The compute, hardware, platforms, and operational foundations required to train, serve, and run AI systems at scale or locally.
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17 articles in this tag.
An export control is a licensing requirement, not a ban. That single distinction decides whether a rule is a wall or a toll booth — and which layer of the…
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The new AI data center is not built where the users are. It is built where the power is.
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A capacity plan built from average QPS and a single latency target will survive the spreadsheet and die on the first traffic spike. The number was never…
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Two accelerators can sit within a few percent of each other on the spec sheet and produce very different monthly bills. The gap is not fraud, and it is not…
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Two accelerators can post nearly identical peak compute numbers and still differ by a factor of several on tokens per second. The spec sheet will not tell…
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The expensive serving decision is the one you make before you have traffic data.
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The cluster is provisioned, the dashboards are green, and the inference bill is still climbing while latency drifts. That combination — healthy…
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Whoever holds the most advanced model is not automatically winning. Whoever can train and serve it at scale holds the stronger position.
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Peak FLOPS is the number everyone quotes and the number that predicts the least.
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Your dashboard is green. GPU utilization sits in a healthy band, average latency looks fine, and nobody has filed a complaint this week. Then the invoice…
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You have a model file, a GPU, and a demo that works on your laptop. Now answer the only question that matters: what breaks first when this leaves your…
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The model loads. The first prompt returns in two seconds. Then the context grows, a second request arrives, and the whole thing crawls.
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The demo ends the moment the model answers. The operations commitment begins the moment it answers twice, at 2 a.m., on a Tuesday, while the one engineer…
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A prototype works on a hosted API, then someone says "let's just run it locally." That sentence usually bundles three different decisions into one, and…
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A voice agent that transcribes every word correctly can still feel broken. The transcript is not the conversation.
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A policy that succeeds in simulation and fails on the third shift is not a model problem. It is a systems problem.
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A country can own the datacenter and still not own the decision. That gap is where sovereign AI lives.
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