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NVIDIA AI Open-Sources ViPE (Video Pose Engine): A Powerful and Versatile 3D Video Annotation Tool for Spatial AI ViPE integrates bundle adjustment with dense optical flow, sparse keypoint tracking, and metric depth priors to estimate camera intrinsics, poses, and dense depth maps at 3–5 FPS on a single GPU....

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217,453 görüntüleme • 9 ay önce •via X (Twitter)

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ViPE: Video Pose Engine for 3D Geometric Perception Contributions: • A robust and efficient framework, ViPE, for estimating camera parameters and dense depth from diverse, in-the-wild videos. • A system design that integrates the strengths of classical SLAM (efficiency, scalability) and learned models (robustness), with key improvements in efficiency, dynamic object handling, and depth quality over prior work. • A large-scale dataset of annotated videos, created using ViPE, to facilitate future research in 3D computer vision.
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ViPE: Video Pose Engine for 3D Geometric Perception Contributions: • A robust and efficient framework, ViPE, for estimating camera parameters and dense depth from diverse, in-the-wild videos. • A system design that integrates the strengths of classical SLAM (efficiency, scalability) and learned models (robustness), with key improvements in efficiency, dynamic object handling, and depth quality over prior work. • A large-scale dataset of annotated videos, created using ViPE, to facilitate future research in 3D computer vision.

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📈 NVIDIA tops AI leaderboards and benchmarks with open models driven by extreme co-design across compute, networking, memory, storage, and software. This includes models for biology, AI physics, agentic AI, physical AI, robotics, and autonomous vehicles. By being vertically integrated and horizontally open, NVIDIA enables its ecosystem to scale agentic workflows at every layer of the stack with the lowest cost per token.
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📈 NVIDIA tops AI leaderboards and benchmarks with open models driven by extreme co-design across compute, networking, memory, storage, and software. This includes models for biology, AI physics, agentic AI, physical AI, robotics, and autonomous vehicles. By being vertically integrated and horizontally open, NVIDIA enables its ecosystem to scale agentic workflows at every layer of the stack with the lowest cost per token.

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Watch our CEO Jensen Huang outline the blueprint for America’s AI century in Washington, D.C. at NVIDIA GTC. From national AI infrastructure and quantum computing to robotics and reindustrialization, see how NVIDIA and its partners are advancing America's AI leadership.
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Watch our CEO Jensen Huang outline the blueprint for America’s AI century in Washington, D.C. at NVIDIA GTC. From national AI infrastructure and quantum computing to robotics and reindustrialization, see how NVIDIA and its partners are advancing America's AI leadership.

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Ropedia Xperience-10M is out on Hugging Face a large-scale egocentric multimodal dataset of human experience for embodied AI, robotics, world models, and spatial intelligence It contains 10 million experiences (interaction) and 10,000 hours of synchronized first-person recordings with six video streams, audio, stereo depth, camera pose, hand mocap, full-body mocap, IMU, and hierarchical language annotations dataset:
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Ropedia Xperience-10M is out on Hugging Face a large-scale egocentric multimodal dataset of human experience for embodied AI, robotics, world models, and spatial intelligence It contains 10 million experiences (interaction) and 10,000 hours of synchronized first-person recordings with six video streams, audio, stereo depth, camera pose, hand mocap, full-body mocap, IMU, and hierarchical language annotations dataset:

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🤝 Alphabet and NVIDIA are expanding their decade-long partnership to advance agentic AI, robotics, drug discovery, and more. This involves deep co-engineering with integrated platforms, open-source frameworks, and managed services. ✅ Google Cloud is one of the first to bring the NVIDIA Blackwell platform to the cloud. ✅ Google Distributed Cloud using NVIDIA Confidential Computing on #NVIDIABlackwell for enterprises to run Google Gemini on-premises. ✅ Integration of the NVIDIA AI platform across Vertex AI, Cluster Director and Google Kubernetes Engine. ✅ Bringing the NVIDIA Nemotron family of open models to Vertex AI Model Garden. Watch the full video to learn more ➡️
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🤝 Alphabet and NVIDIA are expanding their decade-long partnership to advance agentic AI, robotics, drug discovery, and more. This involves deep co-engineering with integrated platforms, open-source frameworks, and managed services. ✅ Google Cloud is one of the first to bring the NVIDIA Blackwell platform to the cloud. ✅ Google Distributed Cloud using NVIDIA Confidential Computing on #NVIDIABlackwell for enterprises to run Google Gemini on-premises. ✅ Integration of the NVIDIA AI platform across Vertex AI, Cluster Director and Google Kubernetes Engine. ✅ Bringing the NVIDIA Nemotron family of open models to Vertex AI Model Garden. Watch the full video to learn more ➡️

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NVIDIA open models provide the foundation to innovate across agentic AI, robotics, autonomous vehicles, and research. 🤖 This release contributes 10 trillion language tokens, 500,000 robotics trajectories, and 100 terabytes of vehicle sensor data to the community. These frameworks are designed to significantly accelerate specialized AI development and discovery. Learn more:

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Unsloth AI and NVIDIA are Revolutionizing Local LLM Fine-Tuning: From RTX Desktops to DGX Spark Fine-tune popular AI models faster with Unsloth on NVIDIA RTX AI PCs such as GeForce RTX desktops and laptops to RTX PRO workstations and the new DGX Spark to build personalized assistants for coding, creative work, and complex agentic workflows. The landscape of modern AI is shifting. We are moving away from a total reliance on massive, generalized cloud models and entering the era of local, agentic AI. Whether it is tuning a chatbot to handle hyper-specific product support or building a personal assistant that manages intricate schedules, the potential for generative AI on local hardware is boundless. However, developers face a persistent bottleneck: How do you get a Small Language Model (SLM) to punch above its weight class and respond with high accuracy for specialized tasks? The answer is Fine-Tuning, and the tool of choice is Unsloth. Unsloth provides an easy and high-speed method to customize models. Optimized for efficient, low-memory training on NVIDIA GPUs, Unsloth scales effortlessly from GeForce RTX desktops and laptop all the way to the DGX Spark, the world’s smallest AI supercomputer...... Full analysis: NVIDIA NVIDIA AI NVIDIA AIDev NVIDIAnewsroom Unsloth AI Unsloth
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Unsloth AI and NVIDIA are Revolutionizing Local LLM Fine-Tuning: From RTX Desktops to DGX Spark Fine-tune popular AI models faster with Unsloth on NVIDIA RTX AI PCs such as GeForce RTX desktops and laptops to RTX PRO workstations and the new DGX Spark to build personalized assistants for coding, creative work, and complex agentic workflows. The landscape of modern AI is shifting. We are moving away from a total reliance on massive, generalized cloud models and entering the era of local, agentic AI. Whether it is tuning a chatbot to handle hyper-specific product support or building a personal assistant that manages intricate schedules, the potential for generative AI on local hardware is boundless. However, developers face a persistent bottleneck: How do you get a Small Language Model (SLM) to punch above its weight class and respond with high accuracy for specialized tasks? The answer is Fine-Tuning, and the tool of choice is Unsloth. Unsloth provides an easy and high-speed method to customize models. Optimized for efficient, low-memory training on NVIDIA GPUs, Unsloth scales effortlessly from GeForce RTX desktops and laptop all the way to the DGX Spark, the world’s smallest AI supercomputer...... Full analysis: NVIDIA NVIDIA AI NVIDIA AIDev NVIDIAnewsroom Unsloth AI Unsloth

Marktechpost AI Dev News ⚡

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NVIDIA CEO Jensen Huang outlines the next phase of accelerated computing and AI — from national AI infrastructure and quantum computing to robotics and reindustrialization. Broadcast from the nation’s capital, #NVIDAIGTC Washington, D.C. highlights how NVIDIA and its partners are advancing America’s AI leadership. Watch the keynote >
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NVIDIA CEO Jensen Huang outlines the next phase of accelerated computing and AI — from national AI infrastructure and quantum computing to robotics and reindustrialization. Broadcast from the nation’s capital, #NVIDAIGTC Washington, D.C. highlights how NVIDIA and its partners are advancing America’s AI leadership. Watch the keynote >

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This week, the TARS AI 🤖 team and I will meet with the NVIDIA Inception team in London to discuss further work we can do together. We'll share a video next week about this meeting, but for now, I want to share my take on NVIDIA GTC 2025! This year’s event focused on pushing AI into the real world, and we’re excited about what’s coming from NVIDIA and Tars! NVIDIA dropped the Blackwell Ultra GPU and teased the Vera Rubin platform, which is insanely powerful for AI workloads. They also unveiled GR00T, an open-source humanoid robot model that shows how AI can move from screens to physical action, like automating tasks or enhancing customer experiences. This is core to our mission and aligned with our market for all AI commodities, from autonomous agents to tokenized datasets, tools, and even robotics. At Tars AI, we’re all about innovative, faster AI that works for people at scale, and GTC 2025 just lit the path ahead. Take a look at some of the highlights from the week...
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This week, the TARS AI 🤖 team and I will meet with the NVIDIA Inception team in London to discuss further work we can do together. We'll share a video next week about this meeting, but for now, I want to share my take on NVIDIA GTC 2025! This year’s event focused on pushing AI into the real world, and we’re excited about what’s coming from NVIDIA and Tars! NVIDIA dropped the Blackwell Ultra GPU and teased the Vera Rubin platform, which is insanely powerful for AI workloads. They also unveiled GR00T, an open-source humanoid robot model that shows how AI can move from screens to physical action, like automating tasks or enhancing customer experiences. This is core to our mission and aligned with our market for all AI commodities, from autonomous agents to tokenized datasets, tools, and even robotics. At Tars AI, we’re all about innovative, faster AI that works for people at scale, and GTC 2025 just lit the path ahead. Take a look at some of the highlights from the week...

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Harness the latest generative AI models locally on your RTX AI PC with NVIDIA NIM Microservices and AI Blueprints. 🎨🖼️ Learn how NVIDIA NIM, @BFL_ML Flux, and ComfyUI empower creators to use 3D objects and simple text prompts to bring ideas to life.

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The team at NVIDIA AI Developer really nailed it with ViPE!! This SLAM system generated pose, depth, point clouds, etc, in a few seconds! Now to get the output to work with GEN3C... If you are interested in running this yourself, it took about 5 minutes to get up and running from scratch.
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The team at NVIDIA AI Developer really nailed it with ViPE!! This SLAM system generated pose, depth, point clouds, etc, in a few seconds! Now to get the output to work with GEN3C... If you are interested in running this yourself, it took about 5 minutes to get up and running from scratch.

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The NVIDIA Blackwell platform just swept MLPerf Training 6.0, delivering fastest performance and largest scale. Beyond the benchmarks, capabilities like the Reliability, Availability, and Serviceability Engine and NVIDIA Resiliency Extension deliver fewer interruptions and faster recovery to keep massive training jobs on track.
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The NVIDIA Blackwell platform just swept MLPerf Training 6.0, delivering fastest performance and largest scale. Beyond the benchmarks, capabilities like the Reliability, Availability, and Serviceability Engine and NVIDIA Resiliency Extension deliver fewer interruptions and faster recovery to keep massive training jobs on track.

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Open models are accelerating development and deployment across agentic AI, physical AI, and a growing range of industries. ✨ “We have billions of dollars of supercomputers in operation, so we can develop our open models,” said NVIDIA CEO Jensen Huang in a recent keynote. “That work is starting to attract attention across industries worldwide, as we build frontier AI models in many different domains.” This includes leading open models from NVIDIA, including: ⚙️ NVIDIA Nemotron for agentic AI ⚙️ NVIDIA Cosmos and GR00T for physical AI ⚙️ NVIDIA Alpamayo for autonomous vehicles ⚙️ NVIDIA Clara for biomedical AI Learn more about open source and AI ➡️
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Open models are accelerating development and deployment across agentic AI, physical AI, and a growing range of industries. ✨ “We have billions of dollars of supercomputers in operation, so we can develop our open models,” said NVIDIA CEO Jensen Huang in a recent keynote. “That work is starting to attract attention across industries worldwide, as we build frontier AI models in many different domains.” This includes leading open models from NVIDIA, including: ⚙️ NVIDIA Nemotron for agentic AI ⚙️ NVIDIA Cosmos and GR00T for physical AI ⚙️ NVIDIA Alpamayo for autonomous vehicles ⚙️ NVIDIA Clara for biomedical AI Learn more about open source and AI ➡️

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What happens when open-source robotics meets agentic AI? 🤖 On the NVIDIA AI Podcast, Seeed Studio’s Eric Pan and Elaine Wu discuss OpenClaw, NVIDIA Jetson-powered robot arms, and how makers are bringing physical AI into the real world. 🎧 Listen now:
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What happens when open-source robotics meets agentic AI? 🤖 On the NVIDIA AI Podcast, Seeed Studio’s Eric Pan and Elaine Wu discuss OpenClaw, NVIDIA Jetson-powered robot arms, and how makers are bringing physical AI into the real world. 🎧 Listen now:

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Build AI Factories with Supermicro and NVIDIA! Flexible, proven end-to-end solutions to accelerate at-scale AI factory deployments.
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Build AI Factories with Supermicro and NVIDIA! Flexible, proven end-to-end solutions to accelerate at-scale AI factory deployments.

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Build AI Factories with Supermicro and NVIDIA! Flexible, proven end-to-end solutions to accelerate at-scale AI factory deployments.
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Build AI Factories with Supermicro and NVIDIA! Flexible, proven end-to-end solutions to accelerate at-scale AI factory deployments.

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NVIDIA just introduced Cosmos, a platform for world foundation models designed for robotics. ⦿ It features advanced tokenizers, an AI-accelerated data pipeline, and integration with NVIDIA Omniverse. Humanoid makers 1X, Figure, and Agility are among the first to adopt Cosmos. ⦿ Cosmos generates synthetic, physics-based data, accelerating model training and customization. ⦿ It also features a CUDA-accelerated data processing pipeline that enables developers to process, curate, and label 20 million hours of videos in 14 days using the NVIDIA Blackwell platform.
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NVIDIA just introduced Cosmos, a platform for world foundation models designed for robotics. ⦿ It features advanced tokenizers, an AI-accelerated data pipeline, and integration with NVIDIA Omniverse. Humanoid makers 1X, Figure, and Agility are among the first to adopt Cosmos. ⦿ Cosmos generates synthetic, physics-based data, accelerating model training and customization. ⦿ It also features a CUDA-accelerated data processing pipeline that enables developers to process, curate, and label 20 million hours of videos in 14 days using the NVIDIA Blackwell platform.

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