Menu
Sign In Search Podcasts Libraries Charts People & Topics Add Podcast API Blog Pricing

Terence Tao

πŸ‘€ Speaker
3220 total appearances

Appearances Over Time

Podcast Appearances

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

So in partial differential equations, often these equations are like a tug of war between different forces.

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

So in Navier-Stokes, there's the dissipation force coming from viscosity, and it's very well understood.

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

It's linear.

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

It calms things down.

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

If viscosity was all there was, then nothing bad would ever happen.

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

But there's also transport, that energy in one location of space can get transported because the fluid is in motion to other locations.

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

And that's a nonlinear effect, and that causes all the problems.

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

So there are these two competing terms in the Navier-Stokes equation, the dissipation term and the transport term.

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

If the dissipation term dominates, if it's large, then basically you get regularity.

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

And if the transport term dominates, then we don't know what's going on.

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

It's a very nonlinear situation.

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

It's unpredictable.

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

It's turbulent.

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

So sometimes these forces are in balance at small scales, but not in balance at large scales or vice versa.

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

So Navier-Stokes is what's called supercritical.

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

So at smaller and smaller scales,

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

the transport terms are much stronger than the viscosity terms.

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

So the viscosity terms are the things that calm things down.

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

And so this is why the problem is hard.

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

In two dimensions, so the Soviet mathematician Ladislav Skaya, she, in the 60s, showed in two dimensions there was no blow-up.