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This magic is unlocked by AI in combination with high-quality, diverse vision and force feedback data. Memo by Sunday Robotics autonomously stacks and folds socks into a tucked bundle (1x speed). The task generalizes across diverse rooms and table setups. It took 3 months of engineering effort and 16...

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The Humanoid Hub

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32,239 Aufrufe • vor 7 Monaten •via X (Twitter)

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The Memo robot by Sunday Robotics autonomously stacks and folds socks into a tucked bundle. The robot is operated by the ACT-1 foundation model built in-house at Sunday. It learns from data captured by humans wearing gloves that match Memo's hands.
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The Memo robot by Sunday Robotics autonomously stacks and folds socks into a tucked bundle. The robot is operated by the ACT-1 foundation model built in-house at Sunday. It learns from data captured by humans wearing gloves that match Memo's hands.

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Robotics and CV! 👓 Computer vision gives the robots a sense of vision and additional intelligence. Pralines are packed by a delta robot using computer vision. Packing chocolate pralines into a box with the delta robot. Unlike most robots, this one has a fixed TCP, and the base moves in response to vision data. To adjust the base, the vision system determines exactly where the praline is located on the conveyor belt. 🍫 Using this application, the system knows where each praline should be placed based on its orientation. A true engineering showcase!
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Robotics and CV! 👓 Computer vision gives the robots a sense of vision and additional intelligence. Pralines are packed by a delta robot using computer vision. Packing chocolate pralines into a box with the delta robot. Unlike most robots, this one has a fixed TCP, and the base moves in response to vision data. To adjust the base, the vision system determines exactly where the praline is located on the conveyor belt. 🍫 Using this application, the system knows where each praline should be placed based on its orientation. A true engineering showcase!

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1/ We are speed running industrial robotics. It took us just 19 days from the first day of data collection to filming a 2.5-hour continuous run of our model autonomously breaking down industrial containers — zero human intervention. The data efficiency of our DVA model is fundamentally changing how fast we bring robots out of the lab and into the factory. Autonomous operation with 3 hours of data collection at a customer factory.
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the micro1 robotics lab: real world data for intelligent models that co-exist in the physical world. we’re in-the-wild across 75 countries in 6,000+ unique environments collecting data. diverse movements, objects, and settings. the future of AI is as human as you can imagine. join us to start training robots today (link in comments).
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the micro1 robotics lab: real world data for intelligent models that co-exist in the physical world. we’re in-the-wild across 75 countries in 6,000+ unique environments collecting data. diverse movements, objects, and settings. the future of AI is as human as you can imagine. join us to start training robots today (link in comments).

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1/ The data parsing market for robotics is just emerging, and it’s already valued in the tens of billions. Data parsing to build data models and software for Robotics is a $20B market in 2024 and is expected to reach $150B+ by 2034 Cherry AI Robotics has built a data parsing tool for robotics, which goes live next week, and will effectively make this project one of the pioneers in data parsing for robotics.
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1/ The data parsing market for robotics is just emerging, and it’s already valued in the tens of billions. Data parsing to build data models and software for Robotics is a $20B market in 2024 and is expected to reach $150B+ by 2034 Cherry AI Robotics has built a data parsing tool for robotics, which goes live next week, and will effectively make this project one of the pioneers in data parsing for robotics.

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Sunday Robotics' Tony Zhao says they're using gloves worn by people doing household chores to create the dataset they'll use to train their foundation model: “This gives us really high-quality data, but also a really high diversity and quantity of data.”
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Sunday Robotics' Tony Zhao says they're using gloves worn by people doing household chores to create the dataset they'll use to train their foundation model: “This gives us really high-quality data, but also a really high diversity and quantity of data.”

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Train robots. Earn rewards. Base is pioneering the Train-to-Earn model for robotics. With Axis Robotics, anyone can help train robot simulations from a laptop and be rewarded for contributing data. The future of robotics won’t be trained by a handful of companies. It’ll be trained by everyone. PL 漂亮 (✱,✱) showcased this vision at SuperAI, the largest AI event in Asia 👇
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AI is transforming the way businesses operate 🤖. It helps companies work faster, cut costs, and make smarter decisions. From automating repetitive tasks to predicting trends and uncovering insights, AI is becoming the backbone of modern business. But AI can’t function without data 📊. Massive amounts of high-quality data are required to train models and make them effective. Right now, most of this data is controlled by a few centralized giants 🔒, making it expensive, siloed, and out of reach for smaller businesses and innovators. This is where OORT | The Data Cloud for Decentralized AI comes in 🌐✨. By combining decentralized storage with AI infrastructure powered by blockchain, OORT makes data open, secure, and accessible to everyone. It’s building a foundation where businesses of all sizes can tap into AI’s full potential and compete in the AI-driven economy 🚀
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AI is transforming the way businesses operate 🤖. It helps companies work faster, cut costs, and make smarter decisions. From automating repetitive tasks to predicting trends and uncovering insights, AI is becoming the backbone of modern business. But AI can’t function without data 📊. Massive amounts of high-quality data are required to train models and make them effective. Right now, most of this data is controlled by a few centralized giants 🔒, making it expensive, siloed, and out of reach for smaller businesses and innovators. This is where OORT | The Data Cloud for Decentralized AI comes in 🌐✨. By combining decentralized storage with AI infrastructure powered by blockchain, OORT makes data open, secure, and accessible to everyone. It’s building a foundation where businesses of all sizes can tap into AI’s full potential and compete in the AI-driven economy 🚀

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We just launched a major new Data Engineering Professional Certificate on Coursera! Data underlies all modern AI systems, and engineers who know how to build systems to store and serve it are in high demand. If you're interested in learning this skill, please check out this 4-course sequence, which is designed to make you job-ready to be a Data Engineer. This is a new specialization taught by Joe Reis, the co-author of the best-selling book “Fundamentals of Data Engineering," in collaboration with AWS. (Disclosure, I serve on Amazon's board.) For many AI systems, data engineering is 80% of the work, and modeling is 20%. But people’s attention on these two topics is often flipped. This makes the job of the data engineer particularly important. In this professional certificate, you'll learn foundational data engineering skills while implementing modern data architectures using open-source tools: - Learn the key steps of the data lifecycle, to generate, ingest, store, transform, and serve data. - Learn to align with organizational goals to design the data pipeline right for your business' needs. - Understand how to make necessary trade-offs between speed, scalability, security, and cost. Joe has distilled into this specialization decades of experience helping startups and large companies with data infrastructure. He is also joined by 17 other industry leaders in the data field, who will help you learn in-demand skills for the growing field of data engineering. Please sign up here:
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Been looking into RICE AI ( ◉ - ◉ ) lately, and it’s one of the few projects actually tackling a real challenge in robotics and AGI: the lack of high-quality training data. Robots can’t get truly intelligent without it. They building a decentralized way to collect and share robotics data, using a DePIN network to train physical AI foundation models. The project was even hand-picked by CZ as a winner of the Dubai BNB Chain Demo Day, and it’s backed by Floki while also being part of the NVIDIA Inception Program. They also launched FLOKI Minibot M1 - a small AI companion that doubles as a data node. Every interaction with it feeds the RICE AI Foundry, the first decentralized platform for Robotics Foundation Models, and contributors earn $RICE tokens in return. And it’s working: – 800 minibots sold in 24h – 33,000% oversubscribed Binance IDO – 500+ robots already deployed worldwide Feels like a project with real long-term potential. Worth keeping an eye on. RICE AI ( ◉ - ◉ )

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AI is transforming the way businesses operate 🤖. It’s no longer just a tool, it powers decision-making, efficiency, and growth. From automating tasks to predicting trends and uncovering insights, AI is becoming the backbone of modern business. But AI isn’t magic. It needs massive amounts of high-quality data 📊. Companies like Scale AI and other Web2 giants thrive because they control the pipelines of this data, turning it into a huge competitive advantage. The problem is most of this data is locked in centralized systems 🔒, expensive, and often inaccessible for smaller companies or innovators. That’s where OORT | The Data Cloud for Decentralized AI comes in 🌐✨. By building decentralized storage and AI infrastructure, OORTECH makes data open, secure, and accessible to everyone. It’s a foundation for the next generation of AI-powered businesses, giving all innovators the chance to compete and create 🚀

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We asked Angus about the future of robotics and AI training. “I built an industrial-grade kinematic solver for 6 degrees of freedom motion, with full path planning and joint control." "You can stream AI model outputs into it, or run it like a traditional industrial robot." "The benefit of that is all of that information you can stream and record from those joints… you can use that as the training data." "Frankly, moving a robot with a lever is really crap data for training robots. But this gives you smooth, high-quality motion, without needing two robots.”
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We asked Angus about the future of robotics and AI training. “I built an industrial-grade kinematic solver for 6 degrees of freedom motion, with full path planning and joint control." "You can stream AI model outputs into it, or run it like a traditional industrial robot." "The benefit of that is all of that information you can stream and record from those joints… you can use that as the training data." "Frankly, moving a robot with a lever is really crap data for training robots. But this gives you smooth, high-quality motion, without needing two robots.”

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=Game Recommendation= Sky Blitz by Studio Cubicular Sky Blitz is a racing game where players soar through the skies in high speed races! Choose from a diverse cast of characters and compete across multiple vibrant tracks! #Robloxdev #Roblox Link:
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=Game Recommendation= Sky Blitz by Studio Cubicular Sky Blitz is a racing game where players soar through the skies in high speed races! Choose from a diverse cast of characters and compete across multiple vibrant tracks! #Robloxdev #Roblox Link:

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California's SAFE Task Force is currently underway in Long Beach, addressing the national homelessness crisis by connecting people with support and care. This is proof that with urgency, compassion, and accountability, we can improve the safety and quality of life for everyone.
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Elon Musk: Optimus is awesome! “Something that's going to be very important in the future is combining deep AI in the data center or supercluster with robotics, like the Optimus humanoid robot. Optimus is awesome! There's going to be so many humanoid robots and robots of all sizes and shapes. But my prediction is that there will be more humanoid robots by far than all other robots combined by maybe an order of magnitude, like a big difference.” Interview at Y Combinator, June 16, 2025

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