The biggest win for AI dev efficiency is cutting down what gets loaded into context. Semantically matching tasks to the top tools helps a lot.

> The model weights and inference code need to be contained within 25KB of user-space memory

Wouldn’t it be era-appropriate to allow relying on banked memory? You’d still need to hold the inference code, but you could effectively stream(ing page) the weights as you compute on them.

Cool to think this demo would have been possible over fifty years ago. I wonder what someone from 1975 would have said if you had shown this to them back then.

This is super cool! As someone who's worked a little with NES programming and tried out cc65, I'm surprised he didn't just hand write some assembly, he likely couldve saved a lot of space if I had to guess.

This is amazing project! I hope it will result in real miniaturization of AI - for example, edge LLM inside of glasses. That will be awesome.

The 6502 is notoriously unfit for a C compiler, so probably there is room for more performance in the future. :)