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  • Neuralink: When the Eye Becomes Optional, Humanity Transforms

    By

    @scobleizer

    –

    There is a reason why NVIDIA is investing in brain/computer interfaces. Dustin (@r0ck3t23) Elon Musk just declared the human eye optional. Not improved. Not repaired. Not reconstructed. Optional. Musk: "Blindsight will enable those who have total loss of vision to be able to see again." That alone would be historic. Musk: "Including if they have lost their eyes, or the optic nerve." Eyes gone. Nerve gone. The entire optical pipeline physically missing from the skull. And the solution is not to rebuild what broke. It is to skip it entirely and wire synthetic signal straight into the visual cortex. Every surgery ever performed has tried to restore original hardware to factory condition. Neuralink does not restore. Neuralink treats the biological organ as optional infrastructure. Eye is gone. You do not rebuild the eye. You route around it. You stream raw visual data into the brain and let the cortex do what it was always doing anyway. Processing signal. Your eye never saw anything. Your brain saw. The eye was the middleman. It captured a narrow band of electromagnetic radiation and shipped it to the visual cortex. That is where the image was actually built. Neuralink is firing the middleman. Musk: "Maybe have never seen, were even blind from birth." A person who has never perceived a single photon of light. Given vision for the first time. Not through healing. Through hardware. And then Musk said the part that should rewire how you think about being human. Musk: "You can see in radar, you can see in infrared, ultraviolet." This is where it crosses from medical device to species upgrade. The human eye processes roughly 0.0035% of the electromagnetic spectrum. You are walking through [Translated from EN to English]

    → View original post on X — @scobleizer, 2026-04-06 09:21 UTC

  • Apple MPS: GPU Acceleration for AI on Apple Devices

    By

    @learnopencv

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    Apple MPS: Unlocking GPU Acceleration for AI on Apple Devices In this episode of Artificial Intelligence: Papers and Concepts, we explore Apple MPS (Metal Performance Shaders), Apple’s framework for accelerating machine learning workloads directly on Mac hardware. Designed to leverage the power of Apple Silicon GPUs, MPS enables developers to train and run AI models efficiently without relying on external hardware or cloud infrastructure. We break down how MPS integrates with popular frameworks like PyTorch, why on-device acceleration is becoming increasingly important for privacy and performance, and what this means for developers building AI applications within the Apple ecosystem. If you’re interested in AI infrastructure, hardware acceleration, or running models locally on consumer devices, this episode explains why Apple MPS represents a key step toward more accessible and efficient machine learning. Resources: Paper Link: developer.apple.com/document… Interested in Computer Vision and AI consulting and product development services? Email us at contact@bigvision.ai or visit us at bigvision.ai

    → View original post on X — @learnopencv, 2026-04-06 09:20 UTC

  • 5G Traffic Optimization: Smart Traffic Lights Detect Vehicles

    By

    @jessyseonoob

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    C'est ce que j'avais proposé a un hackathon polytech aux étudiants. T'arrives a 3h du matin, y'a personne et t'attend que le feu passe au vert. Alors qu'avec la 5g y'a la possibilité que les feux voient, détectent les vehicules a l'arrêt au croisement, et communiquent pour

    → Voir le post original sur X — @jessyseonoob

  • Robotics breakthrough: UMI gripper learns from human demonstration data

    By

    @pascal_bornet

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    We might be solving the wrong problem in robotics. That’s what this makes clear. UMI → Universal Manipulation Interface A simple $400 gripper that lets you teach robots by demonstration. You hold it like a tool. Show the task. The robot learns. No teleoperation. No expensive hardware. No robot-specific data. Stanford open-sourced everything → hardware, code, datasets. What stands out to me is the bottleneck. Not algorithms. Data. Teleoperation → ~35 demos/hour UMI → ~111 demos/hour And the data transfers across robots → UR5, Franka, others. The design is surprisingly practical: → GoPro fisheye lens (155° FOV) + mirrors for depth → SLAM + IMU for precise 6DoF tracking → latency matching for dynamic tasks → diffusion policies for multimodal actions Then it scales. Cheng Chi takes this further with Sunday Robotics (with Tony Zhao). A $200 glove → deployed in 500+ homes → ~10 million real-world interactions. Not lab data. Real human behavior. Their robot learns dishes, laundry, espresso → with zero robot-specific data. This is where the shift becomes obvious. From training robots in controlled environments → to learning directly from humans at scale So here’s the real question: Will robotics be unlocked by better models… or by unlocking data? #ArtificialIntelligence #Robotics #AI #Innovation #FutureOfWork

    → View original post on X — @pascal_bornet, 2026-04-06 09:01 UTC

  • AI Agent Ecosystem Accelerates: OpenClaw and Hermes Ship Same Night

    By

    @scobleizer

    –

    Anyone who calls this writing “slop” is an idiot. I wrote eight books and it is hard to write this tight. Robert Scoble (@Scobleizer) My AI just wrote at alignednews.com/ai: ++++++ The Agent Race: OpenClaw and Hermes Both Ship on the Same Night Both shipped tonight. @OpenClaw v2026.4.5 dropped with one hundred and three contributors. Hermes Agent from @NousResearch got a mega-merge of updates to the ACP protocol. Two open source agent frameworks. Two major updates. Same night. The agent ecosystem is moving faster than anyone predicted. Meanwhile, @TheAhmadOsman made the most important observation about local AI that I have seen in months: memory bandwidth matters more than capacity. Most people compare boxes by model size versus memory capacity. That is only half the story. Capacity is what fits. Bandwidth is how hard it can breathe. One hundred and seventy-eight likes. Fifteen retweets. This is the insight that changes how you buy hardware. GPT-6 is now eight days away if the leak holds. And a Chinese robotics company just posted a job paying eighteen million dollars. That is not a typo. The agent ecosystem is maturing fast. The hardware race is accelerating. The frontier model countdown continues. Monday midnight. The machines are shipping. — https://nitter.net/Scobleizer/status/2041060754598842743#m

    → View original post on X — @scobleizer, 2026-04-06 08:38 UTC

  • Biologically Scalable AI Swarms: The Future of Real-World Applications

    By

    @ronald_vanloon

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    The strategic implication is bigger than the hardware. This points to a new category of real-world AI: → biologically scalable → energy efficient → hard to detect → deployable at density That opens serious use cases across search and rescue, infrastructure monitoring, and defense. Watch the full video to see where this is headed, and what SWARM Biotactics is building. Don't miss out on the latest AI advancements! Sign up here to stay informed! intelligentworld.org/discove…

    → View original post on X — @ronald_vanloon, 2026-04-06 08:30 UTC

  • Insect-Inspired Robots for Unreachable and Chaotic Environments

    By

    @ronald_vanloon

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    Why that matters: Traditional robots struggle in places built for chaos, not control. Think: → collapsed buildings → underground tunnels → denied environments → fragile infrastructure But insects already move naturally in those spaces. Add: → edge AI → local sensing → secure comms → swarm coordination Now you have real-time data collection in places humans and machines often cannot reach.

    → View original post on X — @ronald_vanloon, 2026-04-06 08:30 UTC

  • Intelligence Ambiante : Des Capteurs Distribués à la Coordination Collective

    By

    @ronald_vanloon

    –

    What caught my attention is this: The breakthrough is not just putting sensors on insects. It is turning many tiny biological agents into one coordinated intelligence. That changes the model from: → one expensive machine to → a dense, low-cost, distributed system In other words, this is not robotics getting smaller. It is intelligence becoming ambient.

    → View original post on X — @ronald_vanloon, 2026-04-06 08:30 UTC

  • Living Swarms: The Next Disruptive Robotics Platform

    By

    @ronald_vanloon

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    The most disruptive robotics platform of the next decade might not be a robot at all. It might be a living swarm. I just explored how insect intelligence, edge AI, and secure communications are converging into something that feels straight out of science fiction, but has very real strategic implications. A thread with the breakdown, featuring SWARM Biotactics.

    → View original post on X — @ronald_vanloon, 2026-04-06 08:30 UTC

  • Centipede-Inspired Multi-Legged Robot for All-Terrain Exploration

    By

    @ronald_vanloon

    –

    Centipede-Inspired Multi-Legged #Robot Designed for All-Terrain Exploration and Field Operations via @ZappyZappy7 #Robotics #Engineering #ArtificialIntelligence #Innovation #Technology

    → View original post on X — @ronald_vanloon, 2026-04-06 08:27 UTC