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Here, we quantify the epistemic shift from the llm's prior beliefs about a hypothesis to its posterior beliefs after gathering experimental results. The allen institute for artificial intelligence (ai2) introduced autods (autonomous discovery via surprise), a revolutionary prototype engine for an open autonomous scientific discovery. A core technical advancement in this field is the use of bayesian surprise, a mechanism for guiding exploration that underpins the architecture of hypothetical systems like ai2’s “autods.”
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The allen institute for ai launched autods, an autonomous engine that generates and tests hypotheses by detecting bayesian surprise We provide the first formal definition of surprise within the context of autonomous scientific discovery, inspired by prior work on bayesian surprise It explores scientific discovery without preset goals, using llms and efficient search algorithms.
