My guest today is <a href="https://x.com/neilmovva">Neil Movva</a>, founder of Sail. Sail is building what Neil calls a token factory, an inference company designed for a specific kind of future, one where AI agents run in the background for hours or days at a time rather than answering a human in real time.&nbsp;
In that world, latency matters less and cost matters more, and Neil has built the whole company around driving the cost of a token as low as it can possibly go.
What makes this conversation special is that it is one of the most detailed tours I have ever done through the full stack of intelligence, the software, the chips, and the power, and how all three connect.&nbsp;
Along the way we cover the trade-off between speed and cost that lives inside every GPU, his scavenger strategy for buying the chips and power nobody else wants, his contrarian view on Nvidia, and why the premium the frontier labs charge for being three to six months ahead may not last.&nbsp;
Please enjoy my conversation with Neil Movva.
For the full show notes, transcript, and links to mentioned content, check out the episode page ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠he<a href="https://colossus.com/episode/from-transistor-to-token/">r</a>e⁠⁠⁠⁠⁠.&nbsp;
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Editing and post-production work for this episode was provided by <a href="https://thepodcastconsultant.com/">The Podcast Consultant</a>.
Timestamps:
(00:00:00) Welcome to Invest Like The Best
(00:02:20) Neil Movva
(00:03:22) Building a Token Factory
(00:05:32) The Rise of Long-Running Agents
(00:08:47) Deep Research and Cybersecurity
(00:15:12) The Full Stack of Intelligence
(00:20:03) Throughput Versus Latency
(00:24:58) The Future of AI Chips
(00:33:19) Why Transformers Work
(00:36:43) The Future of Data
(00:44:05) The Market for AI Chips
(00:47:56) Is the AI Boom Different?
(00:51:08) Reinventing the Data Center
(00:56:43) Scavenging Power
(01:01:04) Where Compute Is Most Inefficient
(01:07:02) Open Versus Closed Models
(01:10:37) A Trillion Tokens a Day
(01:12:42) The Contrarian Case on NVIDIA
(01:14:38) Advice for AI Hardware Founders

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