fp4

FP4 training research points to the next fight over AI efficiency

Efficiency research is becoming one of the highest-leverage parts of AI progress. Work on FP4 block scaling for stable language-model pretraining points at the pressure to train capable models with less memory, less power, and better hardware utilization.

Why it matters: For the market, efficiency work compounds. Better training formats can lower the cost of future models, improve utilization of new accelerators, and make infrastructure investments stretch further.