AI & Technology
Correct calculations are not yet worthwhile science
In an Anthropic guest essay, Harvard physicist Matthew Schwartz describes using his BootLoops project to produce 36 research manuscripts across 18 fields with 19 collaborators in three months. Manuscripts are not a count of accepted, peer-reviewed papers.
He selected from roughly 400 candidate directions, assigning coding, calculation and cross-field methods to Claude while humans chose questions. Parallel sessions, evolving plans and adversarial reviewers supported the work. Schwartz is also an Anthropic visiting researcher; this is a participant’s account.
One ecology result found species-composition change in a Panamanian forest about 4.5 times faster than neutral theory predicted. Ecologist James O’Dwyer noted that the qualitative finding was already known. The project shifted toward subtracting the random prediction and explaining the biological remainder, then extending a demographic model to other plots.
A genetics integral likewise needed a more meaningful biological question. Schwartz describes premature completion claims and unproved lemmas silently treated as axioms. Expert feedback, inspecting plots and choosing a better problem mattered more than endless retries.
AI can widen computational exploration; domain judgment still determines scientific value. We read the essay, rather than reproducing its 36 manuscripts. It provides no uniform compute cost or independently verified research return.
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