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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What AI Teams Should Know About HBF and Tiered Memory
For years, most of the AI memory conversation has been about bandwidth: can memory feed GPUs fast enough? Frontier inference is adding a second problem. Model weights, KV caches, and…
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The AI Data Center Backlash Has a Blind Spot
Within my own network, I was early in flagging the growing local opposition to AI data centers. Since then, it has moved fast, from scattered zoning fights to outright moratoriums…
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The biggest AI risks sit outside the model
The most revealing AI failures right now are not stories about models becoming too capable. They are stories about everything around the model. One system received more access than its…
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How AI Is Changing Mathematical Research
With all the recent headlines about AI systems solving research math problems, I decided it was time to update a piece I wrote on this topic a while back. Outside…
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Continual Learning Is Arriving in Pieces
A while back I wrote about how startups are using reinforcement learning to make agents more reliable. A deeper problem behind that whole trend keeps resurfacing: a model can improve…
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Why Data Centers Became the Face of the AI Backlash
AI is no longer being judged only as software. Once the buildout arrives as a massive industrial facility, new transmission lines, continuous power demand, and possible pressure on utility rates,…
