This is neat. At least I'm still better than the models at pac-man.
Also love the idea of a shared pool for users to try things out. I was considering more of a crowdfunded approach for one of my toy projects, something like... Giving it $10 in credits to begin and somehow allowing users to feed a buck in if they wanted.
Running cloud API inference for Pac-Man is peak modern software engineering. A 2 MB local ONNX model on a CPU core beats network round-trip jitter every time.
Also love the idea of a shared pool for users to try things out. I was considering more of a crowdfunded approach for one of my toy projects, something like... Giving it $10 in credits to begin and somehow allowing users to feed a buck in if they wanted.
I trained some to do some interesting things, including playing doom: https://github.com/nicobrenner/jeffy
I’ll try training one for this benchmark, seems like fun
I wish the controls were a little easier on mobile.
What even is this reality.