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Tiny Recursive Models Beat the Giants - Alexia Jolicoeur-Martineau (Microsoft)

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Microsoft researcher Alexia Jolicoeur-Martineau explains the Tiny Recursive Model and the reasoning behind her work on small networks that repeatedly refine an internal state and proposed answer. The conversation examines truncated gradients, puzzle-solving benchmarks and the differences from autoregressive language generation. It also considers molecular modelling, limits of data scaling and which research directions she would prioritize. Hosted by Ravid Shwartz Ziv and Allen Roush. Watch the full conversation on the publisher’s YouTube channel.

Topics

Tiny Recursive Modelsmall networksinternal statetruncated gradientspuzzle-solving benchmarksautoregressive language generationMolecular ModellingData scalingAlexia Jolicoeur-Martineau

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