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The techniques they used are general, and especially useful for RL on hard-to-verify-solution-correctness problems.
It now says when it doesn't know something, or didn't figure it out. This is a requisite for training the model successfully on its own output.
The people behind the model are from the multi agent team. For one age to be bale to work with another, the reports from the other agent need to be trustworthy.
Yikes. If they're telling the truth about all this---particularly the "useful for RL on hard-to-verify-solution-correctness problems"---then this is all markedly timeline-shortening. What's the community consensus on how likely this is to be true?
I have no idea what the community consensus is. I doubt they're lying.
For anyone who already had short timelines this couldn't shorten them that much. For instance, 2027 or 2028 is very soon, and https://ai-2027.com/ assumed there would be successful research done along the way. So for me, very little more "yikes" than yesterday.
It does not seem to me like this is the last research breakthrough needed for full fledged agi, either. LLMs are superhuman at no/low context buildup tasks, but haven't solved context management (be that through long context ... (read more)