Funding opportunity
Mathematical Foundations of Artificial Intelligence
Offered by National Science Foundation · Federal Agency
Engineering & Technology
About this opportunity
The NSF's "Mathematical Foundations of Artificial Intelligence" grant addresses critical foundational gaps in the
Previous awards & what wins
Successfully funded projects typically propose rigorous mathematical and theoretical frameworks to address fundamental challenges in advanced AI models, particularly Generative AI and Large Language Models. They aim to elucidate underlying mechanisms, enhance capabilities like generalization and reasoning, and often consider practical implications such as AI safety and efficiency. These projects frame their research as critical for advancing the field beyond brute-force scaling and maintaining global leadership in AI.
Mathematical Foundations of Generative AIUnderstanding and Optimizing Language Models through DataGeneralization and Theoretical Elucidation of Diffusion and Flow-Based ModelsOvercoming Fundamental Limits of Large-Scale AI and Brute-Force ScalingAdvancing AI Capabilities for Complex Reasoning and Novel InferenceAI Safety, Privacy, and Responsible Development
- Proposals should deeply explore the mathematical and theoretical underpinnings of cutting-edge AI, especially Generative AI and Large Language Models, rather than just empirical applications.
- Successful projects aim to resolve fundamental unknowns, such as the mechanisms behind model effectiveness or the role of data, often by developing novel theoretical tools or geometric perspectives.
- Framing the research within the context of overcoming current limitations (e.g., brute-force scaling, lack of generalization in novel situations) and contributing to AI safety or national competitiveness enhances competitiveness.
- Collaborative efforts between institutions on shared foundational problems are a recurring theme among funded projects, suggesting a preference for broader impact and resource sharing.