OpenAI Announces Three Major Science Discoveries with Academics
Following a mass release of mathematics manuscripts last month, OpenAI has announced three new major discoveries in math, computer science, and physics using a new approach involving academic experts.
Radwan AbdulhadiEditor and technology writer
New Scientific Discoveries Across Fields
Less than a month after its mass release of hundreds of manuscripts that it said contained solutions to long-standing mathematics questions, OpenAI has announced three more “major” discoveries in math, computer science, and physics. The latest announcements detail breakthroughs produced by the company's models, including a math output that addresses local smoothing for the Euclidean wave equation.
According to the company, the math model produced a proof of the local smoothing conjecture in every dimension, thereby resolving the Kakeya conjecture and Stein's restriction conjecture in all dimensions. This follows recent academic milestones in the field, such as when NYU professor Hong Wang was awarded a prestigious Fields Medal by the International Mathematical Union for resolving the Kakeya conjecture in three dimensions.
Refuting the Exponential Time Hypothesis
In computer science, OpenAI's models produced a breakthrough stating that the Exponential Time Hypothesis (ETH), which has been widely believed to be true, is actually false. The resulting paper details a deterministic algorithm that exactly counts satisfying assignments of fixed-width CNF formulas in subexponential time and polynomial space, with the case of 3-SAT refuting the hypothesis.
An independent working group of computer scientists led by Russell Impagliazzo, Ramamohan Paturi—who were part of the group that originally proposed the hypothesis in 1999—and MIT professor Ryan Williams will examine and explain the proof. At the group's request, OpenAI made the materials public immediately, and OpenAI results added to GitHub today provide the write-up and Lean proof.
Physics Discoveries and External Shepherds
The physics information has not been released in full by OpenAI, but is described as a mathematically rigorous existence proof of certain interacting quantum field theories containing gauge fields and fermions in four dimensions. This includes Quantum Chromodynamics and a unified completion of the Standard Model of particle physics.
What is different about this announcement is the choice to have external experts that OpenAI describes as shepherds guiding the results in computer science and physics. For the physics work, David Gross will lead a group including Michael Douglas, Arthur Jaffe, Igor Klebanov, and Nikita Nekrasov.
Academic Feedback and Advisory Panel Guidance
While OpenAI says it is taking new advice from scientists on how to release results, the approach has drawn scrutiny. The AGMAI panel of math advisers put together by OpenAI issued a statement recommending that AI companies do not adopt practices of designating certain people to receive outputs first. The panel cited issues such as unequal access, borrowed reputation, and biased selection.
Instead, the advisory panel recommended that AI labs release outputs on scholarly repositories with Lean-formalized proofs, information on how problems were chosen, and funding for researchers working to understand the results. Previous drops have also prompted widespread reactions across academia, with some observers calling the complex releases 'Pure insanity' and noting that mathematicians will need years to make sense of them.
Open Letter to the Scientific Community
Alongside the discoveries, OpenAI released an open letter to the community asking for input on how to examine claims and set norms for dealing with AI-generated breakthroughs. The company welcomed discussion on governing early access, disclosing conflicts of interest, recognizing credit for checking and extending work, and supporting students and researchers as methods change.
Discussions surrounding these developments continue to unfold amidst all the drama around AI's takeover of mathematics, as researchers weigh the implications of automated proof generation on traditional academic workflows and standards.
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- The VergeOpenAI announces three big science discoveries and a new way to work with academics
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