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Working with academic communities to build scientific understanding

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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.

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.


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