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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

So it's a little bit more efficient than a rotation.

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

And so for a while, people thought that was the most efficient way to turn things around.

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

But Bezekovic showed that, in fact, you could actually turn the needle around using as little area as you wanted.

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

So 0.001, there was some really fancy multi back and forth U-turn thing that you could do.

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

that you could turn a needle around.

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

And in so doing, it would pass through every intermediate direction.

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

Is this in the two-dimensional plane?

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

This is in the two-dimensional plane.

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

So we understand everything in two dimensions.

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

So the next question is what happens in three dimensions.

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

So suppose the Hubble Space Telescope is a tube in space, and you want to observe every single star in the universe.

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

So you want to rotate the telescope to reach every single direction.

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

And his unrealistic part, suppose that space is at a premium, which it totally is not.

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

You want to occupy as little volume as possible in order to rotate your needle around in order to see every single star in the sky.

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

How small a volume do you need to do that?

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

And so you can modify it based on Copic's construction.

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

And so if your telescope has zero thickness, then you can use as little volume as you need.

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

That's a simple modification of the two-dimensional construction.

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

But the question is that if your telescope is not zero thickness, but just very, very thin, some thickness delta, what is the minimum volume needed to be able to see every single direction as a function of delta?

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

So as delta gets smaller, as your needle gets thinner, the volume should go down, but how fast does it go down?