Jakub Pachocki is Chief Scientist at OpenAI. He outlines OpenAI's strategic direction toward automating scientific research and evaluating AI models on economically impactful tasks.
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Pachocki: Standard AI evaluation benchmarks are close to saturation
“One thing is that indeed for like these e-files that we've been using for the last few years, they're indeed pretty close to saturated.”
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Pachocki: AI models will soon conquer the hardest math and programming problems
“If you look at things like Well, I guess the IMO problem six, or maybe some very hardest programming competitions problems. Like, I think there's still a little bit of headway to go for the models, but I wouldn't expect that to last very long.”
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Pachocki: AI progress will remain compute-constrained rather than data-constrained
“I haven't really bought that much into the, like, will be data constraint claim. And yeah, I don't expect that to change.”
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Pachocki: AI progress over the next year will dwarf current gains
“But I expect that well, now as we're seeing you know, these models like actually able to automate, well, yes, like we're saying solving contest problems over, over longer time horizons. I expect that that is, well, that's, that, that was quite small compared t…”
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Pachocki: Current OpenAI models can perform one to five hours of reasoning
“And so now, as we kind of, like, get to a level of near mastery of this high school competitions, let's say, I would say, like, we get to, like, maybe on, on the order of one to five hours, Of reasoning.”
Insight
Pachocki: Long-horizon AI research blurs verifiable and open-ended domains
“I think if you actually truly want to extend to research and, you know, finding, discovering ideas that, that meaningfully advanced technology on the, on, you know, the scale of like months and years, like I think the, these questions like stop being so differ…”