> Some proposals to regulate and pace AI development rely on monitoring hardware and how it is used. For example, a provider might be required to devote its hardware to inference rather than to training a powerful new model. The provider might try to cheat by serving cheaper models or using compute in an unexpected way, freeing up resources for training. How can a regulator reliably ensure that the hardware is used for inference?

Is this even a real problem? Forcing a company to only do inference?