Scientific Foundation Models
Large-scale AI models trained on extensive scientific datasets to provide a robust basis for various scientific applications.
How the laws define this
Both provisions from Executive Order 14363 — Launching the Genesis Mission agree that scientific foundation models are artificial intelligence models trained on vast scientific datasets to support hypothesis generation and testing for the Genesis Mission. They establish that these advanced tools are built to drive scientific progress by serving as a core layer for research activities. The principal divergence lies in the specified origin of the training data and the scope of automated functions. One definition under Executive Order 14363 — Launching the Genesis Mission broadly describes the training inputs as vast collections of scientific data meant for diverse applications, predictive modeling, and simulation across different domains. Conversely, the other definition explicitly requires the training source to consist of vast Federal scientific datasets, while specifically highlighting the use of AI agents to automate research workflows and accelerate advancement within the Genesis Mission.
Synthesised from the 2 statutory definitions below. Each one is quoted in full, with its source.
Definitions (2)
Scientific foundation models are advanced artificial intelligence models developed by the Genesis Mission. They are trained on vast collections of scientific data to serve as a fundamental layer for diverse scientific applications, enabling predictive modeling, simulation, and hypothesis generation across different domains.
AI models trained on vast Federal scientific datasets, intended to accelerate scientific advancement and enable AI agents to test hypotheses and automate research workflows within the Genesis Mission.