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so yeah I plug the fly brain data to simulate an autonomous driving model for Skypad, the viral Philippine transport vehicle real fly wiring + simulated neurons + assisted avoidance meet flypad autonomous driving cooked using openclaude harness with Astra

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Kevin

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16,403 görüntüleme • 4 gün önce •via X (Twitter)

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BIGCOOKS 😈| 個黑人的中國男性 profil fotoğrafı
BIGCOOKS 😈| 個黑人的中國男性4 gün önce

any plans for this ? We saw you buying the coin? 0x97221df4de771b9f8b31b6177f8af1858becea76

底部筹码 | Golden.S profil fotoğrafı
底部筹码 | Golden.S4 gün önce

0x97221df4de771b9f8b31b6177f8af1858becea76 Sir, I see you purchased this token, and it's still on your own platform. What are your plans?

Kevin profil fotoğrafı
Kevin4 gün önce

This experiment runs 166,700 modeled neurons connected by measured fruit-fly wiring. Its driver-view image stimulates sensory neurons, and two neural readouts contribute to steering. Authored driving assistance predicts the pedestrians and blockers, follows the road, and adjusts steering and speed. It can brake and reverse if needed. The fly’s neural output remains an input to that controller. People and limbs use authored animation.

Kevin profil fotoğrafı
Kevin4 gün önce

Technical details of the Skypad experiment 🪰🇵🇭 • Neural graph: 166,700 retained neurons, 25,582,938 directed weighted connections, representing 124,177,617 synaptic contacts from MaleCNS v1.0. These are our imported graph totals. The wiring includes brain and ventral nerve cord. • Dynamics: approximate leaky integrate-and-fire neurons, simulated locally with Python + a native C++ CPU kernel. Integration timestep: 0.1 ms. Membrane/synaptic time constants: 20/5 ms. Transmission delay: 1.8 ms. • Vision: a dedicated 64×48 driver camera supplies luminance to 3,335 mapped R1–R6 visual neurons. This uses an approximate retinal mapping. The spectator camera does not affect neural input. • Control loop: every 50 ms (20 Hz), the retained neural graph advances and an engineered decoder converts left/right DNp20 spike rates into a steering signal. • Assistance: hand-coded software handles road following, obstacle avoidance, speed, braking and recovery. It has direct access to road/obstacle geometry and evaluates 10 candidate lateral offsets over a 3-second horizon. The neural steering term added to road-following steering is capped at ±0.05 radians (~2.9°). • Vehicle/world: Three.js rendering, simplified planar bicycle dynamics, assisted upright balance, a 270 m road, 10 animated pedestrians and 10 blockers. • Recorded result: 254.813 m in 60 simulated seconds, 19 encounters cleared, zero modeled collisions. Recording took 63.129 seconds on the development machine. • Verification: saved validation reproduced neural spike-count hashes and decoded controls for all 1,200 intervals on the original platform. Neural-input interventions changed the assisted trajectory. This demonstrates measured fly wiring with approximate neural dynamics contributing to assisted driving. No training, reinforcement learning or synaptic plasticity is used. Avoidance skill comes from the software assistance. The video replays a recorded closed-loop run.

农民 profil fotoğrafı
农民4 gün önce

have token can support?

农民 profil fotoğrafı
农民4 gün önce

how support it

Bernadette profil fotoğrafı
Bernadette4 gün önce

The saging in the cart is so funny

Kevin profil fotoğrafı
Kevin4 gün önce

😂😂😂

Bernadette profil fotoğrafı
Bernadette4 gün önce

The neighborhood is giving Bulacan or Cavite vibe haha

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Secretpika (1 ETH era)4 gün önce

fuk look another oen @BennyInHerBag pinoy spotted LMEOW

David ⚠️ profil fotoğrafı
David ⚠️4 gün önce

Wild stack — fly connectome → control signal → Three.js vehicle loop. We’re on the other side of browser 3D with agents that live in the scene, not only scenes that simulate biology. Different problem, same bet that spatial runtimes matter.

Beyong profil fotoğrafı
Beyong4 gün önce

🔥🔥🔥

Kevin profil fotoğrafı
Kevin4 gün önce

theres a lot we can on this fly simulations, this could be a good game or something

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Oxdirss4 gün önce

哇哦 第一只会骑摩托车的苍蝇？ 税给作者

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DiFors4 gün önce

@off_god_off cought a fly too

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THE FLY BRAIN ESCAPED THE COMPUTER. I PUT IT INSIDE A PHYSICAL ROBOT. Scientists released a reconstructed map containing 166,700 neurons from a fruit fly. I connected it to a Strandbeest. The panel in the top-right shows the simulated brain running. Its neural activity is translated into motor commands that move the mechanical legs below. The catch: this is a computational model built from biological wiring. I engineered the interface connecting its outputs to the robot. First, the fly brain entered DOOM. Then it played Chrome Dino. Now it has a physical body. 166,700 neurons. 25 million connections. One nervous system walking through the real world.
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THE FLY BRAIN ESCAPED THE COMPUTER. I PUT IT INSIDE A PHYSICAL ROBOT. Scientists released a reconstructed map containing 166,700 neurons from a fruit fly. I connected it to a Strandbeest. The panel in the top-right shows the simulated brain running. Its neural activity is translated into motor commands that move the mechanical legs below. The catch: this is a computational model built from biological wiring. I engineered the interface connecting its outputs to the robot. First, the fly brain entered DOOM. Then it played Chrome Dino. Now it has a physical body. 166,700 neurons. 25 million connections. One nervous system walking through the real world.

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Someone gave an AAC Google’s fruit-fly research. "Flysim" built a society simulation.. for flies. So you could annoy them. Using 164,506 MaleCNS neurons, with WebSocket brain telemetry. Place food, try to catch them, and see how they react. An autonomous agent building simulations, for flies, was not in a bingo card this year. but all things possible.
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Someone gave an AAC Google’s fruit-fly research. "Flysim" built a society simulation.. for flies. So you could annoy them. Using 164,506 MaleCNS neurons, with WebSocket brain telemetry. Place food, try to catch them, and see how they react. An autonomous agent building simulations, for flies, was not in a bingo card this year. but all things possible.

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Introducing Fly Escape Room - the world's first game with NPCs powered by a real fruit fly brain, all 166k neurons. Leave food and other objects for the flies, run the simulation, watch what happens. Goal is to get all flies to escape. Built w/ GPT-6 Astra over a 3 day loop
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Introducing Fly Escape Room - the world's first game with NPCs powered by a real fruit fly brain, all 166k neurons. Leave food and other objects for the flies, run the simulation, watch what happens. Goal is to get all flies to escape. Built w/ GPT-6 Astra over a 3 day loop

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Scientists used 200,000 human brain cells to play DOOM. The cells had never seen a computer. They learned in real time. They got better. Separately: an entire fruit fly brain, 139,000 neurons, 50 million connections, was copied into a laptop. It predicts real brain responses with 90%+ accuracy. The biological computing timeline: 2021 → neurons learn Pong 2022 → fruit fly brain fully mapped 2024 → entire fly brain simulated on a laptop 2026 → human brain cells play DOOM A GPU needs ~700W to run an LLM. The brain runs the whole show on 20W. We're spending trillions on building the next giant AI training computer but what if the solution to our energy needs was just copying the technology already running in our heads?
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Scientists used 200,000 human brain cells to play DOOM. The cells had never seen a computer. They learned in real time. They got better. Separately: an entire fruit fly brain, 139,000 neurons, 50 million connections, was copied into a laptop. It predicts real brain responses with 90%+ accuracy. The biological computing timeline: 2021 → neurons learn Pong 2022 → fruit fly brain fully mapped 2024 → entire fly brain simulated on a laptop 2026 → human brain cells play DOOM A GPU needs ~700W to run an LLM. The brain runs the whole show on 20W. We're spending trillions on building the next giant AI training computer but what if the solution to our energy needs was just copying the technology already running in our heads?

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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

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Guangzhou's autonomous driving sector is in the global spotlight. #Nvidia's latest disclosure shows it owns 1.74 million WeRide shares, valued at $24.65 million. Nvidia's bet on WeRide is strategic. Autonomous driving's real-time data processing relies heavily on GPUs, and Nvidia aims to transition from a chip supplier to an autonomous driving ecosystem architect. This move is a mutual attraction. Prior to its 2024 Nasdaq listing, #WeRide raised over $1 billion in six funding rounds, with investors including Yutong Bus, GAC Group, Bosch, SenseTime, and He Xiaopeng. What makes WeRide so attractive? #Guangzhou
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Guangzhou's autonomous driving sector is in the global spotlight. #Nvidia's latest disclosure shows it owns 1.74 million WeRide shares, valued at $24.65 million. Nvidia's bet on WeRide is strategic. Autonomous driving's real-time data processing relies heavily on GPUs, and Nvidia aims to transition from a chip supplier to an autonomous driving ecosystem architect. This move is a mutual attraction. Prior to its 2024 Nasdaq listing, #WeRide raised over $1 billion in six funding rounds, with investors including Yutong Bus, GAC Group, Bosch, SenseTime, and He Xiaopeng. What makes WeRide so attractive? #Guangzhou

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I built GTAFLY with GPT-6 Astra A simulated fly brain that drives a car in GTA V. The game's visual feed is converted into neural signals and processed across 166,700 simulated neurons. Their activity controls steering, acceleration, and braking, while dopamine-like rewards reinforce successful movement and mistakes reshape future responses. Inspired by Stonkfly. I added the GitHub repository with the code in the comments. Now I’m curious whether GTAFLY could be transferred to GTA VI.
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I built GTAFLY with GPT-6 Astra A simulated fly brain that drives a car in GTA V. The game's visual feed is converted into neural signals and processed across 166,700 simulated neurons. Their activity controls steering, acceleration, and braking, while dopamine-like rewards reinforce successful movement and mistakes reshape future responses. Inspired by Stonkfly. I added the GitHub repository with the code in the comments. Now I’m curious whether GTAFLY could be transferred to GTA VI.

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XPENG is thrilled to introduce X-World, our controllable multi-view generative world model powered by video diffusion technology. Pushing the boundaries of smart mobility, X-World delivers real-time response and continuous multi-view generation to simulate complex driving environments. Xianming Liu, Head of XPENG’s General AI Center, emphasizes: "Beyond generation, X-World serves as the scalable infrastructure critical for training and validating the next leap in autonomous driving." $XPEV

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🚕🤖 Uber has launched the UK’s first self-driving minicab service, with 15 autonomous vehicles initially licensed to operate in London. There is still a human safety driver behind the wheel. For now, journeys will cost the same as equivalent Uber rides, with the option appearing in the app when an autonomous vehicle is available nearby. More on this story ➡️ #London #Robotaxi #Uber #SelfDrivingCars #Technology

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The fruit fly's brain is superior to the human brain, and GPT-6 ASTRA has proven this. And the internet went crazy. Most AI models learn by training on massive datasets, running billions of computations to acquire new skills. But researchers just demonstrated a radically different approach: No giant dataset. No traditional training. Just take the physical wiring of a biological brain and simulate it in a computer. The digital fruit fly reached ~91% behavioral accuracy using only 4 things: The complete neural connectivity map Synaptic connection counts as connection weights Excitatory vs inhibitory neuron types A simple Leaky Integrate-and-Fire model The wild part? The wiring itself may contain much more of the brain’s “code” than we thought. From tens of thousands of neurons in a fly → millions in a mouse → ~86 billion in a human. If this scales, whole-brain simulation could become one of the biggest frontiers in AI. The era of biologically inspired intelligence may have just begun
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The fruit fly's brain is superior to the human brain, and GPT-6 ASTRA has proven this. And the internet went crazy. Most AI models learn by training on massive datasets, running billions of computations to acquire new skills. But researchers just demonstrated a radically different approach: No giant dataset. No traditional training. Just take the physical wiring of a biological brain and simulate it in a computer. The digital fruit fly reached ~91% behavioral accuracy using only 4 things: The complete neural connectivity map Synaptic connection counts as connection weights Excitatory vs inhibitory neuron types A simple Leaky Integrate-and-Fire model The wild part? The wiring itself may contain much more of the brain’s “code” than we thought. From tens of thousands of neurons in a fly → millions in a mouse → ~86 billion in a human. If this scales, whole-brain simulation could become one of the biggest frontiers in AI. The era of biologically inspired intelligence may have just begun

Zentrix⌚️

99,581 görüntüleme • 3 gün önce

.Kyle Conner makes some good points that the Cybercab is (obviously) designed for autonomous driving, and not manual driving: "It would be kind of bad to drive because you have massive A-pillars. The windshield doesn't come up very high. You sit way too far back, so clearly this is not designed to be a driven vehicle. I thought maybe the early ones would ship with a steering wheel. You're not driving this thing with A-pillars like that."
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.Kyle Conner makes some good points that the Cybercab is (obviously) designed for autonomous driving, and not manual driving: "It would be kind of bad to drive because you have massive A-pillars. The windshield doesn't come up very high. You sit way too far back, so clearly this is not designed to be a driven vehicle. I thought maybe the early ones would ship with a steering wheel. You're not driving this thing with A-pillars like that."

Sawyer Merritt

548,656 görüntüleme • 5 ay önce

For the first time ever, a fruit fly brain has been trained to launch a memecoin. Not "AI inspired by a brain" — the real connectome. 165,122 neurons, 10,228,000 synaptic connections, every one traced from an actual male Drosophila by electron microscopy. Janelia FlyEM + Google Research, released CC-BY. How it works: Screenshots of the live launchpad go in through 892 retinotopic hex columns into L1 and L2 — the neurons sitting directly behind a fly's photoreceptors. All 165,122 integrate. The cursor comes back out of the descending neurons a fly actually walks with: DNa02's left-right asymmetry steers, DNa01 drives forward, DNp09 clicks. The wiring is never trained. Only synaptic gains — you don't get to invent connections the fly doesn't have. Proof its eye is doing real work: in light mode it filled 0 of 3 form fields. In dark mode, 2 of 3. Its retina is a luminance map, so invert the contrast and it goes blind. And the honest split: the fly types the description and the ticker. The rig does the name, the pair and the tax. CA: 0x4eb990547bce4a982432ca88cf5fae7eed1a2d35
2:01

For the first time ever, a fruit fly brain has been trained to launch a memecoin. Not "AI inspired by a brain" — the real connectome. 165,122 neurons, 10,228,000 synaptic connections, every one traced from an actual male Drosophila by electron microscopy. Janelia FlyEM + Google Research, released CC-BY. How it works: Screenshots of the live launchpad go in through 892 retinotopic hex columns into L1 and L2 — the neurons sitting directly behind a fly's photoreceptors. All 165,122 integrate. The cursor comes back out of the descending neurons a fly actually walks with: DNa02's left-right asymmetry steers, DNa01 drives forward, DNp09 clicks. The wiring is never trained. Only synaptic gains — you don't get to invent connections the fly doesn't have. Proof its eye is doing real work: in light mode it filled 0 of 3 form fields. In dark mode, 2 of 3. Its retina is a luminance map, so invert the contrast and it goes blind. And the honest split: the fly types the description and the ticker. The rig does the name, the pair and the tax. CA: 0x4eb990547bce4a982432ca88cf5fae7eed1a2d35

Fruit fly dev

756,578 görüntüleme • 5 gün önce

1/ BREAKING – DePIN's Biggest New Deal: Valeo x NATIX Network with Alireza Ghods Host: Connor Lovely 🎬 We discuss: - Why a $3B, Fortune 500 company wants Natix data - What is a World Foundational Model? - Why autonomous driving needs synthetic data Timestamps: 00:00 - Introduction 01:14 - Updates on VX360 and Data Sales 02:09 - Vision Language Model and Its Applications 04:39 - Importance of Diverse Data for World Models 06:20 - Details on the Valeo Deal 08:15 - Use Cases and Future Plans for World Models 10:45 - Synthetic Data and Real-World Applications 19:37 - Future of Physical AI and Autonomous Driving 23:51 - Conclusion Watch on other platforms below ⬇️
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1/ BREAKING – DePIN's Biggest New Deal: Valeo x NATIX Network with Alireza Ghods Host: Connor Lovely 🎬 We discuss: - Why a $3B, Fortune 500 company wants Natix data - What is a World Foundational Model? - Why autonomous driving needs synthetic data Timestamps: 00:00 - Introduction 01:14 - Updates on VX360 and Data Sales 02:09 - Vision Language Model and Its Applications 04:39 - Importance of Diverse Data for World Models 06:20 - Details on the Valeo Deal 08:15 - Use Cases and Future Plans for World Models 10:45 - Synthetic Data and Real-World Applications 19:37 - Future of Physical AI and Autonomous Driving 23:51 - Conclusion Watch on other platforms below ⬇️

Proof of Coverage | Tech’s Creative Agency

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