NVIDIA's AI Engineers: Agent Inference at Scale and "Speed of Light" https://
latent.space/p/nvidia-brev-
dynamo
… @nvidia is embracing Engineers at all levels of the stack: from the sublime DX of @brevdev
, to the open source datacenter framework of Dynamo. @KranenKyle and @NaderLikeLadder join
COMPUTING
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NVIDIA Scales Agent Inference with Engineering Stack Innovation
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NVIDIA CEO Jensen Huang on AI’s Five-Layer Stack Rebuild
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The AI era is a full-stack rebuild, from power to models to real-world applications. Here’s NVIDIA CEO Jensen Huang on the five-layer AI cake driving the shift.
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Critical Infrastructure: Space Links and Subsea Cables Enable Global Digital Services
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Global digital services rely on infrastructure that remains invisible to most organizations. Space links and subsea cables sustain data flows across continents, and their resilience conditions financial transactions, cloud operations, and supply coordination Microblog @antgrasso
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Meta partners with NVIDIA for 1GW compute infrastructure and AI systems
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Excited to partner with NVIDIA. bringing up 1GW or more of compute starting with Vera Rubin, co-designing systems and architectures together, and more. NVIDIA has also made a significant investment in @thinkymachines Thinking Machines (@thinkymachines) We are partnering with @nvidia to power our frontier model training and platforms delivering customizable AI. thinkingmachines.ai/news/nvi… — https://nitter.net/thinkymachines/status/2031356627916603876#m
→ View original post on X — @soumithchintala, 2026-03-10 13:51 UTC
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Compute Layer as Strategic Resource for AI Scaling
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I am glad the analogy connected with you. The compute layer is indeed becoming a strategic resource, since scaling these systems requires not only technology but also careful planning around energy and investment horizons.
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Building AI Infrastructure: Long-term Commitment and Competitive Advantage
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Thank you, Yash. Building the track requires long-term commitment across infrastructure and talent, which is not an easy path for many countries. Over time, it will become quite visible who is laying foundations and who is simply traveling on systems developed elsewhere.
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DeepSeek Shows AI Excellence Possible With Computational Constraints
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The compute gap conversation always assumes China wants to play the same game. DeepSeek proved you can do incredible things with constraints.
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AI Inference Era: The Next Architectural Shift Beyond Training
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The AI training era is reaching its limit. While the world is obsessed with $100B "Gigafactories," we’re looking at what happens next. At MWC Barcelona, Axelera AI CEO Fabrizio Del Maffeo sat down with theCUBE to discuss the Inference Era. The architectural reset of the
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Foundation layers shape how AI innovation develops forward
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The real impact tends to appear in the layers that support everything else, because once those foundations are in place, they influence how innovation develops.
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Energy and Talent: Critical Bottlenecks for Large-Scale AI
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At the moment, the pressure seems to concentrate on two areas: energy and talent, since large-scale compute requires enormous power capacity while the number of people who can design and operate these systems remains relatively small. Over time, the balance may change, but today