Yes. Zero backpropagation. Zero reinforcement learning.

I downloaded the fly's connectome, filtered it down to the motor pathways, and built an artificial retina so it can see the world through a car’s dashcam (just 900 pixels total, black and white!).

The result? It uses just 1,555 FLOPs per frame. Despite the circuit having zero concept of a “car” or a “road” to begin with, it seems to (very primitively) keep a lane, turn, and dodge stuff it’s never explicitly seen before.

Code + writeup + demos at the link (addresses the limitations too, of course!): siddaarth.com/fly-by-wire

Really curious to hear your thoughts and learn what you would have done differently.