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The Cheapest Millisecond

  Notes from Chicago on why inference infrastructure stopped being a compute problem I gave a keynote at The Connected World Live in Chicago on September 9th, and I enjoyed it more than I expected to. Twelve minutes is a punishing format. It is long enough to need a real argument and short enough that a single tangent costs you a fifth of it. Constraints like that are clarifying. You find out quickly which parts of your thesis you actually believe, because there is no room to carry the parts you are only fond of. Afterward I joined a fireside chat and then a panel with NVIDIA, Edgecore, and Interglobix. More on that at the end. Here is the argument I made. The question the building has to answer has changed From 2021 to 2024 we built data centers to answer one question. How large a model can we build? That question has a shape. It wants the largest coherent cluster you can power and cool. It tolerates a bad night, because you checkpoint and resume. It books capacity in GPU hours an...
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The Day the Robots Won a Million-Dollar Math Prize (Sort Of)

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  Copyright: Sanjay Basu On the morning of Tuesday, September 8, 2026, a group of mathematicians at a company called OpenAI said something remarkable. They had set 10,000 computer helpers loose on a math problem that people had been stuck on for over a hundred years. And the computers cracked it. The problem is one of six famous puzzles called the Millennium Prize Problems. Whoever solves one gets a million dollars. Only one of the six had been solved before this. Now the computers may have gotten a second. Let me tell you what the puzzle is, why it matters, and why grown-up mathematicians are both cheering and squabbling about it. What was the puzzle? Imagine you are watching water flow down a river, or smoke curl up from a candle, or air moving over an airplane wing. Way back in the 1800s, two scientists wrote down a set of math rules that describe how all of that moving stuff behaves. We call them the Navier-Stokes equations. Say it out loud: "nav-YAY STOKES." Fancy name, ...
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The Feasibility of Nuclear Power for AI Infrastructure and Data Centers

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  A technology and economics assessment — September 2026 Copyright: Sanjay Basu Sitting through the panels at Datacloud USA and Metro Connect Fall in Austin this week, from the Nuclear for AI Summit to the site-selection and power-procurement sessions, I came away convinced that the industry is still conflating two very different timelines, and the conference stage did little to separate them. The energy on the floor around nuclear was real and, I think, largely justified. Firm, carbon-free, co-locatable power is exactly the solution that hyperscale AI wants, and behind-the-meter generation is the one credible path around interconnection queues that now stretch past five years. But too many of the discussions treated announced SMR gigawatts as if they were bankable capacity rather than options on a 2030s bet whose economics remain unproven. Every unit built anywhere in the world so far has cost more and arrived later than promised, and NuScale should still be haunting these rooms. ...
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