Earlier quoted context omitted.
the most unintuitive part is that from my understanding, individual tokens are routed to different experts. this is hard to comprehend with "experts" as that means two you can have different experts for two sequential tokens right? I think where MoE is misleading is that the experts aren't what we would call "experts" in the normal world but rather they are experts for a specific token . that concept feels difficult…
It's not even per token. The routing happens once per layer, with the same token bouncing between layers. It's more of a performance optimization than anything else, improving memory liquidity. Except it's not an optimization for running the model locally (where you only run a single query at a time, and it would be nice to keep the weights on the disk until they are relevant). It's a performance optimization for lar…
so you mean a "load balancer" for neural nets … well, why don't they call it that then?