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LEONARDO, also called LEO, was built by researchers at Caltech’s Center for Autonomous Systems and Technologies. Its full name means LEgs ONboARD drOne. The idea is simple but unusual: • Build a small biped robot • Give it drone-style thrust • Use the legs for ground contact • Use...

135,515 görüntüleme • 1 ay önce •via X (Twitter)

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This work makes a humanoid robot do simple parkour moves by looking with a depth camera and choosing the right move on the fly. The big deal is that it turns lots of small human moves into long, real-time robot behavior, without hand-coding every transition or retraining for each new course. A humanoid robot is usually good at steady walking, but it often fails when it has to do fast moves like jumping up, vaulting, or rolling, and then keep going to the next obstacle. The hard part is that you cannot easily collect training data for every possible obstacle shape, distance, and mistake, so robots end up learning a few moves that only work in a narrow setup. This work starts from short clips of real human parkour moves, like stepping over, vaulting, climbing, and rolling. It uses motion matching, which is basically a smart “pick the next clip that fits best right now” search, to stitch those short clips into a long, smooth plan that looks like a human doing a whole course. Then it trains a controller with reinforcement learning (RL), which means the robot learns by trial and error to copy that plan while staying balanced and not falling. After training separate expert controllers for different moves, it compresses them into 1 controller that uses only onboard depth sensing and a simple “go this fast in this direction” command. In real tests on a Unitree G1 humanoid, it can clear multiple obstacles in a row, adapt when obstacles get moved, and climb a wall up to 1.25m.

Rohan Paul

37,121 görüntüleme • 6 ay önce

Rio de Janeiro just became the first city in the world to start reforesting itself with AI drones and the more i read about how it works the cooler it gets: the reason a city would even need this is that dead land is brutally hard to bring back when cattle farming or mining wrecks a piece of land, the soil turns hard and dry and basically dies. left alone it can stay like that for decades the only fix used to be huge crews planting seedlings by hand. one person covers about a hectare a day. at that pace a real forest takes years and a fortune, so most wrecked land just stays dead the company Rio hired is called MORFO. their answer is one drone plus an AI model doing the work of that entire crew it starts with the drone scanning the whole area from above from that scan, the AI studies the soil, the water, the slope, the plants already growing nearby it uses all of that to pick which native species have the best shot at surviving in each exact spot, choosing from a catalog of 300+ local plants once it knows what goes where, the drone flies back over and fires biodegradable seed pods into the ground, 180 every minute each pod holds seeds, nutrients, moisture. a little starter kit for surviving in dead soil flying like that, one drone covers up to 50 hectares a day. the work of a 50-person planting crew and it actually works. they tested it on Brazilian pasture that years of cattle farming had killed. a few months after planting, that same land had grass, bushes, small trees growing again the system keeps learning after the drones leave too. satellites watch what actually grows back, so each new project starts smarter than the last my favorite detail: the AI even decides where NOT to plant it left 16% of one 8,420-hectare site untouched because it detected the forest there was already regrowing on its own easily one of the coolest AI applications i've seen this year

Ole Lehmann

13,123 görüntüleme • 1 ay önce

April 30 • 12:00pm ET Art Blocks + OpenSea “Gift of time” began during my residency in Marfa, Texas, as part of the Art Blocks and OpenSea artist residency program, where a distinct shift in the experience of time became central to the work. In the desert, I felt time move differently. It stretched, slowed, and became something I noticed. After a few days, the rhythm changed. Moments felt longer, attention sharpened, and I became increasingly aware of each moment as it passed. This work comes from that condition. Time is not treated only as a theme, but as a system embedded in the structure of the piece. Different ways of measuring time, such as mechanical cycles, calendars, and lunar phases, are translated into rules that continuously transform the work. The piece does not represent time. It runs on it. Its movement is tied to blockchain time. Even when unseen, it continues to rotate and evolve. When loaded, it synchronizes with the present moment, but it does not begin when it is viewed, and it does not stop when it disappears from the screen. During the residency, I spent hours thinking, sketching, and making connections. Those connections are also visible. Elastic lines, like rubber bands, link elements across the piece, representing how memories connect, how one thought leads to another, and how everything builds over time. These same connections introduce moments where the system attempts to pull itself back, as if trying to regain control. But it never fully resets. It is not a loop. The movement continues, drifting forward, never returning to a fixed state. Visually, the work reveals its own construction. Lines, paths, and rotations expose an internal logic, like looking inside a mechanism. The drawing language recalls diagrams, technical sketches, or the interior of a mechanical watch. It is a system in motion, always active. “Gift of Time” exists because I was given time by Art Blocks, OpenSea, and above all my family. It is my way of saying thank you. It is both a reflection on time and a product of it. April 30 @ 12:00pm ET on Art blocks & OpenSea 1 / 1 / 365 • 0.02 Eth Art Blocks, OpenSea

Manuel Lariño ☔️

21,901 görüntüleme • 4 ay önce