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NVIDIA

AI compute, chips, and accelerated computing

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Showing 20 of 394 matching collected records. Text matches can include mentions by other organizations.

  1. Sep 25, 2026 · UTC · TechCrunch AI

    Ahead of US IPO, British AI neocloud Nscale secures $3.36B in convertible financing

    The funding, which comes from Third Point, Nvidia, and others, will fuel the company's massive AI data center buildout.

  2. Sep 24, 2026 · UTC · The Verge AI

    Jensen Huang talks about AI and climate change like a supervillain

    As Jensen Huang puts it, AI can help fight climate change - but only if it inflicts "an enormous amount of pain and suffering" first. The Nvidia CEO discussed the future of energy and AI's impact on our planet in the latest episode of The Ezra Klein Show. But his comments boil down to the […]

  3. Sep 24, 2026 · UTC · Hugging Face Models

    nvidia/Nemotron-3-Diarization

  4. Sep 23, 2026 · UTC · Hugging Face Blog

    How to Use NVIDIA Warp and MjWarp to Accelerate Robotics Simulation and Learning Workflows

  5. Sep 23, 2026 · UTC · arXiv · AI, language, vision and robotics

    GLASS: Architecture-Tuned, Composable, Device-Side Linear Algebra for Edge Robotics and Beyond

    GPU robotics lacks the reusable numerical infrastructure of mature CPU stacks, instead relying on compiler frameworks that introduce overhead or repeatedly reimplementing numerical libraries. To address this, we introduce GLASS (GPU Linear Algebra Simple Subroutines), a header-only CUDA C++ library that provides thread-, warp-, block-, and NVIDIA-backed implementations of robotics-scale linear algebra and geometric computations under one composable device API. GLASS treats implementation choice, execution scope, and launch packing as architecture-specific placement decisions determined by offl

  6. Sep 23, 2026 · UTC · Hugging Face Blog

    **Know Who Spoke When: Build Real-Time, Multi-Speaker AI with NVIDIA Nemotron 3 Diarization**

  7. Sep 23, 2026 · UTC · arXiv · AI, language, vision and robotics

    Evaluating Open-Weight LLMs for Turkish Domain Documents Under Retrieval and Hardware Constraints

    Most Turkish-capable large language models (LLMs) are evaluated using general-purpose benchmarks rather than long, structurally complex domain documents. This paper evaluates five open-weight 7B-8B models for Turkish document question answering under a resource-constrained local deployment setting. The primary benchmark contains 100 systematically validated questions derived from a 109-page industrial R&D report, and the evaluation protocol is replicated using a second 112-page public-sector report and an independently constructed 100-question set. All models are evaluated locally on an NVIDIA

  8. Sep 23, 2026 · UTC · NVIDIA AI

    At AI Day Singapore, NVIDIA and Partners Showcase AI Advancements Across Southeast Asia

    NVIDIA AI Day Singapore, which takes place Sept. 22-23 at the Raffles City Convention Centre, is offering attendees opportunities to explore the hands-on training, expert-led sessions and advanced tools to accelerate their work in AI and high-performance computing. At the event, NVIDIA and its partners are showcasing breakthrough AI advancements across the Southeast Asia region […]

  9. Sep 22, 2026 · UTC · The Verge AI

    Andreessen Horowitz is launching an ‘academy’ with no homework and partnerships with Palantir, Google, and Meta

    Venture capital firm Andreessen Horowitz (a16z) is creating an "academy" positioned as a pipeline for young people to build or join a Silicon Valley startup. The "Horowitz Andreessen Academy" will launch with 10 partners, including Anduril, Anthropic, Coinbase, Google, Meta, Nvidia, OpenAI, Palantir, Replit, and Stripe, along with $42 million in funding led by a16z. […]

  10. Sep 22, 2026 · UTC · TechCrunch AI

    Five AI safety sessions every founder should have on their TechCrunch Disrupt 2026 agenda

    At TechCrunch Disrupt 2026, five sessions across the AI Stage and Real World AI Stage cover AI safety, featuring leaders from Anthropic, Nvidia, AWS, Waabi, and more. Register before September 25 to save up to $200.

  11. Sep 22, 2026 · UTC · NVIDIA Newsroom

    NVIDIA Isaac ROS 5.0 Advances Agentic, Open Source Robotics Development

    To build and deploy sophisticated robotics applications that can perceive, reason and act in dynamic environments, developers need new physical AI models and tools. The ROS open framework is a project from Open Robotics that helps humans build robots. NVIDIA Isaac ROS 5.0 — a collection of GPU-accelerated packages built on ROS, released today at […]

  12. Sep 22, 2026 · UTC · EPO Open Patent Services

    Anomalous event detection

    Patent publication US12743580B1 · Applicant: NVIDIA CORP. Bibliographic metadata from the European Patent Office.

  13. Sep 22, 2026 · UTC · OpenAlex research metadata

    The Evolution of NVIDIA AI Accelerators and Their Impact on Artificial Intelligence Model Performance: A Comparative Analysis of NVIDIA A100, H100, H200, and Blackwell Architectures

    Comprehensive Journal of Science · Advanced Neural Network Applications

  14. Sep 21, 2026 · UTC · NVIDIA Newsroom

    NVIDIA Launches DSX Ready to Qualify Power and Cooling Products for AI Factories

    Every AI factory needs power and cooling that fit its computing architecture. As AI infrastructure expands, power, cooling, water, site and grid constraints are shaping what builders can deploy. Choosing products that fit the complete factory design helps builders turn computing capacity into useful AI output. To help builders make those decisions, NVIDIA is introducing […]

  15. Sep 21, 2026 · UTC · NVIDIA AI

    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 […]

  16. Sep 21, 2026 · UTC · NVIDIA Newsroom

    Why Deploying Physical AI at Scale Demands Safety at Every Layer

    Physical AI is moving rapidly from research to large-scale deployment. By 2035, ABI Research projects an installed base of 49 million level 3-5 autonomous vehicles (AVs), while Omdia estimates that roughly 60 million industrial robots will be deployed between 2026 and 2035. As these machines enter roads, factories, warehouses and other environments shared with people, […]

  17. Sep 21, 2026 · UTC · NVIDIA AI

    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, […]

  18. Sep 21, 2026 · UTC · NVIDIA AI

    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 […]

  19. Sep 20, 2026 · UTC · The Verge AI

    No one is surprised that Nvidia’s Jensen Huang thinks AI fears are overblown

    The man who may stand to make the most money from the AI boom seems to think he knows better than anyone else, including researchers who have studied and worked on AI for decades. In an interview with CBS Sunday Morning, he claimed there was a "0% chance" of AI being the end of the […]

  20. Sep 20, 2026 · UTC · arXiv · AI, language, vision and robotics

    ARID: A Deployable Edge AI System for Structured Information Extraction from Industrial Maintenance Work Orders

    Maintenance work orders must often be processed offline on embedded hardware, yet downstream software requires predictable structured output. We present ARID (Aviation-inspired Routing for Industrial Deployment), which extracts component, failure mode, symptom, and maintenance action into fixed-schema JSON on an 8 GB NVIDIA Jetson Orin NX. ARID combines conservative dual-teacher filtering, targeted noise-aware synthesis, one routing decision per work order, 4-bit inference, and grammar-constrained decoding. From 2,326 unlabeled OMIn records, it retains 716 training pairs and adds 99 topology-c

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