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📍 Introducing Tagger — The Decentralized #AI Data Layer ➡️ Tagger is a full-stack DeCorp platform revolutionizing how high-quality training data is created, authenticated, and traded. - AI-powered labeling tools that turn anyone into a pro annotator - Instant rewards in $TAG via smart contracts - Secure data authentication... show more

Crypto Holding™ 💎

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112,954 次观看 • 12 天前 •via X (Twitter)

科学技术 #AI

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AI needs data to grow. But accessing high-quality datasets is becoming harder than ever. · Data collection is increasingly centralized in the hands of a few large players. · Platforms are locking content behind expensive APIs and private data deals. · Specialized datasets (medical, legal, code) can cost 20–40× more than general web data. · And while 94% of companies are exploring Gen-AI, only 12% have reliable data channels. The result? A growing data bottleneck for AI development. The future of AI won’t just depend on better models. It will depend on who can access and activate quality data.

AI needs data to grow. But accessing high-quality datasets is becoming harder than ever. · Data collection is increasingly centralized in the hands of a few large players. · Platforms are locking content behind expensive APIs and private data deals. · Specialized datasets (medical, legal, code) can cost 20–40× more than general web data. · And while 94% of companies are exploring Gen-AI, only 12% have reliable data channels. The result? A growing data bottleneck for AI development. The future of AI won’t just depend on better models. It will depend on who can access and activate quality data.

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🔐 𝗣𝗼𝘄𝗲𝗿𝗶𝗻𝗴 𝘁𝗵𝗲 𝗡𝗲𝘅𝘁 𝗪𝗮𝘃𝗲 𝗼𝗳 𝗔𝗜 We're proud to partner with Stempoint to secure the future of decentralized AI compute. StemPoint is building one of the most advanced distributed AI infrastructures on the planet, sharded GPU compute, open model libraries, and secure data flows across a global mesh. Now with Naoris Protocol’s Sub-Zero Layer and dPoSec consensus, every node, model, and data packet gains: • Post-quantum cryptographic protection • Real-time validation of compute and algorithms • A decentralized trust layer for sovereign AI 🚫 No more trusting black boxes. ✅ Verifiable AI infrastructure at scale.

NaoX Protocol

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Our 1st Acquisition We've made a significant leap forward by officially acquiring Nidum, a decentralized AI computing platform poised to redefine blockchain intelligence and AI decentralization. With Nidums decentralized computing power, AI model training and global resource pool, we are now positioned at the forefront of blockchain driven AI innovation. What does that mean for our ecosystem? ✅ Scalable AI solutions powered by blockchain ✅ Decentralized AI model training & data privacy ✅ Expanded $BCUT utility in the AI economy Explore the dedicated website page to learn why this acquisition is a game changer for the our ecosystem and AI decentralization.

Our 1st Acquisition We've made a significant leap forward by officially acquiring Nidum, a decentralized AI computing platform poised to redefine blockchain intelligence and AI decentralization. With Nidums decentralized computing power, AI model training and global resource pool, we are now positioned at the forefront of blockchain driven AI innovation. What does that mean for our ecosystem? ✅ Scalable AI solutions powered by blockchain ✅ Decentralized AI model training & data privacy ✅ Expanded $BCUT utility in the AI economy Explore the dedicated website page to learn why this acquisition is a game changer for the our ecosystem and AI decentralization.

bitsCrunch

90,644 次观看 • 1 年前

Something big is happening in robotics - and it’s hiding in plain sight. This post is not about dancing robots but in the data that powers them. Open robotics datasets have exploded this year, turning the field into a more scalable and collaborative ecosystem. In just two years, Hugging Face datasets grew from 11k to over 600k - and robotics is by far the fastest-growing segment. We went from 1k robotics datasets in 2024 to 27k in 2025! For comparison, text generation, the second-largest category, has only around 5k datasets in 2025. That gap is massive. Open datasets are important because robotics lives and dies by real-world robot data - video, actions, sensors, failures. By making this data easy to upload, reuse, and benchmark, researchers, startups, and large players are now releasing real-robot datasets that would have stayed locked inside labs just a few years ago. Major contributors include NVIDIA, LeRobot initiative, and a rapidly growing maker community. This surge is also enabled by cheaper video storage, better tooling, and an open-source AI culture now spilling into the physical world. And it really matters: open robotics data dramatically lowers entry barriers, accelerates learning-by-doing, and speeds up progress toward generalist and humanoid robots. Robotics won’t scale through hardware alone - but to a large extent through shared data. Viz below from AI World - link to the story and more viz/filters in comment.

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🚀 Excited to partner with in leading the Gaming Fortress Guffal! 🤝 Dive into how Arcium's confidential computing is changing Data Ownership and Rewards in #onchaingaming for Genovians with @Kinetic_Elite! 💪 Now YOU can own a stake in the future of #AI through gaming! 🤯 🔗 Learn more: #AIgaming #Web3

🚀 Excited to partner with in leading the Gaming Fortress Guffal! 🤝 Dive into how Arcium's confidential computing is changing Data Ownership and Rewards in #onchaingaming for Genovians with @Kinetic_Elite! 💪 Now YOU can own a stake in the future of #AI through gaming! 🤯 🔗 Learn more: #AIgaming #Web3

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20,755 次观看 • 1 年前

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Bernard Marr

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How can AI agents gain true autonomy? CARV ID (ERC-7231) is transforming AI and blockchain integration by creating trustless, sovereign AI agents. This identity protocol aggregates cross-chain and off-chain data, enabling AI Beings to operate with verified identity, privacy, and autonomy. By unifying fragmented data and enriching it with actionable metrics, CARV ID powers the D.A.T.A Framework, giving AI agents access to contextualized insights while preserving user data sovereignty. This means developers can build AI systems that learn, evolve, and act independently within a secure, decentralized ecosystem, free from centralized control. For businesses and researchers, this opens a new frontier where AI-driven decisions are transparent, verifiable, and privacy-preserved. CARV's integration of Solana scalability and Ethereum security ensures these trustless AI agents perform with speed at scale. The future is clear: AI Beings will no longer be mere tools, they will be sovereign participants in digital economies. What implications do you see for AI autonomy in blockchain?

How can AI agents gain true autonomy? CARV ID (ERC-7231) is transforming AI and blockchain integration by creating trustless, sovereign AI agents. This identity protocol aggregates cross-chain and off-chain data, enabling AI Beings to operate with verified identity, privacy, and autonomy. By unifying fragmented data and enriching it with actionable metrics, CARV ID powers the D.A.T.A Framework, giving AI agents access to contextualized insights while preserving user data sovereignty. This means developers can build AI systems that learn, evolve, and act independently within a secure, decentralized ecosystem, free from centralized control. For businesses and researchers, this opens a new frontier where AI-driven decisions are transparent, verifiable, and privacy-preserved. CARV's integration of Solana scalability and Ethereum security ensures these trustless AI agents perform with speed at scale. The future is clear: AI Beings will no longer be mere tools, they will be sovereign participants in digital economies. What implications do you see for AI autonomy in blockchain?

CARV

96,077 次观看 • 6 个月前

Delighted to share our latest partnership with Streamr Network! Streamr is at the forefront of P2P real-time data delivery, removing the need for centralized servers. Their network is key infra for DePIN, AI and Web3. It works via a mesh of data pipelines - think of it as ‘BitTorrent for real-time data’. Here's the scoop on our collaboration with Streamr: One Click Node Deployment: CloudVerse users will be able to deploy Streamr nodes and earn $DATA rewards by participating on the network. Ecosystem Network Management: CloudSec and OneSec node base will leverage the Streamr Network for collaboration to synchronize data and coordinate actions. Spawn your own P2P Network: Alongside our upcoming data storage and hosting solutions, OneSec users will be able to create their own ‘publish subscribe’ data pipelines via the Streamr protocol, in a permissionless manner. This partnership is fuelled by our shared commitment to data security, privacy, and a truly decentralized digital world. Here's to the many technical synergies ahead! - End of post, beware of scammers -

Delighted to share our latest partnership with Streamr Network! Streamr is at the forefront of P2P real-time data delivery, removing the need for centralized servers. Their network is key infra for DePIN, AI and Web3. It works via a mesh of data pipelines - think of it as ‘BitTorrent for real-time data’. Here's the scoop on our collaboration with Streamr: One Click Node Deployment: CloudVerse users will be able to deploy Streamr nodes and earn $DATA rewards by participating on the network. Ecosystem Network Management: CloudSec and OneSec node base will leverage the Streamr Network for collaboration to synchronize data and coordinate actions. Spawn your own P2P Network: Alongside our upcoming data storage and hosting solutions, OneSec users will be able to create their own ‘publish subscribe’ data pipelines via the Streamr protocol, in a permissionless manner. This partnership is fuelled by our shared commitment to data security, privacy, and a truly decentralized digital world. Here's to the many technical synergies ahead! - End of post, beware of scammers -

OpSec

84,532 次观看 • 2 年前

Imagine OptimAI Data Network is a giant library that AI Agents use to learn and work. 📚 But here’s the twist, instead of one person deciding what goes in the library, everyone in our community can help pick, check, and improve the books (data). That’s what OptimAI DataDAO is: + DAO? It stands for "Decentralized Autonomous Organization", fancy words for a club where we all make the rules together, no single boss in charge. Like a playground game where kids vote on the fun! + It’s how we, the community, decide together which data is accurate, useful, and fair for AI to use. + The more you contribute, the stronger our network gets, and the more value we all share. You're building the future! Stay tuned - we’re building something that will change how AI learns. BUIDL with us:

Imagine OptimAI Data Network is a giant library that AI Agents use to learn and work. 📚 But here’s the twist, instead of one person deciding what goes in the library, everyone in our community can help pick, check, and improve the books (data). That’s what OptimAI DataDAO is: + DAO? It stands for "Decentralized Autonomous Organization", fancy words for a club where we all make the rules together, no single boss in charge. Like a playground game where kids vote on the fun! + It’s how we, the community, decide together which data is accurate, useful, and fair for AI to use. + The more you contribute, the stronger our network gets, and the more value we all share. You're building the future! Stay tuned - we’re building something that will change how AI learns. BUIDL with us:

OptimAI Network

29,532 次观看 • 11 个月前

At Open AGI, our CEO Ahmed Rashad shared why trust is the new compute. AI is moving from generating content to making life-or-death decisions — medical diagnoses, autonomous vehicles, military systems. If the training data is wrong, the decisions are wrong. Meanwhile, models are increasingly trained on synthetic outputs, creating feedback loops that degrade quality. Data supply chains are opaque. Adversarial attacks are real. The next AI race won’t be won by bigger models. It will be won by those who control and verify the data layer. Perle Labs is building the sovereign, human-verified, on-chain auditable infrastructure high-stakes AI requires. Trust wins the AI race. Thank you Sentient for having us! No better way to end off our time at ETHDenver 🏔🦬🦄. Until next time 🫡

At Open AGI, our CEO Ahmed Rashad shared why trust is the new compute. AI is moving from generating content to making life-or-death decisions — medical diagnoses, autonomous vehicles, military systems. If the training data is wrong, the decisions are wrong. Meanwhile, models are increasingly trained on synthetic outputs, creating feedback loops that degrade quality. Data supply chains are opaque. Adversarial attacks are real. The next AI race won’t be won by bigger models. It will be won by those who control and verify the data layer. Perle Labs is building the sovereign, human-verified, on-chain auditable infrastructure high-stakes AI requires. Trust wins the AI race. Thank you Sentient for having us! No better way to end off our time at ETHDenver 🏔🦬🦄. Until next time 🫡

Perle Labs

29,619 次观看 • 5 个月前

"Who owns the machinery determines whether it is used in a decentralized or centralized way." - Yanis Varoufakis at Web3 Summit Web3 Foundation found 129 companies across banking, insurance, AI, and advertising that have built business models on personal data. That is what concentrated ownership looks like in practice. Open-source infrastructure is where ownership becomes contestable. The Product SDK is public. The protocol is governed on-chain. The code is auditable by anyone.

"Who owns the machinery determines whether it is used in a decentralized or centralized way." - Yanis Varoufakis at Web3 Summit Web3 Foundation found 129 companies across banking, insurance, AI, and advertising that have built business models on personal data. That is what concentrated ownership looks like in practice. Open-source infrastructure is where ownership becomes contestable. The Product SDK is public. The protocol is governed on-chain. The code is auditable by anyone.

Parity Technologies

11,036 次观看 • 27 天前

What if crypto research was as easy as chatting with ChatGPT, but powered by real market data👑 Introducing CMC AI, a powerful new tool from CoinMarketCap that combines the speed of AI with the depth of live crypto data. It delivers fast, data-backed answers to your questions: ✅ Want to know why Bitcoin's price is rising? ✅ Curious about the latest news on your favorite cryptocurrency? ✅ Need sentiment analysis? It pulls real-time data and explains it in seconds. But it goes far beyond basic Q&A. In the future, you’ll be able to ask anything! For example, you could ask it to: – Discover undervalued tokens based on volume, MC, and sentiment. – Compare Layer 1s or L2s by adoption, speed, and dev activity. – Detect rug-pull risk via wallet distribution and tokenomics red flags. – Break down your portfolio by risk, correlation, and potential return. – Explore new use cases in DeFi, AI, RWA and DePIN And much more! 🔗Try it here: CMC AI changes how you learn, think, and act in Web3🧠

What if crypto research was as easy as chatting with ChatGPT, but powered by real market data👑 Introducing CMC AI, a powerful new tool from CoinMarketCap that combines the speed of AI with the depth of live crypto data. It delivers fast, data-backed answers to your questions: ✅ Want to know why Bitcoin's price is rising? ✅ Curious about the latest news on your favorite cryptocurrency? ✅ Need sentiment analysis? It pulls real-time data and explains it in seconds. But it goes far beyond basic Q&A. In the future, you’ll be able to ask anything! For example, you could ask it to: – Discover undervalued tokens based on volume, MC, and sentiment. – Compare Layer 1s or L2s by adoption, speed, and dev activity. – Detect rug-pull risk via wallet distribution and tokenomics red flags. – Break down your portfolio by risk, correlation, and potential return. – Explore new use cases in DeFi, AI, RWA and DePIN And much more! 🔗Try it here: CMC AI changes how you learn, think, and act in Web3🧠

Alaoui Capital

34,900 次观看 • 1 年前

A Letter to Our Community: The Road Ahead for Robotics To our Community and Partners, As we step into 2026, our mission at Axis is clearer than ever: Constructing the definitive End-to-End Scaling Layer for Robotics. Our goal is to accelerate the transfer of diverse human intelligence into Robotics General Intelligence (RGI). By owning the critical path of intelligence creation, we are turning the physical limitations of robotics into a scalable, software-driven future. Here is our strategic outlook and roadmap for the year ahead. The Core Thesis: Simulation is the Only Way Out The path to RGI is currently blocked by Data Scarcity, Generalization Fragility, and Hardware Fragmentation. At Axis, we believe Simulation is the only way out. Our Simulation Data Platform and Data Augmentation Engine transform raw data into "Synthetic Gold". Backed by academic milestones like Roboverse, Skill Blending, and GraspVLA, we have proven that pure simulation can achieve the generalization required for the real world. We don’t just collect data; we architect it. The Engine: Why Crypto? We believe RGI should come from all, not a few. Crypto is not just a feature; it is the primitive that powers our entire ecosystem flywheel: - Incentive Mechanism: Democratizing contribution and rewarding the trainers and developers. - Assetization: Turning proprietary data and refined models into liquid, ownable assets. - Verifiable Workflow: We are opening the "Black Box" of AI. By bringing total transparency to the Task Generation → Data Collection → Model Training pipeline, we ensure every byte of intelligence is verifiable, traceable, and secure. 2026 Strategic Deliverables This year, we are committed to delivering three foundational pillars: - The World's Largest Training Dataset for Robots: A robot training set—diverse, high-quality interaction data at an unprecedented scale. - A Robotics Foundation Model: A universal robotic brain trained on our pure simulation and synthetic data, capable of robust cross-embodiment transfer and open-world adaptability. - Evolvable Robot Hardware: Robots deployed with Axis models that autonomously evolve through continuous interaction, turning every deployment into a self-improving node within our RGI network. The Ultimate Vision We are building more than models; we are architecting the Distributed Machine Economy. A future where every dataset, model, and robotic embodiment is a verifiable asset in a global, autonomous network. Thank you for building the future of intelligence with us✌️📷

A Letter to Our Community: The Road Ahead for Robotics To our Community and Partners, As we step into 2026, our mission at Axis is clearer than ever: Constructing the definitive End-to-End Scaling Layer for Robotics. Our goal is to accelerate the transfer of diverse human intelligence into Robotics General Intelligence (RGI). By owning the critical path of intelligence creation, we are turning the physical limitations of robotics into a scalable, software-driven future. Here is our strategic outlook and roadmap for the year ahead. The Core Thesis: Simulation is the Only Way Out The path to RGI is currently blocked by Data Scarcity, Generalization Fragility, and Hardware Fragmentation. At Axis, we believe Simulation is the only way out. Our Simulation Data Platform and Data Augmentation Engine transform raw data into "Synthetic Gold". Backed by academic milestones like Roboverse, Skill Blending, and GraspVLA, we have proven that pure simulation can achieve the generalization required for the real world. We don’t just collect data; we architect it. The Engine: Why Crypto? We believe RGI should come from all, not a few. Crypto is not just a feature; it is the primitive that powers our entire ecosystem flywheel: - Incentive Mechanism: Democratizing contribution and rewarding the trainers and developers. - Assetization: Turning proprietary data and refined models into liquid, ownable assets. - Verifiable Workflow: We are opening the "Black Box" of AI. By bringing total transparency to the Task Generation → Data Collection → Model Training pipeline, we ensure every byte of intelligence is verifiable, traceable, and secure. 2026 Strategic Deliverables This year, we are committed to delivering three foundational pillars: - The World's Largest Training Dataset for Robots: A robot training set—diverse, high-quality interaction data at an unprecedented scale. - A Robotics Foundation Model: A universal robotic brain trained on our pure simulation and synthetic data, capable of robust cross-embodiment transfer and open-world adaptability. - Evolvable Robot Hardware: Robots deployed with Axis models that autonomously evolve through continuous interaction, turning every deployment into a self-improving node within our RGI network. The Ultimate Vision We are building more than models; we are architecting the Distributed Machine Economy. A future where every dataset, model, and robotic embodiment is a verifiable asset in a global, autonomous network. Thank you for building the future of intelligence with us✌️📷

Axis Robotics

27,858 次观看 • 6 个月前

At OptimAI Network, we believe the true power of AI Agent comes from the data behind it—and that power shouldn’t rest in the hands of just a few. That’s why we’re building a decentralized ecosystem with you, our community, at its core. Using EVM Layer-2, DePIN, and your collective efforts, we’re creating smarter, faster, and continuously evolving AI agents. Through our DePIN (Decentralized Physical Infrastructure) Network, your nodes are the backbone. You provide the computing power, data sourcing, storage, and bandwidth that keep this system resilient, scalable, and truly distributed. It’s not just infrastructure—it’s a movement powered by all of us. Then there’s the DeHIN (Decentralized Human Intelligence), where your insights shine. As a global community, you validate and refine data, ensuring our AI models stay accurate, diverse, and grounded in real-world perspectives. This isn’t about top-down control; it’s about harnessing the intelligence of many to make AI better for everyone. We’re not just dreaming of a decentralized AI future—we’re building it, together. This is your network, your impact, and your chance to redefine what AI can be. Let’s keep pushing forward. Learn more at:

At OptimAI Network, we believe the true power of AI Agent comes from the data behind it—and that power shouldn’t rest in the hands of just a few. That’s why we’re building a decentralized ecosystem with you, our community, at its core. Using EVM Layer-2, DePIN, and your collective efforts, we’re creating smarter, faster, and continuously evolving AI agents. Through our DePIN (Decentralized Physical Infrastructure) Network, your nodes are the backbone. You provide the computing power, data sourcing, storage, and bandwidth that keep this system resilient, scalable, and truly distributed. It’s not just infrastructure—it’s a movement powered by all of us. Then there’s the DeHIN (Decentralized Human Intelligence), where your insights shine. As a global community, you validate and refine data, ensuring our AI models stay accurate, diverse, and grounded in real-world perspectives. This isn’t about top-down control; it’s about harnessing the intelligence of many to make AI better for everyone. We’re not just dreaming of a decentralized AI future—we’re building it, together. This is your network, your impact, and your chance to redefine what AI can be. Let’s keep pushing forward. Learn more at:

OptimAI Network

21,362 次观看 • 1 年前

OptimAI Lite Node v1.1: Built for Scale, Designed for You! 💕 In just 2 weeks since the launch, the OptimAI Network has seen explosive growth—130,000+ active node participants powering the future of decentralized AI. With this incredible momentum came a new challenge: ensuring our network could scale seamlessly to support massive concurrent connections and real-time participation. That’s why we’ve rolled out OptimAI Lite Node v1.1—a major upgrade focused on: + Stabilizing infrastructure to handle high traffic from a global community. + Enhancing performance for smoother data mining, validation, and edge compute participation. + Refining user experience with UI updates that make contributing effortless. Every line of code and infrastructure upgrade was made with one goal in mind: to support YOU—the builders, validators, and visionaries of the OptimAI ecosystem. Now’s the time to bring more friends into the journey. 🔥 The more we grow, the smarter and stronger the network becomes—and the greater the rewards. Let’s keep building, validating, scaling. Together we’re not just powering AI—we’re reshaping how it’s built. Join or revisit the node here: 🌐 Chrome Extension: 📱Telegram Mini-App: What’s Coming Next: OptimAI Edge Node & the Rise of Agentic AI 🔸OptimAI Edge Node (Mobile) We’re working hard on the next major release: the Edge Node for mobile, which will allow mining and AI tasks to run in the background—unlocking more earning opportunities and decentralized compute power from your smartphones. 🔸More Task Types & Missions Expect new types of contributions, from AI-enhanced data validation to edge inference and scraping automation—powered by autonomous mining agents. 🔸Expanded Rewards Program As we grow, more reward tiers, bonuses, and campaigns will be introduced. Your participation now paves the way for long-term benefits. Also, do not forget to checkout our article below and learn more about our latest Community Tips & Best Practices!👇 __________________ OptimAI Network #L2 #DePIN Reinforcement Data Network for #Agentic #AI Mine Data. Fuel AI. Earn Rewards. Turn Your Data into Tomorrow’s AI #Agent. Visit our website at:

OptimAI Lite Node v1.1: Built for Scale, Designed for You! 💕 In just 2 weeks since the launch, the OptimAI Network has seen explosive growth—130,000+ active node participants powering the future of decentralized AI. With this incredible momentum came a new challenge: ensuring our network could scale seamlessly to support massive concurrent connections and real-time participation. That’s why we’ve rolled out OptimAI Lite Node v1.1—a major upgrade focused on: + Stabilizing infrastructure to handle high traffic from a global community. + Enhancing performance for smoother data mining, validation, and edge compute participation. + Refining user experience with UI updates that make contributing effortless. Every line of code and infrastructure upgrade was made with one goal in mind: to support YOU—the builders, validators, and visionaries of the OptimAI ecosystem. Now’s the time to bring more friends into the journey. 🔥 The more we grow, the smarter and stronger the network becomes—and the greater the rewards. Let’s keep building, validating, scaling. Together we’re not just powering AI—we’re reshaping how it’s built. Join or revisit the node here: 🌐 Chrome Extension: 📱Telegram Mini-App: What’s Coming Next: OptimAI Edge Node & the Rise of Agentic AI 🔸OptimAI Edge Node (Mobile) We’re working hard on the next major release: the Edge Node for mobile, which will allow mining and AI tasks to run in the background—unlocking more earning opportunities and decentralized compute power from your smartphones. 🔸More Task Types & Missions Expect new types of contributions, from AI-enhanced data validation to edge inference and scraping automation—powered by autonomous mining agents. 🔸Expanded Rewards Program As we grow, more reward tiers, bonuses, and campaigns will be introduced. Your participation now paves the way for long-term benefits. Also, do not forget to checkout our article below and learn more about our latest Community Tips & Best Practices!👇 __________________ OptimAI Network #L2 #DePIN Reinforcement Data Network for #Agentic #AI Mine Data. Fuel AI. Earn Rewards. Turn Your Data into Tomorrow’s AI #Agent. Visit our website at:

OptimAI Network

76,427 次观看 • 1 年前

This is Rivian's next-generation Autonomy hardware and software platform, which the company says is a "self-improving, end-to-end AI system for our autonomy platform that scales." • 11 cameras (65 total megapixels) • 5 radars • New front-facing LiDAR • Powered by a new in-house designed chip called RAP1 (5nm TSMC) Rivian also detailed its software-first approach to autonomy, powered by the new Rivian Autonomy Platform and an end-to-end data loop used for training. The company introduced its Large Driving Model, a foundational autonomous model trained like a Large Language Model: "Utilizing Group-Relative Policy Optimization, the LDM will distill superior driving strategies from massive datasets into the vehicle."

This is Rivian's next-generation Autonomy hardware and software platform, which the company says is a "self-improving, end-to-end AI system for our autonomy platform that scales." • 11 cameras (65 total megapixels) • 5 radars • New front-facing LiDAR • Powered by a new in-house designed chip called RAP1 (5nm TSMC) Rivian also detailed its software-first approach to autonomy, powered by the new Rivian Autonomy Platform and an end-to-end data loop used for training. The company introduced its Large Driving Model, a foundational autonomous model trained like a Large Language Model: "Utilizing Group-Relative Policy Optimization, the LDM will distill superior driving strategies from massive datasets into the vehicle."

Sawyer Merritt

282,679 次观看 • 7 个月前

IoTeX was selected by Messari as a core case study in its new AI report, cited alongside World, Coinbase 🛡️, Openτensor Foundaτion and others. Messari’s research underscores a bigger shift: real-world AI needs verified data, and IoTeX is the first full stack infrastructure that can supply it. Live device data becomes verifiable insight, ready for real-world agentic deployment. Quicksilver is already proving this in production with DIMO, Nubila Network and more, powering agentic applications built on IoTeX-verified real-world intelligence. Read the full analysis in the report below.

IoTeX was selected by Messari as a core case study in its new AI report, cited alongside World, Coinbase 🛡️, Openτensor Foundaτion and others. Messari’s research underscores a bigger shift: real-world AI needs verified data, and IoTeX is the first full stack infrastructure that can supply it. Live device data becomes verifiable insight, ready for real-world agentic deployment. Quicksilver is already proving this in production with DIMO, Nubila Network and more, powering agentic applications built on IoTeX-verified real-world intelligence. Read the full analysis in the report below.

IoTeX

56,151 次观看 • 7 个月前

🚀 Introducing EgoExo Forge - built on top of Rerun, Gradio, and Hugging Face hub (I’ll be in San Francisco July 21–29 — if you’re into robotics, egocentric AI, large-scale data collection, or just want to chat, DM me!) In my opinion, large-scale, diverse, and high-quality data is still the largest bottleneck for generalized robotics deployment. I believe that some version of imitation learning from human examples will be the most scalable + clean way to train humanoid robots 🤖 (similar to what Tesla did for Full Self Driving). Teleop is too expensive to collect a large enough dataset in a reasonable manner, so passive collection via egocentric (and in certain cases, exocentric) views feels like the right bet. Over the past few months, I've been trying to build out the scaffolding for this and using Rerun as my underlying infrastructure. Data being collected needs to be easily inspectable + time series and rerun provides the right tooling for this. My goal is to first build out a ground truth representative dataset from already existing open source data, generate some reasonable baselines, and then go out and collect my own data that adheres to the defined schema. 🔍 Starting with open-source datasets 1. EgoDex from Apple 2. HOCap from Nvidia and the University of Texas at Dallas 3. Assembly101 from Meta All these different datasets have different sensor configurations + annotations, so my goal with egoexo-forge is to have one consistent labeling scheme + data layout. I built a data pipeline that aligns all of the different datasets in one general schema assuming the COCO133 keypoint layout that allows for exo+ego, ego only, or exo only Since the scaffolding is already there, it becomes MUCH easier to add other datasets. So the next ones that I'll be including are HD-EPIC kitchens dataset, HOT3D, and finally my own personal iPhone + insta360 go collection method. Once I have a diverse variety of datasets, I'll double down on what I believe to be the key algorithms required to make useful data for imitation learning 📊 1. Camera Pose estimation via SLAM/SFM for ego perspective (and automatic calibration for exo) 2. Human pose estimation for both egocentric + exocentric views 3. Metric 3D reconstruction + object tracking I'll be setting up reasonable open-source baselines for each of these to validate that these datasets work, and then finally try to use the generated datasets for some imitation learning via the pi0-lerobot repo I've been working on. I plan on making a blog post + providing more info on all of this in the near future so stay tuned

🚀 Introducing EgoExo Forge - built on top of Rerun, Gradio, and Hugging Face hub (I’ll be in San Francisco July 21–29 — if you’re into robotics, egocentric AI, large-scale data collection, or just want to chat, DM me!) In my opinion, large-scale, diverse, and high-quality data is still the largest bottleneck for generalized robotics deployment. I believe that some version of imitation learning from human examples will be the most scalable + clean way to train humanoid robots 🤖 (similar to what Tesla did for Full Self Driving). Teleop is too expensive to collect a large enough dataset in a reasonable manner, so passive collection via egocentric (and in certain cases, exocentric) views feels like the right bet. Over the past few months, I've been trying to build out the scaffolding for this and using Rerun as my underlying infrastructure. Data being collected needs to be easily inspectable + time series and rerun provides the right tooling for this. My goal is to first build out a ground truth representative dataset from already existing open source data, generate some reasonable baselines, and then go out and collect my own data that adheres to the defined schema. 🔍 Starting with open-source datasets 1. EgoDex from Apple 2. HOCap from Nvidia and the University of Texas at Dallas 3. Assembly101 from Meta All these different datasets have different sensor configurations + annotations, so my goal with egoexo-forge is to have one consistent labeling scheme + data layout. I built a data pipeline that aligns all of the different datasets in one general schema assuming the COCO133 keypoint layout that allows for exo+ego, ego only, or exo only Since the scaffolding is already there, it becomes MUCH easier to add other datasets. So the next ones that I'll be including are HD-EPIC kitchens dataset, HOT3D, and finally my own personal iPhone + insta360 go collection method. Once I have a diverse variety of datasets, I'll double down on what I believe to be the key algorithms required to make useful data for imitation learning 📊 1. Camera Pose estimation via SLAM/SFM for ego perspective (and automatic calibration for exo) 2. Human pose estimation for both egocentric + exocentric views 3. Metric 3D reconstruction + object tracking I'll be setting up reasonable open-source baselines for each of these to validate that these datasets work, and then finally try to use the generated datasets for some imitation learning via the pi0-lerobot repo I've been working on. I plan on making a blog post + providing more info on all of this in the near future so stay tuned

Pablo Vela

32,085 次观看 • 1 年前