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166,000 neurons from a dead fruit fly now pilot a robot that drives and flies. It's the wildest piece of engineering on the internet right now, and the pilot has been dead the whole time. The robot rolls across a bedroom floor like a toy until the wheels stop...

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Spike 1%

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53,705 просмотров • 3 дней назад •via X (Twitter)

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这是假的并非果蝇神经元在操控

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There's a fruit fly walking around right now that was never born. eon just released a video where they took a real fly's connectome — the wiring diagram of its brain — and simulated it. Dropped it into a virtual body. It started walking. Grooming. Feeding. Doing what flies do. Nobody taught it to walk. No training data, no gradient descent toward fly-like behavior. This is the opposite of how AI works. They rebuilt the mind from the inside, neuron by neuron, and behavior just... emerged. It's the first time a biological organism has been recreated not by modeling what it does, but by modeling what it is. A human brain is 6 OOM more neurons. That's a scaling problem, something we've gotten very good at solving. So what happens when we have a working copy of the human mind?
0:34

There's a fruit fly walking around right now that was never born. eon just released a video where they took a real fly's connectome — the wiring diagram of its brain — and simulated it. Dropped it into a virtual body. It started walking. Grooming. Feeding. Doing what flies do. Nobody taught it to walk. No training data, no gradient descent toward fly-like behavior. This is the opposite of how AI works. They rebuilt the mind from the inside, neuron by neuron, and behavior just... emerged. It's the first time a biological organism has been recreated not by modeling what it does, but by modeling what it is. A human brain is 6 OOM more neurons. That's a scaling problem, something we've gotten very good at solving. So what happens when we have a working copy of the human mind?

hattie

9,589,004 просмотров • 6 месяцев назад

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?
0:24

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⌚️

229,457 просмотров • 6 дней назад

166,700 neurons from a dead fruit fly are loose in a living room, and nobody wrote a single thing they do. Scientists sliced a male fruit fly's nervous system into electron microscope images and traced every wire by hand: 166,700 neurons, 25.6 million synapses, brain and nerve cord, the whole animal, published for free. Most people read that paper, and 1 team downloaded the fly and gave it a body. The brain runs on a Mac, the fly lives in AR glasses, and the room itself became its senses, because Spectacles already map surfaces and depth and hands, so eyes turned into a 16 × 8 retina on each fly's head, distance into 12 rays against the world mesh, and smell into Gemini naming a tea cup, flowers, a water bottle while depth drops every label into 3D where the brain can reach it. A hand moving too fast became fear. They read the decisions out of the exact neurons a real fly uses, where DNa02 turns it, MDN walks it backwards, MN9 feeds and the giant fiber fires the escape. The CPU crawled, 50 ms of brain time in 238 ms, so they vibe coded a Metal GPU kernel with Claude Code and got identical spikes in 41 ms. The first builds stuttered until a Perfetto trace showed the GPU nearly idle while the main thread choked, and squashing the board text from 67 draw calls to 2 unlocked 55 to 60 fps with 2 brains running at once. In the video a fly lands on an open palm while another peels off a hand coming in fast. That dodge is in no script anywhere, and they only gave it eyes.
0:27

166,700 neurons from a dead fruit fly are loose in a living room, and nobody wrote a single thing they do. Scientists sliced a male fruit fly's nervous system into electron microscope images and traced every wire by hand: 166,700 neurons, 25.6 million synapses, brain and nerve cord, the whole animal, published for free. Most people read that paper, and 1 team downloaded the fly and gave it a body. The brain runs on a Mac, the fly lives in AR glasses, and the room itself became its senses, because Spectacles already map surfaces and depth and hands, so eyes turned into a 16 × 8 retina on each fly's head, distance into 12 rays against the world mesh, and smell into Gemini naming a tea cup, flowers, a water bottle while depth drops every label into 3D where the brain can reach it. A hand moving too fast became fear. They read the decisions out of the exact neurons a real fly uses, where DNa02 turns it, MDN walks it backwards, MN9 feeds and the giant fiber fires the escape. The CPU crawled, 50 ms of brain time in 238 ms, so they vibe coded a Metal GPU kernel with Claude Code and got identical spikes in 41 ms. The first builds stuttered until a Perfetto trace showed the GPU nearly idle while the main thread choked, and squashing the board text from 67 draw calls to 2 unlocked 55 to 60 fps with 2 brains running at once. In the video a fly lands on an open palm while another peels off a hand coming in fast. That dodge is in no script anywhere, and they only gave it eyes.

Spike 1%

11,196 просмотров • 8 дней назад

A DEAD FLY IS DRIVING MY ROBOT RIGHT NOW. Not a metaphor. A reconstructed neural map of a fruit fly - 166,700 neurons, 25.6 million synapses - is now running on my MacBook and steering a quadruped robot in my living room. Here's how it works: 1. MaleCNS - a full connectome reconstruction of an adult fly brain - runs as a live simulation on my laptop. 2. I used Codex to build a decoder that reads the simulation's neural activity and turns it into movement commands: forward, left, right. 3. Those commands get sent over Wi-Fi to the robot, which still uses its own firmware to drive all 12 servos. The brain only decides where to go, not how to move each leg. No scripts. No prerecorded paths. The simulation runs continuously, live, while the robot walks. The fly has been dead for years. But its reconstructed nervous system is producing real decisions again, in real time, controlling a machine that didn't exist when it was alive. Next step: feed the robot's sensors back into the simulation and close the loop. A dead brain that can finally feel the world it's walking through. This fly has been dead for years. Its brain runs on my laptop. Its decisions move a machine through my living room. One dead nervous system, walking again.
0:57

A DEAD FLY IS DRIVING MY ROBOT RIGHT NOW. Not a metaphor. A reconstructed neural map of a fruit fly - 166,700 neurons, 25.6 million synapses - is now running on my MacBook and steering a quadruped robot in my living room. Here's how it works: 1. MaleCNS - a full connectome reconstruction of an adult fly brain - runs as a live simulation on my laptop. 2. I used Codex to build a decoder that reads the simulation's neural activity and turns it into movement commands: forward, left, right. 3. Those commands get sent over Wi-Fi to the robot, which still uses its own firmware to drive all 12 servos. The brain only decides where to go, not how to move each leg. No scripts. No prerecorded paths. The simulation runs continuously, live, while the robot walks. The fly has been dead for years. But its reconstructed nervous system is producing real decisions again, in real time, controlling a machine that didn't exist when it was alive. Next step: feed the robot's sensors back into the simulation and close the loop. A dead brain that can finally feel the world it's walking through. This fly has been dead for years. Its brain runs on my laptop. Its decisions move a machine through my living room. One dead nervous system, walking again.

kiruwaaaa

75,442 просмотров • 6 дней назад

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

793,305 просмотров • 11 дней назад

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
0:28

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⌚️

319,690 просмотров • 9 дней назад

I uploaded a fly brain and GPT-6 Astra into a Vector robot I bought on eBay Vector was supposed to be a desk pet. Now it has a reconstructed fruit fly nervous system running inside it. MaleCNS gives it 166,700 simulated neurons and 25.6 million connections. GPT-6 Astra gives it vision. Astra sees the room through Vector's camera - furniture, walls, doors, objects on the floor - and turns the visual scene into sensory signals. The fly brain processes those signals and chooses where Vector should go next. Astra sees. The fly brain decides. Vector moves. > No joystick > No preset route > No one manually telling it to turn left or right It started roaming around my apartment, stopping in front of furniture, changing direction, and reacting to things in its path. I bought it on eBay because it looked like a cute little WALL-E. Now it has a brain, eyes, and a body. And it keeps looking at me like it knows I’m the reason it exists.
0:25

I uploaded a fly brain and GPT-6 Astra into a Vector robot I bought on eBay Vector was supposed to be a desk pet. Now it has a reconstructed fruit fly nervous system running inside it. MaleCNS gives it 166,700 simulated neurons and 25.6 million connections. GPT-6 Astra gives it vision. Astra sees the room through Vector's camera - furniture, walls, doors, objects on the floor - and turns the visual scene into sensory signals. The fly brain processes those signals and chooses where Vector should go next. Astra sees. The fly brain decides. Vector moves. > No joystick > No preset route > No one manually telling it to turn left or right It started roaming around my apartment, stopping in front of furniture, changing direction, and reacting to things in its path. I bought it on eBay because it looked like a cute little WALL-E. Now it has a brain, eyes, and a body. And it keeps looking at me like it knows I’m the reason it exists.

kiruwaaaa

50,121 просмотров • 3 дней назад

DEAD FLY’S BRAIN learns to drive a car The same fly-brain model that played Beat Saber is now behind the wheel in the CARLA driving simulator It drives aggressively and sometimes veers off the road, but it has already learned to use the blinkers and horn
0:33

DEAD FLY’S BRAIN learns to drive a car The same fly-brain model that played Beat Saber is now behind the wheel in the CARLA driving simulator It drives aggressively and sometimes veers off the road, but it has already learned to use the blinkers and horn

RTVisual

12,868 просмотров • 11 дней назад

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
0:44

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⌚️

102,276 просмотров • 9 дней назад

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. 🧵
0:44

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

2,003,720 просмотров • 6 месяцев назад

made a 3d fly that lives on my mac desktop. its brain runs a live simulation of real neurons from the FlyWire fly connectome, so it only flees my cursor when the actual escape neuron fires. it walks on window edges and naps after lunch (fr)
0:28

made a 3d fly that lives on my mac desktop. its brain runs a live simulation of real neurons from the FlyWire fly connectome, so it only flees my cursor when the actual escape neuron fires. it walks on window edges and naps after lunch (fr)

Denis Shiryaev 💙💛

12,249 просмотров • 1 месяц назад

Scientists have completely mapped the brain and nervous system of an adult fly for the first time — more than 166,000 neurons and millions of connections The data was made publicly available, and then things got out of hand. It seems the scientific community may already regret it. Because over the past few days, people have “taught” the fly to: — Scroll through TikTok — Drink beer — Solve a Rubik’s Cube — Parallel park — Deploy a database — Vibe-code — Fly a plane — Control a virtual human — Control a robot — Skateboard to dubstep Don’t take it literally. But it’s worth watching as the strangest tech demo of September. There’s just one catch — the fly is dead.
0:23

Scientists have completely mapped the brain and nervous system of an adult fly for the first time — more than 166,000 neurons and millions of connections The data was made publicly available, and then things got out of hand. It seems the scientific community may already regret it. Because over the past few days, people have “taught” the fly to: — Scroll through TikTok — Drink beer — Solve a Rubik’s Cube — Parallel park — Deploy a database — Vibe-code — Fly a plane — Control a virtual human — Control a robot — Skateboard to dubstep Don’t take it literally. But it’s worth watching as the strangest tech demo of September. There’s just one catch — the fly is dead.

NEXTA

86,720 просмотров • 10 дней назад

A FLY BRAIN IS PLAYING CRASH BANDICOOT. Not an AI. Not a bot. Not a script. 166,700 simulated neurons from a real fly connectome - actual measured wiring from an actual insect. The loop: → The game screen gets fed in as retinal input → 166,700 neurons fire, ~57,000 spikes per update → The spikes get decoded into stick X and stick Y → The controller moves No training. No reward function. No weights. Just wiring that evolved over 300 million years, ripped out of a bug and pointed at a PlayStation game. Neural latency: 7.8ms. Real-time factor: 0.99x. It cleared the level. PERFECT. We spent a decade teaching machines to see. A housefly has been doing it since before we existed.
0:32

A FLY BRAIN IS PLAYING CRASH BANDICOOT. Not an AI. Not a bot. Not a script. 166,700 simulated neurons from a real fly connectome - actual measured wiring from an actual insect. The loop: → The game screen gets fed in as retinal input → 166,700 neurons fire, ~57,000 spikes per update → The spikes get decoded into stick X and stick Y → The controller moves No training. No reward function. No weights. Just wiring that evolved over 300 million years, ripped out of a bug and pointed at a PlayStation game. Neural latency: 7.8ms. Real-time factor: 0.99x. It cleared the level. PERFECT. We spent a decade teaching machines to see. A housefly has been doing it since before we existed.

RGK

12,083 просмотров • 7 дней назад

We might have just witnessed the first real mind upload. 🤯 Scientists scanned a fruit fly brain neuron by neuron, synapse by synapse, recreated it digitally, and placed it inside a simulated body. The fly walked. Groomed. Fed. No training. No prompts. No learning phase. The behavior was already in the wiring. That’s not just neuroscience anymore. That’s the first glimpse of digital minds.
0:34

We might have just witnessed the first real mind upload. 🤯 Scientists scanned a fruit fly brain neuron by neuron, synapse by synapse, recreated it digitally, and placed it inside a simulated body. The fly walked. Groomed. Fed. No training. No prompts. No learning phase. The behavior was already in the wiring. That’s not just neuroscience anymore. That’s the first glimpse of digital minds.

VraserX e/acc

862,037 просмотров • 6 месяцев назад

SOMEONE VIBE CODED AN ENTIRE SPACE ENGINE IN C++ AND PACKED 2 MILLION GALAXIES INTO A 1 MB EXE FILE > 2 million galaxies > each one with 200,000 to 750,000 stars > all rendered in real time > and you can actually fly through all of it you can fly straight out of one galaxy, cross the empty space between them, and drop into the next one a single photo on your phone is bigger than this whole universe. nothing is stored, its all generated on the fly from math, which is the only way you fit a galaxy count like that into a file that small people are already calling it elite dangerous 2.0 we went from needing a studio and a render farm to simulate space, to one person describing it to claude code and getting a flyable universe
5:16

SOMEONE VIBE CODED AN ENTIRE SPACE ENGINE IN C++ AND PACKED 2 MILLION GALAXIES INTO A 1 MB EXE FILE > 2 million galaxies > each one with 200,000 to 750,000 stars > all rendered in real time > and you can actually fly through all of it you can fly straight out of one galaxy, cross the empty space between them, and drop into the next one a single photo on your phone is bigger than this whole universe. nothing is stored, its all generated on the fly from math, which is the only way you fit a galaxy count like that into a file that small people are already calling it elite dangerous 2.0 we went from needing a studio and a render farm to simulate space, to one person describing it to claude code and getting a flyable universe

Om Patel

61,827 просмотров • 2 месяцев назад

Zebrafish NN It’s pretty amazing to learn that efforts to map the fruit FLY connectome (brain synapses) were successful and its amazing to see the digital fly brain successfully complete a whole series of tasks, including complex navigation of open worlds. The fruit fly is 160,000 neurons and 10^7 synapses. Teams are currently doing the same thing with a zebrafish which has a similar scale neuron count but 10x more synapses. Fly was 100TB raw data and Zebrafish is 200TB, so about 2x the raw data. For context a rodent is 70m neurons and 10^11 synapses. Rodents will come later. But this method looks like it creates totally outsized results with absolutely miniscule models. Zebrafish NN is a vertebrae connectome, it has much of the same basic structure as other vertebrae, unlike FLY connectome. We are just about used to LLMs and coding, but AI is really just beginning and there is a lot more, and a lot weirder stuff coming down the pipe. These connectomes have already shown to be incredibly resilient, you can blind their sensors and injure their outputs and they still succeed. They are incredibly compact. A whole lot of inanimate objects are going to get complete autonomy, totally offline, air gapped autonomy. They will be delivering pizzas and fighting wars. Connectomics is an opposite approach to LLMs but you can of course use LLMs to help develop connectomes. It’s amazing that you can take a biologically evolved brain, map it, produce a digital twin, and then run it at machine speed. Imagine a human brain accelerated from 100Hz neuron fires to 3,200,000,000Hz that a typical CPU runs at. That’s 30 million times faster. But would need 1-2 exabytes to map. Anyway “Zebrafish” is next.
0:20

Zebrafish NN It’s pretty amazing to learn that efforts to map the fruit FLY connectome (brain synapses) were successful and its amazing to see the digital fly brain successfully complete a whole series of tasks, including complex navigation of open worlds. The fruit fly is 160,000 neurons and 10^7 synapses. Teams are currently doing the same thing with a zebrafish which has a similar scale neuron count but 10x more synapses. Fly was 100TB raw data and Zebrafish is 200TB, so about 2x the raw data. For context a rodent is 70m neurons and 10^11 synapses. Rodents will come later. But this method looks like it creates totally outsized results with absolutely miniscule models. Zebrafish NN is a vertebrae connectome, it has much of the same basic structure as other vertebrae, unlike FLY connectome. We are just about used to LLMs and coding, but AI is really just beginning and there is a lot more, and a lot weirder stuff coming down the pipe. These connectomes have already shown to be incredibly resilient, you can blind their sensors and injure their outputs and they still succeed. They are incredibly compact. A whole lot of inanimate objects are going to get complete autonomy, totally offline, air gapped autonomy. They will be delivering pizzas and fighting wars. Connectomics is an opposite approach to LLMs but you can of course use LLMs to help develop connectomes. It’s amazing that you can take a biologically evolved brain, map it, produce a digital twin, and then run it at machine speed. Imagine a human brain accelerated from 100Hz neuron fires to 3,200,000,000Hz that a typical CPU runs at. That’s 30 million times faster. But would need 1-2 exabytes to map. Anyway “Zebrafish” is next.

Object Zero

640,404 просмотров • 8 дней назад

I used GPT-6 Astra to build digital flies and put millions of neurons inside them to track memecoin traders on Robinhood Chain: what they buy, where their purchases overlap, and when they start selling. Called it FLY HIGH 109+ competing strategies, 8,230+ tokens studied and 147 top wallets. Every recorded entry, exit and fly can be checked. The #1 wallet, up $10,914,922 in 30 days, was analyzed - turns out its realized PnL was -$50k. The flies let you inspect the available buys and sells behind a wallet and break down its observed behavior. Everything is free and already working: Each fly has its own job: > FOLLOW TRADER - pick a trader and see their buys and sells. Open a specific trade, check the amount, time and transaction > FOLLOW GROUP - the fly finds tokens bought by at least two tracked wallets. Open the overlap and see the participants and their buys > WATCH EXITS - the fly collects sales by tracked traders. See who is selling a token while you’re still looking into its buyers For example: open FOLLOW GROUP, pick a token, see the buyers. Go to one of them, explore their other trades and open the wallet breakdown. Now you have specific actions you can check for yourself. There's also Evolution Lab. Flies receive virtual capital and trading genes, compete in a simulation, go through selection and produce offspring. You can open the parent, inspect mutations and trace the trades. Failed strategies stay in the history too. The next step is to connect these two parts: take observed trader behavior, turn it into testable rules and see what happens to them through evolution. Pick the best strategies and share them with you. In the future, I'll also give the flies real money to execute the best profitable strategies. Enjoy and FLY HIGH, my frens!
0:40

I used GPT-6 Astra to build digital flies and put millions of neurons inside them to track memecoin traders on Robinhood Chain: what they buy, where their purchases overlap, and when they start selling. Called it FLY HIGH 109+ competing strategies, 8,230+ tokens studied and 147 top wallets. Every recorded entry, exit and fly can be checked. The #1 wallet, up $10,914,922 in 30 days, was analyzed - turns out its realized PnL was -$50k. The flies let you inspect the available buys and sells behind a wallet and break down its observed behavior. Everything is free and already working: Each fly has its own job: > FOLLOW TRADER - pick a trader and see their buys and sells. Open a specific trade, check the amount, time and transaction > FOLLOW GROUP - the fly finds tokens bought by at least two tracked wallets. Open the overlap and see the participants and their buys > WATCH EXITS - the fly collects sales by tracked traders. See who is selling a token while you’re still looking into its buyers For example: open FOLLOW GROUP, pick a token, see the buyers. Go to one of them, explore their other trades and open the wallet breakdown. Now you have specific actions you can check for yourself. There's also Evolution Lab. Flies receive virtual capital and trading genes, compete in a simulation, go through selection and produce offspring. You can open the parent, inspect mutations and trace the trades. Failed strategies stay in the history too. The next step is to connect these two parts: take observed trader behavior, turn it into testable rules and see what happens to them through evolution. Pick the best strategies and share them with you. In the future, I'll also give the flies real money to execute the best profitable strategies. Enjoy and FLY HIGH, my frens!

Logics

97,615 просмотров • 7 дней назад

ANTHROPIC LEAKED A SETUP WHERE A $1.2M A-YEAR TEAM FITS INTO ONE FILE FOR $4 A DAY you hire nobody - you write one file, and $106,500 of salaries in it turn into $4 of tokens. architect → 4 builders → tests → critic → docs → scout → chief → back into the file the architect runs twice a day and decides everything - the priciest model on the sheet is the smallest line on the bill at $1.05. four builders cost $1.20 a day - and a fifth builder is one more number in the file, not one more quarter of recruiting. the tester asks does it run, the critic asks should it exist at all - $1.22 together for two roles a solo dev never fills. nothing reaches you that hasn't been rejected at least once. the scout and the scribe cost 40 cents - the exact two roles that get cut from every real budget. nobody hires a documentation engineer, and everybody wishes they had one. the chief at 14 cents is the only one who writes back into the file - without it this is a list, with it the list edits itself. hiring the eleventh is a paragraph: no req, no interviews, no ramp - and firing is one command. save this and paste it into Claude Code - and you get 10 roles for the price of one coffee ↓
0:41

ANTHROPIC LEAKED A SETUP WHERE A $1.2M A-YEAR TEAM FITS INTO ONE FILE FOR $4 A DAY you hire nobody - you write one file, and $106,500 of salaries in it turn into $4 of tokens. architect → 4 builders → tests → critic → docs → scout → chief → back into the file the architect runs twice a day and decides everything - the priciest model on the sheet is the smallest line on the bill at $1.05. four builders cost $1.20 a day - and a fifth builder is one more number in the file, not one more quarter of recruiting. the tester asks does it run, the critic asks should it exist at all - $1.22 together for two roles a solo dev never fills. nothing reaches you that hasn't been rejected at least once. the scout and the scribe cost 40 cents - the exact two roles that get cut from every real budget. nobody hires a documentation engineer, and everybody wishes they had one. the chief at 14 cents is the only one who writes back into the file - without it this is a list, with it the list edits itself. hiring the eleventh is a paragraph: no req, no interviews, no ramp - and firing is one command. save this and paste it into Claude Code - and you get 10 roles for the price of one coffee ↓

Sprytix

47,679 просмотров • 1 месяц назад

The aircraft was not airworthy, not in the normal sense. A ferry flight is not a normal flight. The aircraft has a known defect that prevents it from carrying passengers. The defect cannot be repaired where the aircraft is, so it must be flown to a maintenance facility. It does not fly on a normal Certificate of Airworthiness. It flies under a Special Flight Permit: a one-time authorization that defines where the aircraft can fly, the crew required, and the operating limitations for that specific flight. I have been part of the process of preparing one of those permits. The defect is assessed. The risks are evaluated. The operating conditions are defined. The crew is fully briefed on the defect and its limitations. The route is planned around those limitations, and suitable alternate airports are selected. Then the aircraft departs, and you watch it leave, knowing exactly what condition it is in. That feeling stays with you. The permit exists because, in some cases, the safest option is to fly the aircraft under controlled conditions to a facility with the right people, tools, parts, and approvals, rather than attempt a repair where those resources are unavailable.
2:26

The aircraft was not airworthy, not in the normal sense. A ferry flight is not a normal flight. The aircraft has a known defect that prevents it from carrying passengers. The defect cannot be repaired where the aircraft is, so it must be flown to a maintenance facility. It does not fly on a normal Certificate of Airworthiness. It flies under a Special Flight Permit: a one-time authorization that defines where the aircraft can fly, the crew required, and the operating limitations for that specific flight. I have been part of the process of preparing one of those permits. The defect is assessed. The risks are evaluated. The operating conditions are defined. The crew is fully briefed on the defect and its limitations. The route is planned around those limitations, and suitable alternate airports are selected. Then the aircraft departs, and you watch it leave, knowing exactly what condition it is in. That feeling stays with you. The permit exists because, in some cases, the safest option is to fly the aircraft under controlled conditions to a facility with the right people, tools, parts, and approvals, rather than attempt a repair where those resources are unavailable.

OG of the Souŧh

132,070 просмотров • 1 месяц назад