Gradient Flow’s analysis of data, technology, and business, with a focus on machine learning and AI — one of the Top 10 Sites for Data Scientists.
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AI Can Win While Data Centers Lose
I keep coming back to the same uncomfortable math on AI data centers: the money going in is piling up faster than any economic proof that it should. Usage of…
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Three New Models, One Signal About Where AI Spending Goes Next
Three frontier level models landed within weeks of each other this fall, GLM 5.2 from Zhipu, Kimi K3 from Moonshot, and Gemini 3.6 Flash from Google, and I wanted to…
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Open Models Will Absorb Most of the AI Spend
Here is my bet: open models (open weights and open source alike) will end up absorbing most of the money and compute the world spends on AI. The proprietary frontier…
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What We Actually Know About China’s AI Export Controls
Since June 2026, Chinese officials have been in closed door talks about restricting foreign access to the country’s most advanced AI models, both open and closed. The Ministry of Commerce…
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What Startups Taught Me About the Next Layer of AI Infrastructure
A little while back I wrote about how teams use reinforcement learning (RL) to make agents reliable. Since then I keep bumping into startups where RL is not a research…
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Your CLI Was Built for Humans, Not Agents
There’s a friendly debate among developers about how to give AI agents reliable ways to use external tools, data, and services so they can do useful work beyond generating text.…
