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Ed Addison took his first AI course at MIT in 1985 and has spent the four decades since building through every wave of the field, from brittle rule-based expert systems in the 80s, to neural nets in the 90s, to the deep learning breakthrough of 2006, to the generative AI and transformer architectures that produced today’s large language models.

He’s founded five AI companies with three exits, most of it in the notoriously difficult world of AI drug discovery, where he argues the algorithms getting all the attention aren’t actually the valuable asset: the data is, and Big Pharma still owns most of it. In this conversation with Jeff Pedowitz, Addison lays out why no AI-discovered drug has made it through FDA approval yet, why failure rate rather than speed or cost is the only number that will prove the technology works, and why he believes the AI industry has a financial bubble but not a scientific one.

The conversation closes with the story behind his “accidental novel,” Probability of Doom, written with AI as a collaborator after a family road trip conversation, and now used in his own classroom to teach engineers what can go wrong when humans, humanoids, and multi-agent systems start operating side by side.