Image created with gemini-2.5-flash-image with claude-sonnet-4-5-20250929. Image prompt: A majestic stone courtroom interior with dark oak paneling, where a large golden NVIDIA GPU die is embedded as an ornate judicial seal above the bench, its circuit patterns rendered like heraldic engravings, illuminated by warm light streaming through tall leaded windows in the style of Lincoln’s Inn.
Nvidia and Intel announce jointly developed ‘Intel x86 RTX SOCs’ for PCs with Nvidia graphics, also custom Nvidia data center x86 processors — Nvidia buys $5 billion in Intel stock in seismic deal | Tom’s Hardware https://www.tomshardware.com/pc-components/cpus/nvidia-and-intel-announce-jointly-developed-intel-x86-rtx-socs-for-pcs-with-nvidia-graphics-also-custom-nvidia-data-center-x86-processors-nvidia-buys-usd5-billion-in-intel-stock-in-seismic-deal
NVIDIA and Intel to Develop AI Infrastructure and Personal Computing Products | NVIDIA Newsroom https://nvidianews.nvidia.com/news/nvidia-and-intel-to-develop-ai-infrastructure-and-personal-computing-products?ncid=so-twit-672238
Teams at Nvidia and Intel have been working in secret on jointly developed processors for a year — ‘The Trump administration has no involvement in this partnership at all’ | Tom’s Hardware https://www.tomshardware.com/pc-components/cpus/teams-at-nvidia-and-intel-have-been-working-in-secret-on-jointly-developed-processors-for-a-year-the-trump-administration-has-no-involvement-in-this-partnership-at-all
Jensen Huang ‘disappointed’ by reported China Nvidia chip ban https://www.bbc.com/news/articles/cqxz29pe1v0o
The new open-source Qwen3-Next Instruct and Thinking models put state-of-the-art long-context reasoning into the hands of everyone. We collaborated with #opensource frameworks from SGLang (@lmsysorg) and @vllm_project to enable communities to deploy Qwen3-Next across the https://x.com/NVIDIAAIDev/status/1967575419638468667
Serving a model at scale is hard. Serving it across three hardware platforms (AWS Trainium, NVIDIA GPUs, Google TPUs) while maintaining strict equivalence is a whole other level. Makes you wonder if the hardware flexibility is truly worth the hit to development speed and https://x.com/_philschmid/status/1968586407548518565
Scaling AI requires leaps in hardware. NVIDIA Blackwell is the latest step forward. On Oct 1, we’re bringing together Dylan Patel (@SemiAnalysis_), Ian Buck (@nvidia) and Charles Zedlewski (Together AI) to unpack its architecture, optimizations and impact on AI infrastructure. https://x.com/togethercompute/status/1968367704621863154
Stanford Seminar – Nvidia’s H100 GPU Deep dive into H100’s architecture, covering Hopper streaming multiprocessors, Transformer Engine, NVLink interconnects, and HPC/AI workloads optimization strategies. https://x.com/vivekgalatage/status/1968117707812774259
“People who are serious about robot learning should build their own hardware,” says NVIDIA’s embodied AI research co-lead. This is likely a general statement, not a hint at NVIDIA’s plans, but it would be awesome if NVIDIA designed and made its own robot hardware. https://x.com/TheHumanoidHub/status/1966216768290222552
