Just a few weeks after OpenAI released manuscripts with over 700 pages of solutions and progress for 372 major math problems, the company has announced even more discoveries. This time, the discoveries don't just cover math results, but also results for computer science and physics problems. 

For this release, OpenAI has experimented with three different strategies. It has published the math results, so researchers can look them up and make their own efforts to explain them. But for the computer science and physics results, it formed an external group of expert collaborators. OpenAI asked the group working on the computer science results to explain them in their own writeups and materials, while also releasing the AI output to the public. Meanwhile, OpenAI has deferred the release of the physics materials to the group handling them. The company is welcoming feedback "on how to broaden participation and make this process more useful."

OpenAI has added two new manuscripts on GitHub you can access right now. One establishes Sogge's local smoothing for waves in every spatial dimension, which is a conjecture about the behavior of solutions to the wave equation. The other shows proof that the Exponential Time Hypothesis, which is an assumption in computer science that some problems are just too hard to solve quickly, is false. 

As OpenAI notes, ETH is widely believed to be true and has been the basis on hundreds of papers across a wide variety of fields, including databases and computation biology and geometry. If it is indeed false, then we could, in theory, find better algorithms to solve problems in those fields more efficiently. The scientists who proposed ETH are now part of the group OpenAI has asked to examine and explain the results generated by its models.

Finally, the physics results involve proof of interacting quantum field theories containing gauge fields and fermions in four dimensions. The group examining the physics results has yet to publish anything about it, but it has provided an email – YANGMILLS4D[@]gmail.com — for all questions about its efforts. 

The company says it will not seek any academic credit for its models' discoveries. Instead, the people in each group will get credit for the writeups and materials they create. The groups will also be in charge of making sure that the AI-generated results appropriately credit all the researchers, techniques and ideas the company's models drew on.