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Yann LeCun's tiny 109M model aligns with vision better than 72B LLMs

Summary by Startup Fortune
The authors argue the gap comes from training structure, not scale: good views, such as a photo and its caption, need 42 times fewer training samples than next-token prediction. No independent group has yet replicated the 109M-versus-72B result.
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In a study published on October 29, Yann LeCun and Randall Balestriero claim to demonstrate that a small, well-nourished AI model makes a better picture of the world than a 660-fold larger LLM. " Yann LeCun was right," excited the influencer IA Shruti Mishra on X, November 1, 2026.

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Startup Fortune broke the news on Sunday, November 1, 2026.
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