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Newest first · page 4 of 28AIArticleNvidia espionage scandal weakens Huang's lobby against tighter AI chip export controlsNvidia CEO Jensen Huang admitted he had an inappropriate relationship with a woman suspected of being a Chinese intelligence informant. The board has launched an independent investigation. The scandal is likely to weaken Huang's lobbying to ease AI chip export restrictions.The Decoder AIOfficialNVIDIA Announces New Planned Investments in Korean Startups at the MSIT-NVIDIA AI Startup Partnership ForumNvidia announced plans to invest in Korean startups at an AI startup forum it held with the Ministry of Science and ICT. More than 20 Korean startups took part in the forum. Nvidia has already invested in Point2 and said it plans to invest further in Motif Technologies, RLWRLD, and Upstage.NVIDIA blog 
AIOfficialKorea Advances Physical AI Across Industries With NVIDIANvidia is helping AI move into machines and processes in the real world, building on Korea's strengths in manufacturing and engineering. Samsung Electronics, Kakao Mobility, and LG Electronics are each expanding their collaboration in their own fields.NVIDIA blog 
AIOfficialKorea’s AI Ecosystem Advances and Secures Agentic AI With NVIDIAAs AI agents (artificial intelligence programs that handle tasks on their own) become more common, technology to manage them safely is becoming important. Nvidia's blog introduced how Korean companies are releasing security tools and AI models to keep up with this trend.NVIDIA blog 
AIOfficialFrom Chips to Skills, NVIDIA and Korea Expand Sovereign AI CollaborationNvidia is expanding its cooperation with South Korea's Ministry of Science and ICT. The work covers many areas, from chips and data centers to talent development, startups, AI models, and security.NVIDIA blog 
AIOfficialNVIDIA Dynamo Recipes Bring Korea’s Leading Open Models to ProductionNVIDIA has released deployment settings that let four open AI models made by Korean companies run quickly across multiple GPUs (graphics processing units). The settings are optimized for NVIDIA's open-source tool Dynamo.NVIDIA blog 
AIArticleDeepSeek Passes 1.54 Million Daily Users as Nvidia CEO Faces InvestigationThe daily users of DeepSeek, a Chinese AI company, have passed 1.54 million. On the same day, it was reported that Nvidia's chief executive officer (CEO) is under investigation. You can check the full details in the original article.AI news RobotsVideoHow Siemens Accelerates Production Planning and Quality Control With NVIDIA AIGermany's Siemens, which makes industrial products and automation equipment, has released a video showing how it uses NVIDIA AI tools to speed up production planning and quality control. It covers using AI agents, programs that divide up and handle tasks on their own, together with digital twins, which are virtual copies of real equipment, to help run factories.NVIDIA on YouTube 
AIOfficialSpeed Up Image Generation with FLUX 3 Image Klein on NVIDIA Blackwell GPUsNVIDIA has explained how to run the FLUX 3 Image Klein image generation model faster on Blackwell GPUs. By combining several optimization techniques, it greatly reduced the time needed to create images.NVIDIA Technical blog AIArticleAWS Adds NVIDIA GPU Partitioning to SageMaker Inference Endpoints to Cut CostsAWS now lets a single GPU be split into several pieces on SageMaker real-time endpoints, so multiple models can share it. This uses resources more efficiently than giving an entire GPU to one model. However, it does not benefit every workload.Quantum news 
AIOfficialAccelerating Reinforcement Learning Weight Refit with the Reshard CollectiveIn reinforcement learning post-training, the latest model weights must be continuously moved from training GPUs to inference GPUs. This transfer is called refit, and as models have grown, the amount of data that must be moved at once has increased sharply. NVIDIA introduced Reshard, a new communication method that moves only the necessary data.NVIDIA Technical blog QuantumOfficialHow NVIDIA Open Source Tools Are Helping Researchers Build Next-Generation 6G NetworksNVIDIA's released wireless software and open-source tools are being used in 6G network research. Researchers are testing ways to help robots react faster and receive signals better.NVIDIA blog 
AIOfficialVera Delivers the Best of Both Worlds: Highest Throughput and Fastest AgentsAI agents handle tasks like searching, querying databases, and writing and running code, and each of these steps needs a CPU (the central processing unit of a computer). NVIDIA says its new Vera CPU delivers both high speed and high throughput per unit of power in a single chip.NVIDIA blog 
RobotsOfficialNew NVIDIA Cosmos 3 Open Models for Interactive World SimulationNVIDIA has released four AI models that make virtual worlds nearly real-time. It has opened them so anyone can download the model weights (the values an AI gets through training). They are mainly tools used by robotics and self-driving researchers.Hugging Face blog AIVideoWashington, D.C. is up next. 🏛️NVIDIA's official channel posted a short teaser video. It says the next event will be held in Washington, D.C., the U.S. capital.NVIDIA on YouTube 
AIOfficialConfigure, Certify, and Operate Kubernetes GPU Clusters with NVIDIA DSX OSNVIDIA has introduced DSX OS, a set of open-source software for setting up, verifying, and running Kubernetes clusters (tools that group multiple computers together and manage programs across them) that use GPUs. Even after a cluster is first certified, its condition keeps changing as hardware is replaced or drivers are upgraded, so these tools help run repeated checks at several stages.NVIDIA Technical blog AIOfficialThe Wizard of Open Weights: Chris Alexiuk Makes AI Easy With Open ModelsChris Alexiuk, an NVIDIA engineer, works to spread awareness of open-source AI that anyone can use. He teaches AI development on YouTube and shares his knowledge with many people.NVIDIA blog 
Chips & deep techOfficialFive Ways NVIDIA Co-Design Maximizes the Value of Every Byte in the AI FactoryIn data centers that run AI services, how usefully companies use high-bandwidth memory (HBM, fast memory attached next to the GPU) has become important, because it is fast but expensive and scarce. NVIDIA says it is solving this problem by designing chips, software, CPUs, and storage together.NVIDIA Technical blog Chips & deep techOfficialMore Performance From Every Byte: How Full-Stack Codesign Solves AI’s Memory ChallengeAs AI grows and handles longer conversations, GPU high-speed memory is running short. Instead of simply adding more memory, NVIDIA says it designs GPUs, CPUs, networks, storage, and software together so the same memory can do more work.NVIDIA blog 