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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

And there could be one outlier choice of a special number that you stick in that shoots off to infinity while all other numbers crash to earth, crash to one.

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

In fact, there's some mathematicians, Alex Kontorovich, for instance, who've proposed that actually these Caldatz iterations are like these similar automata.

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

If you look at what happened in binary, they do actually look a little bit like

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

like these Game of Life-type patterns.

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

And in an analogy to how the Game of Life can create these massive self-applicating objects and so forth, possibly you could create some sort of heavier-than-air flying machine, a number which is actually encoding this machine, whose job it is to encode, is to create a version of itself which is larger.

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

heavier-than-air machine encoded in a number that flies forever.

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

So Conway, in fact, worked on this problem as well.

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

Oh, wow.

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

So Conway, so similar, in fact, that was one of my inspirations for the Navi Stokes project, that Conway studied generalizations of the collapse problem where instead of

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

multiplying by three and adding one or dividing by two, you have more complicated branching rules.

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

But instead of having two cases, maybe you have 17 cases and then you go up and down.

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

And he showed that once your iteration gets complicated enough, you can actually encode Turing machines and you can actually make these problems undecidable and do things like this.

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

In fact, he invented a programming language for these kind of fractional linear transformations.

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

He called it FactRat as a play on FortRat.

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

And he showed that you can program... It was too incomplete.

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

You could...

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

You could make a program that if your number you insert in was encoded as a prime, it would sink to zero.

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

It would go down, otherwise it would go up, and things like that.

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

So the general class of problems is really as complicated as all the mathematics.

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

Yeah, if you want to do it, not statistically, but you really want 100% of all inputs for the Earth.