AI coding agent rewrites algorithm to be 10x faster but introduces errors
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Astronomers used an AI coding agent to rewrite the void-finding algorithm VIDE; the new version runs 10 times faster and can handle survey data 100 times larger. But at the reporting session, a colleague pointed out a subtle error in its edge-handling logic, which caused all downstream results to be invalid. The author therefore argues that LLMs are essentially next-word predictors, and correctness is merely a byproduct; human-preference fine-tuning also makes them fluent and likable, so AI cannot simply be trusted.
AI overview based on source reports · Updated 40 min ago
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An astrophysicist describes presenting a major update to his void-finding algorithm VIDE, built with heavy AI assistance, only to have a collaborator expose a subtle but fundamental error in its edge handling that invalidated everything downstream. He argues that LLMs are fluent next-word predictors tuned to please users, and that their usefulness requires borrowing the alchemists' discipline: grounding outputs in verification, tracing provenance, and keeping human judgment as the final authority.
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