Standardizing training compute measurement with quantization and dropout

Determine how training compute metrics used for governance should account for techniques such as quantization and dropout, and propose a standardized definition and measurement methodology.

Background

Training compute is widely used as a risk proxy, but modern training techniques complicate consistent measurement.

Standardizing how compute metrics incorporate quantization, dropout, and other methods is necessary for fair and effective regulation.