Image created with gemini-2.5-flash-image with claude-sonnet-4-5. Image prompt: Cinematic 80s suburban front porch at Halloween dusk, warm amber lighting, carved pumpkins and fall leaves, close-up of ceramic bowl filled with gleaming silicon wafers and computer chips instead of candy, child’s hand reaching toward bowl, Spielberg-style nostalgic glow, shallow depth of field.
About a year ago, this site near South Bend, Indiana was just cornfields. Today, it’s 1 of our U.S. data centers powering Project Rainier – one of the world’s largest AI compute clusters, built in collaboration with @AnthropicAI. It is 70% larger than any AI computing platform https://x.com/ajassy/status/1983616724642730217
Meta’s $75B AI Infrastructure Bet: Inside the Biggest Cloud Deals of 2025 https://allenarch.dev/blog/meta-75b-ai-infrastructure-bet/
Nvidia just released ChronoEdit-14B on Hugging Face enables physics-aware image editing and action-conditioned world simulation through temporal reasoning. It distills priors from a 14B-parameter pretrained video generative model and separates inference into (i) a video https://x.com/_akhaliq/status/1983953896415604836
👀 Meet @NVIDIAAI Nemotron Nano 2 VL, now hosted on Nebius AI Studio – 10× higher throughput – Document + video intelligence – Open weights, open data – Ready for production Build multimodal assistants today → https://x.com/nebiusaistudio/status/1983243873317974318
NVIDIA Launches Open Models and Data to Accelerate AI Innovation | NVIDIA Blog https://blogs.nvidia.com/blog/open-models-data-ai/
Nvidia becomes first company to reach $5 trillion valuation https://www.cnbc.com/2025/10/29/nvidia-on-track-to-hit-historic-5-trillion-valuation-amid-ai-rally.html
A new open-source physics engine just dropped… and it could change how robots learn. Newton, built by @nvidia with support from @GoogleDeepMind and Disney Research, is now part of The Linux Foundation. It’s designed to bring precise, GPU-powered physics to robotics and https://x.com/IlirAliu_/status/1982726852507521065
We just launched new open models and datasets to make AI research and development more accessible 🤝 You now have open foundations to build specialized intelligent agents faster, safer, and at scale — from Nemotron to Cosmos, Isaac GR00T to Clara. Over 650 open models and 250 https://x.com/NVIDIAAIDev/status/1983227688333574318
Jensen at NVIDIA GTC: It’s likely that humanoid robots, which my friend Elon is also working on, will be one of the largest consumer electronics markets and one of the largest industrial equipment markets. https://x.com/TheHumanoidHub/status/1983230275694760271
Sam Altman Seeks Trillions of Dollars to Reshape Business of Chips and AI – WSJ https://www.wsj.com/tech/ai/sam-altman-seeks-trillions-of-dollars-to-reshape-business-of-chips-and-ai-89ab3db0?gaa_at=eafs&gaa_n=AW
(28) NVIDIA GTC Washington, D.C. Keynote with CEO Jensen Huang – YouTube https://www.youtube.com/watch?v=lQHK61IDFH4&t=2s
@SemiAnalysis_ Noticing a shift toward open, self-hosted GPU orchestration tools. @dstackai seems worth a look if you’re avoiding lock-in. It’s available under MPL-2.0 licence: https://x.com/andrey_cheptsov/status/1984136998190510280
A shoutout to @modal for sponsoring GPUs for ArcticTraining CI – thank you very much, @akshat_b and the Modal team! https://x.com/StasBekman/status/1984293939583856751
After months of feedback from our early customers and thousands of jobs completed, Baseten Training is officially ready for everyone. 🚀 Access compute on demand, train any model, run multi-node jobs, and deploy from checkpoints with cache-aware scheduling, an ML Cookbook, tool https://x.com/basetenco/status/1983958807353934180
Hello Thermo World. https://x.com/Extropic_AI/status/1983579587649904960
Releasing Fast-Plaid 1.2.5 FastPlaid is the counterpart of Faiss / pgvector for late-interaction model which we we design at @LightOnIO. It’sCompatible with ColPali, ColQwen and PyLate of course. Faster and less GPU memory usage”” / X https://x.com/raphaelsrty/status/1983906400725024931
We are excited to partner with @lmsysorg on the release of SGLang-jax, streamlining provisioning, interactive development & scaling of LLMs on TPUs. Great milestone for SGLang to natively support TPUs! Easiest way to run sglang-jax on TPU: $ sky launch sgl-jax.yaml https://x.com/skypilot_org/status/1983957542863851899
If you’re running LLM inference at scale and still relying solely on “requests per second” or “GPU usage,” you might be missing critical insights. At Red Hat, we’ve been rethinking observability for LLM systems, from token throughput and latency metrics to cache reuse and https://x.com/RedHat_AI/status/1983193927105622126
Super excited to launch a new AI course! 🚀 Fine-Tuning & Reinforcement Learning for LLMs: Intro to Post-Training A collaboration between @AMD 🤝 @AndrewYNg’s @DeepLearningAI to give every developer the tools & compute to work with the same post-training techniques, used across https://x.com/realSharonZhou/status/1983202270335664156
A small follow-up to my DGX Spark post. Courtesy of NVIDIA, I got to try the DGX on my workflows (coding LLMs from scratch in pure PyTorch) and wanted to share my first impressions after using it for a week. Before getting to the performance, there was a neat bonus I didn’t https://x.com/rasbt/status/1983895811915214996
🚀Excited to team up with @NVIDIAAIDev to bring Nemotron Nano 2 VL to vLLM – a multimodal model powered by a hybrid Transformer-Mamba language backbone, built for video understanding and document intelligence✨ Full post here👇 https://x.com/vllm_project/status/1984334926972592193
We are so excited to be a launch partner for @nvidia Nemotron Nano 2 VL today and offer day-zero support for this highly accurate and efficient vision language model, alongside other models in the Nemotron family. To learn more, read our blog here https://x.com/basetenco/status/1983243273171845596
Got to say hi to @adcock_brett at the NVIDIA GTC pregame. Jensen’s keynote starts in one hour. https://x.com/TheHumanoidHub/status/1983187543349965082
people are sleeping on this release NVIDIA blessed us with a new family of Nemotron RAG models 🔥 it comes with text retrievers, multimodal retrievers as well as layout detectors with commercially permissive license 👏 https://x.com/mervenoyann/status/1984302303570960666
Nemotron Nano VL 12B V2 by @nvidia is now on Replicate A 12B vision-language beast for document intelligence & video understanding. Handles up to 4 images or 1 video, extract data from invoices, compare pics, summarize clips, all in 10 languages! https://x.com/replicate/status/1983242266836890026
I spoke at NVIDIA yesterday about Figure and why solving general robotics is priority zero https://x.com/adcock_brett/status/1983576387895357643
Jensen’s keynote discussing NVIDIA + Figure https://x.com/adcock_brett/status/1983522032924111224
w/ Jensen at NVIDIA GTC https://x.com/adcock_brett/status/1983219943073362041
Brett Adcock at NVIDIA GTC: Solving general-purpose AI for humanoid robots is ten to a hundred times harder than making the humanoid robots. https://x.com/TheHumanoidHub/status/1983199160875790426
Listening to Jensen talk about his favorite maths – specs of Vera Rubin chips, and the full stack from lithography to robot fleets assembling physical fabs in Arizona & Houston. Quoting Jensen, “these factories are basically robots themselves”. I visited NVIDIA facilities https://x.com/DrJimFan/status/1983232823784853998
Clearly NVIDIA’s nccl isn’t good enough for scaling up as there are new alternative collective comms libraries being developed Meta has published a paper on NCCLX Collective Communication for 100k+ GPUs https://x.com/StasBekman/status/1982861472024932409
NVIDIA Just Released 8M Sample Open Dataset + OCR Tooling on @huggingface – 3x larger than v1 (just 2 months ago!) – Image/video QA, reasoning, multilingual OCR – Commercial-ready (CC-BY-4.0) @NVIDIAAI is one of the few major AI labs releasing datasets 🤗 https://x.com/vanstriendaniel/status/1983238971644608924
”NVIDIA Isaac GR00T N open reasoning VLA models are now integrated into @huggingface’s LeRobot with the v0.4.0 release. 🤖 Making it easier than ever for the open-source robotics community to customize and deploy robot foundation models. 👉 https://x.com/NVIDIARobotics/status/1983564485588549657
Yesterday we did a livestream. TL;DR: We have set internal goals of having an automated AI research intern by September of 2026 running on hundreds of thousands of GPUs, and a true automated AI researcher by March of 2028. We may totally fail at this goal, but given the”” / X https://x.com/sama/status/1983584366547829073
NEO Specs – Weight: 66 lbs – Height: 5’6″” – Lift Capacity: 154 lbs – Carry Capacity: 55 lbs – Battery Life: 4 Hours (with Fast Charging) – Processor: Based on NVIDIA Jetson Thor – Vision: 2x 8MP Fisheye Cameras – 4 Mics, 3 Speakers – Noise Level: 22 dB (Max) – 22 DoF hand https://x.com/TheHumanoidHub/status/1983306801551376611
After ~4 years building SOTA models & datasets, we’re sharing everything we learned in ⚡The Smol Training Playbook We cover the full LLM cycle: designing ablations, choosing an architecture, curating data, post-training, and building solid infrastructure. We’ll help you https://x.com/LoubnaBenAllal1/status/1983929546014433385
Circuits Updates – October 2025 https://transformer-circuits.pub/2025/october-update/index.html#svg-cross-modal
I was puzzled by why their paper claims “”bfloat16″” training crashes — since we trained for 100,000 GPU hours and 7K+ training steps for both dense and MoEs in the ScaleRL paper stably without any crashes. I think it matters what kind of GPUs they used — they mention in the https://x.com/agarwl_/status/1984416235774247273
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