Can scaling past the data wall enter double descent's interpolation regime?
xidulu · x · 2026-11-06
A user asks: if we're hitting the data wall, why not keep scaling model size and hope to enter double descent's interpolation regime, where test error falls again after the peak?
The attached chart shows the classic curve: test error peaks at the interpolation threshold (1 parameter/data ratio) then declines with further scale. The question drew a dismissive response from OpenAI researcher willdepue, who says the theory "is just not real."
Related event: OpenAI Researcher Debates Data Wall and Double Descent Theory on X(7 posts)→
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