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AI doesn’t scale on mega-models — it scales on distilled skills at the edge. From Davos, Qualcomm's Nakul Duggal breaks down the real physics of edge AI: smaller, purpose-built models, mixed precision, and ruthless focus on power + cost efficiency. The biggest constraint is that if AI runs in... show more

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74,120 Aufrufe • vor 6 Monaten •via X (Twitter)

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As Larry Ellison explains, there are two types of AI models: real-time models, also called AI on the edge, where you need ultra-low latency decisions (think autonomous driving or robotics), and models that don’t need an immediate response, like ChatGPT, where the system has time to reason. Real-time models require local compute inside the device, and these chips have nothing to do with the GPUs running in data centers. The AI-on-the-edge market is still largely untapped — and it’s going to be a multi-trillion-dollar opportunity. I believe $AMD will be one of the biggest beneficiaries

As Larry Ellison explains, there are two types of AI models: real-time models, also called AI on the edge, where you need ultra-low latency decisions (think autonomous driving or robotics), and models that don’t need an immediate response, like ChatGPT, where the system has time to reason. Real-time models require local compute inside the device, and these chips have nothing to do with the GPUs running in data centers. The AI-on-the-edge market is still largely untapped — and it’s going to be a multi-trillion-dollar opportunity. I believe $AMD will be one of the biggest beneficiaries

Daniel

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50% of the world's data is created at the edge and that % will only increase - making the PC the fulcrum of the edge AI revolution. Our latest AI advancements — from AI PCs to cutting-edge data center solutions — are designed to help organizations of every size to seamlessly adopt AI, drive faster insights, improve efficiency and accelerate their results 💻 #DellTechWorld

50% of the world's data is created at the edge and that % will only increase - making the PC the fulcrum of the edge AI revolution. Our latest AI advancements — from AI PCs to cutting-edge data center solutions — are designed to help organizations of every size to seamlessly adopt AI, drive faster insights, improve efficiency and accelerate their results 💻 #DellTechWorld

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Ready to experience the future of #AI? #Inferium's MVP is coming. Be among the first to: 🧠 Evaluate cutting-edge AI models ⚡ Run #inference on AI models 💰 Earn rewards & top the leaderboard Join waitlist now to secure early access and exclusive perks: #Inferium #MVP #AI #Inference

Ready to experience the future of #AI? #Inferium's MVP is coming. Be among the first to: 🧠 Evaluate cutting-edge AI models ⚡ Run #inference on AI models 💰 Earn rewards & top the leaderboard Join waitlist now to secure early access and exclusive perks: #Inferium #MVP #AI #Inference

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Exciting to see the new RTX 50-series GPUs and Windows Subsystem for Linux powering models from Nvidia NIM and Azure AI Foundry on Windows 11 PCs. A game-changer for running AI on the edge.

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⚡Why Edge Compute Matters for the Future of Agentic AI AI isn’t just about smarter models, it’s about where they run. Centralized clouds are costly, slow, and controlled by a few. That’s not the future. 👉Join the OptimAI Network: With OptimAI Edge Compute and the upcoming Core Node release, every device becomes part of a decentralized supercomputer: + AI models run directly on your devices (phones, desktops, IoT devices) + Data stays local, secure, and real-time + Compute scales with the community, not corporations This is how we power the next generation of Agentic AI - AI systems that don’t just think, but act like you. Lightweight, fast, everywhere, for everyone. Stay tuned. The Edge is coming.

⚡Why Edge Compute Matters for the Future of Agentic AI AI isn’t just about smarter models, it’s about where they run. Centralized clouds are costly, slow, and controlled by a few. That’s not the future. 👉Join the OptimAI Network: With OptimAI Edge Compute and the upcoming Core Node release, every device becomes part of a decentralized supercomputer: + AI models run directly on your devices (phones, desktops, IoT devices) + Data stays local, secure, and real-time + Compute scales with the community, not corporations This is how we power the next generation of Agentic AI - AI systems that don’t just think, but act like you. Lightweight, fast, everywhere, for everyone. Stay tuned. The Edge is coming.

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🌟 Another Epic Sneak Peek: OptimAI Core Node’s Edge AI Computing Power! We’re excited to continue unveiling the upcoming OptimAI Core Node features! This time, we’re introducing Edge AI Computing, a game-changing feature that will make your devices even more powerful in contributing to the OptimAI Network. 🔥 What is Edge AI Computing? With the OptimAI Core Node, your device’s idle computing resources (CPU/GPU) and storage will be put to work, powering critical AI computing tasks, including: 🔸Edge Inference: Running real-time AI predictions directly on your device without sending data to centralized servers. 🔸Hot LLM Models: Accelerating large language models for high-speed NLP tasks. 🔸Generative AI Models and More: Contributing to the training and inference of cutting-edge generative AI, like text-to-image models, deep learning, and more. More Contributions, Bigger Rewards Await! This Edge AI Computing feature allows us to leverage the full potential of decentralized computing power, reducing latency, increasing efficiency, and making AI more accessible. The more you contribute, the bigger the rewards!🔥 Stay in the Loop—Start Today with OptimAI Lite Node! While the OptimAI Core Node is still in the works, you don’t have to wait to join the action. The more you contribute, the greater the rewards! Let’s build a stronger, smarter, and more decentralized AI network together. Stay tuned for more exciting updates! 🔸Extension Node: 🔸Telegram Node: 🔸Register at: #DePIN

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America has the edge in the world’s most powerful AI models, no question. But China is playing a different game: efficiency, scale, and global deployment. Kyle Chan from Brookings China explains: "Does winning mean developing the world's most powerful AI models? If yes, then the us has the decisive lead. American ai models are widely recognized as the best in the world on virtually every metric you can think of, from math and reasoning to coding and AI agents, American private companies continue to set the pace at the technological frontier supported by deep capital markets, a dynamic innovation ecosystem, and the best talent from around the world. China's AI models are improving quickly but continue to lag behind. Chinese AI companies face real constraints on compute due to our export controls and their own limited capital resources, so instead they're prioritizing other goals. They're focused on efficiency, building models that are cheaper to train and run. They're focused on adoption using an open source strategy to win users around the world, and they're focused on integration with other platforms and services. On sheer performance, I would expect the gap between our models and theirs to persist or even widen over time. But model performance is not everything."

America has the edge in the world’s most powerful AI models, no question. But China is playing a different game: efficiency, scale, and global deployment. Kyle Chan from Brookings China explains: "Does winning mean developing the world's most powerful AI models? If yes, then the us has the decisive lead. American ai models are widely recognized as the best in the world on virtually every metric you can think of, from math and reasoning to coding and AI agents, American private companies continue to set the pace at the technological frontier supported by deep capital markets, a dynamic innovation ecosystem, and the best talent from around the world. China's AI models are improving quickly but continue to lag behind. Chinese AI companies face real constraints on compute due to our export controls and their own limited capital resources, so instead they're prioritizing other goals. They're focused on efficiency, building models that are cheaper to train and run. They're focused on adoption using an open source strategy to win users around the world, and they're focused on integration with other platforms and services. On sheer performance, I would expect the gap between our models and theirs to persist or even widen over time. But model performance is not everything."

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Instead of all AI running in centralized data centers... We're moving to "edge computing" - where AI runs directly on devices. Imagine your smart home devices, cars, and phones all running their own AI models. The implications are massive:

Instead of all AI running in centralized data centers... We're moving to "edge computing" - where AI runs directly on devices. Imagine your smart home devices, cars, and phones all running their own AI models. The implications are massive:

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Physics AI 🌊 Jensen just unveiled the NVIDIA Isaac GR00T Reference Humanoid Robot at GTC Taipei--the world’s first open-source humanoid robot reference design Built on Jetson Thor edge computing and the Isaac GR00T open platform, it features a Unitree H2 Plus body with Sharpa five-finger dexterous hands and 75 degrees of freedom. Even before Physical AI truly explodes, NVIDIA has built a complete end-to-end full-stack infrastructure: >chips (Jetson Thor + Blackwell), >synthetic data (GR00T-Dreams), >world models (Cosmos), >foundation models (GR00T N-series VLA), >high-fidelity simulation platforms (Isaac Sim + Isaac Lab + Omniverse). Dozens of humanoid robot companies ,including Agility Robotics, Aglie robotics,Boston Dynamics, Figure, 1X, NEURA Robotics, XPENG Robotics, and more are already running large-scale daily simulation training on this platform, rapidly iterating perception, reasoning, and actions in virtual environments, speeding up the jump from lab prototypes to real factory deployment. By providing an open reference design and full-stack tools, NVIDIA has dramatically lowered the barrier, letting every robotics team join the Physical AI wave with low cost and high efficiency.

Physics AI 🌊 Jensen just unveiled the NVIDIA Isaac GR00T Reference Humanoid Robot at GTC Taipei--the world’s first open-source humanoid robot reference design Built on Jetson Thor edge computing and the Isaac GR00T open platform, it features a Unitree H2 Plus body with Sharpa five-finger dexterous hands and 75 degrees of freedom. Even before Physical AI truly explodes, NVIDIA has built a complete end-to-end full-stack infrastructure: >chips (Jetson Thor + Blackwell), >synthetic data (GR00T-Dreams), >world models (Cosmos), >foundation models (GR00T N-series VLA), >high-fidelity simulation platforms (Isaac Sim + Isaac Lab + Omniverse). Dozens of humanoid robot companies ,including Agility Robotics, Aglie robotics,Boston Dynamics, Figure, 1X, NEURA Robotics, XPENG Robotics, and more are already running large-scale daily simulation training on this platform, rapidly iterating perception, reasoning, and actions in virtual environments, speeding up the jump from lab prototypes to real factory deployment. By providing an open reference design and full-stack tools, NVIDIA has dramatically lowered the barrier, letting every robotics team join the Physical AI wave with low cost and high efficiency.

CyberRobo

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Destra Edge — $DSYNC From Idea to Reality Yesterday, we introduced Destra Edge. Today, we show you what it means. For too long, AI has lived in data centers. Expensive. Centralized. Controlled by a few. Meanwhile, billions of smartphones sit idle. Powerful GPUs. Doing nothing. That doesn’t make sense. So we’re building something different. Destra Edge turns everyday smartphones into a global AI inference network. No servers. No cloud monopolies. Just real compute at the edge. This video shows the system taking shape — how inference is distributed, how it runs on-device, and how results come together without central control. This is not finished. And that’s the point. You’re watching it being built. Layer by layer. In public. The magic is in the scale. More phones means more power. More power means stronger AI. The network grows simply because people join. No passive mining. No fake activity. Only real GPU inference. Measured. Verified. Rewarded. AI shouldn’t live in warehouses. It should live in your pocket. This is edge-level decentralization. This is permissionless inference. This is Destra Network.

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🤖 "Everything ends up running on the edge." In a recent interview, our founder Joseph Denne shared his thoughts on AI, Agents, and the massive opportunity ahead with Robotics. The common thread? These systems demand speed, locality, and scale. Edge is built for all three 🧵👇

🤖 "Everything ends up running on the edge." In a recent interview, our founder Joseph Denne shared his thoughts on AI, Agents, and the massive opportunity ahead with Robotics. The common thread? These systems demand speed, locality, and scale. Edge is built for all three 🧵👇

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General purpose AI got us here but it won’t take us where we’re going. When everyone is using the same models, there’s no edge. The shift is clear from renting AI to owning AI and that's what Manos Koukoumidis is pushing forward with Oumi. This is where AI gets real.

General purpose AI got us here but it won’t take us where we’re going. When everyone is using the same models, there’s no edge. The shift is clear from renting AI to owning AI and that's what Manos Koukoumidis is pushing forward with Oumi. This is where AI gets real.

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🔔 The Google AI Edge Gallery is now live on iOS via TestFlight. Experience the power and speed of LLMs models running entirely on-device, including support for image and audio modalities.️

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AMD expands the AMD Ryzen AI Embedded P100 Series portfolio, delivering more cores and more system TOPS vs. previously introduced Ryzen AI Embedded P100 for energy-efficient, low-latency performance at the industrial edge. Built for advanced physical AI acceleration, it powers factory automation, robotics, test and measurement, healthcare imaging, and more, in rugged, “always-on” environments. Learn more:

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I sat down with Manish Gupta, co-founder of Corridor Platforms, to dive into how AI (and Gen AI) is reshaping the highly regulated banking industry. From automating customer interactions to tackling risk & compliance, banks have to adapt—or fall behind. How do you govern AI in a world where trust is everything? Manish breaks it down, including: ✅ AI-driven customer service that actually works ✅ The challenge of bias & compliance in AI decisions ✅ Why smaller banks might have an edge over the big guys ✅ The secret to getting AI past the first sales call in enterprise The race is on. Banks that embrace AI responsibly will dominate the next decade. 🚀 Watch the full conversation here:

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