Posts

Improved Inference Efficiency Does Not Mean Training Costs Have Been Rewritten

AI chip 'cost breakthroughs' often conflate two separate accounting ledgers: the investment required to train a model, and the ongoing expense of keeping that trained model in service. The former involves long-cycle cluster computing, data preparation, engineering, and infrastructure; the latter is more directly affected by response latency, energy efficiency, and per-inference service cost. Improvements in inference chip efficiency metrics cannot be taken to imply that the total cost of training frontier models has dropped by the same magnitude.