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Terence Tao

๐Ÿ‘ค Person
2047 total appearances

Appearances Over Time

Podcast Appearances

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

So it turns out this directed motion doesn't actually work.

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

There was a separate paper by some other authors that actually showed this in three dimensions.

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

So what I needed was to program a delay.

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

So kind of like airlocks.

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

So I needed an equation which would start with a fluid...

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

doing something at one scale, it would push its energy into the next scale, but it would stay there until all the energy from the larger scale got transferred.

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

And only after you pushed all the energy in, then you sort of open the next gate and then you push that in as well.

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

So by doing that, the energy inches forward scale by scale in such a way that it's always localized at one scale at a time.

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

And then it can resist the effects of viscosity because it's not dispersed.

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

So in order to make that happen,

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

yeah, I had to construct a rather complicated non-linearity.

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

Um, and it was basically like, um, you know, like it was constructed like an electronic circuit.

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

So I, I actually thank my wife for this because she was trained as a electrical engineer.

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

Um, and, um, you know, she talked about, um,

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

He had to design circuits and so forth.

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

And if you want a circuit that does a certain thing, like maybe have a light that flashes on and then turns off and then on and then off, you can build it from more primitive components, capacitors and resistors and so forth.

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

And you have to build a diagram.

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

And these diagrams, you can sort of follow it with your eyeballs and say, oh yeah, the current will build up here and then it will stop and then it will do that.

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

So I knew how to build the analog of basic electronic components, like resistors and capacitors and so forth, and I would stack them together in such a way that I would create something that would open one gate, and then there would be a clock, and then once the clock hits a certain threshold, it would close it.

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

It was kind of a Rube Goldberg-type machine, but described mathematically.