  We investigate whether large language models can perform the creative
hypothesis generation that human researchers regularly do. While the error rate
is high, generative AI seems to be able to effectively structure vast amounts
of scientific knowledge and provide interesting and testable hypotheses. The
future scientific enterprise may include synergistic efforts with a swarm of
"hypothesis machines", challenged by automated experimentation and adversarial
peer reviews.
