# nvidia Published articles for nvidia. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Nvidia представила Axolotl3D -- модель для достраивания скрытых частей 3D-объектов DevFeed: [Nvidia представила Axolotl3D -- модель для достраивания скрытых частей 3D-объектов]() Original publisher: [Read original article]() Author: daniilshat Published: 2026-09-17T20:54:47Z Content type: news Language: ru Sources: [Tagir Valeev]() Topics: [3D](), [Nvidia]() Tags: [3d](), [3d-66bde4d200c5](), [axolotl3d](), [image](), [nvidia](), [tag-055aee430837](), [tag-13e2af703774](), [tag-1cd610c0e518](), [tag-86b843454893](), [tag-8e9a901cca08]() ### AI overview Nvidia introduced Axolotl3D, a generative model that reconstructs and edits 3D objects from incomplete data. It combines multiple images, camera positions, visibility masks, and partial point clouds to restore missing geometry. The model was trained on 407,000 models, but its code and weights have not yet been published. ### Source excerpt Nvidia представила Axolotl3D -- генеративную модель для восстановления и редактирования 3D-объектов по неполным данным. Она учитывает несколько фотографий, положение камеры, маски видимости и частичное облако точек, а после восстанавливает недостающую геометрию. Читать далее ## Snap SPECS standalone AR glasses combine AI, real-time overlays, and hands-free apps DevFeed: [Snap SPECS standalone AR glasses combine AI, real-time overlays, and hands-free apps]() Original publisher: [Read original article]() Author: Gaurav Sood Published: 2026-09-17T18:20:01Z Content type: article Language: en Sources: [Yanko Design]() Topics: [immersive web](), [snap](), [Artificial Intelligence](), [iOS](), [Amazon Web Services](), [Nvidia](), [Shopify]() Tags: [ai](), [ar-vr](), [ar-vr-wearables-augmented-reality-smart-glasses](), [augmented-reality](), [aws](), [ios](), [meta](), [nvidia](), [shopify](), [smart-glasses](), [snap](), [wearables]() ### AI overview The article presents Snap's SPECS as standalone AR glasses with built-in computing, SPECS Intelligence AI, iOS support, and developer tools through Lens Studio. It describes enterprise exploration by NVIDIA, AWS, and Salesforce, plus real-time AR applications, translations, voice and gesture shopping, and streaming features. The article also notes limitations in perceived realism despite a 51-degree field of view. ### Source excerpt SPECS standalone AR glasses could undercut VR headsets sans all the bulk Smart glasses and VR headsets have a big, gaping rift that a keen manufacturer could fill. Evan Spiegel has been working to bring the best of... ## Mojo 1.1 Released, Now Accepting Community Contributions To The Compiler DevFeed: [Mojo 1.1 Released, Now Accepting Community Contributions To The Compiler]() Original publisher: [Read original article]() Author: Michael Larabel Published: 2026-09-17T16:26:41Z Content type: release Language: en Sources: [Phoronix]() Topics: [releases](), [Compiler](), [Code](), [Development](), [Nvidia](), [Qualcomm](), [GitHub]() Tags: [ai](), [amd](), [code](), [compiler](), [contributions](), [desktop-linux](), [development](), [github](), [language](), [linux-benchmarking](), [linux-hardware-benchmarks](), [linux-hardware-reviews](), [linux-how-to](), [linux-performance](), [linux-server-benchmarks](), [nvidia](), [open](), [open-source-graphics](), [performance](), [phoronix](), [phoronix-test-suite](), [qualcomm](), [releases](), [standard-library](), [ubuntu-benchmarks](), [ubuntu-hardware]() ### AI overview Mojo 1.1 and MAX 26.6 have been released. Mojo 1.1 adds inferred member references, improved compile times, better generated code performance, and more stable standard-library APIs, while the development process now accepts community contributions to the compiler. MAX 26.6 adds audio generation support and kernel speedups across AMD and NVIDIA GPUs. ### Source excerpt Last month Modular's Mojo language was open-sourced following the acquisition of Modular by Qualcomm. Modular was the AI startup founded by Chris Lattner of LLVM and Swift fame. Released today was Mojo 1.1 and also marks the project recently now beginning code contributions from the community to its compiler... ## CoreWeave Deploys Multi-Rack Vera Rubin NVL72 Cluster: Hundreds of Rubin GPUs, 1.6 Tb/s Per GPU, and a No-Fee Archive Tier DevFeed: [CoreWeave Deploys Multi-Rack Vera Rubin NVL72 Cluster: Hundreds of Rubin GPUs, 1.6 Tb/s Per GPU, and a No-Fee Archive Tier]() Original publisher: [Read original article]() Author: Harold Fritts Published: 2026-09-17T15:48:47Z Content type: news Language: en Sources: [StorageReview.com]() Topics: [Vera Rubin NVL72](), [GPU](), [Cloud](), [Nvidia](), [Artificial Intelligence](), [NVLink](), [dell](), [Hardware](), [Network](), [Inference Performance]() Tags: [ai](), [cloud](), [dell](), [enterprise](), [gpu](), [hardware](), [mlperf](), [network](), [nvidia](), [nvl72](), [nvlink](), [vera-rubin-nvl72]() ### AI overview CoreWeave has deployed a multi-rack NVIDIA Vera Rubin NVL72 cluster on CoreWeave Cloud for agentic AI workloads. The deployment connects hundreds of Rubin GPUs through NVLink 6 and NVIDIA Spectrum-X Ethernet, with up to 1.6 Tb/s of backend connectivity per GPU. CoreWeave also announced cross-region write acceleration and a new Archive tier for CoreWeave AI Object Storage. ### Source excerpt CoreWeave has deployed a multi-rack NVIDIA Vera Rubin NVL72 cluster on CoreWeave Cloud, connecting hundreds of Rubin GPUs into a single scale-out environment aimed at agentic AI workloads. Each Dell-built rack carries 72 Rubin GPUs, 36 Vera CPUs, NVLink 6 as the scale-up fabric, BlueField-4 DPUs, and two ConnectX-9 SuperNICs per GPU, and the racks The post CoreWeave Deploys Multi-Rack Vera Rubin NVL72 Cluster: Hundreds of Rubin GPUs, 1.6 Tb/s Per GPU, and a No-Fee Archive Tier appeared first on StorageReview.com. ## HP EliteBook 8470p and Dell Precision T1650 support added to Libreboot DevFeed: [HP EliteBook 8470p and Dell Precision T1650 support added to Libreboot]() Original publisher: [Read original article]() Author: Leah Rowe Published: 2026-09-17T04:32:50.666044Z Content type: news Language: en Sources: [News about Libreboot releases and development]() Topics: [libreboot](), [dell](), [coreboot](), [intel](), [Linux](), [Debian](), [Nvidia]() Tags: [article](), [bios](), [canoeboot](), [coreboot](), [debian](), [dell](), [free-software](), [intel](), [libre](), [libreboot](), [linux](), [news](), [nvidia](), [opensource](), [precision](), [uefi]() ### AI overview Libreboot added support for the HP EliteBook 8470p and Dell Precision T1650. The article describes tested hardware variants, installation guidance, graphics limitations, boot configuration, and the T1650's ECC memory support. ### Source excerpt Article: HP EliteBook 8470p and Dell Precision T1650 support added to Libreboot Web link: https://libreboot.org/news/hp8470p_and_dell_t1650.html ## Dell Latitude E6400 added to Libreboot (blob-free, no disassembly) DevFeed: [Dell Latitude E6400 added to Libreboot (blob-free, no disassembly)]() Original publisher: [Read original article]() Author: Leah Rowe Published: 2026-09-17T04:32:50.666044Z Content type: news Language: en Sources: [News about Libreboot releases and development]() Topics: [dell](), [Hardware](), [boot]() Tags: [added](), [bios](), [boot](), [canoeboot](), [coreboot](), [dell](), [firmware](), [flashing](), [free-software](), [intel](), [laptop](), [libre](), [libreboot](), [nvidia](), [opensource](), [uefi]() ### AI overview Libreboot added support for the Dell Latitude E6400 through a blob-free port. The article says the laptop can be flashed without disassembly or a clip, using a utility that bypasses relevant firmware protections. Later updates confirmed support for E6400 XFR and the Nvidia GPU variant. ### Source excerpt Article: Dell Latitude E6400 added to Libreboot (blob-free, no disassembly) Web link: https://libreboot.org/news/e6400.html ## Experimental Nvidia GPU support on Dell Latitude E6400 variants, plus E6400 XFR support now confirmed DevFeed: [Experimental Nvidia GPU support on Dell Latitude E6400 variants, plus E6400 XFR support now confirmed]() Original publisher: [Read original article]() Author: Leah Rowe Published: 2026-09-17T04:32:50.666044Z Content type: news Language: en Sources: [News about Libreboot releases and development]() Topics: [dell](), [GPU](), [Nvidia](), [Linux]() Tags: [bios](), [canoeboot](), [coreboot](), [dell](), [experimental](), [free-software](), [gpu](), [libre](), [libreboot](), [news](), [nvidia](), [opensource](), [uefi]() ### AI overview The article reports experimental Nvidia GPU support for Dell Latitude E6400 variants in Libreboot, alongside confirmed support for the Intel-graphics Dell Latitude E6400 XFR. It explains that Nvidia variants require the appropriate VGA ROM and identifies Libreboot release versions associated with support. ### Source excerpt Article: Experimental Nvidia GPU support on Dell Latitude E6400 variants, plus E6400 XFR support now confirmed Web link: https://libreboot.org/news/e6400nvidia.html ## How to Use AI Agents to Prepare 3D Scenes for Simulation DevFeed: [How to Use AI Agents to Prepare 3D Scenes for Simulation]() Original publisher: [Read original article]() Author: Tanya Lenz Published: 2026-09-16T23:20:33Z Content type: tutorial Language: en Sources: [NVIDIA Developer](), [NVIDIA Technical Blog]() Topics: [Artificial Intelligence](), [Simulation](), [Physical AI](), [Simulation and Design](), [blender](), [Isaac Sim](), [Omniverse](), [Robotics Simulation](), [Robotics]() Tags: [3d](), [agentic](), [agentic-ai-generative-ai](), [agents](), [ai](), [blender](), [gpt-6-astra](), [how-to](), [isaac-sim](), [nemoclaw](), [nvidia](), [omniverse](), [openai](), [openusd](), [physical-ai](), [robotics](), [robotics-simulation](), [simulation](), [simulation-modeling-design]() ### AI overview This tutorial describes an agentic workflow for preparing Blender 3D scenes for robotics simulation. It covers scene inspection, OpenUSD metadata, physics properties, rendering preflight views, and validation for simulation-ready handoff to NVIDIA Isaac Sim or Isaac Lab. ### Source excerpt 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... ## Nvidia goes green to keep grid capacity from zapping its revenues DevFeed: [Nvidia goes green to keep grid capacity from zapping its revenues]() Original publisher: [Read original article]() Author: Tobias Mann Published: 2026-09-16T21:37:05Z Content type: news Language: en Sources: [www.theregister.com - Articles]() Topics: [Nvidia](), [datacenter](), [Cloud]() Tags: [ai](), [ai-factory](), [cloud](), [datacenter](), [gpu](), [nvidia](), [systems]() ### AI overview The article reports that Nvidia is courting neocloud providers with more efficient and profitable data centers. ### Source excerpt GPUzilla woos neoclouds into another walled garden, promising smarter, more efficient, and profitable bit barns ## Deveillance представила Kalypta -- приложение, которое мешает нейросетям расшифровывать созвоны DevFeed: [Deveillance представила Kalypta -- приложение, которое мешает нейросетям расшифровывать созвоны]() Original publisher: [Read original article]() Author: daniilshat Published: 2026-09-16T21:03:18Z Content type: news Language: ru Sources: [Tagir Valeev]() Topics: [Whisper](), [OpenAI](), [Nvidia]() Tags: [deveillance](), [kalypta](), [nvidia](), [openai](), [tag-13e2af703774](), [tag-2a5d58595ac8](), [tag-3150a442d159](), [tag-4d5248fd6bfe](), [tag-74c19fd8f316](), [tag-86b843454893](), [whisper]() ### AI overview Deveillance has introduced Kalypta, a macOS beta application that locally modifies outgoing audio in real time so people can understand the speaker while speech-recognition systems receive a distorted transcription. The startup says its model targets systems based on OpenAI Whisper and Nvidia Canary, though developers may counter the technique by retraining models. ### Source excerpt Стартап Deveillance представил Kalypta -- приложение, которое мешает нейросетям расшифровывать речь во время созвонов. Программа работает локально и в реальном времени изменяет исходящий аудиопоток так, чтобы собеседник продолжал понимать пользователя, но системы распознавания речи получали искажённую расшифровку. Читать далее ## TensorRT Edge-LLM Completes the MLPerf Edge Agentic Benchmark 6.4x Faster on Jetson AGX Thor DevFeed: [TensorRT Edge-LLM Completes the MLPerf Edge Agentic Benchmark 6.4x Faster on Jetson AGX Thor]() Original publisher: [Read original article]() Author: Elizabeth Goodman Published: 2026-09-16T20:37:07Z Content type: article Language: en Sources: [NVIDIA Developer](), [NVIDIA Technical Blog]() Topics: [Jetson AGX Thor Developer Kit](), [Inference Performance](), [benchmarking](), [TensorRT](), [Large Language Model](), [quantization](), [Artificial Intelligence]() Tags: [agentic-ai-generative-ai](), [ai-agent](), [ai-inference](), [evaluation](), [jetson](), [jetson-agx-thor-developer-kit](), [llm](), [llm-benchmarking](), [mlperf](), [nvidia](), [performance](), [quantization](), [tensorrt](), [tensorrt-llm](), [thor]() ### AI overview This article reports that NVIDIA TensorRT Edge-LLM ran Qwen3.6-27B on a single NVIDIA Jetson AGX Thor Developer Kit for the MLPerf Inference v6.1 Edge Agentic benchmark. Using NVFP4 quantization, tree-based multi-token prediction, and KV cache reuse, it achieved 52.33 tokens per second and completed 1,007 turns in 24 minutes and 36 seconds, 6.4 times faster than the llama.cpp reference submission. ### Source excerpt 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... ## GNOME 51 Released With Improved Frame Scheduling, Many App Improvements DevFeed: [GNOME 51 Released With Improved Frame Scheduling, Many App Improvements]() Original publisher: [Read original article]() Author: Michael Larabel Published: 2026-09-16T16:25:21Z Content type: news Language: en Sources: [Phoronix]() Topics: [releases](), [Wayland](), [Release notes](), [Software](), [ui](), [legacy](), [Nvidia]() Tags: [desktop](), [desktop-linux](), [driver](), [experience](), [faster](), [improvements](), [legacy](), [linux-benchmarking](), [linux-hardware-benchmarks](), [linux-hardware-reviews](), [linux-how-to](), [linux-performance](), [linux-server-benchmarks](), [notes](), [nvidia](), [offline](), [open-source-graphics](), [other](), [phoronix](), [phoronix-test-suite](), [protocols](), [release](), [release-notes](), [settings](), [software](), [time](), [ubuntu](), [ubuntu-benchmarks](), [ubuntu-hardware](), [ui](), [wayland](), [workstation]() ### AI overview GNOME 51 has been released with improved frame scheduling and desktop responsiveness, new Wayland protocol support, removal of legacy NVIDIA EGLStreams driver support, and updates to several GNOME applications and settings. ### Source excerpt Right on schedule and in time for appearing in the likes of Ubuntu 26.10 and Fedora Workstation 45, the GNOME 51 desktop is officially released... ## NVIDIA Vera Rubin NVL72 Delivers Leading Performance in MLPerf Inference v6.1 Debut DevFeed: [NVIDIA Vera Rubin NVL72 Delivers Leading Performance in MLPerf Inference v6.1 Debut]() Original publisher: [Read original article]() Author: Zhihan Jiang Published: 2026-09-16T15:00:48Z Content type: article Language: en Sources: [NVIDIA Blog]() Topics: [NVIDIA Vera Rubin](), [Vera Rubin NVL72](), [benchmarking](), [Inference Performance](), [Dynamo](), [vllm](), [Nvidia](), [TensorRT-LLM]() Tags: [ai-infrastructure](), [benchmarks](), [dynamo](), [efficiency](), [hardware](), [inference](), [mlperf](), [networking](), [nvidia](), [nvidia-vera-rubin](), [nvl72](), [optimization](), [performance](), [software](), [tensorrt](), [tensorrt-llm](), [vera-rubin-nvl72](), [vllm]() ### AI overview NVIDIA reports MLPerf Inference v6.1 preview results for Vera Rubin NVL72 and GB300 NVL72 systems. Vera Rubin NVL72 delivered up to 3.7x higher throughput than GB300 NVL72 on Qwen3-VL and up to 2.5x higher throughput on DeepSeek-R1, while a four-rack GB300 NVL72 submission achieved 99% scaling efficiency. The results used vLLM, NVIDIA Dynamo, and TensorRT-LLM. ### Source excerpt System performance, efficient infrastructure scaling and continuous software optimization are key levers that determine AI inference economics. Higher system performance means more tokens generated, resulting in higher revenue. Efficient scaling means throughput grows proportionally as hardware gets added, requiring fewer resources to serve users at scale. Continuous optimization means generating more value from infrastructure investments. [...] ## MLPerf Inference v6.1: 5.7x Per-Accelerator Gains, a 512-GPU Run, and Vera Rubin's First Peer-Reviewed Numbers DevFeed: [MLPerf Inference v6.1: 5.7x Per-Accelerator Gains, a 512-GPU Run, and Vera Rubin's First Peer-Reviewed Numbers]() Original publisher: [Read original article]() Author: Harold Fritts Published: 2026-09-16T15:00:00Z Content type: news Language: en Sources: [StorageReview.com]() Topics: [Benchmark](), [Inference Performance](), [Retrieval Augmented Generation (RAG)](), [agentic-coding](), [GPU](), [Vera Rubin NVL72](), [Nvidia](), [Vera Rubin]() Tags: [agentic-coding](), [ai](), [benchmark](), [enterprise](), [gpt-oss](), [gpu](), [inference](), [llama-cpp](), [numbers](), [nvidia](), [qwen3](), [rag]() ### AI overview MLCommons published MLPerf Inference v6.1 with record participation, two new inference tests, and peer-reviewed results for several newly covered accelerators. The release reports a 5.7x improvement in the best per-accelerator DeepSeek-R1 server result compared with v5.1. ### Source excerpt MLCommons has published MLPerf Inference v6.1, and the round sets a participation record with 30 submitting organizations and 486 datacenter and edge results. Two new tests join the suite: an End-to-End RAG pipeline for the datacenter and an Edge Agentic Inference benchmark for single-user devices, and the results carry the first peer-reviewed numbers for NVIDIA's The post MLPerf Inference v6.1: 5.7x Per-Accelerator Gains, a 512-GPU Run, and Vera Rubin's First Peer-Reviewed Numbers appeared first on StorageReview.com. ## Emerald AI, Google and NVIDIA Launch Alliance to Advance Flexible AI Data Centers DevFeed: [Emerald AI, Google and NVIDIA Launch Alliance to Advance Flexible AI Data Centers]() Original publisher: [Read original article]() Author: Josh Parker Published: 2026-09-16T13:00:33Z Content type: news Language: en Sources: [NVIDIA Blog]() Topics: [data centers](), [AI Infrastructure](), [Google](), [Nvidia](), [Artificial Intelligence](), [datacenter](), [benchmarking](), [Requirements]() Tags: [ai](), [ai-data-centers](), [ai-infrastructure](), [capacity](), [corporate](), [data-centers](), [energy](), [google](), [infrastructure](), [launch](), [metrics](), [nvidia](), [performance-metrics](), [requirements](), [resource](), [systems]() ### AI overview Emerald AI, Google and NVIDIA announced the AI Energy Management Alliance, a coalition focused on flexible AI data centers that can dynamically adjust electricity use in response to grid conditions. The article describes technology-neutral, performance-based requirements covering response speed, duration, predictability and emergency behavior. ### Source excerpt AI factories are the infrastructure of the intelligence era. Scaling them responsibly will depend as much on innovation across the grid as inside the data center. Today, Emerald AI, Google and NVIDIA announced the launch of the AI Energy Management Alliance (AEMA), a first-of-its-kind coalition advancing data centers that can dynamically manage their electricity use [...] ## University of Manchester Uses NVIDIA Earth-2 to Forecast Air Pollution Across the UK DevFeed: [University of Manchester Uses NVIDIA Earth-2 to Forecast Air Pollution Across the UK]() Original publisher: [Read original article]() Author: Isha Salian Published: 2026-09-16T05:00:42Z Content type: article Language: en Sources: [NVIDIA Blog]() Topics: [Artificial Intelligence](), [AI Models](), [Supercomputing](), [DGX Spark](), [Simulation](), [Training AI Models](), [data](), [Inference](), [real-time]() Tags: [ai](), [ai-for-good](), [ai-models](), [climate](), [compute](), [dgx-spark](), [government](), [healthcare](), [inference](), [nvidia](), [open-source](), [real-time](), [science](), [supercomputing](), [training](), [uk]() ### AI overview The University of Manchester is working with NVIDIA to use Earth-2 generative AI models to forecast air pollution across the U.K. The team trained Earth-2 CorrDiff on chemistry-climate simulation data using Isambard-AI, added StormCast for time-dependent forecasts using air-quality observations, and demonstrated workflows on DGX Spark. ### Source excerpt Air pollution is a serious public health risk, contributing to an estimated 30,000 deaths in the U.K. alone last year. Data-driven insights can help -- but computing air quality with traditional chemistry-based models is expensive, which limits how detailed they can be and how regularly they can be run. David Topping, a professor in the [...] ## Salesforce Announces Koa Reasoning Model Built on NVIDIA Nemotron 3 Super DevFeed: [Salesforce Announces Koa Reasoning Model Built on NVIDIA Nemotron 3 Super]() Original publisher: [Read original article]() Author: Brian Caulfield Published: 2026-09-15T22:24:34Z Content type: news Language: en Sources: [NVIDIA Blog]() Topics: [Koa](), [Nemotron](), [Artificial Intelligence](), [Nvidia](), [post-training](), [ai safety]() Tags: [agentic](), [agentic-ai](), [ai](), [cloud](), [corporate](), [events](), [model](), [nemotron](), [nvidia](), [nvidia-nemo](), [post-training](), [safety](), [security](), [software]() ### AI overview At Salesforce Dreamforce, NVIDIA CEO Jensen Huang discussed AI infrastructure, safety, and enterprise adoption alongside Salesforce CEO Marc Benioff. The event coincided with the announcement of Koa, Salesforce's first CRM reasoning model, built by post-training NVIDIA Nemotron 3 Super on a proprietary synthetic dataset derived from nearly three decades of enterprise CRM deployments. ### Source excerpt Know everything. Do anything. That was the message NVIDIA founder and CEO Jensen Huang brought to Salesforce Dreamforce Tuesday, joining CEO Marc Benioff onstage in an appearance that coincided with the announcement of Koa -- Salesforce's first CRM reasoning model, built on NVIDIA Nemotron 3 Super. Huang didn't just take the stage. He walked into [...] ## Cornelis and Delos Data propose open alternatives to Nvidia's NVLink for AI scale-up networking DevFeed: [Cornelis and Delos Data propose open alternatives to Nvidia's NVLink for AI scale-up networking]() Original publisher: [Read original article]() Author: Tobias Mann Published: 2026-09-15T20:56:48Z Content type: news Language: en Sources: [www.theregister.com - Articles]() Topics: [NVLink](), [AI Networking](), [Nvidia](), [networking](), [Hardware](), [High-Performance Computing]() Tags: [ai](), [ai-networking](), [cornelis-networks](), [delos-data](), [hardware](), [high-performance-computing](), [network](), [networking](), [nvidia](), [nvlink](), [performance](), [software](), [systems]() ### AI overview The article reports that Cornelis Networks and Delos Data have entered the AI scale-up networking market with proposed alternatives to Nvidia's NVLink. Cornelis introduced its open Active Compute Fabric architecture, which combines programmable in-network compute with scale-up and scale-out networking, while the broader market is developing alternatives using protocols such as Ultra Ethernet and UALink. ### Source excerpt Intel spin-off Cornelis and newcomer Delos Data pitch open alternatives for scaling AI beyond the rack ## From Megawatts to Tokens: How NVIDIA Maximizes AI Factory Production DevFeed: [From Megawatts to Tokens: How NVIDIA Maximizes AI Factory Production]() Original publisher: [Read original article]() Author: Vishal Ganeriwala Published: 2026-09-15T16:55:59Z Content type: article Language: en Sources: [NVIDIA Blog]() Topics: [AI Factory](), [NVIDIA DSX](), [datacenter](), [Orchestration](), [Inference](), [High-Performance Computing]() Tags: [ai](), [ai-factory](), [ai-infrastructure](), [capacity](), [compute](), [dsx](), [efficiency](), [inference](), [nvidia](), [orchestration](), [production]() ### AI overview The article describes how Emerald AI's Conductor platform responds to utility demand signals by adjusting flexible data-center workloads while keeping high-priority AI inference running. It also reports that Lambda's validation found a fixed power budget could support 24% more token throughput when managed intelligently. ### Source excerpt On a sweltering August evening in Silicon Valley, as the sun dropped and air conditioning loads spiked, Silicon Valley Power sent a signal to an AI factory to adjust its power consumption. Varun Sivaram was watching on Zoom with about forty others -- his team at Emerald AI in their San Francisco conference room, engineers [...] ## AI Infra Summit: NVIDIA Vera Rubin and DSX Platform Advancements Showcase Energy Efficiencies of Optimizing Tokens Per Watt for AI Factories DevFeed: [AI Infra Summit: NVIDIA Vera Rubin and DSX Platform Advancements Showcase Energy Efficiencies of Optimizing Tokens Per Watt for AI Factories]() Original publisher: [Read original article]() Author: NVIDIA Writers Published: 2026-09-15T16:55:40Z Content type: news Language: en Sources: [NVIDIA Blog]() Topics: [AI Infrastructure](), [Nvidia](), [DSX](), [Vera Rubin](), [Low-Latency Inference](), [NVLink](), [Conversational AI]() Tags: [ai](), [ai-infrastructure](), [dsx](), [inference](), [infra](), [latency](), [low-latency-inference](), [networking](), [nvidia](), [nvidia-blackwell](), [nvidia-dsx](), [nvidia-vera](), [nvidia-vera-rubin](), [nvlink]() ### AI overview NVIDIA's AI Infra Summit coverage describes collaborations and platform updates focused on improving AI factory efficiency. The article highlights Vera Rubin systems, DSX MaxLPS, Dynamo inference software, NVLink and networking technologies, including claims of up to 1.4x more tokens per megawatt through factory-wide power optimization. ### Source excerpt Ian Buck, vice president of hyperscale and high-performance computing at NVIDIA, Tuesday spoke on AI factory efficiency at the AI Infra Summit, the Santa Clara Convention Center event that has morphed into a Coachella of infrastructure tech. Before a packed audience -- with more than 8,000 attendees this year, up from 3,500 last year -- [...] ## How NVIDIA NVLink 6 Delivers Multi-Layer Resiliency for AI Factories DevFeed: [How NVIDIA NVLink 6 Delivers Multi-Layer Resiliency for AI Factories]() Original publisher: [Read original article]() Author: Elizabeth Goodman Published: 2026-09-15T16:55:00Z Content type: article Language: en Sources: [NVIDIA Developer](), [NVIDIA Technical Blog]() Topics: [NVLink](), [Nvidia](), [AI Factory](), [AI Infrastructure](), [Hardware]() Tags: [agentic-ai-generative-ai](), [ai](), [ai-factory](), [ai-infrastructure](), [data-center-cloud](), [hardware](), [industry](), [networking](), [networking-communications](), [nvidia](), [nvlink](), [resiliency](), [vera-rubin]() ### AI overview The article describes how NVIDIA NVLink 6 supports resiliency in large-scale AI factories. It explains that Vera Rubin NVL72 connects 72 Rubin GPUs into a single scale-up domain and outlines a multilayer approach using lossless networking, error correction, retry, flow control, and error containment to support continuous training and inference operations. ### Source excerpt For operators of large-scale AI factories, maximizing continuous output is essential for productivity. In massive-scale AI training, every GPU in the cluster... ## NVIDIA Adds CUDA-Q Logical for Fault-Tolerant Quantum Application Design DevFeed: [NVIDIA Adds CUDA-Q Logical for Fault-Tolerant Quantum Application Design]() Original publisher: [Read original article]() Author: Harold Fritts Published: 2026-09-15T16:47:58Z Content type: news Language: en Sources: [StorageReview.com]() Topics: [CUDA](), [Quantum Computing](), [Nvidia](), [Orchestration](), [Open Source](), [Algorithm]() Tags: [ai](), [algorithm](), [applications](), [cuda](), [enterprise](), [nvidia](), [open-source](), [orchestration](), [quantum]() ### AI overview NVIDIA added CUDA-Q Logical to its open-source CUDA-Q platform for designing applications on fault-tolerant quantum computers. Early-access reports say Fermilab reduced an algorithm design cycle from five months to three weeks, while Iceberg Quantum modeled a Diraq spin-qubit architecture using about 150,000 physical qubits for 1,000 logical qubits. ### Source excerpt NVIDIA has added CUDA-Q Logical to its open-source CUDA-Q platform, an orchestration layer for building applications that run on fault-tolerant quantum computers, and it arrives with two numbers that are interesting. Fermilab says the tool cut a fault-tolerant algorithm design cycle from five months to three weeks, and Iceberg Quantum used it to show that The post NVIDIA CUDA-Q Logical Debuts With a 7x Fermilab Speedup and a 10x Cut in Diraq's Qubit Estimate appeared first on StorageReview.com. ## Scaling Federated Learning Across Docker, Kubernetes, and Slurm with NVIDIA FLARE DevFeed: [Scaling Federated Learning Across Docker, Kubernetes, and Slurm with NVIDIA FLARE]() Original publisher: [Read original article]() Author: Elizabeth Goodman Published: 2026-09-15T15:00:00Z Content type: article Language: en Sources: [NVIDIA Developer](), [NVIDIA Technical Blog]() Topics: [Federated Learning](), [Docker](), [Kubernetes](), [Nvidia](), [Server](), [dataset](), [Deployment]() Tags: [architecture](), [compute](), [configuration](), [container](), [data-analytics-processing](), [data-science](), [dataset](), [deployment](), [docker](), [docker-container](), [federated-learning](), [gpu](), [job](), [kubernetes](), [nvidia](), [nvidia-flare](), [server]() ### AI overview This article explains how NVIDIA FLARE scales federated learning across sites with different infrastructure, including Docker, Kubernetes, and Slurm. Its two-layer architecture separates persistent federation services from on-demand job execution, while allowing each site to retain local control over compute, data, secrets, and scheduling. ### Source excerpt Federated learning (FL) projects often begin with a straightforward setup: one server, a few clients, and one dataset at each site. As those projects grow, the... ## MSI XpertStation WS300 Thermals: Why a 1,300W GB300 Doesn't Throttle on a Desk DevFeed: [MSI XpertStation WS300 Thermals: Why a 1,300W GB300 Doesn't Throttle on a Desk]() Original publisher: [Read original article]() Author: Brian Beeler Published: 2026-09-14T19:41:35Z Content type: article Language: en Sources: [StorageReview.com]() Topics: [Blackwell](), [cpu](), [GPU](), [Grace CPU](), [Nvidia](), [DGX Station]() Tags: [blackwell](), [consumer](), [dgx-station](), [gpu](), [grace-cpu](), [heat](), [memory](), [nvidia](), [performance](), [review](), [workstation]() ### AI overview The article explains why MSI's XpertStation WS300 can sustain a 1,300W GB300 Grace Blackwell Ultra Superchip without throttling on a desk. It attributes the thermal stability to cold plates covering the major heat-producing components, dual 360mm radiators, multiple fans, and a cooling loop rated above the system's nominal CPU and GPU load. ### Source excerpt The most common question we got about the MSI XpertStation WS300 after our review coalesces around one key theme. The GB300 Grace Blackwell Ultra Superchip is a 1,300W part that normally lives in a liquid-cooled rack, so what happens to thermals when you put it in a tower? The concern is fair: a GB300 system The post MSI XpertStation WS300 Thermals: Why a 1,300W GB300 Doesn't Throttle on a Desk appeared first on StorageReview.com. [Next page]()