Harvard physicist Matthew Schwartz said in a post on Anthropic’s science blog that scientific work with AI faces an "impedance mismatch," arguing that treating large language models as human-style collaborators is not the best way to draw out their scientific potential. To address that issue, Schwartz built a toolkit designed for precise calculation in quantitative science. Anthropic’s Claude then identified links between the toolkit and more than 10 fields, including ecology and population genetics, based on the recurrence of similar calculations across disciplines. Schwartz also worked with domain experts to guide the AI as it explored those questions. The update was cited by Techub, which attributed the information to Schwartz’s article and Anthropic.
Harvard physicist Matthew Schwartz said in a post on Anthropic’s science blog that there is an "impedance mismatch" in how AI is used in scientific collaboration. In his view, treating large language models as if they were human collaborators is not the best way to unlock their scientific potential.
To tackle that problem, Schwartz built a toolkit for precise calculation in quantitative science. According to the post, similar calculations often appear across different scientific disciplines, and Anthropic’s AI model Claude identified connections between the toolkit and more than 10 fields, including ecology and population genetics.
Schwartz then worked with experts in those fields to guide the AI in exploring those questions.
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