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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 this, in principle, would create a blur for the actual Navier-Stokes.

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

And this is what I managed to accomplish for this average Navier-Stokes.

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

So it provided this sort of roadmap to solve the problem.

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

Now, this is...

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

a pipe dream because there are so many things that are missing for this to actually be a reality.

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

So I can't create these basic logic gates.

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

I don't have these special configurations of water.

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

I mean, there's candidates that include vortex rings that might possibly work, but also, you know, analog computing is really nasty compared to digital computing.

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

I mean, because there's always errors.

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

You have to do a lot of error correction.

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

along the way.

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

I don't know how to completely power down the big machine so that it doesn't interfere with the running of the smaller machine.

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

But everything in principle can happen.

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

It doesn't contradict any of the laws of physics.

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

So it's sort of evidence that this thing is possible.

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

There are other groups who are

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

now pursuing ways to make Navisworks blow up, which are nowhere near as ridiculously complicated as this.

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

They actually are pursuing much closer to the direct self-similar model, which can, it doesn't quite work as is, but there could be some simpler scheme than what I just described to make this work.

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

I mean, that's a big leap.

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

So there's precedent.