Working with academic communities to build scientific understanding

We are announcing three new discoveries in mathematics, computer science, and physics about harmonic analysis, complexity theory, and quantum field theory.Our release process continues to evolve in response to feedback from the associated academic communities. In our view, these manuscripts are best understood as a form of raw research data. To convert this raw research data into scientific understanding, in this release we are experimenting with a new approach. We reached out to external experts and asked them to act as shepherds, organizing groups to understand the new results. They advised three different release strategies:For the math result, release the AI output, leaving researchers free to organize their own efforts to explain the result.For the computer science result, form an external group of collaborators to explain the result, while making the AI output publicly available for anyone to examine and build on.For the physics result, form an external group of collaborators and defer to them on the release of materials.We do not yet know which of these three approaches will be most useful, and we welcome feedback on what works and what we can improve.The external collaborations will follow four principles:Transparency. We are transparent about the existence of our collaborations. Participants will not be asked to sign nondisclosure agreements and will be free to discuss the work, share intermediate products, and publish their conclusions.No Academic Credit. We do not seek academic credit for the discoveries produced by our internal models. Inviting a researcher to help steward a collaboration also does not imply that they or their working group made the original discovery.Recognition. This group should receive recognition for the understanding they develop, the writeups they author, and the other materials they create. The group will also help ensure that the work appropriately credits researchers, techniques, and ideas that it draws on.Independence. Participation is voluntary and unpaid. Working-group members participate independently, and their conclusions are their own. They do not speak on behalf of OpenAI, and OpenAI does not speak on their behalf.We will turn over materials and artifacts related to these results to the collaborations. For the computer science collaboration, the group has decided to make the natural language proof and Lean formalization public immediately, and we are publishing them directly to our GitHub repository. For the …