Eli Lilly & Company Built an AI Supercomputer to Ask Bigger Questions

About this episode

What changes when scientists stop thinking about how much compute they can afford to use and start thinking about what they could discover with more of it?

That question sits behind LillyPod, Eli Lilly & Company’s on-prem AI supercomputer. Chief AI Officer Dr. Thomas Fuchs sees compute less as infrastructure and more as a scientific instrument, something that allows researchers to work at a scale that changes not only the answers they can find, but the questions they’re willing to ask.  

It’s a philosophy that runs counter to much of the current enterprise AI conversation. While companies wrestle with token costs, cloud economics and how tightly to ration increasingly expensive AI, Lilly is exploring what happens when some of those constraints begin to disappear. Fuchs calls it a move from scarcity to abundance. And when the underlying economics change, so does the ambition. 

But Fuchs is no AI maximalist. After two decades in machine learning, he is remarkably unsentimental about the hype. AI, in his view, becomes far more interesting when you stop asking it to be magic and start getting serious about what it can actually do.

Support for this episode provided by: Infoblox

Thomas Fuchs, Dr.sc., is Eli Lilly& Company’s first Chief AI Officer and a machine learning scientist who has spent two decades pushing AI into places where the stakes are real. His career spans NASA’s Jet Propulsion Laboratory, Mount Sinai and founding Paige AI. He holds a doctorate in machine learning from ETH Zurich and now leads Lilly’s use of AI across science, medicine and the enterprise.

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