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Waste sorting is difficult to automate because materials vary in shape, condition, and placement. EverestLabs' Physical AI platform combines computer vision, AI, and robotics to identify more than 60 material classes with over 95% accuracy, using models trained on billions of recyclable objects to improve sorting consistency and efficiency... show more

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The Ameru Smart Bin is an AI-powered waste management solution designed to enhance recycling efficiency in office and public spaces. Equipped with a high-definition 8MP camera, a 10.1-inch full HD touchscreen, and powered by an Nvidia Jetson Orin Nano computing unit, the bin utilizes advanced AI algorithms to identify and sort waste into multiple categories. Video credit: Ameru.ai #engineering #technology #ai #artificialintelligence -------------------------------- Stay ahead of the curve! Follow us now on our WhatsApp ( and Telegram ( channels and stay updated about the cutting edge.

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Jensen Huang explains that AI has progressed through four major phases. The first wave was Perception AI, where deep learning enabled superhuman vision and speech recognition. The second wave was Generative AI, allowing AI to create text, images, video, and more. We are now in the third wave, Reasoning AI, where models can think through problems, apply logic, and even conduct research. The fourth wave will be Physical AI, where models gain real-world understanding and common sense, leading to advanced robotics.

Jensen Huang explains that AI has progressed through four major phases. The first wave was Perception AI, where deep learning enabled superhuman vision and speech recognition. The second wave was Generative AI, allowing AI to create text, images, video, and more. We are now in the third wave, Reasoning AI, where models can think through problems, apply logic, and even conduct research. The fourth wave will be Physical AI, where models gain real-world understanding and common sense, leading to advanced robotics.

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Lukas Ziegler

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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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A flying robot that moves like a snake in the air. 🐍🤖 This multi-jointed aerial robot can bend its body mid-flight and grasp objects with precision. A new generation of drones is going beyond flying they’re learning how to interact with the world. 🎥 Media: JSK Lab at The University of Tokyo ⚠️ This content is shared for informational purposes only. CTO Robotics Media is a media platform and does not own or develop the technology shown. Credit belongs to the original creators. #Robotics #Engineering #Drone #AI

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.Applied Intuition wants to make robotics as easy as building an iPhone app: "Dana is our new agentic platform for physical AI. This really is the culmination of pretty much everything we've worked on now over the last decade." "Building physical AI is extremely complicated... We know how to make the chips. We know how to make the hardware for these systems. It's more so actually developing all of this technology and getting it to work that is very, very difficult." "With modern AI and with this new Dana platform, we're really drastically reducing the barrier to entry to building physical AI and deploying it in the real world." "If you're building an app for an iPhone, high school kids can do that now because there's all of these things that exist and that make it easy... It's very hard to do that in terms of robotics." "The thing that Peter's really emphasizing and thing that we really wanna do is just lower the bar. So anybody really out there, starting with engineers, but ultimately really anybody can develop robots." Applied Intuition Co-founders Peter Ludwig and Qasar Younis on Business Breakdowns

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RailScan Multi-Function Robot: Railway Surface Inspection The RailScan robot is designed for track inspection, using a self-moving platform and precise sensors to quickly detect track defects. It assists track inspectors with nighttime inspections, addressing challenges in traditional manual inspections such as heavy workload, missed detections, and difficult tasks. The robot helps reduce inspection costs, improve efficiency, and enhance safety by identifying potential hazards in the rail track. Video source: Shenhao Robotics #robotics #inspection #RailwayRobot #technology #engineering #stem #innovation #robots #automation ----------------------- Wanna get your company on Wevolver too? Learn how:

Wevolver

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Jensen Huang on "distillation" On his new interview with axios, he was asked this question "Should open source model companies be allowed to distill closed models" "Distillation—learning from AI, learning from other people, and learning from other sources of knowledge, is fundamental to intelligence. We are constantly learning from other people. I am learning from you through the questions you are asking, and you are learning from me. All day long, we are learning from one another. AI also has to learn from something. The original AI models, whether they were open or closed, were trained on previously created knowledge from the internet. Now, AI is generating more content than humans. In a few more years, the internet could be 99% AI-generated content, and that content will have been created by some form of AI. As a result, AI systems will constantly be distilling knowledge and intelligence from other AI systems. The fact that AI can learn is a good thing. We want AI systems to be intelligent because a smarter AI can also be a safer AI." ---- From "Axios" YouTube channel, (full video link in comment)

Jensen Huang on "distillation" On his new interview with axios, he was asked this question "Should open source model companies be allowed to distill closed models" "Distillation—learning from AI, learning from other people, and learning from other sources of knowledge, is fundamental to intelligence. We are constantly learning from other people. I am learning from you through the questions you are asking, and you are learning from me. All day long, we are learning from one another. AI also has to learn from something. The original AI models, whether they were open or closed, were trained on previously created knowledge from the internet. Now, AI is generating more content than humans. In a few more years, the internet could be 99% AI-generated content, and that content will have been created by some form of AI. As a result, AI systems will constantly be distilling knowledge and intelligence from other AI systems. The fact that AI can learn is a good thing. We want AI systems to be intelligent because a smarter AI can also be a safer AI." ---- From "Axios" YouTube channel, (full video link in comment)

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🚨 BREAKING: ABB Robotics + NVIDIA close the sim-to-real gap with 99% accuracy! 👾 ABB Robotics is integrating NVIDIA Omniverse libraries into RobotStudio to deliver physical AI for industry, closing the gap from virtual training to real-world deployment with up to 99% accuracy. RobotStudio HyperReality, available second half of 2026, will fundamentally change how quickly manufacturers can scale production: reducing costs by up to 40%, accelerating time-to-market by 50%, and cutting setup and commissioning times by up to 80%. For decades, the deficit between simulation accuracy and real-world lighting, materials, and environments has limited manufacturers' ability to design advanced manufacturing processes in the virtual world. The only robot manufacturer with a virtual controller running the same firmware as the hardware, ensuring near-perfect correlation between simulation and real-world performance. The system uses physically accurate simulations and foundation models endlessly optimized with real-world data feedback. These models can train any number of ABB robots anywhere in the world with industrial-grade reliability. Foxconn is using RobotStudio HyperReality for consumer electronics assembly. Assembly robots are trained virtually using synthetic data to perfect multiple production processes across various scenarios, then moved to production lines with 99% accuracy. This eliminates physical training and tests, reducing setup times and costs. Workr is demonstrating AI-powered robotic systems at NVIDIA GTC 2026. Built on ABB technology, trained with synthetic data using NVIDIA Omniverse, deployed without operators needing programming knowledge . 🚨 I’ll be onsite in San Jose during GTC 2026, and will be showing all the cool stuff that ABB Robotics prepared this year! Can’t wait! 🫡 ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

🚨 BREAKING: ABB Robotics + NVIDIA close the sim-to-real gap with 99% accuracy! 👾 ABB Robotics is integrating NVIDIA Omniverse libraries into RobotStudio to deliver physical AI for industry, closing the gap from virtual training to real-world deployment with up to 99% accuracy. RobotStudio HyperReality, available second half of 2026, will fundamentally change how quickly manufacturers can scale production: reducing costs by up to 40%, accelerating time-to-market by 50%, and cutting setup and commissioning times by up to 80%. For decades, the deficit between simulation accuracy and real-world lighting, materials, and environments has limited manufacturers' ability to design advanced manufacturing processes in the virtual world. The only robot manufacturer with a virtual controller running the same firmware as the hardware, ensuring near-perfect correlation between simulation and real-world performance. The system uses physically accurate simulations and foundation models endlessly optimized with real-world data feedback. These models can train any number of ABB robots anywhere in the world with industrial-grade reliability. Foxconn is using RobotStudio HyperReality for consumer electronics assembly. Assembly robots are trained virtually using synthetic data to perfect multiple production processes across various scenarios, then moved to production lines with 99% accuracy. This eliminates physical training and tests, reducing setup times and costs. Workr is demonstrating AI-powered robotic systems at NVIDIA GTC 2026. Built on ABB technology, trained with synthetic data using NVIDIA Omniverse, deployed without operators needing programming knowledge . 🚨 I’ll be onsite in San Jose during GTC 2026, and will be showing all the cool stuff that ABB Robotics prepared this year! Can’t wait! 🫡 ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Lukas Ziegler

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So many robotics companies trying to solve everything at once… Last year I talked to Nima Gard, Director of AI at Path Robotics about this… Doing one thing really really well. They went after welding. Today they’re introducing Rove™, which embodies Obsidian™ (Path's physical AI model for manufacturing) on a legged mobile platform. The result is the intelligence to autonomously weld with the mobility to bring the worker to the work. Path Robotics (Columbus, Ohio) has raised more than $300 million in venture capital to build autonomous AI-powered welding cells. I think the tech is pretty impressive and video really cool. Congrats guys! Credit: Path Robotics

So many robotics companies trying to solve everything at once… Last year I talked to Nima Gard, Director of AI at Path Robotics about this… Doing one thing really really well. They went after welding. Today they’re introducing Rove™, which embodies Obsidian™ (Path's physical AI model for manufacturing) on a legged mobile platform. The result is the intelligence to autonomously weld with the mobility to bring the worker to the work. Path Robotics (Columbus, Ohio) has raised more than $300 million in venture capital to build autonomous AI-powered welding cells. I think the tech is pretty impressive and video really cool. Congrats guys! Credit: Path Robotics

Ilir Aliu

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is changing its name. 13 years ago, launched with a simple idea: every student should learn computer science — to learn how technology works and how to create it — not just how to use it. After more than 2 billion hours of learning, the focus of CS has moved from coding to AI. As AI reshapes every part of daily life, students need digital fluency: the ability to understand AI, direct it, question it, and create with it — built on the foundations of computer science, AI science, and data science. Today, enters its next chapter as CodeAI. Our curriculum, teacher training, and frameworks, are there already: AI Discoveries and AI Foundations are free and in classrooms now. The K-12 digital sciences pathway is expanding. Our goal is a generation with agency over the systems shaping their lives — prepared to shape the work, civic life, relationships, and meaning that come after. Welcome to CodeAI.

is changing its name. 13 years ago, launched with a simple idea: every student should learn computer science — to learn how technology works and how to create it — not just how to use it. After more than 2 billion hours of learning, the focus of CS has moved from coding to AI. As AI reshapes every part of daily life, students need digital fluency: the ability to understand AI, direct it, question it, and create with it — built on the foundations of computer science, AI science, and data science. Today, enters its next chapter as CodeAI. Our curriculum, teacher training, and frameworks, are there already: AI Discoveries and AI Foundations are free and in classrooms now. The K-12 digital sciences pathway is expanding. Our goal is a generation with agency over the systems shaping their lives — prepared to shape the work, civic life, relationships, and meaning that come after. Welcome to CodeAI.

Hadi Partovi

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🚀 Introducing Nexgent AI — your always-on trading assistant. Nexgent AI empowers you to automate, customize, and monetize your own AI trading agent, giving you control over powerful trading technology designed for everyone. Our ambition is to take the guesswork out of trading by analyzing enormous sets of data at lightning speed. Our platform identifies liquidity surges, tracks market sentiment, and monitors whale movements in real time, helping you trade smarter, and with confidence. Getting started is simple: set up your agent, let it perform, and when you’re ready, allow others to stake in your high-performing creation, unlocking new ways to monetize your expertise. It’s more than world-class technology - it’s technology you own. This is more than a vision. We have a working platform delivering tangible results, with a clear road map to becoming the world’s most advanced trading agent. With utility built into our core mechanics, our token has genuine purpose and real value. 🔥 Follow us on X & Telegram for IEO updates and launch dates! 🔥 Nexgent AI. Hindsight today. #trading #crypto #AI #Nexgent

Nexgent.AI

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Today we’re releasing V-JEPA, a method for teaching machines to understand and model the physical world by watching videos. This work is another important step towards Yann LeCun’s outlined vision of AI models that use a learned understanding of the world to plan, reason and accomplish complex tasks. Details ➡️ We're releasing a collection of V-JEPA vision models trained with a feature prediction objective using self-supervised learning. The models are able to understand and predict what is going on in a video, even with limited information. It learns by predicting missing or obscured parts of a video in its internal feature space. Unlike generative approaches that fill in missing pixels, this flexible approach enables up to 6x improvements in training and sample efficiency. The models were pre-trained on entirely unlabeled data, and a small amount of labeled data can be used to train a task-specific prediction head on top after pre-training. Our results show that, using a frozen backbone, our top V-JEPA models achieve 82.0% on Kinetics-400, 72.2% on Something-Something-v2 and 77.9% on ImageNet1K — competitive with or exceeding previous leading video models. We believe that this work is an important milestone on the path to advancing machine intelligence.

Today we’re releasing V-JEPA, a method for teaching machines to understand and model the physical world by watching videos. This work is another important step towards Yann LeCun’s outlined vision of AI models that use a learned understanding of the world to plan, reason and accomplish complex tasks. Details ➡️ We're releasing a collection of V-JEPA vision models trained with a feature prediction objective using self-supervised learning. The models are able to understand and predict what is going on in a video, even with limited information. It learns by predicting missing or obscured parts of a video in its internal feature space. Unlike generative approaches that fill in missing pixels, this flexible approach enables up to 6x improvements in training and sample efficiency. The models were pre-trained on entirely unlabeled data, and a small amount of labeled data can be used to train a task-specific prediction head on top after pre-training. Our results show that, using a frozen backbone, our top V-JEPA models achieve 82.0% on Kinetics-400, 72.2% on Something-Something-v2 and 77.9% on ImageNet1K — competitive with or exceeding previous leading video models. We believe that this work is an important milestone on the path to advancing machine intelligence.

AI at Meta

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ICP MCP making games on Internet Computer a reality...?! DFINITY Foundation's Model Context Protocol (MCP), a standard introduced to let AI models connect securely to external data and tools, is already being put to good use. A new post shares X2 using Anthropic's Claude to play a generated video game with instructions routed through $ICP's MCP. Are we seeing the dawn of AI on Internet Computer happening in real time?

ICP MCP making games on Internet Computer a reality...?! DFINITY Foundation's Model Context Protocol (MCP), a standard introduced to let AI models connect securely to external data and tools, is already being put to good use. A new post shares X2 using Anthropic's Claude to play a generated video game with instructions routed through $ICP's MCP. Are we seeing the dawn of AI on Internet Computer happening in real time?

BSCN

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Dr. Fei-Fei Li (Fei-Fei Li), the Godmother of AI, on the origin of computer vision and why spatial intelligence is the next frontier. At AI Startup School in San Francisco. 01:00 - Origins of ImageNet 02:15 - The Dream to Make Machines See 03:28 - A paradigm shift in AI 05:50 - AlexNet and Deep Learning 08:00 - Evolving Computer Vision 12:20 - Building World Labs 13:00 - The next frontier in AI 14:20 - Why Spatial Intelligence Is Harder Than Language 18:40 - Technical Barriers for Vision-Based AI 20:00 - AI is more than LLMs 25:50 - Fei Fei’s Journey 29:30 - Mentoring some of the legends of AI 33:00 - Audience Q&A

Dr. Fei-Fei Li (Fei-Fei Li), the Godmother of AI, on the origin of computer vision and why spatial intelligence is the next frontier. At AI Startup School in San Francisco. 01:00 - Origins of ImageNet 02:15 - The Dream to Make Machines See 03:28 - A paradigm shift in AI 05:50 - AlexNet and Deep Learning 08:00 - Evolving Computer Vision 12:20 - Building World Labs 13:00 - The next frontier in AI 14:20 - Why Spatial Intelligence Is Harder Than Language 18:40 - Technical Barriers for Vision-Based AI 20:00 - AI is more than LLMs 25:50 - Fei Fei’s Journey 29:30 - Mentoring some of the legends of AI 33:00 - Audience Q&A

Y Combinator

194,393 görüntüleme • 1 yıl önce

In a recent interview, Jensen Huang, the CEO of NVIDIA, pointed out that China has three unique advantages in developing robots, and his insights have drawn widespread attention in the tech world. First, China has outstanding AI technology. With a large number of excellent AI researchers and continuous innovation, China has made remarkable achievements in AI algorithms, machine learning, and other aspects. These advancements lay a solid foundation for the intelligent development of robots. Second, China excels in mechatronics. The combination of mechanical and electrical technologies allows Chinese - made robots to have better physical performance, more precise movement control, and higher reliability, making them more competitive in the global market. Last but not least, China's huge manufacturing base provides broad application scenarios for robots. From large - scale industrial production lines to various service industries, robots can be widely deployed, which promotes the continuous improvement of robot technology through large - scale practical applications. With these three powerful advantages, China is set to play a leading role in the global robotics field. It's exciting to look forward to the brilliant future of China's robotics development. 新浪科技 #Robotics #NVIDIA #JensenHuang #AI #ArtificialIntelligence

In a recent interview, Jensen Huang, the CEO of NVIDIA, pointed out that China has three unique advantages in developing robots, and his insights have drawn widespread attention in the tech world. First, China has outstanding AI technology. With a large number of excellent AI researchers and continuous innovation, China has made remarkable achievements in AI algorithms, machine learning, and other aspects. These advancements lay a solid foundation for the intelligent development of robots. Second, China excels in mechatronics. The combination of mechanical and electrical technologies allows Chinese - made robots to have better physical performance, more precise movement control, and higher reliability, making them more competitive in the global market. Last but not least, China's huge manufacturing base provides broad application scenarios for robots. From large - scale industrial production lines to various service industries, robots can be widely deployed, which promotes the continuous improvement of robot technology through large - scale practical applications. With these three powerful advantages, China is set to play a leading role in the global robotics field. It's exciting to look forward to the brilliant future of China's robotics development. 新浪科技 #Robotics #NVIDIA #JensenHuang #AI #ArtificialIntelligence

Zhang Heqing

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Today I'm soft launching , the world's first AI computer. Most people could be creating way more with their computers. Instead, they're stuck consuming content made by other people. Zo Computer is a new kind of computer in the cloud, with an AI that "lives" in your computer. You can choose between all the leading models, and just chat (or text) with your new computer to: • write • research • vibe code • generate images and videos • host websites and APIs • save articles • set reminders • automate your life and much more. And because Zo is *your* personal server, everything is stored and hosted on it – your files, your sites, and even the Zo app itself.

Today I'm soft launching , the world's first AI computer. Most people could be creating way more with their computers. Instead, they're stuck consuming content made by other people. Zo Computer is a new kind of computer in the cloud, with an AI that "lives" in your computer. You can choose between all the leading models, and just chat (or text) with your new computer to: • write • research • vibe code • generate images and videos • host websites and APIs • save articles • set reminders • automate your life and much more. And because Zo is your personal server, everything is stored and hosted on it – your files, your sites, and even the Zo app itself.

hraness

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