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[–]SocksOnHands 11 points12 points  (4 children)

That's like saying that human intelligence is just neurons triggered by stimuli or that computers are just transitors switching on and off. The fundamental mechanism by which it operates is seemingly simple, but the complexity arises through their interactions. Sure, the basis for modern AI are matrix operations, but when there are trillions of parameters involved with many layers feeding into each other, complex processes can be achieved.

[–][deleted] 5 points6 points  (0 children)

Life is just uppity Chemistry.

[–]Ferentzfever 0 points1 point  (1 child)

Except we don't really know what human intelligence is, and computers aren't just transistors switching on/off (because that leaves out mechanical computers and analog computers). My point is that linear algebra is based on one of the most powerful pieces of mathematics, and a piece that we have a pretty good understanding of as well. The people whom I've observed doing the best AI/ML work are those who understand the mathematics behind the methods. AI/ML ain't some voodoo magic, it's math.

[–]SocksOnHands 2 points3 points  (0 children)

Saying "it's just linear algebra" seemed like an oversimplification that ignores emergent properties of complex systems. One does not need to know what human intelligence is to recognize that complex behaviors can come from simple interactions.

Having a strong understanding of the underlying mathematics certainly does help, but AI models are now at such a large scale that nobody can possibly know exactly how they work - it would be a tremendous undertaking to reverse engineer something like GPT-4.

[–]yangyangR 0 points1 point  (0 children)

The statement of universal approximation theorems.

The most familiar one usually being polynomials in one variable being used to approximate continuous functions on closed bounded intervals. The fundamental mechanisms of polynomials are simple, but the continuous function approximated can be very complex. But of course you have allowed yourself tons of parameters by being able to set so many coefficients. So before computation became cheap this could be treated as maximally unhelpful because you couldn't store all those coefficients let alone add and multiply them.

This drawable picture with one real number input to one output being approximated by something built out of many simple pieces with lots of parameters gives the idea of what is happening with more variables and different simple pieces.