Welcome to "AI in the Real World." I'm Steve Vassallo, a General Partner at Foundation Capital. In this series, we talk with leading AI researchers about their groundbreaking work and how it's being applied in real businesses today.

Joining me is Sean Lie, co-founder and CTO of Cerebras Systems. I’ve known Sean since early 2016 before leading the Series A investment in Cerebras. At the time, Sean was just wrapping up a three-year stint as Chief Architect of data center solutions at AMD, which he joined via AMD’s acquisition of his last startup, SeaMicro.

Sean is one of the biggest brains I know around hardware systems, bringing a rare expertise and passion for advanced architectures, many of which break from tradition and traditional approaches to computing.

In this episode, Sean guides us through the world of AI hardware innovation. He breaks down the concept of wafer-scale processing, the challenges of building monstrous AI chips, and the massive potential of sparsity. He offers valuable lessons from his journey as a deep tech entrepreneur, including the importance of thinking end-to-end and planning for scale from day one.

We close by peering into AI’s future and sharing advice for founders taking on similarly complex, system-level problems.

It was a really fun and insightful discussion that I think you'll enjoy. Here's my conversation with Sean.

(00:00:00) Introduction
(00:02:28) Sean’s background in hardware systems
(00:05:26) Cerebras’ origin story: Recognizing the need for AI-specific hardware
(00:10:13) Wafer-scale processing and its advantages
(00:15:50) Technical challenges and innovations in wafer-scale integration
(00:19:18) The importance of end-to-end system design in AI hardware
(00:24:54) Cerebras’ approach to scaling AI models
(00:28:27) Introduction of the Wafer-Scale Engine 3 and its capabilities
(00:32:00) Sparsity in neural networks and Cerebras’ hardware acceleration
(00:36:49) What’s next for AI hardware?
(00:37:38) Closing thoughts: Advice for deep tech entrepreneurs