Now the next bottleneck is the compiler - which we can model in an LLM! It's only wrong 15% of the time :) But truly, using Cerebras at ~2k tokens/s, with very

Now the next bottleneck is the compiler - which we can model in an LLM! It's only wrong 15% of the time :) But truly, using Cerebras at ~2k tokens/s, with very low latency is like a vision into the future. You start to rework your workflow around things that can happen without onerous manual review - stating the conditions for success, etc. It's rare that I have a problem that maps well to that, but I expect this is where things are headed. Of course the fast models tend to not be the SOTA ones, but if that was the case - high quality and near-instant thinking, that's a game changer that I don't think we're really prepared for. The things that get unlocked with higher-than-reasonable speed become very interesting.