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The Evolution of AI Models and Infrastructure
This chapter discusses the progression of AI models and the infrastructure needed to support them, including the challenges of hardware requirements, chip design, and data center centralization. It speculates on the future market structure for AI hardware and explores the geopolitical significance of data centers in maintaining competitive advantage.
Today, my guest is 21-year-old Gavin Uberti, who dropped out of Harvard to build Etched, which is one of the most fascinating companies I’ve seen. The topic of our conversation is the ongoing revolution in artificial intelligence, and more specifically the chips and technology that powers these incredible models. To date, general-purpose AI chips like Nvidia GPUs have powered the revolution, but Gavin’s bet is that purpose-built chips, hard-coded for the underlying model architecture, will dramatically reduce the latency and cost of running models like GPT4. We’re about to embark on what Gavin calls the “largest infrastructure buildout since the industrial revolution”, and I won’t spoil what he thinks this will unlock for all of us. It is so uplifting to me that someone so young can be working on something so big. Please enjoy this great conversation with Gavin Uberti.
Check out Etched.AI
Listen to Founders Podcast
For the full show notes, transcript, and links to mentioned content, check out the episode page here.
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Invest Like the Best is a property of Colossus, LLC. For more episodes of Invest Like the Best, visit joincolossus.com/episodes.
Past guests include Tobi Lutke, Kevin Systrom, Mike Krieger, John Collison, Kat Cole, Marc Andreessen, Matthew Ball, Bill Gurley, Anu Hariharan, Ben Thompson, and many more.
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Show Notes:
(00:03:41) - (first question) - Born too late to explore the world, too early to explore the stars
(00:05:59) - Interpreting and defining superintelligence
(00:07:20) - Excitement we can have for an AI driven future
(00:09:25) - Overview and basic terminology of the transformers that power AI
(00:15:53) - What Q* is and the rumors around it
(00:20:41) - Robotics, machinery, and what’s interesting about them
(00:23:18) - The problem of latency and computing power
(00:8:55) - Needing to build physical infrastructure that doesn’t exist
(00:32:18) - Inference and training AI models
(00:36:00) - Major stages of chip design and the upper limits of speed
(00:45:56) - Customers for billion dollar generative AI models
(00:48:56) - A sci-fi-esque reality and the politicization of AI
(00:50:38) - The Bitter Lesson and the implications of powerful AI models
(00:56:27) - The most important companies in the AI space today
(00:61:52) - Strategically building a defensible AI product
(01:04:07) - Software development and why other AI companies fail
(01:06:51) - Specialization and chip performance improvement
(01:15:34) - Why the transformer remains the leading architecture
(01:17:26) - A proliferation of models beyond the major players and data access
(01:21:19) - The kindest thing anyone has ever done for Gavin
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