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From Enablement to Execution, Egypt’s AI Ecosystem Reaches Production Scale

Today, Egypt’s AI builders gathered in the Grand Egyptian Museum for a reception that highlighted the nation’s rapidly growing AI ecosystem — spanning AI natives, developers, researchers, startups and enterprises — building applications across industries. The event included a keynote from Paolo Guglielmini, vice president of EMEA at NVIDIA. Ahmed Mostafa, regional AI adoption lead […]

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Turn Your Latest Observations Into Timely Weather Decisions With NVIDIA Earth-2

Weather-sensitive industries increasingly have access to observations that offer an earlier, more local view of changing conditions. Energy companies collect…

Weather-sensitive industries increasingly have access to observations that offer an earlier, more local view of changing conditions. Energy companies collect measurements across wind and solar assets, emergency management teams rely on radar and local sensors, and satellite providers continuously observe the Earth. This data helps organizations understand and manage physical risk across sectors…

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AI Security Is an Engineering Problem — How to Solve It at Every Layer of the Agent Stack

AI security is an engineering problem. That means defined security requirements, enforceable controls, named owners and evidence that protections work.  As AI becomes more capable, the industry must accelerate security engineering, broaden access to defensive tools and share what works faster.  Technology Changes, Security Fundamentals Endure The internet and cloud computing changed how software operates, […]

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tokenizers v1: encode, decode and scaling, measured

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Misc

Pruning LLMs Like a Physicist: Block Removal as an Ising Optimization Problem

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Misc

5 Companies Using NVIDIA AI for Clean Energy

Clean energy isn’t hard to come by, but the pace of large-scale adoption has historically been slow due to bottlenecks — including out-of-date infrastructure, elongated research and development timelines, and upfront cost barriers.  At New York Climate Week, NVIDIA is highlighting five companies pioneering clean energy projects with AI baked into their foundation, accelerating research-to-inception […]

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Benchmarking LLM Inference at Scale with AIPerf

You’re deploying a model on a system. It starts up, prompts are getting responses. Now the hard question: Is this fast? Your instincts might lead you to send…

You’re deploying a model on a system. It starts up, prompts are getting responses. Now the hard question: Is this fast? Your instincts might lead you to send curl commands, hand-roll an asyncio script, or vibe code yet another one-off load generator. All of these paths have the same problem: single-process performance limits, Python’s GIL capping concurrency, or numbers measured against a…

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Cute Critters Come to the Cloud: ‘Aniimo’ Launches on GeForce NOW

A new creature-catching adventure is ready to stream from the cloud this week. Pawprint Studio’s Aniimo arrives on GeForce NOW at launch, inviting gamers to explore the vibrant continent of Idyll across supported devices. Also this week, 007 First Light receives a path-tracing update on GeForce NOW, alongside a smashing limited-time Deluxe Edition sale on […]

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How to Use AI Agents to Prepare 3D Scenes for Simulation

Agentic AI workflows can be used to prepare and validate digital twins for physical AI systems. Agents can inspect 3D scenes, author simulation-relevant data in…

Agentic AI workflows can be used to prepare and validate digital twins for physical AI systems. Agents can inspect 3D scenes, author simulation-relevant data in OpenUSD, add physics properties, render preflight views, and validate the result against simulation-ready (SimReady) requirements. This workflow follows that process from a scene in Blender to a simulation-ready OpenUSD handoff for NVIDIA…

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TensorRT Edge-LLM Completes the MLPerf Edge Agentic Benchmark 6.4x Faster on Jetson AGX Thor

AI agents are moving from cloud data centers to vehicles, robots, and other edge devices. Unlike a chatbot that answers a single prompt, an agent works through…

AI agents are moving from cloud data centers to vehicles, robots, and other edge devices. Unlike a chatbot that answers a single prompt, an agent works through a sequence of steps. It selects tools, evaluates their results, and continues reasoning within an increasingly long conversation. This workflow places new demands on edge inference. The model must generate tokens quickly…

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