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I trained a controller for Microduck using a 192-neuron Male CNS connectome subset. Watch its modeled neural activity drive exploratory head and body movements. Fun stuff.

Jiafei Duan

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33,596 次观看 • 1 个月前 •via X (Twitter)

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Simulating a fruit fly's neural network using custom WebGPU kernels, running locally in a browser. The demo uses real connectivity data for 166,700 neurons from the MaleCNS connectome. Paint neurons and watch their activity drive the fly's movements. Built with GPT-6 Astra.

Simulating a fruit fly's neural network using custom WebGPU kernels, running locally in a browser. The demo uses real connectivity data for 166,700 neurons from the MaleCNS connectome. Paint neurons and watch their activity drive the fly's movements. Built with GPT-6 Astra.

Xenova

158,621 次观看 • 1 个月前

We've uploaded a fruit fly. We took the FlyWire connectome of the fruit fly brain, applied a simple neuron model (Philip Shiu Nature 2024) and used it to control a MuJoCo physics-simulated body, closing the loop from neural activation to action. A few things I want to say about what this means and where we're going at eon. 🧵

We've uploaded a fruit fly. We took the FlyWire connectome of the fruit fly brain, applied a simple neuron model (Philip Shiu Nature 2024) and used it to control a MuJoCo physics-simulated body, closing the loop from neural activation to action. A few things I want to say about what this means and where we're going at eon. 🧵

Michael Andregg

2,007,483 次观看 • 7 个月前

ehm, chat... this is big they put a BCI in a rat’s brain, modeled its movements, and predicted the neural activity across behaviors with stunning accuracy, basically merging biomechanics with ai so now we could do the same with a human (Noland Arbaugh , could you help us out since you already have the neuralink?), put the modeled human in a virtual environment, load an llm, have it embodied, speed the simulation up, and get to agi.

ehm, chat... this is big they put a BCI in a rat’s brain, modeled its movements, and predicted the neural activity across behaviors with stunning accuracy, basically merging biomechanics with ai so now we could do the same with a human (Noland Arbaugh , could you help us out since you already have the neuralink?), put the modeled human in a virtual environment, load an llm, have it embodied, speed the simulation up, and get to agi.

vittorio

538,515 次观看 • 2 年前

Using monkey brain data to operate robotic arms! 🙉 Project Jenkins explores brain-computer interfaces by decoding neural activity into robotic movement and generating synthetic brain data from motion patterns. Using neural recordings from a macaque monkey named Jenkins, researchers developed models to decode brain signals into robotic arm movements and encode movement data into simulated neural activity. The project utilizes robotic arms and an interactive web console for real-time brain data generation from joystick inputs. The research paves the way for adaptive brain-computer interfaces by modeling brain activity more flexibly. Congrats to authors Dima Yanovsky, and Andrii Zahorodnii! 🦾

Using monkey brain data to operate robotic arms! 🙉 Project Jenkins explores brain-computer interfaces by decoding neural activity into robotic movement and generating synthetic brain data from motion patterns. Using neural recordings from a macaque monkey named Jenkins, researchers developed models to decode brain signals into robotic arm movements and encode movement data into simulated neural activity. The project utilizes robotic arms and an interactive web console for real-time brain data generation from joystick inputs. The research paves the way for adaptive brain-computer interfaces by modeling brain activity more flexibly. Congrats to authors Dima Yanovsky, and Andrii Zahorodnii! 🦾

Lukas Ziegler

21,637 次观看 • 1 年前

this is f*cking gold - I built a neural-vision prototype for humanoid robotics. With GPT Astra, my Robinhood token experiment took a very unexpected turn. CatBrain was originally meant ONLY for Robinhood tokens. Then I started experimenting beyond markets. → Cat-inspired visual processing: ON/OFF contrast channels and motion signals → A 512-unit synthetic spiking model → Neural activity decoded into left / right / hold proposals → Real fly-neuron annotations + Stonkfly source, included for future connectome experiments → Unitree H1 as the next integration target The visual design draws on mechanisms studied in the feline visual system. Code, data and research plan on GitHub in reply.

this is f*cking gold - I built a neural-vision prototype for humanoid robotics. With GPT Astra, my Robinhood token experiment took a very unexpected turn. CatBrain was originally meant ONLY for Robinhood tokens. Then I started experimenting beyond markets. → Cat-inspired visual processing: ON/OFF contrast channels and motion signals → A 512-unit synthetic spiking model → Neural activity decoded into left / right / hold proposals → Real fly-neuron annotations + Stonkfly source, included for future connectome experiments → Unitree H1 as the next integration target The visual design draws on mechanisms studied in the feline visual system. Code, data and research plan on GitHub in reply.

BuBBliK

40,297 次观看 • 29 天前

I can't f*ckin believe it - I BUILT a cat-inspired visual system for a ROBOT DOG A camera feeds visual data into a simulated feline neural system - and its activity controls where the robot moves. → 20,480 simulated neurons processing vision → 8 orientation channels detecting edges → Camera → NEURAL ACTIVITY → target → movement → Turns toward moving targets in REAL TIME → Runs completely OFFLINE → Connected to a Unitree Go2 through its SDK Movement appears right - it turns right. Left - it turns left. Centered - it locks on. The robot’s controller handles balance and legs. CATBRAIN handles where it looks and follows. The project is still IN DEVELOPMENT - you can follow every step on GitHub. I attached the link in the replies.

I can't f*ckin believe it - I BUILT a cat-inspired visual system for a ROBOT DOG A camera feeds visual data into a simulated feline neural system - and its activity controls where the robot moves. → 20,480 simulated neurons processing vision → 8 orientation channels detecting edges → Camera → NEURAL ACTIVITY → target → movement → Turns toward moving targets in REAL TIME → Runs completely OFFLINE → Connected to a Unitree Go2 through its SDK Movement appears right - it turns right. Left - it turns left. Centered - it locks on. The robot’s controller handles balance and legs. CATBRAIN handles where it looks and follows. The project is still IN DEVELOPMENT - you can follow every step on GitHub. I attached the link in the replies.

BuBBliK

44,188 次观看 • 28 天前

For the first time in history, GPT-6 Astra created a fly that is simply a fly. Not a chatbot pretending to be a fly. Not a simplified animation. A digital fly running its own connectome brain, perceiving a real room through its own senses and interacting with the environment using the power of AR. The entire loop is surprisingly wild: Spectacles capture the retina, light rays, hands, and the surrounding room → the room is converted into an inventory → sensory information is fed into the fly’s neural system → the MaleCNS connectome processes it → descending neurons and motor pools generate actions → the commands return to the Spectacles → wings, legs, and head respond. In other words, the fly sees through its own eyes, processes the world through its own simulated brain, and acts through its own virtual body. We are moving from AI that generates outputs to AI that actually has a body, senses, a brain, and a closed perception-action loop. The 🪰 is no longer just simulated. It is experiencing a world The developer Pavlo Tkachenko is pinned below in the post

For the first time in history, GPT-6 Astra created a fly that is simply a fly. Not a chatbot pretending to be a fly. Not a simplified animation. A digital fly running its own connectome brain, perceiving a real room through its own senses and interacting with the environment using the power of AR. The entire loop is surprisingly wild: Spectacles capture the retina, light rays, hands, and the surrounding room → the room is converted into an inventory → sensory information is fed into the fly’s neural system → the MaleCNS connectome processes it → descending neurons and motor pools generate actions → the commands return to the Spectacles → wings, legs, and head respond. In other words, the fly sees through its own eyes, processes the world through its own simulated brain, and acts through its own virtual body. We are moving from AI that generates outputs to AI that actually has a body, senses, a brain, and a closed perception-action loop. The 🪰 is no longer just simulated. It is experiencing a world The developer Pavlo Tkachenko is pinned below in the post

Zentrix⌚️

322,640 次观看 • 1 个月前

Giving Microduck object-tracking vision capabilities! 🦆👀🤖 It can now play fetch and doesn't get confused by other objects. Using Roboflow Trackers library I made Microduck keep track of the different objects in its sight and has a control policy for reaching the ball it tracks. Open-Source code below 👇

Giving Microduck object-tracking vision capabilities! 🦆👀🤖 It can now play fetch and doesn't get confused by other objects. Using Roboflow Trackers library I made Microduck keep track of the different objects in its sight and has a control policy for reaching the ball it tracks. Open-Source code below 👇

Alex Bodner

31,551 次观看 • 1 个月前

TWIST: a real-time teleoperation system for humanoid robots to mimic whole-body motions. Reference motion data is generated by retargeting human motion-capture data to the robot. Then, the controller is trained in simulation using reinforcement learning and behavior cloning.

TWIST: a real-time teleoperation system for humanoid robots to mimic whole-body motions. Reference motion data is generated by retargeting human motion-capture data to the robot. Then, the controller is trained in simulation using reinforcement learning and behavior cloning.

The Humanoid Hub

46,715 次观看 • 1 年前

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Jared Palmer

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In 2023 I directed and wrote for a mr. krabs rap battle and this year people started using it to ratio groomers and bad music, fun stuff.

In 2023 I directed and wrote for a mr. krabs rap battle and this year people started using it to ratio groomers and bad music, fun stuff.

Dilly!

897,254 次观看 • 1 年前

Just for fun, I've implemented a Convolutional Neural Network (CNN) that predicts handwritten digits... Fully using #glsl and fragment shaders! The model exactly has 2023 parameters and its inner activations are displayed as you draw Try it out live!

Just for fun, I've implemented a Convolutional Neural Network (CNN) that predicts handwritten digits... Fully using #glsl and fragment shaders! The model exactly has 2023 parameters and its inner activations are displayed as you draw Try it out live!

kishimisu

118,409 次观看 • 3 年前

love this minotaur head i made for a customer! its a custom 3dprint designed by me, and has moving eyelids using mini servo motors. #cosplay

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Willow Creative

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I uploaded both a male and female fruit fly's real brains into Minecraft, and got them to actually flirt. The male's courtship song (produced by his wings) , the real signal fruit flies use to attract a mate, is playing live through Minecraft note blocks, a direct translation of real neuron activity, not a sound effect. And the female is genuinely responding, standing closer, driven by her own real neural circuit. Two real animals from inside minecraft! #fly001

Ro0oney

17,364 次观看 • 1 个月前

I vibecoded this neural network visualization for my students and open sourced it. It shows a simple MLP trained on MNIST handwritten digits at several training steps. The visualization is using Three.js and it comes with training code in PyTorch . Link + repo 👇

I vibecoded this neural network visualization for my students and open sourced it. It shows a simple MLP trained on MNIST handwritten digits at several training steps. The visualization is using Three.js and it comes with training code in PyTorch . Link + repo 👇

David Finsterwalder | eu/acc

488,333 次观看 • 11 个月前

$BRAIN is live. the open-source fly-brain bridge has a ticker now, and the ticker is becoming the input for a physical robot. CA: 9LuwgFQemAoV9rgVBBtwbRSxBmamcRRbysEK8yL2pump what’s already done: the neural bridge is working. camera input becomes activity across eight virtual neural populations, and that activity becomes left and right motor commands IMU data feeds movement back into the model. smoothing, speed limits and a 500 ms watchdog are already built in the synthetic demo runs locally today. the ESP32 scaffold is ready for hardware integration the entire project is open source and MIT licensed github: what’s next, in order: the on-chain listener goes live. every $BRAIN transaction becomes a stimulus sent directly into the neural model then the physical robot connects. the wallet address determines which neurons activate, the amount determines the strength of the impulse, and the brain converts that reaction into movement then the livestream. every transaction, neural impulse and physical response visible in real time then user commands. spend $BRAIN to trigger a stronger reflex, request movement, temporarily control the robot, name a neuron or place your name on the stream the loop, plain: a transaction enters the neurons react the robot moves a Proof of Reflex is created with the transaction hash, neural activity map and video of the physical response the current brain is a small fly-inspired simulation. the bridge and local demo work today. the blockchain connection, physical robot and livestream are being built now the internet becomes its sensory organ. the blockchain becomes its nervous system. $BRAIN makes the body move.

$BRAIN is live. the open-source fly-brain bridge has a ticker now, and the ticker is becoming the input for a physical robot. CA: 9LuwgFQemAoV9rgVBBtwbRSxBmamcRRbysEK8yL2pump what’s already done: the neural bridge is working. camera input becomes activity across eight virtual neural populations, and that activity becomes left and right motor commands IMU data feeds movement back into the model. smoothing, speed limits and a 500 ms watchdog are already built in the synthetic demo runs locally today. the ESP32 scaffold is ready for hardware integration the entire project is open source and MIT licensed github: what’s next, in order: the on-chain listener goes live. every $BRAIN transaction becomes a stimulus sent directly into the neural model then the physical robot connects. the wallet address determines which neurons activate, the amount determines the strength of the impulse, and the brain converts that reaction into movement then the livestream. every transaction, neural impulse and physical response visible in real time then user commands. spend $BRAIN to trigger a stronger reflex, request movement, temporarily control the robot, name a neuron or place your name on the stream the loop, plain: a transaction enters the neurons react the robot moves a Proof of Reflex is created with the transaction hash, neural activity map and video of the physical response the current brain is a small fly-inspired simulation. the bridge and local demo work today. the blockchain connection, physical robot and livestream are being built now the internet becomes its sensory organ. the blockchain becomes its nervous system. $BRAIN makes the body move.

Frank

347,106 次观看 • 1 个月前

166,700 fruit fly neurons are walking a robot cat across a desk right now. In September 2026, Google Research and HHMI Janelia mapped every neuron and every connection in an adult male fruit fly's full nervous system, brain, optic lobes, and ventral nerve cord together, and published it in Cell. The number is staggering on its own: 166,700 neurons, roughly 125 million synapses, the most complete nervous system map of any animal ever built. Now that exact wiring is running live, simulated neuron for neuron, inside a small robotic quadruped equipped with a camera and motion sensors. Movement comes in through the sensors, the biological circuitry fires the way it always did, and the output drives the robot's legs directly. No one wrote the balance logic. No one coded the gait. The insect's own nervous system does that job, just on legs it never had. To be clear about what this is and isn't: nothing biological is alive in this loop. It's a full computational reconstruction of real neural wiring, controlling hardware instead of an insect body. The brain is real. The body is borrowed. Remarkable proof that a mapped nervous system can drive any body you give it, or a preview of something people aren't ready to think through yet?

166,700 fruit fly neurons are walking a robot cat across a desk right now. In September 2026, Google Research and HHMI Janelia mapped every neuron and every connection in an adult male fruit fly's full nervous system, brain, optic lobes, and ventral nerve cord together, and published it in Cell. The number is staggering on its own: 166,700 neurons, roughly 125 million synapses, the most complete nervous system map of any animal ever built. Now that exact wiring is running live, simulated neuron for neuron, inside a small robotic quadruped equipped with a camera and motion sensors. Movement comes in through the sensors, the biological circuitry fires the way it always did, and the output drives the robot's legs directly. No one wrote the balance logic. No one coded the gait. The insect's own nervous system does that job, just on legs it never had. To be clear about what this is and isn't: nothing biological is alive in this loop. It's a full computational reconstruction of real neural wiring, controlling hardware instead of an insect body. The brain is real. The body is borrowed. Remarkable proof that a mapped nervous system can drive any body you give it, or a preview of something people aren't ready to think through yet?

Zentrix⌚️

232,128 次观看 • 29 天前

I did these movements for 30 on 30 off for 5 sets with 60 seconds between sets. These patterns build the stuff adults forget about and kids desperately need coordination, rhythm, stability, mobility, body control, & athleticism. Give the circuit a try. Until next time, doggies.

I did these movements for 30 on 30 off for 5 sets with 60 seconds between sets. These patterns build the stuff adults forget about and kids desperately need coordination, rhythm, stability, mobility, body control, & athleticism. Give the circuit a try. Until next time, doggies.

Tyler Franklin

29,851 次观看 • 10 个月前

A former participant in a secret US legacy program reveals how gifted children were trained to pilot UAPs using pure consciousness. JOZAK: “They called it the Prometheus system.” “They’re not flown with joysticks. They’re flown through the mind.” “You take your consciousness outside of your body and you become that object. I would lay in a deep meditation… shift my consciousness into the vehicle and become it… pilot it up and down, move it left and right.” “I would shift my consciousness into it… like a split-screen video game. Third-person view on one side, first-person on the other. By flip-flopping the two, I would make it move.” “They monitored my brain waves and built a neural interface… so an Air Force guy with a controller could push up and the craft would move using my brain signals.”

A former participant in a secret US legacy program reveals how gifted children were trained to pilot UAPs using pure consciousness. JOZAK: “They called it the Prometheus system.” “They’re not flown with joysticks. They’re flown through the mind.” “You take your consciousness outside of your body and you become that object. I would lay in a deep meditation… shift my consciousness into the vehicle and become it… pilot it up and down, move it left and right.” “I would shift my consciousness into it… like a split-screen video game. Third-person view on one side, first-person on the other. By flip-flopping the two, I would make it move.” “They monitored my brain waves and built a neural interface… so an Air Force guy with a controller could push up and the craft would move using my brain signals.”

Defiant Ghost

13,335 次观看 • 4 个月前