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Natural Intelligence
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徐和平 西湖大学
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马颖毅
Organic Ai
Chongker Interactive Robot Cat
Incremental Learning
Human and Robot Toching Fingers Video
Ai 芯片中 Pe Matrix-Vector Noc 各个模块的作用与合作关系
Live from the 2026 AI Summit: "Decoding Nature: Nature’s Intelligence Meets Machine Intelligence" | Flagship Pioneering
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A brain-computer interface co-piloted by artificial intelligence could improve how people with paralysis complete tasks, according to a study published in Nature Machine Intelligence. Link to the article in the comments. | Nature Portfolio
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A paper in Nature Machine Intelligence presents a sensor design that offers accurate force sensation across a three-dimensional surface while being robust, low-cost and easy to fabricate. It can be transferred to a wide variety of robot parts. Read the paper: https://go.nature.com/3JQGa4s | Nature Portfolio
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A Nature Machine Intelligence paper presents a robot, named Morti, that is inspired by animals. The robot learns to match the controller to its mechanics and learns to walk within 1 hour. Read the paper: https://go.nature.com/3B3jHQO | Nature Portfolio
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A paper in Nature Machine Intelligence introduces "Foldaway," a compact origami robot that can be used as a portable interface for haptic interactions. Read the paper here: https://go.nature.com/38tXDOz | Nature Portfolio
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The morphology of a robot determines how efficiently it can traverse different terrain. A Nature Machine Intelligence paper presents a robot that can adapt it’s morphology when it is detecting different terrain and learn which configuration is most effective. Read the paper: https://go.nature.com/3bVbfWy | Nature Portfolio
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A paper in Nature Machine Intelligence presents a wearable system designed to assist navigation for blind and partially sighted people. This system uses AI algorithms to survey the environment and send signals to the wearer as they approach an obstacle or object. Link to the research in the comments. | Nature Portfolio
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A recent study reveals the potential of cutting-edge machine learning technology to revolutionise the operation of nuclear reactors. In a remarkable combination of nuclear technology and machine learning, a team of researchers from the U.S. Department of Energy's (DOE) Argonne National Laboratory have made a substantial breakthrough in enhancing safety and efficiency in a type of next-generation nuclear reactor, specifically a sodium-cooled fast reactor (SFR). The paper details an SFR as a type
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