The Simons Foundation announced a new set of initiatives to help the mathematics community navigate the rapid rise of artificial intelligence in the field, backed by $15 million in combined funding and resources from the foundation, Anthropic, and OpenAI.

The foundation will manage and award the funding, including through an open call for proposals, to support workshops and initiatives that help researchers evaluate recent AI-assisted results, learn and use new tools, share perspectives, and shape collective standards for how AI is used in mathematical research. For more context on this story, see our ongoing AI industry coverage.

Tools and Compute Beyond Mathematics

Beyond the funding, Anthropic and OpenAI will provide AI tools and computing resources to researchers supported by the Simons Foundation. According to the foundation's announcement, that support extends beyond mathematics to include basic science more broadly — an unusually direct channel between frontier AI labs and working academic researchers.

The arrangement is notable for its structure: rather than the labs setting the agenda, the foundation controls how the money is awarded, and the press material emphasizes that the awards and resources will be community-driven.

Why Mathematics Is the Front Line

Mathematics has become one of the most consequential testing grounds for AI in science. The Simons Foundation was an early backer of machine learning for science, including funding the development of the Lean proof assistant, which has reshaped how mathematicians formalize work and made AI-assisted proofs possible. As AI systems increasingly contribute to mathematical discovery, the community faces a practical problem: how to verify, evaluate, and trust results produced with substantial machine assistance.

That verification problem is central to what the new initiative is funding. Workshops and initiatives aimed at "evaluating recent AI-assisted results" acknowledge that the traditional peer review process was not designed for proofs drafted with, or in some cases substantially produced by, AI systems.

The Foundation's Framing: Community First

Simons Foundation President David Spergel framed the effort as a moment for collective decision-making. "As artificial intelligence rapidly reshapes the research landscape, we want to help the mathematical community come together and forge the best path forward," Spergel said in the announcement. "Now is the time to look at mathematics as a whole — not as a collection of proofs and theorems, but as a collective understanding driven by human curiosity."

Spergel was explicit about who should set the terms of adoption. "The community should be driving discussions of how these tools are evaluated, adopted and used, not any single company or institution," he said. "The goal of the program is to support the mathematics community."

The statement reads as a deliberate contrast to a dynamic familiar across AI adoption: individual institutions negotiating separate deals with model providers, with norms set by whichever lab or university moves first. By routing the funding through an open call and emphasizing collective standards, the foundation is attempting to establish a coordination point for a discipline whose output — proofs — is unusually verifiable, and therefore unusually exposed to AI-assisted shortcuts.

A Model for Other Fields

The initiative may serve as a template beyond mathematics. Basic science fields face the same underlying question — how to absorb AI tools without ceding standards to the vendors of those tools — and the Simons Foundation's structure, in which a neutral philanthropy manages resources donated by competing AI companies, is one of the first attempts at an answer.

The foundation's history gave it credibility to play that role: beyond its early funding of the Lean proof assistant, it has convened workshops, lectures, and collaborations exploring AI's role in mathematics. The new $15 million commitment formalizes that convening power into a funded program at precisely the moment AI-assisted results are arriving faster than the community's norms can absorb them.

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