Thomas, welcome.
If we could just start, what is the link—it seems to be an ever
increasing link—between business and mathematical sciences?
So business looks at, is driven by innovation, right?
So what is innovation?
It's technology, and technology seems to be speeding up, right.
We know that's happening, and if we can understand how technology
works, if we can understand the sort of mathematical structure
behind it, then we can understand why it's speeding up,
speed it up more and and influence the direction in which
it grows.
Tell me more, if you would, about the work that you're doing
at the London Institute for Mathematical Sciences and how
that relates to business.
So we work in a bunch of things ranging from string theory,
which is a theory of everything, to artificial intelligence of
new discoveries, but also something called the theory of
human enterprise.
In particular, we've looked at the mathematical structure of
innovation, of how technologies work. And a technology,
and the simplest definition of a technology comes from Brian
Arthur at the Santa Fe Institute.
Technology is a combination of more primitive technologies,
which harnesses the scientific principle. And then when that
technology, it becomes useful and becomes recognized, it
becomes a building block for
even, you know, more advanced technologies like a touchscreen.
A touchscreen is made as a complex technology, but
eventually people think, oh, I've got a touchscreen, that's
one of my building blocks.
I got this, overall combined those.
So technology has this recursive structure, you know. Primitive
ones make more complex ones, just make yet more complex ones.
And it's that recursive structure that we can understand
mathematically.
Fantastic.
Tell me if you would, about your collaboration with BCG Henderson
Institute, particularly around innovation.
So that came about several years ago when I got an e-mail from
someone called Martin Reeves.
He said, look, is innovation like evolution or is it
something different on its own?
And we met and started thinking about that, started working on
it and we found, well, actually innovation and evolution are
different things.
Innovation doesn't imitate biology, how life advances.
It has its own sort of mathematical structure.
And we dug into that. And it's quite beautiful, the mathematics
behind it.
And in fact, we found that you can, understand what the factors
are that speed it up and you can look to different sectors and
influence how different sectors grow relative to others.
How is that—and bear with me in layman's terms here—how is that
applicable in the real world, what you've been discovering?
So you know a lot of people think that the future happens to
us. But Peter Thiel said to a recent debate, he says you know,
but you and I are creating it right now. And you know the
direction that technology takes isn't just something you know,
like we're watching the movie.
We're actors in the movie.
So, you know, the technologies that we push, you know the way
that we think of how, of the modules that make up, the ones
that we promote, have a profound effect on the future of
technology.
So, you know, small choices we make now get amplified as
technologies, you know, give birth to new technologies.
You've also been looking at AI assisted discoveries.
Tell me about, tell me about that.
So a lot of people.
So first of all, I'm a great AI skeptic.
So in general, I think AI is like Explain? Well, I think, you
know, what's amazing about AI is not how much it's done, it's how
little it's done, right.
I mean, basically AI right now is automated curve fitting.
But here's where I think it's going to make its first steps in
the creative world.
So this is something a lot of people think about.
Well, AI is not creative.
It's not really creative, right?
And maybe it can, you know, construct silly poems.
But I think, counterintuitively, the first time we're going to
see creative AI is in mathematics and theoretical
physics.
Now you may think that's nuts, but there are two reasons for
that.
Well, the the main reason is that and this sounds, this is a
mad thing, that in mathematics there are no coincidences.
And I mean that there are no false positives, there are no
false negatives.
Whereas in, you know, in ordinary life there are all
sorts of false positives like. You know, is this, you know, is
this gene connected to that disease or is that just a fluke.
So there are no flukes in in theoretical physics and
mathematics.
So AI, which is really good at detecting patterns, when it
detects those patterns, those patterns have meaning.
And that's creative.
Well, I mean, some people would say pure mathematics is it's the
height of human creativity, right?
Like, you know, how do we form a new conjecture?
You know, how do you, how did Gauss prove the density of the
prime numbers, right?
Well, there's a lot of new properties of the mathematical
world and the physics world, right?
I mean, physics is broken.
We're missing big parts of it.
Who's going to find those new things?
Where are those new conjectures, those new ideas going to come
from?
And an AI can guide us, right?
It's not, it can't do it for us, but it can guide us in the right
direction.
So we sometimes call this AI assisted discovery and this is
something that the Bruce Henderson Institute has
supported.
We've had you know—actually, our group in London is is leading
the world in AI assisted conjecture formation.
Thomas, absolute pleasure.
Thank you so much.
Thank you.