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Introducing DreamZero 🤖🌎 from @nvidia > A 14B “World Action Model” that achieves zero-shot generalization to unseen tasks & few-shot adaptation to new robots > The key? Jointly predicting video & actions in the same diffusion forward pass Project Page: https://x.com/jang_yoel/status/2019083437265867057
New milestone: we trained a robot foundation model on a world model backbone, and enabled zero-shot, open-world prompting capability for new verbs, nouns, and environments. If the world model can “”dream”” the right future in pixels, then the robot can execute well in motors. We”” https://x.com/DrJimFan/status/2019112603637920237
📢 New paper from GEAR team @NVIDIARobotics We released DreamZero, a World Action Model that turns video world models into zero-shot robot policies. Built on a pretrained video diffusion backbone, it jointly predicts future video frames and actions. 🌐”” https://x.com/yukez/status/2019096072690553112
Why Nvidia builds open models with Bryan Catanzaro https://www.interconnects.ai/p/why-nvidia-builds-open-models-with
Nvidia CEO Huang denies he’s unhappy with OpenAI, says huge investment planned https://www.cnbc.com/2026/01/31/nvidia-ceo-huang-denies-hes-unhappy-with-openai.html
Introducing NVIDIA Cosmos Policy for Advanced Robot Control https://huggingface.co/blog/nvidia/cosmos-policy-for-robot-control
DreamZero: World Action Models are Zero-shot Policies
https://dreamzero0.github.io/
Jim Fan on X: “The Second Pre-training Paradigm” / X
https://x.com/DrJimFan/status/2018754323141054786
Website: https://t.co/2YwjQs3JMC Robot execution demos across various verbs, nouns, and environments: https://t.co/loUZXZODcR The model is open-source! https://x.com/DrJimFan/status/2019112605315637451
📈 vLLM community + @nvidia pushed gpt-oss-120b performance on Blackwell GPUs to new heights: ⚡ +38% max throughput 🎯 +13% min latency 📈 Entire Pareto frontier improved Key ingredients: FlashInfer integration, torch.compile kernel fusions, async scheduling, and stream”” https://x.com/vllm_project/status/2018859316258931161
🚀🚀🚀 vLLM on NVIDIA GB200: 26.2K prefill TPGS, 10.1K decode TPGS for DeepSeek R1/V3. 📈 3-5x throughput vs H200 – with half the GPUs! Key optimizations: – NVFP4 GEMM for MoE experts – FP8 GEMM for MLA – Kernel fusion (RoPE+Quant+Q Write) – Weight offloading v2 with async”” https://x.com/vllm_project/status/2019105689403334825
Nemotron ColEmbed V2: Raising the Bar for Multimodal Retrieval with ViDoRe V3’s Top Model https://huggingface.co/blog/nvidia/nemotron-colembed-v2
can someone explain to me in simple words why the CEO of the highest valued company in the world is having a conference in the middle of a one way street during rush hour”” https://x.com/yacinelearning/status/2018689145086898466
NVFP4-QAD-Report.pdf https://research.nvidia.com/labs/nemotron/files/NVFP4-QAD-Report.pdf
We love working with NVIDIA and they make the best AI chips in the world. We hope to be a gigantic customer for a very long time. I don’t get where all this insanity is coming from.”” https://x.com/sama/status/2018451015272694248
Hard to know which X articles are valuable, but this is a good summary of the significance of world modeling by a distinguished scientist and robot expert NVIDIA”” https://x.com/emollick/status/2018774863734075878
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