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New framework combines language models with a doubt detector to find optimal experimental recipes faster

GOLLuM cuts the number of experiments needed by over 40% while matching Bayesian optimization across 23 chemistry and materials science benchmarks.

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Research is shifting the performance envelope, which can change serving cost, responsiveness, and how much agent work fits into production budgets.

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New framework combines language models with a doubt detector to find optimal experimental recipes faster

Why it matters: Research is shifting the performance envelope, which can change serving cost, responsiveness, and how much agent work fits into production budgets.

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