Researcher's tinfoil theory: bad ML papers may slow AI self-improvement below math/code pace
RylanSchaeffer · x · 2026-09-28
Rylan Schaeffer offers a new "tinfoil hat" theory for why recursive self-improvement (RSI) might arrive slower than math and code benchmarks suggest:
- Most math on Arxiv is probably mostly correct
- Most code on GitHub is probably mostly correct
- Most AI/ML research on Arxiv is probably mostly incorrect
The implication: an AI automating AI research would rely on a corpus far noisier than math or code, dragging down the pace of self-improvement.
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