Every week, I organize 400 to 700 links into roughly 60 categories as part of my ongoing effort to learn about AI. This is my personal notebook, which I enjoy sharing with friends… a hobby and a labor of love, rather than a commercial publication or product.
If you arrived here through a search or shared link, this page collects the links I found for NVIDIA for the week ending July 31, 2026.
As part of my learning process, I like to automate the category covers. It gives me a chance to learn Python and APIs.
This week’s cover prompt was written using Claude Opus 4.7, and the image was generated using Gemini 3.1 Flash Image Preview.
Category Cover Image Prompt: Cinematic 1980s neo-noir movie poster of a matte primer gray 1973 Chevrolet Chevelle Malibu with its hood popped open in a dim Los Angeles parking garage at night, revealing an oversized server-grade GPU with twin fans glowing emerald green where the engine should be, a single anonymous gloved hand resting on the fender, sodium-vapor amber haze and deep teal shadows, 35mm anamorphic grain with soft halation, wet concrete reflections, the words 'NVIDIA' scrawled in the upper third as a quick hot magenta-pink handwritten brush script resembling Mistral typeface with a faint glow, cinematic negative space, no other text.
This Week in NVIDIA News
Summary by Claude Sonnet 5.5 based on this week’s links:
- Open Secure AI Alliance: Nvidia launched the alliance to share models, tooling and research for securing software and agents. Hugging Face, LangChain, Databricks and OpenClaw announced they were joining. Jensen Huang argued that during the Hugging Face incident, closed AI blocked forensics while an open-weight model helped contain the intrusion. A Reddit post claimed OpenAI management chose not to join.
- Open-weights letter: Nvidia and Microsoft were among the signers of a letter urging policymakers not to restrict open-weight models. Per Andrew Curran, OpenAI, Anthropic, Google and xAI did not sign. Andrew Ng called the letter well written and worth reading.
- Big compute deals: Nvidia is making a substantial investment in Ilya Sutskever's Safe Superintelligence, which says it will let SSI scale its compute tenfold over the next 12 months. SSI had mainly relied on Google's TPUs before this. Separately, the WSJ reported Nvidia is in talks to guarantee $250 billion in financing for an OpenAI data center lease in Ohio.
This summary was generated by Claude Sonnet 5.5 to help you explore the links below. Rest assured, I select, organize, and check the links by hand in Google Sheets, and write the introduction and personal commentary in The Main Newsletters myself each week as a labor of love.
This week's links related to NVIDIA
NVIDIA has been an incredible partner in helping make OpenClaw more secure. Security is a team sport, and open collaboration is how we protect the next generation of agents. Proud to join the Open Secure AI Alliance. More defenders, fewer sharp corners. 🦞🔐”
https://x.com/openclaw/status/2081791120858837465
Proud to be an inaugural partner alongside @NVIDIA and other industry leaders in the Open Secure AI Alliance. We look forward to accelerating the adoption and trust of open models and harnesses through this initiative.”
https://x.com/LangChain/status/2081708229663277365
Databricks has joined Nvidia as a member of the Open Secure AI Alliance. Open models, open agent frameworks, and open security tools aren’t the threat. They’re the infrastructure that defenders need. We believe open AI powers innovation.”
https://x.com/Yuchenj_UW/status/2081788381076574295
Nvidia is making a “substantial” investment in Ilya Sutskever’s Safe Superintelligence, and providing enough GPUs to increase its compute tenfold. SSI had previously relied mainly on Google’s TPUs. The new long-term partnership gives the secretive AI lab access to Nvidia’s”
https://x.com/kimmonismus/status/2081740668125225229
Ilya Sutskever’s Safe Superintelligence partners with Nvidia to scale its AI research | TechCrunch
https://techcrunch.com/2026/07/27/ilya-sutskevers-safe-superintelligence-partners-with-nvidia-to-scale-its-ai-research/
Yes, this is the real Jensen Huang. Satya Nadella shared the same letter this morning. It was released simultaneously by the companies and organizations listed here, urging policymakers not to restrict open-weight models. OpenAI, Anthropic, Google and xAI did not sign the letter.”
https://x.com/AndrewCurran_/status/2080668162765520955
Exclusive | Nvidia in Talks With OpenAI to Guarantee $250 Billion Financing to Lease Ohio Data Center – WSJ
https://www.wsj.com/tech/ai/nvidia-in-talks-with-openai-to-guarantee-250-billion-financing-for-data-center-3dd6eae3
OpenAI management decided earlier today not to join the “Open Secure AI Alliance”, founded by Nvidia CEO Jensen Huang. The decision was shared internally and reportedly met with backlash from employees. : r/LocalLLaMA
https://www.reddit.com/r/LocalLLaMA/comments/1v8e36c/openai_management_decided_earlier_today_not_to/
We are announcing a long-term strategic partnership with NVIDIA. NVIDIA is making a substantial investment in SSI that will let us 10x our compute in the next 12 months. We reached the point where our research is worth scaling and with this partnership we will be able to. We are”
https://x.com/ssi/status/2081732119194394763
Good move by @JensenHuang. The Nvidia letter is well written and worth reading. As we saw with the OpenAI-Hugging Face hack, we need open models and harnesses for defense. Lets stop believing the PR that closed models are safer. – that’s just regulatory capture.”
https://x.com/AndrewYNg/status/2081787106062746002
AI security improves when organizations share research, tools and real-world experience. We’re joining industry leaders, including @NVIDIA, in the Open Secure AI Alliance to help organizations identify and address software vulnerabilities and strengthen critical systems. Learn”
https://x.com/huggingface/status/2081718698608402818
Attackers have frontier AI. Defenders need a frontier AI ecosystem… the best open and closed models, force-multiplied by a global community. During the Hugging Face incident, closed AI blocked essential forensics. An open-weight frontier model helped contain the intrusion.”
https://x.com/JensenHuang/status/2081698060330250294
Open models are critical to American AI leadership, driving innovation, competition and national security. Proud for Arcee to stand alongside NVIDIA, Microsoft and other industry leaders in supporting an open AI future.”
https://x.com/MarkMcQuade/status/2080702381084610574
For my first post, I’m sharing a letter @NVIDIA signed on why open models matter. AI will transform every industry, power every company, and be built by every country. Open models strengthen safety and cybersecurity, accelerate innovation and diffusion, and enable sovereignty.”
https://x.com/JensenHuang/status/2080643682408321103
Industry Leaders Join Open Secure AI Alliance for AI Safety and Security | NVIDIA Blog
https://blogs.nvidia.com/blog/open-secure-ai-alliance/
Open Weights and American AI Leadership
https://images.nvidia.com/pdf/Open-Weights-and-American-AI-Leadership.pdf
Moonshot Openly Defies The Trump Administration By Seeking Access To Additional NVIDIA GPUs For Training The Next-Gen Kimi K4 Model
https://wccftech.com/moonshot-openly-defies-the-trump-administration-by-seeking-access-to-additional-nvidia-gpus-for-training-the-next-gen-kimi-k4-model/
AI security advances when the industry builds in the open, together. We’re introducing the Open Secure AI Alliance with industry leaders to develop new techniques and tools to safeguard software and agents. By sharing models, tooling and research in the open, we can broaden the”
https://x.com/nvidia/status/2081666629264449730
New research from NVIDIA. They just dropped a PyTorch-native training framework for agentic RL. (bookmark it) Paper summary: Molt is a PyTorch-native agentic RL framework with an unusual design target. The codebase should be compact enough for a researcher to hold in their”
https://x.com/dair_ai/status/2081770344952803628
We just published a guide to installing OpenCV 5 on Linux. The teaser image maps three tested routes: Python wheel, CPU source build, and CUDA source build. Pick the smallest one your application actually needs.”
https://x.com/LearnOpenCV/status/2080889571018244443
FastGen-PDD: Parallel Decoding Distillation for Image and Video Generation
https://research.nvidia.com/labs/genair/pdd/
Kimi K3 has first class support for vLLM on NVIDIA! vLLM serves K3 across Grace Blackwell, Blackwell, Hopper, and NVL72 systems, also integrating with Dynamo to keep a model this large, fast and efficient at production scale. Available Day 0, the moment the weights went public.”
https://x.com/vllm_project/status/2082559386535550983
AI leadership is built through a thriving open ecosystem that enables every company, researcher, and institution to build, improve, and own its intelligence. Open-weight models are essential to that future. Thank you Jensen and Satya for your leadership! Proud to have Prime”
https://x.com/vincentweisser/status/2080883585050202475
@JensenHuang @nvidia Happy to see that @JensenHuang explicitly mentions distillation”
https://x.com/SchmidhuberAI/status/2080704707526377562
@JensenHuang @nvidia”
https://x.com/DennysDiner/status/2081069889931112816
Jensen, who is running the Alliance? We think @natolambert will be an excellent choice for that”
https://x.com/TheTuringPost/status/2081746218699346007
NVIDIA Exemplar Cloud: Lessons for Unlocking Full Performance on AI Infrastructure | NVIDIA Technical Blog
https://developer.nvidia.com/blog/nvidia-exemplar-cloud-lessons-for-unlocking-full-performance-on-ai-infrastructure/
The best first post we could’ve hoped for from Jensen Huang”
https://x.com/TheTuringPost/status/2080962531040850310
What’s in @saranormous’s bag? The ultimate robotics brain. 🧠 NVIDIA Jetson AGX Thor, packing up to 2,070 FP4 TFLOPS of AI compute and 128 GB of memory. Power next generation humanoids and autonomous systems with real-time reasoning and server class performance, built for the”
https://x.com/NVIDIARobotics/status/2082846134024765679
ModelExpress: Distributing Model Artifacts at the Speed of Light | NVIDIA Technical Blog
https://developer.nvidia.com/blog/modelexpress-distributing-model-artifacts-at-the-speed-of-light/
One easy trap: Ubuntu 24.04 can install OpenCV 4.6.0 even when apt install python3-opencv succeeds. Do not stop at cv2.__version__. Check the import path, libraries, required backends, and real CUDA work if GPU support matters. Read the guide:”
https://x.com/LearnOpenCV/status/2080889572549087260
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