Tracking State-of-the-Art AI Models and Performance is an open-source dataset documenting AI advancements from the 1950s to today. It includes model details, organizations, compute requirements, and benchmarks. Researchers and developers can analyze trends, compare models, and contribute updates. The dataset is open for collaboration $ fostering AI

Boundary-discovery and anti-self-deception framework for AI efficiency research. Produces falsifiable, condition-specific verdicts. First validated result: a hard failure boundary for token pruning.