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Large language models (LLMs) such as ChatGPT promise advances that extend beyond capturing public interest. Because transformer models like GPT have an architecture that supports the understanding of language in context, they point to an array of novel possibilities for scientific research. “The transformer architecture is critical,” according to Michael Connell, the chief operating officer at Enthought. In a recent interview, Connell provided a sense of what to expect from generative AI in drug discovery, touching on how these tools could automate mundane tasks, streamline complex scientific workflows and speed drug discovery. The promises and pitfalls of generative AI in drug discoveryIn scientific research, generative AI, of which LLMs are an example, can partly automate tasks such as summarizing academic papers, solving math problems, coding, ensuring qual…