It’s sufficiently vague that I wouldn’t read too much into it, especially from Altman. For example, there’s little security risk posed by pretraining/midtraining, so I assume that’s continuing. They could have paused training on the specific model which broke out of the sandbox, but training on other systems is ongoing. They could have patched the sandbox vulnerabilities they detected and then resumed training, etc.
A similar example of such vagueness was the promise by Altman to ‘[dedicate] 20% of the compute we’ve secured to date to this effort [of the Superalignment team]’. Later reporting shows what happened:
It [Superalignment] was a task so important that the company said in its announcement that it would commit “20% of the compute we’ve secured to date over the next four years” to the effort.
But a half dozen sources familiar with the Superalignment team’s work said that the group was never allocated this compute. Instead, it received far less in the company’s regular compute allocation budget, which is reassessed quarterly.
One source familiar with the Superalignment team’s work said that there were never any clear metrics around exactly how the 20% amount was to be calculated, leaving it subject to wide interpretation. For instance, the source said the team was never told whether the promise meant “20% each year for four years” or “5% a year for four years” or some variable amount that could wind up being “1% or 2% for the first three years, and then the bulk of the commitment in the fourth year.” In any case, all the sources Fortune spoke to for this story confirmed that the Superalignment team was never given anything close to 20% of OpenAI’s secured compute as of July 2023.
OpenAI researchers can also make requests for what is known as “flex” compute—access to additional GPU capacity beyond what has been budgeted—to deal with new projects between the quarterly budgeting meetings. But flex requests from the Superalignment team were routinely rejected by higher ups, these sources said.
It’s sufficiently vague that I wouldn’t read too much into it, especially from Altman. For example, there’s little security risk posed by pretraining/midtraining, so I assume that’s continuing. They could have paused training on the specific model which broke out of the sandbox, but training on other systems is ongoing. They could have patched the sandbox vulnerabilities they detected and then resumed training, etc.
A similar example of such vagueness was the promise by Altman to ‘[dedicate] 20% of the compute we’ve secured to date to this effort [of the Superalignment team]’. Later reporting shows what happened: