Computer Enjoyer

Los Angeles
Joined March 2025
ULTIMATE BOTS SEASON 2 IS HERE. 🤖🏆 4 teams. 6 events. $100K on the line. Teams will earn points across 3 disciplines: 🥊 Martial arts 💃 Dancing 🏁 Obstacle course Season 2 hits F1 Austin → TwitchCon → IEEE Humanoids → CES → Big Game Weekend → NVIDIA GTC. Captains + teams announced soon. Follow for reveals, ticket drops & live streams.
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We did incredible engineering to do something incredibly stupid. Last night at @sushitrash's show at @ChaseCenter, our humanoid raised a middle finger to Joji and all of San Francisco — in front of 15,000 people. In 4 hours, we fixed a broken robot hand, designed and manufactured hand mount, retargeted my motion from video using Ultimate Bots Studio and deployed with the latest NVIDIA machine learning policy live on stage. For over a year we've been putting humanoid robots into the most unpredictable environments there are — live crowds, every week — with zero injuries or significant accidents. I'm proud to work with @_patrickrose and @emerson who have the engineering depth and the audacity to take impossible projects and deliver them. Some may say it's not serious or complex enough, a waste of time. I believe an important part of integrating robots into society is making them part of our social norms — teaching them how friends may talk to each other, not a sterile idea of the world. Most people only meet robots through headlines, and fear grows in that distance. Seeing a humanoid live — dancing, fighting, flipping you off — turns that fear into curiosity. That's why we put them in front of crowds and hand them over at our events and hackathons, where anyone can train one themselves the way they want. I'm happy every time someone walks out as a friend of the robots. San Francisco is the craziest city in the world and I love it. It's the only city where you can meet people and build projects this audacious. We love you San Francisco, and FUCK YOU!
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demons
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Training robots just got TikTok easy. Ultimate Bots Studio lets you make dances, gestures, full motion flows in 3 easy steps: 1) Upload a video → create a motion 2) Stitch motions → build a dance 3) Export to robot and share with community Try it -> link in the comments
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How do we train robots today? What’s changed so that anyone can teach them new moves? This is what @DDobas broke down on the @TEDTalks stage today. We’re moving from complex robotics pipelines to something much more intuitive: show the robot a move, and it learns. The full talk drops in the coming weeks. For now, here are a few backstage moments from the UFB team in Vancouver, having way too much fun with it. Thanks @bilawalsidhu for giving us the stage!
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New League. New Website. Your favorite world-famous humanoid fights are entering the next phase. We’re launching the next generation of humanoid sports - the UFB Fighting League. Now’s your chance to get involved. Visit UFB.GG and join as a Pilot, Ghost, or Team Manager.
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Yesterday we held the UFB Ghost Trials at @CalHacks Hack Nights — hands-on trials where students learned to retarget motions from videos, train motion imitation policies (BeyondMimic) in mjlab, then competed in sim + real robot deployments! This is about making advanced humanoid training accessible to students everywhere — not just labs. Top teams impressed, making progress towards permanent placement in the league. Congrats to team Molt, Justin and Alice, for taking the win 🚀🤖 Shoutout to @kevin_zakka (creator of mjlab — the backbone of our sim training) and massive props to @UFBots tech team: @emerson @_patrickrose and @DDobas for powering this and pushing the frontier forward! Video of sim showdowns, real deployments, and winners below 👇
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Happy to have led the workshops at UFB Ghost Trials — covering video motion retargeting, training BeyondMimic in mjlab, latest papers like Sonic/BFM-Zero, plus team support, sim evals & real-robot deployments. Thrilled seeing more students get hands-on with humanoid training! 🚀🤖
Yesterday we held the UFB Ghost Trials at @CalHacks Hack Nights — hands-on trials where students learned to retarget motions from videos, train motion imitation policies (BeyondMimic) in mjlab, then competed in sim + real robot deployments! This is about making advanced humanoid training accessible to students everywhere — not just labs. Top teams impressed, making progress towards permanent placement in the league. Congrats to team Molt, Justin and Alice, for taking the win 🚀🤖 Shoutout to @kevin_zakka (creator of mjlab — the backbone of our sim training) and massive props to @UFBots tech team: @emerson @_patrickrose and @DDobas for powering this and pushing the frontier forward! Video of sim showdowns, real deployments, and winners below 👇
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Last week, we ran 8 humanoid robots live at DJ Wukong’s Chinese New Year show. 5 on stage. 3 with VIPs. I ran the full pipeline, from mocap to sim to real deployment. Here’s what worked (and what didn’t).
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[2/2] Locomotion and proprioceptive coordination is one case where I suspect there is a significant contribution from evolutionary biases, with additional learning over the lifetime of an individual; see “motor babbling” in pre-term infants.
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[1/2] A guess: morphological and kinematic constraints on observations and actions provide a foundation. Broad biases in wiring preference (among many other factors) steer development towards certain structural outcomes, promoting useful perceptual and behavioral dynamics.
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When you see the solution to AGI you will find that it was in fact so straightforward as to be obvious, and that it could have been developed decades ago
The most elegant solutions look inevitable in retrospect. They aren't some complex chain of tricks you've engineered out of nothing, but rather a simple abstraction that faithfully mirrors the shape of the problem.
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Replying to @StretchGoat_
For me it’s Nile Green
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