descriptive claim
The speaker says that as models improve into mid-training and post-training, the required learning signal is absent from the original data and cannot be recovered by filtering alone.
Beren Millidge · AI researchers debate how close we are to recursive self-improvement · 11 Sept 2026
In their words
The transcript segments this claim was taken from
“and that's quite an automatable process but like as the models get better as we enter mid-training and post-training the signal just like doesn't exist anywhere in the original data we have like no amount of filtering will like get this you know there's no like hidden proof of like the millennium prize problem sitting in common core we can just like”Play from 1:05:39Report a misattribution
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92%confidence the claim was read correctly