- Benchmarking is a form of data activation, transforming domain data into measurable tasks for models to be evaluated and trained on.
- Clear, verifiable metrics are essential for model improvement, as seen in coding and math, but complex domains like medicine lack inherent benchmarks.
- Activation starts with measurement: converting health data into scores for models can reveal knowledge gaps and drive improvement, even without model changes.
- Verifiers integrate benchmarking with reinforcement learning, turning scores into rewards and merging measurement with optimization, which amplifies both benefits and risks.