[DantesKite]

I'd be curious to see what the upper limit of this is. Could it for example, be trained to optimize video games? I think of the magic fast inverse square root optimization in Quake that dramatically reduced the cost of calculating angles.[1]

I bet there's all sorts of non-intuitive optimizations one could do in modern video games that are otherwise too tedious for most programmers to perform.

[1] https://en.wikipedia.org/wiki/Fast_inverse_square_root

[Cthulhu_]

> Could it for example, be trained to optimize video games?

In a sense, it already is; nVidia's DLSS [0] and AMD's FidelityFX are AI-driven technologies that allow games to be rendered at a faster, lower resolution, then using AI / ML technology to upscale it to HD or 4K resolutions without upscaling artifacts; the technology fills in the blanks based on a lower resolution frame. Apparently applying the AI upscaling is faster than rendering at full resolution.

[0] https://www.nvidia.com/nl-nl/geforce/technologies/dlss/

[1] https://www.amd.com/en/technologies/fidelityfx-super-resolut...

[avaer]

It can't do that from scratch yet; these kinds of optimizations require nontrivial mathematical understanding and informed judgement of trade-offs.

But it is capable of knowing your function is an inverse square root and inserting a known optimized version.