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thanks for sharing! We think the Experiments-as-code path is not the right approach. the beauty of LLMs is their ability to ingest and reason over unstructured data - they remove the need for formalizing experiments. We tried using declarative templates to document our experiments, but realized that most of the interesting insights (for example, how viscous a liquid feels) is easier described by ranting about the experiment to a LLM, than formalizing it via constructs/code.


Pure vibe-sciencing.


Yeah you gotta have some sort of trace and interface to physical reality.

One of the authors of the 2nd paper was Jeff deans undergrad advisor pointing him toward neural networks in the 90s.




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