Nobody trying to compete with Google, OpenAI, and Anthropic should be playing the small models / local models game.

Foundation model labs should be building very large reasoning models, then leaving it to the community to distill them down.

You can't scale a small model up, but you can scale a small model down.

I'm convinced the only way we'll have a seat at the table in the future and avoid total runaway takeoff is if there are very large models within 80% of the capabilities of the frontier models. Tiny RTX models do diddly squat to remain competitive.

Build open weights models for running on H200s. I'll spin them up on RunPod or Lambda.