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Terence Tao

👤 Person
2047 total appearances

Appearances Over Time

Podcast Appearances

Lex Fridman Podcast
#472 – Terence Tao: Hardest Problems in Mathematics, Physics & the Future of AI

And the conjecture was that it goes down very, very slowly, like logarithmicly, roughly speaking.

Lex Fridman Podcast
#472 – Terence Tao: Hardest Problems in Mathematics, Physics & the Future of AI

And that was proved after a lot of work.

Lex Fridman Podcast
#472 – Terence Tao: Hardest Problems in Mathematics, Physics & the Future of AI

So this seems like a puzzle.

Lex Fridman Podcast
#472 – Terence Tao: Hardest Problems in Mathematics, Physics & the Future of AI

Why is it interesting?

Lex Fridman Podcast
#472 – Terence Tao: Hardest Problems in Mathematics, Physics & the Future of AI

So it turns out to be surprisingly connected to a lot of problems in partial differential equations, in number theory, in geometry.

Lex Fridman Podcast
#472 – Terence Tao: Hardest Problems in Mathematics, Physics & the Future of AI

For example, in wave propagation, you splash some water around, you create water waves and they travel in various directions.

Lex Fridman Podcast
#472 – Terence Tao: Hardest Problems in Mathematics, Physics & the Future of AI

But waves exhibit both particle and wave type behavior.

Lex Fridman Podcast
#472 – Terence Tao: Hardest Problems in Mathematics, Physics & the Future of AI

So you can have what's called a wave packet, which is like a very localized wave that is localized in space and moving a certain direction in time.

Lex Fridman Podcast
#472 – Terence Tao: Hardest Problems in Mathematics, Physics & the Future of AI

And so if you plot it in both space and time, it occupies a region which looks like a tube.

Lex Fridman Podcast
#472 – Terence Tao: Hardest Problems in Mathematics, Physics & the Future of AI

And so what can happen is that you can have a wave which initially is very dispersed, but it all focuses at a single point later in time.

Lex Fridman Podcast
#472 – Terence Tao: Hardest Problems in Mathematics, Physics & the Future of AI

Like you can imagine dropping a pebble into a pond and it will spread out.

Lex Fridman Podcast
#472 – Terence Tao: Hardest Problems in Mathematics, Physics & the Future of AI

But then if you time reverse that scenario, and the equations of wave motion are time reversible,

Lex Fridman Podcast
#472 – Terence Tao: Hardest Problems in Mathematics, Physics & the Future of AI

You can imagine ripples that are converging to a single point, and then a big splash occurs, maybe even a singularity.

Lex Fridman Podcast
#472 – Terence Tao: Hardest Problems in Mathematics, Physics & the Future of AI

It's possible to do that, and geometrically what's going on is that there's always light rays.

Lex Fridman Podcast
#472 – Terence Tao: Hardest Problems in Mathematics, Physics & the Future of AI

If this wave represents light, for example, you can imagine this wave as a superposition of photons, all traveling at the speed of light.

Lex Fridman Podcast
#472 – Terence Tao: Hardest Problems in Mathematics, Physics & the Future of AI

They all travel on these light rays, and they're all focusing at this one point.

Lex Fridman Podcast
#472 – Terence Tao: Hardest Problems in Mathematics, Physics & the Future of AI

You can have a very dispersed wave focused into

Lex Fridman Podcast
#472 – Terence Tao: Hardest Problems in Mathematics, Physics & the Future of AI

a very concentrated wave at one point in space and time, but then it defocuses again and it separates.

Lex Fridman Podcast
#472 – Terence Tao: Hardest Problems in Mathematics, Physics & the Future of AI

But potentially, if the conjecture had a negative solution, so what that meant is that there's a very efficient way to pack tubes pointing in different directions into a very, very narrow region of very narrow volume, then you would also be able to create waves that start out, there'll be some arrangement of waves that start out very, very dispersed,

Lex Fridman Podcast
#472 – Terence Tao: Hardest Problems in Mathematics, Physics & the Future of AI

but they would concentrate not just at a single point, but there'll be a lot of concentrations in space and time.