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For the first time, you can watch an AI think
6+ hour, 47+ min ago (491+ words) Anthropic has found an area where the model appears to pause and reflect before responding. For the first time, we can peek inside the AI black box. Related: AI Integration Goes Enterprise-Ready: The Model Context Protocol/Cursor Cloud Agents: Coding…...
4 Percent in the Data Center, 54 at the Power Plant: Where Nvidia's Water Promise Really Ends
1+ day, 17+ hour ago (602+ words) Nvidia cools AI data centers with warm water in a closed loop, saving nearly everything on-site. Nvidia claims it has largely solved the water problem for data centers. A closed-loop system using warm water cools the next generation of chips…...
German Hyperscaler: Who Really Has Substance
6+ day, 18+ hour ago (545+ words) Schwarz Digits, the IT subsidiary of the Lidl Group, aims to become Germany's first home-grown hyperscaler with Stack IT. That's a bold claim in a market currently dominated by AWS, Microsoft and Google. The more pressing question isn't who shouts…...
Germany's Stack Goes Live: 250 Million Euros for the Federal AI Cloud
2+ week, 6+ day ago (724+ words) For private operators, the message is uncomfortable. Sovereignty without key sovereignty is merely a label. If you want to serve the public sector or regulated industries, you will henceforth be measured against exactly these two points. The platform must explicitly…...
800-Volt Direct Current in the Data Center: NVIDIA's Pivot for the Cloud
3+ week, 17+ hour ago (660+ words) Related: Disaggregated Inference: Why AWS and Cerebras Are Splitting the GPU/Cloud Brokers Instead of Cloud Chaos: 30 % Lower Multi-Cloud Costs For operators, the maintenance angle often matters more than raw efficiency. Fewer conversion stages mean fewer power supplies that can…...
Disaggregated Inference: Why AWS and Cerebras Are Splitting with the GPU
3+ week, 4+ day ago (504+ words) AWS and Cerebras are breaking AI inference apart. Instead of a single GPU handling everything, one chip takes the input and a second handles the output. The move sounds like a hardware detail " but it shifts the question every cloud…...
**Reducing GPU Costs for AI Inference: FP8, FP4, and v LLM**
1+ mon, 5+ day ago (699+ words) A production language model doesn't burn its GPU hours during one-time training-it does so with every single request. When a service scales from hundreds to hundreds of thousands of daily calls, inference becomes the largest line item on the cloud…...
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