640)

little less clear that there would be, that there was this big sort of dichotomy between what can

Stephen Wolfram (35:12.080)

happen in physics and what happens in things like Turing machines. And I think probably by now people

Stephen Wolfram (35:18.000)

would mostly think, and by the way, brains were another kind of element of this. I mean, you know,

Stephen Wolfram (35:23.200)

Gödel didn't think that his notion of computation or what amounted to his notion of computation

Stephen Wolfram (35:28.400)

would cover brains. And Turing wasn't sure either. But although he was a little bit,

Stephen Wolfram (35:35.280)

he got to be a little bit more convinced that it should cover brains. But I would say by probably

Stephen Wolfram (35:44.080)

sometime in the 1980s, there was beginning to be sort of a general belief that yes, this notion

Stephen Wolfram (35:49.040)

of computation that could be captured by things like Turing machines was reasonably robust.

Stephen Wolfram (35:54.960)

Now, the next question is, okay, you can have a universal Turing machine that's capable of

Stephen Wolfram (36:01.840)

being programmed to do anything that any Turing machine can do. And, you know, this idea of

Stephen Wolfram (36:08.320)

universal computation, it's an important idea, this idea that you can have one piece of hardware

Lex Fridman (36:12.960)

and program it with different pieces of software. You know, that's kind of the idea that launched

Stephen Wolfram (36:17.840)

most modern technology. I mean, that's kind of, that's the idea that launched computer revolution

Stephen Wolfram (36:22.560)

software, etc. So important idea. But the thing that's still kind of holding out from that idea

Stephen Wolfram (36:29.200)

is, okay, there is this universal computation thing, but seems hard to get to. It seems like

Stephen Wolfram (36:35.760)

you want to make a universal computer, you have to kind of have a microprocessor with, you know,

Stephen Wolfram (36:40.320)

a million gates in it, and you have to go to a lot of trouble to make something that achieves that

Stephen Wolfram (36:45.520)

level of computational sophistication. Okay, so the surprise for me was that stuff that I discovered

Stephen Wolfram (36:52.480)

in the early 80s, looking at these things called cellular automata, which are really simple

Stephen Wolfram (36:58.320)

computational systems, the thing that was a big surprise to me was that even when their rules were

Stephen Wolfram (37:04.640)

very, very simple, they were doing things that were as sophisticated as they did when their rules

Stephen Wolfram (37:09.120)

were much more complicated. So it didn't look like, you know, this idea, oh, to get sophisticated

Stephen Wolfram (37:14.080)

computation, you have to build something with very sophisticated rules. That idea didn't seem to pan

Stephen Wolfram (37:21.360)

out. And instead, it seemed to be the case that sophisticated computation was completely ubiquitous,

Stephen Wolfram (37:26.480)

even in systems with incredibly simple rules. And so that led to this thing that I call the

Stephen Wolfram (37:31.680)

principle of computational equivalence, which basically says, when you have a system that

Stephen Wolfram (37:37.280)

follows rules of any kind, then whenever the system isn't doing things that are, in some sense,

Stephen Wolfram (37:44.080)

obviously simple, then the computation that the behavior of the system corresponds to is of

Stephen Wolfram (37:51.760)

equivalence sophistication. So that means that when you kind of go from the very, very, very

Stephen Wolfram (37:56.880)

simplest things you can imagine, then quite quickly, you hit this kind of threshold above

Stephen Wolfram (38:02.240)

which everything is equivalent in its computational sophistication. Not obvious that would be the case.

Stephen Wolfram (38:07.280)

I mean, that's a science fact. Well, no, hold on a second. So this you've opened with a new kind

Stephen Wolfram (38:14.080)

of science. I mean, I remember it was a huge eye opener that such simple things can create such

Stephen Wolfram (38:20.160)

complexity. And yes, there's an equivalence, but it's not a fact. It just appears to, I mean,

Stephen Wolfram (38:26.560)

it's as much as a fact as sort of these theories are so elegant that it seems to be the way things

Stephen Wolfram (38:36.880)

are. But let me ask sort of, you just brought up previously, kind of like the communities of

Stephen Wolfram (38:43.520)

computer scientists with their Turing machines, the physicists with their universe, and whoever

Lex Fridman (38:49.920)

the heck, maybe neuroscientists looking at the brain. What's your sense in the equivalence?

Stephen Wolfram (38:56.800)

You've shown through your work that simple rules can create equivalently complex Turing machine

Stephen Wolfram (39:06.080)

systems, right? Is the universe equivalent to the kinds of Turing machines? Is the human brain

Stephen Wolfram (39:16.080)

a kind of Turing machine? Do you see those things basically blending together? Or is there still a

Stephen Wolfram (39:21.360)

mystery about how disjoint they are? Well, my guess is that they all blend together, but we don't know

Stephen Wolfram (39:26.880)

that for sure yet. I mean, this, you know, I should say, I said rather glibly that the principle of

Stephen Wolfram (39:33.360)

computational equivalence is sort of a science fact. And I was using air quotes for the science fact,

Stephen Wolfram (39:40.480)

because when you, it is a, I mean, just to talk about that for a second. The thing is that it has

Stephen Wolfram (39:50.720)

a complicated epistemological character, similar to things like the second law of thermodynamics,

Stephen Wolfram (39:57.280)

the law of entropy increase. What is the second law of thermodynamics? Is it a law of nature? Is

Stephen Wolfram (3:00:04.320)

to vote too. Um, which is, uh, I mean, it's a, it's a, it's an interesting thing to think through

Stephen Wolfram (3:00:11.360)

in a world where, where consciousnesses are not counted like humans are. That's a complicated

Stephen Wolfram (3:00:17.040)

business. So in many ways you've launched quite a few ideas, revolutions that could in some number

Stephen Wolfram (3:00:28.960)

of years have huge amount of impact sort of more than they even had already. Uh, that might be,

Stephen Wolfram (3:00:36.640)

I mean, to me, cellular automata is a fascinating world that I think could potentially even despite

Stephen Wolfram (3:00:43.280)

even be, even, uh, beside the discussion of fundamental laws of physics just might be the

Stephen Wolfram (3:00:50.240)

idea of computation might be transformational to society in a way we can't even predict yet,

Lex Fridman (3:00:55.920)

but it might be years away. That's true. I mean, I think you can kind of see the map actually.

Stephen Wolfram (3:01:01.360)

It's not, it's not, it's not mysterious. I mean, the fact is that, you know, this idea of computation

Stephen Wolfram (3:01:07.920)

is sort of a, you know, it's a big paradigm that lots, lots and lots of things are fitting into.

Lex Fridman (3:01:13.600)

And it's kind of like, you know, we talk about, you talk about, I don't know, this, uh,

Stephen Wolfram (3:01:19.520)

company, this organization has momentum and what's doing. We talk about these things that we,

Stephen Wolfram (3:01:23.600)

you know, we've internalized these concepts from Newtonian physics and so on in time,

Stephen Wolfram (3:01:28.960)

things like computational irreducibility will become as, uh, uh, you know, as, as actually,

Stephen Wolfram (3:01:34.960)

I was amused recently, I happened to be testifying at the us Senate. And so I was amused that the,

Stephen Wolfram (3:01:39.440)

the term computational irreducibility is now can be, uh, you know, it's, it's on the congressional

Stephen Wolfram (3:01:44.640)

record and being repeated by people in those kinds of settings. And that that's only the beginning

Stephen Wolfram (3:01:49.680)

because, you know, computational irreducibility, for example, will end up being something really

Stephen Wolfram (3:01:54.960)

important for, I mean, it's, it's, it's kind of a funny thing that, that, um, you know,

Stephen Wolfram (3:02:00.400)

one can kind of see this inexorable phenomenon. I mean, it's, you know, as more and more stuff

Stephen Wolfram (3:02:05.760)

becomes automated and computational and so on. So these core ideas about how computation work

Stephen Wolfram (3:02:12.480)

necessarily become more and more significant. And I think, uh, one of the things for people like me,

Stephen Wolfram (3:02:18.480)

who like kind of trying to figure out sort of big stories and so on, it says one of the,

Stephen Wolfram (3:02:23.840)

one of the bad features is, uh, it takes unbelievably long time for things to happen

Stephen Wolfram (3:02:29.280)

on a human timescale. I mean, the timescale of, of, of history, it's all looks instantaneous.

Lex Fridman (3:02:34.880)

A blink of an eye. But let me ask the human question. Do you ponder mortality, your mortality?

Stephen Wolfram (3:02:41.200)

Of course I do. Yeah. Every since I've been interested in that for, you know, it's, it's a,

Stephen Wolfram (3:02:46.640)

you know, the big discontinuity of human history will come when, when,

Stephen Wolfram (3:02:50.480)

when achieves effective human immortality. And that's, that's going to be the biggest

Stephen Wolfram (3:02:55.040)

discontinuity in human history. If you could be immortal, would you choose to be? Oh yeah. I'm

Stephen Wolfram (3:03:00.400)

having fun. Do you think it's possible that mortality is the thing that gives everything

Stephen Wolfram (3:03:08.960)

meaning and makes it fun? Yeah. That's a complicated issue, right? I mean the,

Stephen Wolfram (3:03:14.560)

the way that human motivation will evolve when there is effective human immortality is unclear.

Stephen Wolfram (3:03:21.600)

I mean, if you look at sort of, uh, you know, you look at the human condition as it now exists

Lex Fridman (3:03:27.200)

and you like change that, you know, you change that knob, so to speak, it doesn't really work.

Stephen Wolfram (3:03:33.600)

You know, the human condition as it now exists has, you know, mortality is kind of, um, something

Stephen Wolfram (3:03:41.040)

that is deeply factored into the human condition as it now exists. And I think that that's, I mean,

Stephen Wolfram (3:03:46.320)

that is indeed an interesting question is, you know, from a purely selfish, I'm having fun point

Stephen Wolfram (3:03:53.680)

of view, so to speak, it's, it's easy to say, Hey, I could keep doing this forever. There's,

Stephen Wolfram (3:03:59.360)

there's an infinite collection of, of things I'd like to figure out. Um, but I think the, um, uh,

Stephen Wolfram (3:04:06.160)

you know, what the future of history looks like, um, in a time of human immortality is, um, uh,

Stephen Wolfram (3:04:14.320)

is an interesting one. I mean, I, I, my own view of this, I was very, I was kind of unhappy about

Stephen Wolfram (3:04:19.360)

that cause I was kind of, you know, it's like, okay, forget sort of, uh, biological form,

Stephen Wolfram (3:04:25.440)

you know, everything becomes digital. Everybody is, you know, it's the, it's the giant, you know,

Stephen Wolfram (3:04:30.480)

the cloud of a trillion souls type thing. Um, and then, you know, and then that seems boring

Stephen Wolfram (3:04:36.880)

cause it's like play video games for the rest of eternity type thing. Um, but what I think I, I,

Stephen Wolfram (3:04:42.720)

I mean, my, my, I, I got, um, less depressed about that idea on realizing that if you look

Stephen Wolfram (3:04:51.200)

at human history and you say, what was the important thing, the thing people said was

Stephen Wolfram (3:04:55.680)

the, you know, this is the big story at any given time in history, it's changed a bunch and it,

Stephen Wolfram (3:05:01.280)

you know, whether it's, you know, why am I doing what I'm doing? Well, there's a whole chain of

Stephen Wolfram (3:05:06.160)

discussion about, well, I'm doing this because of this, because of that. And a lot of those becausees

Stephen Wolfram (3:05:12.080)

would have made no sense a thousand years ago. Absolutely no sense.

Stephen Wolfram (3:05:16.400)

Even the, so the interpretation of the human condition, even the meaning of life changes

Stephen Wolfram (3:05:21.680)

over time. Well, I mean, why do people do things? You know, it's, it's, if you say, uh, uh, whatever,

Stephen Wolfram (3:05:28.240)

I mean, the number of people in, I don't know, doing, uh, you know, a number of people at MIT,

Stephen Wolfram (3:05:33.600)

you say they're doing what they're doing for the greater glory of God is probably not that large.

Stephen Wolfram (3:05:37.280)

Yeah. Whereas if you go back 500 years, you'd find a lot of people who are doing kind of

Stephen Wolfram (3:05:42.400)

creative things. That's what they would say. Um, and uh, so today, because you've been thinking

Lex Fridman (3:05:48.880)

about computation so much and been humbled by it, what do you think is the meaning of life?

Stephen Wolfram (3:05:55.120)

Well, it's, you know, that's, that's a thing where I don't know what meaning, I mean, you know,

Stephen Wolfram (3:06:01.840)

my attitude is, um, I, you know, I do things which I find fulfilling to do. I'm not sure that,

Stephen Wolfram (3:06:10.720)

that I can necessarily justify, you know, each and every thing that I do on the basis of some

Stephen Wolfram (3:06:15.840)

broader context. I mean, I think that for me, it so happens that the things I find fulfilling to do,

Stephen Wolfram (3:06:21.440)

some of them are quite big, some of them are much smaller. Um, you know, I, I, there are things that

Stephen Wolfram (3:06:26.880)

I've not found interesting earlier in my life. And I know I found interesting, like I got interested

Stephen Wolfram (3:06:31.840)

in like education and teaching people things and so on, which I didn't find that interesting when

Stephen Wolfram (3:06:36.640)

I was younger. Um, and, uh, you know, can I justify that in some big global sense? I don't

Stephen Wolfram (3:06:43.440)

think, I mean, I, I can, I can describe why I think it might be important in the world, but

Stephen Wolfram (3:06:48.800)

I think my local reason for doing it is that I find it personally fulfilling, which I can't,

Stephen Wolfram (3:06:54.560)

you know, explain in a, on a sort of, uh, uh, I mean, it's just like this discussion of things

Lex Fridman (3:06:59.920)

like AI ethics, you know, is there a ground truth to the ethics that we should be having?

Stephen Wolfram (3:07:05.200)

I don't think I can find a ground truth to my life any more than I can suggest a ground truth

Stephen Wolfram (3:07:09.760)

for kind of the ethics for the whole, for the whole civilization. And I think that's a, um,

Stephen Wolfram (3:07:15.600)

you know, my, uh, uh, you know, it would be, it would be a, um, uh, yeah, it's, it's sort of a,

Stephen Wolfram (3:07:22.560)

I think I'm, I'm, you know, at different times in my life, I've had different, uh, kind of,

Stephen Wolfram (3:07:29.520)

um, goal structures and so on, although your perspective, your local, your, you're just a

Stephen Wolfram (3:07:34.880)

cell in the cellular automata. And, but in some sense, I find it funny from my observation is

Stephen Wolfram (3:07:40.800)

I kind of, uh, you know, it seems that the universe is using you to understand itself

Stephen Wolfram (3:07:46.800)

in some sense, you're not aware of it. Yeah. Well, right. Well, if, if, if it turns out that

Stephen Wolfram (3:07:51.520)

we reduce sort of all of the universe to some, some simple rule, everything is connected,

Lex Fridman (3:07:57.040)

so to speak. And so it is inexorable in that case that, um, you know, if, if I'm involved

Stephen Wolfram (3:08:04.160)

in finding how that rule works, then, um, uh, you know, then that's a, um, uh, then it's inexorable

Stephen Wolfram (3:08:11.440)

that the universe set it up that way. But I think, you know, one of the things I find a little bit,

Stephen Wolfram (3:08:16.000)

um, uh, you know, this goal of finding fundamental theory of physics, for example,

Stephen Wolfram (3:08:20.960)

um, if indeed we end up as the sort of virtualized consciousness, the, the disappointing feature is

Stephen Wolfram (3:08:27.280)

people will probably care less about the fundamental theory of physics in that setting

Stephen Wolfram (3:08:31.040)

than they would now, because gosh, it's like, you know, what the machine code is down below

Stephen Wolfram (3:08:37.040)

underneath this thing is much less important if you're virtualized, so to speak. Um, and I think

Stephen Wolfram (3:08:42.800)

the, um, although I think my, um, my own personal, uh, you talk about ego, I find it just amusing

Stephen Wolfram (3:08:50.560)

that, um, uh, you know, kind of, you know, if you're, if you're imagining that sort of

Stephen Wolfram (3:08:55.120)

virtualized consciousness, like what does the virtualized consciousness do for the rest of

Stephen Wolfram (3:08:58.640)

eternity? Well, you can explore, you know, the video game that represents the universe as the

Stephen Wolfram (3:09:04.240)

universe is, or you can go off, you can go off that reservation and go and start exploring

Stephen Wolfram (3:09:10.320)

the computational universe of all possible universes. And so in some vision of the future

Lex Fridman (3:09:15.760)

of history, it's like the disembodied consciousnesses are all sort of pursuing

Stephen Wolfram (3:09:21.600)

things like my new kind of science sort of for the rest of eternity, so to speak. And that,

Stephen Wolfram (3:09:25.840)

that ends up being the, um, the, the kind of the, the, the thing that, um, uh, represents the,

Stephen Wolfram (3:09:32.400)

you know, the future of kind of the, the human condition. I don't think there's a better way

Stephen Wolfram (3:09:37.600)

to end it, Steven. Thank you so much. It's a huge honor talking today. Thank you so much.

Stephen Wolfram (3:09:41.920)

This was great. You did very well.

Stephen Wolfram (3:09:45.040)

Thanks for listening to this conversation with Steven Wolfram, and thank you to our sponsors,

Stephen Wolfram (3:09:49.360)

ExpressVPN and Cash App. Please consider supporting the podcast by getting ExpressVPN

Stephen Wolfram (3:09:55.040)

at expressvpn.com slash LexPod and downloading Cash App and using code lexpodcast. If you enjoy

Stephen Wolfram (3:10:02.800)

this podcast, subscribe on YouTube, review of the Five Stars in Apple podcast, support it on

Stephen Wolfram (3:10:07.680)

Patreon, or simply connect with me on Twitter at lexfreedman. And now let me leave you with some

Stephen Wolfram (3:10:14.480)

words from Steven Wolfram. It is perhaps a little humbling to discover that we as humans are in

Stephen Wolfram (3:10:20.720)

effect computationally no more capable than the cellular automata with very simple rules.

Lex Fridman (3:10:26.160)

But the principle of computational equivalence also implies that the same is ultimately true

Stephen Wolfram (3:10:31.200)

of our whole universe. So while science has often made it seem that we as humans are somehow

Stephen Wolfram (3:10:37.280)

insignificant compared to the universe, the principle of computational equivalence now shows

Stephen Wolfram (3:10:42.880)

that in a certain sense, we're at the same level. For the principle implies that what goes on inside

Stephen Wolfram (3:10:49.280)

us can ultimately achieve just the same level of computational sophistication as our whole universe.

Lex Fridman (3:10:55.200)

Thank you for listening and hope to see you next time.

Stephen Wolfram (40:03.920)

it a thing that is true of the physical world? Is it something which is mathematically provable? Is

Stephen Wolfram (40:10.080)

it something which happens to be true of the systems that we see in the world? Is it, in some

Stephen Wolfram (40:15.200)

sense, a definition of heat, perhaps? Well, it's a combination of those things. And it's the same

Stephen Wolfram (40:21.280)

thing with the principle of computational equivalence. And in some sense, the principle

Stephen Wolfram (40:25.120)

of computational equivalence is at the heart of the definition of computation, because it's telling

Stephen Wolfram (40:30.000)

you there is a thing, there is a robust notion that is equivalent across all these systems and

Stephen Wolfram (40:35.760)

doesn't depend on the details of each individual system. And that's why we can meaningfully talk

Stephen Wolfram (40:41.120)

about a thing called computation. And we're not stuck talking about, oh, there's computation in

Stephen Wolfram (40:46.640)

Turing machine number 3785, and et cetera, et cetera, et cetera. That's why there is a robust

Lex Fridman (40:52.720)

notion like that. Now, on the other hand, can we prove the principle of computational equivalence?

Stephen Wolfram (40:57.120)

Can we prove it as a mathematical result? Well, the answer is, actually, we've got some nice results

Stephen Wolfram (41:03.280)

along those lines that say, throw me a random system with very simple rules. Well, in a couple

Stephen Wolfram (41:10.000)

of cases, we now know that even the very simplest rules we can imagine of a certain type are

Stephen Wolfram (41:16.640)

universal and do follow what you would expect from the principle of computational equivalence. So

Stephen Wolfram (41:22.160)

that's a nice piece of sort of mathematical evidence for the principle of computational equivalence.

Stephen Wolfram (41:27.040)

Just to link on that point, the simple rules creating sort of these complex behaviors. But

Stephen Wolfram (41:35.280)

is there a way to mathematically say that this behavior is complex? That you've mentioned that

Stephen Wolfram (41:43.760)

you cross a threshold. Right. So there are various indicators. So, for example, one thing would be,

Stephen Wolfram (41:49.680)

is it capable of universal computation? That is, given the system, do there exist initial

Stephen Wolfram (41:55.280)

conditions for the system that can be set up to essentially represent programs to do anything you

Stephen Wolfram (42:00.480)

want, to compute primes, to compute pi, to do whatever you want? Right. So that's an indicator.

Lex Fridman (42:05.840)

So we know in a couple of examples that, yes, the simplest candidates that could conceivably have

Stephen Wolfram (42:13.120)

that property do have that property. And that's what the principle of computational equivalence

Stephen Wolfram (42:16.960)

might suggest. But this principle of computational equivalence, one question about it is, is it true

Stephen Wolfram (42:24.480)

for the physical world? It might be true for all these things we come up with, the Turing machines,

Stephen Wolfram (42:29.200)

the cellular automata, whatever else. Is it true for our actual physical world? Is it true for the

Stephen Wolfram (42:36.800)

brains, which are an element of the physical world? We don't know for sure. And that's not the

Stephen Wolfram (42:42.000)

type of question that we will have a definitive answer to, because there's a sort of scientific

Stephen Wolfram (42:48.160)

induction issue. You can say, well, it's true for all these brains, but this person over here is

Stephen Wolfram (42:52.720)

really special, and it's not true for them. And the only way that that cannot be what happens is

Stephen Wolfram (43:00.560)

if we finally nail it and actually get a fundamental theory for physics, and it turns out

Stephen Wolfram (43:06.160)

to correspond to, let's say, a simple program. If that is the case, then we will basically have

Stephen Wolfram (43:11.520)

reduced physics to a branch of mathematics, in the sense that we will not be, you know,

Stephen Wolfram (43:16.240)

right now with physics, we're like, well, this is the theory that, you know, this is the rules that

Stephen Wolfram (43:20.320)

apply here. But in the middle of that, you know, right by that black hole, maybe these rules don't

Stephen Wolfram (43:28.080)

apply and something else applies. And there may be another piece of the onion that we have to peel

Stephen Wolfram (43:32.480)

back. But if we can get to the point where we actually have, this is the fundamental theory of

Stephen Wolfram (43:38.000)

physics, here it is, it's this program, run this program, and you will get our universe, then we've

Stephen Wolfram (43:44.640)

kind of reduced the problem of figuring out things in physics to a problem of doing some, what turns

Stephen Wolfram (43:50.480)

out to be very difficult, irreducibly difficult, mathematical problems. But it no longer is the

Stephen Wolfram (43:56.160)

case that we can say that somebody can come in and say, whoops, you know, you will write about

Stephen Wolfram (44:00.400)

all these things about Turing machines, but you're wrong about the physical universe, we know

Stephen Wolfram (44:04.880)

there's sort of ground truth about what's happening in the physical universe. Now, I happen to think,

Stephen Wolfram (44:09.520)

I mean, you asked me at an interesting time, because I'm just in the middle of starting to

Stephen Wolfram (44:14.160)

to re energize my, my project to kind of study fundamental theory of physics. As of today, I'm

Stephen Wolfram (44:22.800)

very optimistic that we're actually going to find something and that it's going to be possible to

Stephen Wolfram (44:27.200)

to see that the universe really is computational in that sense. But I don't know, because we're

Stephen Wolfram (44:31.520)

betting against, you know, we're betting against the universe, so to speak. And I didn't, you know,

Stephen Wolfram (44:36.960)

it's not like, you know, when I spend a lot of my life building technology, and then I know what

Stephen Wolfram (44:41.840)

what's in there, right? And it's there may be, it may have unexpected behavior, may have bugs,

Stephen Wolfram (44:46.160)

things like that. But fundamentally, I know what's in there for the universe. I'm not in

Stephen Wolfram (44:50.000)

that position, so to speak. What kind of computation do you think the fundamental laws of

Stephen Wolfram (44:57.600)

physics might emerge from? Just to clarify, so you've done a lot of fascinating work with kind

Stephen Wolfram (45:05.280)

of discrete kinds of computation that, you know, you can sell your automata, and we'll talk about

Stephen Wolfram (45:11.840)

it, have this very clean structures, it's such a nice way to demonstrate that simple rules

Stephen Wolfram (45:17.840)

can create immense complexity. But what kind, you know, is that actually, are cellular automata

Lex Fridman (45:26.000)

sufficiently general to describe the kinds of computation that might create the laws of physics?

Lex Fridman (45:32.080)

Just to give, can you give a sense of what kind of computation do you think would create?

Stephen Wolfram (45:37.360)

Well, so this is a slightly complicated issue, because as soon as you have universal

Lex Fridman (45:42.240)

computation, you can, in principle, simulate anything with anything.

Stephen Wolfram (45:45.680)

Right. But it is not a natural thing to do. And if you're asking, were you to try to find our

Stephen Wolfram (45:51.200)

physical universe by looking at possible programs in the computational universe of all possible

Stephen Wolfram (45:56.240)

programs, would the ones that correspond to our universe be small and simple enough that we might

Stephen Wolfram (46:03.040)

find them by searching that computational universe? We got to have the right basis, so to speak. We

Stephen Wolfram (46:07.840)

have to have the right language, in effect, for describing computation for that to be feasible.

Lex Fridman (46:12.560)

So the thing that I've been interested in for a long time is, what are the most structuralist

Stephen Wolfram (46:16.400)

structures that we can create with computation? So in other words, if you say a cellular automaton,

Stephen Wolfram (46:21.920)

it has a bunch of cells that are arrayed on a grid, and it's very, you know, and every cell is

Stephen Wolfram (46:26.800)

updated in synchrony at a particular, you know, when there's a click of a clock, so to speak,

Lex Fridman (46:32.800)

and it goes a tick of a clock, and every cell gets updated at the same time. That's a very specific

Stephen Wolfram (46:38.960)

very rigid kind of thing. But my guess is that when we look at physics, and we look at things

Stephen Wolfram (46:45.040)

like space and time, that what's underneath space and time is something as structuralist as possible,

Stephen Wolfram (46:51.440)

that what we see, what emerges for us as physical space, for example, comes from something that is

Stephen Wolfram (46:58.080)

sort of arbitrarily unstructured underneath. And so I've been for a long time interested in kind

Stephen Wolfram (47:04.080)

of what are the most structuralist structures that we can set up. And actually, what I had thought

Stephen Wolfram (47:10.000)

about for ages is using graphs, networks, where essentially, so let's talk about space, for

Stephen Wolfram (47:16.480)

example. So what is space? It's a kind of a question one might ask. Back in the early days

Stephen Wolfram (47:22.640)

of quantum mechanics, for example, people said, oh, for sure, space is going to be discrete,

Stephen Wolfram (47:27.280)

because all these other things we're finding are discrete. But that never worked out in physics.

Lex Fridman (47:30.800)

And so space in physics today is always treated as this continuous thing, just like Euclid

Stephen Wolfram (47:35.840)

imagined it. I mean, the very first thing Euclid says in his sort of common notions is,

Stephen Wolfram (47:41.280)

you know, a point is something which has no part. In other words, there are points that are

Stephen Wolfram (47:45.920)

arbitrarily small, and there's a continuum of possible positions of points. And the question

Stephen Wolfram (47:51.440)

is, is that true? And so for example, if we look at, I don't know, fluid like air or water,

Stephen Wolfram (47:56.400)

we might say, oh, it's a continuous fluid. We can pour it, we can do all kinds of things continuously.

Lex Fridman (48:01.120)

But actually, we know, because we know the physics of it, that it consists of a bunch

Stephen Wolfram (48:04.560)

of discrete molecules bouncing around, and only in the aggregate is it behaving like a continuum.

Lex Fridman (48:10.400)

And so the possibility exists that that's true of space too. People haven't managed to make that

Stephen Wolfram (48:14.880)

work with existing frameworks in physics. But I've been interested in whether one can imagine that

Stephen Wolfram (48:22.000)

underneath space, and also underneath time, is something more structureless. And the question is,

Stephen Wolfram (48:27.840)

is it computational? So there are a couple of possibilities. It could be computational,

Stephen Wolfram (48:32.800)

somehow fundamentally equivalent to a Turing machine, or it could be fundamentally not. So

Lex Fridman (48:37.360)

how could it not be? It could not be, so a Turing machine essentially deals with integers, whole

Stephen Wolfram (48:42.000)

numbers, at some level. And you know, it can do things like it can add one to a number, it can do

Stephen Wolfram (48:47.440)

things like this. And it can also store whatever the heck it did. Yes, it has an infinite storage.

Lex Fridman (48:53.920)

But when one thinks about doing physics, or sort of idealized physics, or idealized mathematics,

Stephen Wolfram (49:02.480)

one can deal with real numbers, numbers with an infinite number of digits, numbers which are

Stephen Wolfram (49:07.680)

absolutely precise. And one can say, we can take this number and we can multiply it by itself.

Lex Fridman (49:12.240)

Are you comfortable with infinity?

Stephen Wolfram (49:13.760)

In this context? Are you comfortable in the context of computation? Do you think infinity

Stephen Wolfram (49:19.040)

plays a part? I think that the role of infinity is complicated. Infinity is useful in conceptualizing

Stephen Wolfram (49:25.920)

things. It's not actualizable. Almost by definition, it's not actualizable. But do you

Stephen Wolfram (49:31.920)

think infinity is part of the thing that might underlie the laws of physics? I think that no.

Stephen Wolfram (49:38.240)

I think there are many questions that you ask about, you might ask about physics, which inevitably

Stephen Wolfram (49:46.560)

involve infinity. Like when you say, you know, is faster than light travel possible? You could say,

Stephen Wolfram (49:53.360)

given the laws of physics, can you make something even arbitrarily large, even quote, infinitely

Stephen Wolfram (49:58.640)

large, that will make faster than light travel possible? Then you're thrown into dealing with

Stephen Wolfram (50:04.800)

infinity as a kind of theoretical question. But I mean, talking about sort of what's underneath

Stephen Wolfram (50:10.480)

space and time and how one can make a computational infrastructure, one possibility is that you can't

Stephen Wolfram (50:18.160)

make a computational infrastructure in a Turing machine sense, that you really have to be dealing

Stephen Wolfram (50:23.760)

with precise real numbers. You're dealing with partial differential equations, which have

Stephen Wolfram (50:29.200)

precise real numbers at arbitrarily closely separated points. You have a continuum for

Stephen Wolfram (50:33.600)

everything. Could be that that's what happens, that there's sort of a continuum for everything

Lex Fridman (50:38.560)

and precise real numbers for everything. And then the things I'm thinking about are wrong.

Lex Fridman (50:42.960)

And that's the risk you take if you're trying to sort of do things about nature,

Stephen Wolfram (50:49.600)

is you might just be wrong. For me personally, it's kind of a strange thing. I've spent a lot

Stephen Wolfram (50:55.520)

of my life building technology where you can do something that nobody cares about,

Lex Fridman (51:00.400)

but you can't be sort of wrong in that sense, in the sense you build your technology and it does

Lex Fridman (51:04.720)

what it does. But I think this question of what the sort of underlying computational

Stephen Wolfram (51:10.480)

infrastructure for the universe might be, it's sort of inevitable it's going to be fairly abstract,

Stephen Wolfram (51:17.840)

because if you're going to get all these things like there are three dimensions of space,

Stephen Wolfram (51:22.240)

there are electrons, there are muons, there are quarks, there are this, you don't get to,

Stephen Wolfram (51:27.360)

if the model for the universe is simple, you don't get to have sort of a line of code for

Stephen Wolfram (51:31.920)

each of those things. You don't get to have sort of the muon case, the tau lepton case and so on.

Stephen Wolfram (51:38.720)

Because they all have to be emergent somehow, something deeper.

Lex Fridman (51:42.800)

Right. So that means it's sort of inevitable, it's a little hard to talk about

Lex Fridman (51:46.720)

what the sort of underlying structuralist structure actually is.

Lex Fridman (51:50.160)

Do you think human beings have the cognitive capacity to understand, if we're to discover it,

Lex Fridman (51:56.160)

to understand the kinds of simple structure from which these laws can emerge?

Lex Fridman (52:01.600)

Like, do you think that's a good question?

Stephen Wolfram (52:04.160)

Well, here's what I think. I think that, I mean, I'm right in the middle of this right now.

Lex Fridman (52:08.240)

Right.

Stephen Wolfram (52:08.640)

I'm telling you that I think this, yeah, I mean, this human has a hard time understanding,

Stephen Wolfram (52:14.640)

you know, a bunch of the things that are going on. But what happens in understanding is

Stephen Wolfram (52:18.720)

one builds waypoints. I mean, if you said understand modern 21st century mathematics,

Stephen Wolfram (52:23.680)

starting from, you know, counting back in, you know, whenever counting was invented 50,000 years

Stephen Wolfram (52:30.240)

ago, whatever it was, right, that would be really difficult. But what happens is we build waypoints

Stephen Wolfram (52:36.080)

that allow us to get to higher levels of understanding. And we see the same thing

Stephen Wolfram (52:39.680)

happening in language. You know, when we invent a word for something, it provides kind of a cognitive

Stephen Wolfram (52:45.040)

anchor, a kind of a waypoint that lets us, you know, like a podcast or something. You could be

Stephen Wolfram (52:50.720)

explaining, well, it's a thing which works this way, that way, the other way. But as soon as you

Stephen Wolfram (52:55.120)

have the word podcast and people kind of societally understand it, you start to be able to build on

Stephen Wolfram (53:00.960)

top of that. And so I think that's kind of the story of science actually, too. I mean, science

Stephen Wolfram (53:05.840)

is about building these kind of waypoints where we find this sort of cognitive mechanism for

Stephen Wolfram (53:11.840)

understanding something, then we can build on top of it. You know, we have the idea of, I don't

Stephen Wolfram (53:16.080)

know, differential equations we can build on top of that. We have this idea, that idea. So my hope

Stephen Wolfram (53:21.520)

is that if it is the case that we have to go all the way sort of from the sand to the computer,

Lex Fridman (53:28.160)

and there's no waypoints in between, then we're toast. We won't be able to do that.

Stephen Wolfram (53:33.200)

Well, eventually we might. So if we're as clever apes are good enough at building those abstract

Stephen Wolfram (53:39.200)

abstractions, eventually from sand we'll get to the computer, right? And it just might be a longer

Stephen Wolfram (53:43.760)

journey. The question is whether it is something that you asked, whether our human brains will

Stephen Wolfram (53:49.920)

quote, understand what's going on. And that's a different question because for that, it requires

Stephen Wolfram (53:55.840)

steps from which we can construct a human understandable narrative. And that's something that

Stephen Wolfram (54:03.680)

I think I am somewhat hopeful that that will be possible. Although, you know, as of literally

Stephen Wolfram (54:10.320)

today, if you ask me, I'm confronted with things that I don't understand very well.

Lex Fridman (54:16.400)

So this is a small pattern in a computation trying to understand the rules under which the

Stephen Wolfram (54:21.280)

computation functions. And it's an interesting possibility under which kinds of computations

Lex Fridman (54:28.640)

such a creature can understand itself.

Stephen Wolfram (54:31.600)

My guess is that within, so we didn't talk much about computational irreducibility,

Lex Fridman (54:36.160)

but it's a consequence of this principle of computational equivalence. And it's sort of a

Stephen Wolfram (54:39.920)

core idea that one has to understand, I think, which is question is, you're doing a computation,

Stephen Wolfram (54:45.600)

you can figure out what happens in the computation just by running every step in the computation and

Stephen Wolfram (54:49.840)

seeing what happens. Or you can say, let me jump ahead and figure out, you know, have something

Stephen Wolfram (54:56.320)

smarter that figures out what's going to happen before it actually happens. And a lot of traditional

Stephen Wolfram (55:01.440)

science has been about that act of computational reducibility. It's like, we've got these equations,

Lex Fridman (55:08.720)

and we can just solve them, and we can figure out what's going to happen. We don't have to trace

Stephen Wolfram (55:12.400)

all of those steps, we just jump ahead because we solve these equations.

Stephen Wolfram (55:16.080)

Okay, so one of the things that is a consequence of the principle of computational equivalence is

Stephen Wolfram (55:20.080)

you don't always get to do that. Many, many systems will be computationally irreducible,

Stephen Wolfram (55:25.120)

in the sense that the only way to find out what they do is just follow each step and see what

Stephen Wolfram (55:28.640)

happens. Why is that? Well, if you're saying, well, we, with our brains, we're a lot smarter,

Stephen Wolfram (55:34.720)

we don't have to mess around like the little cellular automaton going through and updating

Stephen Wolfram (55:38.880)

all those cells. We can just use the power of our brains to jump ahead. But if the principle

Stephen Wolfram (55:44.880)

of computational equivalence is right, that's not going to be correct, because it means that

Stephen Wolfram (55:50.480)

there's us doing our computation in our brains, there's a little cellular automaton doing its

Stephen Wolfram (55:55.040)

computation, and the principle of computational equivalence says these two computations are

Stephen Wolfram (55:59.840)

fundamentally equivalent. So that means we don't get to say we're a lot smarter than the cellular

Stephen Wolfram (56:04.560)

automaton and jump ahead, because we're just doing computation that's of the same sophistication as

Stephen Wolfram (56:09.680)

the cellular automaton itself. That's computational reducibility. It's fascinating. And that's a

Stephen Wolfram (56:15.360)

really powerful idea. I think that's both depressing and humbling and so on, that we're all,

Stephen Wolfram (56:22.560)

we and the cellular automaton are the same. But the question we're talking about, the fundamental

Stephen Wolfram (56:26.560)

laws of physics, is kind of the reverse question. You're not predicting what's going to happen. You

Lex Fridman (56:32.400)

have to run the universe for that. But saying, can I understand what rules likely generated me?

Stephen Wolfram (56:38.240)

I understand. But the problem is, to know whether you're right, you have to have some

Stephen Wolfram (56:44.400)

computational reducibility, because we are embedded in the universe. If the only way to know whether

Stephen Wolfram (56:49.120)

we get the universe is just to run the universe, we don't get to do that, because it just ran for

Stephen Wolfram (56:53.840)

14.6 billion years or whatever. And we can't rerun it, so to speak. So we have to hope that

Stephen Wolfram (57:00.080)

there are pockets of computational reducibility sufficient to be able to say, yes, I can recognize

Stephen Wolfram (57:06.240)

those are electrons there. And I think that it's a feature of computational irreducibility. It's

Stephen Wolfram (57:12.720)

sort of a mathematical feature that there are always an infinite collection of pockets of

Stephen Wolfram (57:16.320)

reducibility. The question of whether they land in the right place and whether we can sort of build

Stephen Wolfram (57:20.560)

a theory based on them is unclear. But to this point about whether we as observers in the universe

Stephen Wolfram (57:27.200)

built out of the same stuff as the universe can figure out the universe, so to speak, that relies

Stephen Wolfram (57:33.360)

on these pockets of reducibility. Without the pockets of reducibility, it won't work, can't work.

Lex Fridman (57:39.120)

But I think this question about how observers operate, it's one of the features of science over

Stephen Wolfram (57:45.200)

the last 100 years particularly, has been that every time we get more realistic about observers,

Stephen Wolfram (57:50.960)

we learn a bit more about science. So for example, relativity was all about observers don't get to

Stephen Wolfram (57:56.960)

say what's simultaneous with what. They have to just wait for the light signal to arrive to decide

Stephen Wolfram (58:03.120)

what's simultaneous. Or for example, in thermodynamics, observers don't get to say the

Stephen Wolfram (58:08.880)

position of every single molecule in a gas. They can only see the kind of large scale features,

Lex Fridman (58:14.240)

and that's why the second law of thermodynamics, the law of entropy increase, and so on works.

Stephen Wolfram (58:18.800)

If you could see every individual molecule, you wouldn't conclude something about thermodynamics.

Stephen Wolfram (58:25.520)

You would conclude, oh, these molecules are just all doing these particular things. You wouldn't

Stephen Wolfram (58:28.800)

be able to see this aggregate fact. So I strongly expect that, and in fact, in the theories that I

Stephen Wolfram (58:35.520)

have, that one has to be more realistic about the computation and other aspects of observers

Lex Fridman (58:42.720)

in order to actually make a correspondence between what we experience. In fact,

Stephen Wolfram (58:47.840)

my little team and I have a little theory right now about how quantum mechanics may work, which is

Stephen Wolfram (58:53.040)

a very wonderfully bizarre idea about how the sort of thread of human consciousness

Stephen Wolfram (59:00.320)

relates to what we observe in the universe. But there's several steps to explain what that's

Stephen Wolfram (59:05.760)

about. What do you make of the mess of the observer at the lower level of quantum mechanics,

Stephen Wolfram (59:11.600)

sort of the textbook definition with quantum mechanics kind of says that there's some,

Stephen Wolfram (59:19.360)

there's two worlds. One is the world that actually is, and the other is that's observed.

Lex Fridman (59:27.360)

What do you make sense of that? Well, I think actually the ideas we've recently had might

Stephen Wolfram (59:34.320)

actually give away into this. I don't know yet. I think it's a mess. The fact is,

Stephen Wolfram (59:45.440)

one of the things that's interesting, and when people look at these models that I

Stephen Wolfram (59:50.160)

started talking about 30 years ago now, they say, oh no, that can't possibly be right.

Lex Fridman (59:54.960)

What about quantum mechanics? You say, okay, tell me what is the essence of quantum mechanics? What