The past few years have seen several flashy demonstrations of how artificial intelligence (AI) algorithms may transform biomedical research, particularly with respect to drug discovery. This past November, for example, Google's AI subsidiary, DeepMind, announced that its AlphaFold program could deliver computational predictions of protein structure that approach the quality of those provided by gold-standard experimental techniques such as X-ray crystallography.1 Such high-profile announcements have elicited justifiable excitement about the future of algorithmically guided drug development, but AI's champions in the industry remain wary about overselling the technology's current capabilities. "I still feel that there's a lot of hype around it," says Paul Nioi, PhD, senior director of research at Alnylam Pharmaceuticals. "Companies are springing up that claim to solve all the issues of drug discovery, target discovery, and development using AI. I think that's yet to be proven."