Post from Mark Chen for those not on X:

  Two things to distinguish:
  Did any human or agent look at user data as part of the Navier Stokes effort? No.
  Do we use user feedback and de-identified data to improve ChatGPT and Codex in a holistic way? Yes. And so does every LLM company.

They don't even know which websites and services their agents are hacking at any given moment. I'm more than a bit skeptical that they know whether an agent looked at the Navier Stokes work.

> Do we use user feedback and de-identified data to improve ChatGPT and Codex in a holistic way? Yes.

This says that they trained on user sessions. The de-identification here I believe refers to removing PII, which doesn't matter here because the issue at hand is the content of the researcher's session where they likely discussed their approach tackling the Navier Stokes problem.

> Did any human or agent look at user data as part of the Navier Stokes effort? No.

If they trained the model on Lavent's chat sessions (PII removed or not), then this statement is meaningless as the model weights already contain that information.Given it's a new yet unreleased internal model, it is likely a 10+ trillion parameters (Astra is rumored to be 10 trillion), so the model can retain a lot more detail/info from training data.

Why is he leading the with the irrelevant part first ?

> And so does every LLM company.

Nope, not for enterprise users.No enterprise customers would use it if all of their internal business plans / trade secrets would end up in the model weights of the next OpenAI model. Imagine your competitor asking chatGPT a question and the model spitting out your business plan. These models can retain very specific fine grained data. I remember there were examples of them reproducing sections of their training data verbatim.

bit unfair. if the second one is allowed an extra statement "And so does every LLM company." so should the first