So how should we be thinking about it and what does that mean in terms of where we expect to see it applied in the next handful of years?

Well, I mean, places where kind of human judgment was useful, there are a whole bunch of those places where you can kind of fill in some AI judgment.

It'll be different, but it'll be faster.

And lots of things, that's one kind of place.

Another kind of place is just by the fact that modern AI systems have ingested a lot of kind of the textual knowledge of the world and other kinds of knowledge of the world it's useful for kind of pulling together sort of different threads from different places.

I mean, there's all sorts of success.

You know, people say, oh, it proved this math theorem.

But what are your principles that you've learned over the years that have enabled you to be more successful at running a company that's effective at that?

I, uh- Let's get you a basket.

Observers who are embedded in that thing, how do we perceive the thing? How do we perceive what's going on? And so you might say, "Well, there's-- what on earth could we possibly say about that?" The thing that is important is we know certain things about the way we are as observers.

So, for example, we know that we can only do a bounded amount of computation.

We can't go and trace the sort of irreducible computation that happens in the history of the universe.

We are, we're limited.

We have finite minds.

We have finite brains that just can figure out a limited amount of computation.

[laughs]

Yeah.

You've got to go visit the experiment.

You've got to go ask about all the experimental data methods, and so on.

It's, it's no good to just say, "Oh, you got this answer." Um, that's-- You have to be involved, so to speak.

But I think, you know, I think for me, an important thing is to understand when I understand and to be very, uh, brutal with myself, so to speak, in not letting myself get away with not really understanding.

So, for example, when I write things, there are times when I'm like, "Oh, I've got-- I'm just so bored with writing this particular thing.

I'm gonna speed this up.

Yeah.

With that very question about, uh, the limitations of science.

Right.

So I mean, the- there's kind of in the development of science You know, 1600s is a big, big period when people realized you could apply mathematics to understand the natural world.

You know, Newton's mathematical principles of natural philosophy was, uh, sort of a surprise at the time.

You could use this idea of mathematics, you could predict things about the natural world.

People got used to the idea that science can predict things, that by using methods typically from mathematics, you could say, "We observe things, we now can predict what's gonna happen in, uh, in the motion of planets or the development of a pandemic or other kinds of things." You could...

That science would give one ways to predict things.

On the one hand, what you think it can and cannot in principle do, and on the other hand, what you think the risks, uh, or dangers or possibilities are for, for, for human beings.

Visit a Sleep Number store near you or learn more at sleepnumber.com. [upbeat music] [gentle music] Chapter 8: Do We Still Live in a Scientific Culture? Stephen Wolfram, a computational scientist and entrepreneur, studied physics at Caltech and stayed friendly with Richard Feynman until Feynman's death.

Near the end of his life, he was like, "Well, now I'm gonna experiment with all kinds of drugs because I'm dying anyway, more or less." I think he was a little embarrassed about that.

In the environment of the time, these were illegal drugs and so on.

I think he viewed himself as a think-for-yourself but nevertheless law-abiding citizen.

I don't think he felt that he was having brilliant insights rushing in because he was in some altered state.

One of the things he said to me was, "If you want to do creative science, peace of mind is an essential feature."

... very small machines, okay?

There wasn't a field called nanotechnology when Dick Feynman was thinking about nanotechnology.

Where do your ideas come from? And when you have an idea, how do you know whether it's promising? And, and maybe even how has the way you think and had ideas changed through your lifetime?

Yeah, I mean, I, I think that...

Well, what can I say? I, I-- My general approach is to try and understand the foundation of things, to try and sort of get to the essence of things.

That seems to be something that I am prepared to fearlessly try to do, and that's a consequence in part of the fact that I've done okay at doing that.

And so I've developed the confidence that that's a thing that's possible to do.

I mean, when you see some field and it's like there's, you know, 100,000 academic papers written about some particular thing, and there's, you know, there's endless detail, and people have assumed the foundations for, for, uh, 200 years or whatever.

It-- At the beginning, that seems just completely daunting.

Yeah

No, that's not something that's going to happen."

I mean, look, he was disdainful of all of these honorific types of things.

I'm Stephen Wolfram, and I do science and technology.

He was...

I mean, I would probably go further than him and say any field for which there is a prize that's defined is a field that already has had its best days behind it.

It's a field that barely has a name that's going to have the most fertile moment.

I happened to get one of these MacArthur awards in the very first batch of those things.

place.Stephen Wolfram

I don't understand how it subtracts.

Oh, I think he had what one might call childlike curiosity, which I think most children have.

The question is, do they lose it before they get to adulthood? And I think that he was a strong enough willed person who wanted to think in his own way for himself, that he kept that childlike curiosity.

Okay, well, let's see.

I'm Stephen Wolfram, and I do science and technology, and I've done that for many years.

I happened to organize the theoretical physics seminars at Caltech for a while and would invite all sorts of people, and Feynman would come, and he would try and have this competition with me for who could find the fatal flaw first, which was, a- actually, in the end, there was some terrible moments there where [laughs] it was an embarrassing thing, although some interesting science got done as a result.

I think Dick Feynman was...

First, can you please explain rullial particles and what those are in the context of the communication that we are engaging with and so forth? But also, are there more efficient ways, particulate forms of rullial particles that have massless properties that travel at some ultimate speed limit? Does C apply to thinking?

That's a good and interesting question and complicated.

So first thing to say is I think our perception of the universe critically depends on the fact that we're not massless.

In other words, if we were photons, massless particles, time would not elapse for us.

And our perception of the photons that you collect... cruelly collect in your detector, those photons, the last thing they knew was when they were emitted at recombination time, 100,000 years after the beginning of the universe.

And the next thing they know is splat.

They ran into Brian's detector of those photons.

What would you – given what you just said about surprise and the experiments, if you could – you know, forced to really add to do something or rent out one very dense portion of it to solve one physical problem, one problem in math or physics, what would be the problem that you'd most like to direct the computational firepower, the biggest computational firepower in the universe, perhaps the whole universe? What would you direct it to? What is the most important problem to you right now? Well,