Larger training datasets expose models to more varied situations and make it possible to examine their reasoning and behavior across those situations.

“And I think maybe what's useful to add is that the benchmark gives a North Star on where some of these things need to be. But to actually train the models to do really well at this benchmark, the private data sets need to be much larger to actually, like, for the model to investigate many different situations and see how it's reasoning through those situations and how it acts in those situation.”