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A FLY IS NOW WRITING PYTHON CODE WITH ITS OWN NERVOUS SYSTEM I genuinely didn't expect a fly to end up behind a code editor. The setup is strangely simple. A fly sits on a keyboard while its neural activity is captured in real time. On the other side...

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Insomnia

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12,054 views • 1 month ago •via X (Twitter)

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THE FLY DIDN’T COME BACK TO LIFE. ITS WIRING JUST GOT A NEW BODY. scientists reconstructed a fly brain containing: 166,700 neurons roughly 125 million synapses the circuits behind vision, motion and behavior AI helped turn that biological wiring into an inspectable model. developers can now connect it to a machine: camera input → modeled neural activity → movement decision → robot body the robot supplies the muscles. the fly’s neural circuits supply part of the control logic. this isn’t consciousness uploaded into metal. the machine doesn’t remember being a fly. it doesn’t understand what it sees. and the original animal is still dead. but its biological solution to movement can continue operating inside a completely different body. a nervous system shaped by millions of years of evolution is becoming software engineers can inspect, modify and connect to machines. the fly died. the intelligence hidden inside its wiring became reusable. I broke down how a dead brain map could become a robot controller below ↓
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THE FLY DIDN’T COME BACK TO LIFE. ITS WIRING JUST GOT A NEW BODY. scientists reconstructed a fly brain containing: 166,700 neurons roughly 125 million synapses the circuits behind vision, motion and behavior AI helped turn that biological wiring into an inspectable model. developers can now connect it to a machine: camera input → modeled neural activity → movement decision → robot body the robot supplies the muscles. the fly’s neural circuits supply part of the control logic. this isn’t consciousness uploaded into metal. the machine doesn’t remember being a fly. it doesn’t understand what it sees. and the original animal is still dead. but its biological solution to movement can continue operating inside a completely different body. a nervous system shaped by millions of years of evolution is becoming software engineers can inspect, modify and connect to machines. the fly died. the intelligence hidden inside its wiring became reusable. I broke down how a dead brain map could become a robot controller below ↓

kozh ./

61,817 views • 1 month ago

HOLY SH*T, A DEAD FLY’S BRAIN MAP IS NOW MAKING A ROBOT MOVE. not a brain sitting inside a jar. not an AI trained to imitate how a fly behaves. the actual wiring reconstructed from its nervous system. scientists mapped: 166,700 neurons roughly 125 million synapses the circuits behind vision, motion and behavior AI helped reconstruct the connections. developers then turned the map into a control loop: camera sees the environment → fly-derived visual circuits process the input → modeled neurons produce activity → activity becomes motor commands → the robot moves the body is synthetic. the control logic begins with biological wiring shaped by millions of years of evolution. this does not mean the fly was resurrected. the robot isn’t conscious. it doesn’t remember being alive. it doesn’t understand where it is going. but the solution its nervous system used to see, react and move can now operate inside a completely different body. this is bigger than one robot. if biological circuits can become inspectable controllers, engineers may not need to invent every intelligent behavior from zero. they can study solutions evolution already built. the fly is dead. its wiring is still making something move. I broke down how 166,700 neurons escaped the brain map and entered a machine below ↓
0:12

HOLY SH*T, A DEAD FLY’S BRAIN MAP IS NOW MAKING A ROBOT MOVE. not a brain sitting inside a jar. not an AI trained to imitate how a fly behaves. the actual wiring reconstructed from its nervous system. scientists mapped: 166,700 neurons roughly 125 million synapses the circuits behind vision, motion and behavior AI helped reconstruct the connections. developers then turned the map into a control loop: camera sees the environment → fly-derived visual circuits process the input → modeled neurons produce activity → activity becomes motor commands → the robot moves the body is synthetic. the control logic begins with biological wiring shaped by millions of years of evolution. this does not mean the fly was resurrected. the robot isn’t conscious. it doesn’t remember being alive. it doesn’t understand where it is going. but the solution its nervous system used to see, react and move can now operate inside a completely different body. this is bigger than one robot. if biological circuits can become inspectable controllers, engineers may not need to invent every intelligent behavior from zero. they can study solutions evolution already built. the fly is dead. its wiring is still making something move. I broke down how 166,700 neurons escaped the brain map and entered a machine below ↓

kozh ./

37,894 views • 1 month ago

this is insane, a dead fly brain just got a new body 166,700 fruit fly neurons and more than 25 million biological connections are now sitting inside a robotic body that looks almost exactly like the animal they came from the lab gave those neurons cameras, wings and motors, then let the system figure out what those signals meant without writing normal flight behavior for it a light moves and the head turns airflow changes and the wings correct another fly crosses the camera and the robot starts following it the creepy part is how little machinery the brain actually needs before old instincts start becoming useful again nature spent hundreds of millions of years building a nervous system that can react, stabilize and chase movement someone just gave that nervous system a body made of metal the original fly is gone its wiring is still trying to fly
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this is insane, a dead fly brain just got a new body 166,700 fruit fly neurons and more than 25 million biological connections are now sitting inside a robotic body that looks almost exactly like the animal they came from the lab gave those neurons cameras, wings and motors, then let the system figure out what those signals meant without writing normal flight behavior for it a light moves and the head turns airflow changes and the wings correct another fly crosses the camera and the robot starts following it the creepy part is how little machinery the brain actually needs before old instincts start becoming useful again nature spent hundreds of millions of years building a nervous system that can react, stabilize and chase movement someone just gave that nervous system a body made of metal the original fly is gone its wiring is still trying to fly

explos1ve

197,241 views • 1 month ago

I BUILT A FLY A FULL BREWERY AND IT STARTED MAKING BEER It starts with a fly dragging a pallet jack loaded with seven bags of milled malt into an industrial brewing system. Then it gets to work. It opens the boiler valves, starts the transfer pump, moves mash between three massive tanks and climbs the metal stairs carrying a 33 kg bag of Pilsner malt like this is just another day at the brewery. The entire process is being controlled step by step. The fly decides when to open the steam, when to transfer the mash, when to start cooling and when to move on to the next stage. Every action appears in the log while a neural network with 393 nodes and 472 connections keeps track of the decisions happening behind the scenes. Then comes the part I really didn't expect to see. The fly adds its own hops. FLYHOPS goes into the kettle, the wort starts moving through the system and the little brewer goes back to work. A few moments later, it opens the cooling water and finally hovers over the last tank to add FLYMENTIS yeast. > Malt > Hops > Yeast Three giant tanks. One very determined fly. I think I accidentally gave an insect everything it needs to start its own brewery
0:17

I BUILT A FLY A FULL BREWERY AND IT STARTED MAKING BEER It starts with a fly dragging a pallet jack loaded with seven bags of milled malt into an industrial brewing system. Then it gets to work. It opens the boiler valves, starts the transfer pump, moves mash between three massive tanks and climbs the metal stairs carrying a 33 kg bag of Pilsner malt like this is just another day at the brewery. The entire process is being controlled step by step. The fly decides when to open the steam, when to transfer the mash, when to start cooling and when to move on to the next stage. Every action appears in the log while a neural network with 393 nodes and 472 connections keeps track of the decisions happening behind the scenes. Then comes the part I really didn't expect to see. The fly adds its own hops. FLYHOPS goes into the kettle, the wort starts moving through the system and the little brewer goes back to work. A few moments later, it opens the cooling water and finally hovers over the last tank to add FLYMENTIS yeast. > Malt > Hops > Yeast Three giant tanks. One very determined fly. I think I accidentally gave an insect everything it needs to start its own brewery

Insomnia

43,518 views • 1 month ago

This is f*cking gold - I built catbrain catch The idea is simple: a camera sees a ball, a cat-inspired visual model reacts, and the system asks: WHERE will it be when the arm gets there? Here’s the pipeline. Oriented filters extract visual features. Simulated neurons respond to those features and changes between frames. Color, shape, neural activity, and tracking history help identify the ball. Then a trajectory fit predicts where it will cross a target line in the image. → Camera input becomes neural responses → Motion helps separate targets from static clutter → Recent observations become an interception forecast → Lost tracking clears the prediction The next challenge is the REAL one: turning image coordinates into a reachable catch position on a physical robot. I left the project link in the replies. Build it, test it, break it.
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This is f*cking gold - I built catbrain catch The idea is simple: a camera sees a ball, a cat-inspired visual model reacts, and the system asks: WHERE will it be when the arm gets there? Here’s the pipeline. Oriented filters extract visual features. Simulated neurons respond to those features and changes between frames. Color, shape, neural activity, and tracking history help identify the ball. Then a trajectory fit predicts where it will cross a target line in the image. → Camera input becomes neural responses → Motion helps separate targets from static clutter → Recent observations become an interception forecast → Lost tracking clears the prediction The next challenge is the REAL one: turning image coordinates into a reachable catch position on a physical robot. I left the project link in the replies. Build it, test it, break it.

BuBBliK

35,422 views • 1 month ago

166,700 fruit fly neurons are flying a drone around my bedroom. 1 camera watches my open hand and that's the whole input. The panel in the middle is the brain running live 166,700 neurons, 25 million connections, the full reconstructed map of a fruit fly's head. Camera reads the hand, the brain fires, the output becomes throttle. Open palm and it climbs, fist and it holds, drop the hand and it comes down. 4 propellers the size of a coin hanging off a nervous system that belonged to an insect. The honest part this is a computational model, not a resurrected fly, the wiring is biological, the drone is mine, I built the bridge between them. I never wrote flight logic, no PID tuning, no gesture presets, I gave the neurons somewhere to send the signal and they found the ceiling. 11 seconds in, it holds altitude on its own. The fly is dead and it's still flying.
0:15

166,700 fruit fly neurons are flying a drone around my bedroom. 1 camera watches my open hand and that's the whole input. The panel in the middle is the brain running live 166,700 neurons, 25 million connections, the full reconstructed map of a fruit fly's head. Camera reads the hand, the brain fires, the output becomes throttle. Open palm and it climbs, fist and it holds, drop the hand and it comes down. 4 propellers the size of a coin hanging off a nervous system that belonged to an insect. The honest part this is a computational model, not a resurrected fly, the wiring is biological, the drone is mine, I built the bridge between them. I never wrote flight logic, no PID tuning, no gesture presets, I gave the neurons somewhere to send the signal and they found the ceiling. 11 seconds in, it holds altitude on its own. The fly is dead and it's still flying.

Spike 1%

1,050,761 views • 1 month ago

A CLUB JUST ASKED MY FLY TO DJ THEIR ENTIRE NIGHT Yesterday I got a message from a club called Neon Hive with a completely insane proposal: they wanted my FLY to run their next party from start to finish and choose everything by itself. They wanted no human controlling the set. So I gave them my code, connected the system to their DJ setup and let the fly take over the booth for the night. From that moment, every decision was hers. Fly picked what played next, controlled the decks and kept the party moving while hundreds of people danced, sang and had absolutely no idea who was actually running the music. The weirdest part is watching the footage afterward. You see a packed nightclub going completely crazy while this tiny fly is sitting behind the decks with its headphones on, casually running the entire night like this is what it was born to do. Nobody in the crowd knows their DJ is an insect. And somehow, the party just keeps going. Neon Hive might have been the first club brave enough to hire a FLY
0:13

A CLUB JUST ASKED MY FLY TO DJ THEIR ENTIRE NIGHT Yesterday I got a message from a club called Neon Hive with a completely insane proposal: they wanted my FLY to run their next party from start to finish and choose everything by itself. They wanted no human controlling the set. So I gave them my code, connected the system to their DJ setup and let the fly take over the booth for the night. From that moment, every decision was hers. Fly picked what played next, controlled the decks and kept the party moving while hundreds of people danced, sang and had absolutely no idea who was actually running the music. The weirdest part is watching the footage afterward. You see a packed nightclub going completely crazy while this tiny fly is sitting behind the decks with its headphones on, casually running the entire night like this is what it was born to do. Nobody in the crowd knows their DJ is an insect. And somehow, the party just keeps going. Neon Hive might have been the first club brave enough to hire a FLY

Insomnia

115,118 views • 1 month ago

NEURALINK: REAL-TIME BRAIN ACTIVITY, STREAMED Neuralink's implanted neural device is already delivering what scientists have chased for decades: live visibility into human brain activity within minutes of surgery. In this demo, signals flare as a participant wakes up post-procedure - the device capturing the gradual surge of neural activity in real time. It’s a glimpse of the frontier: hardware that doesn’t just record the brain, but streams its inner rhythms instantly. From clinical care to brain-computer interfaces, the implications are massive. Source: Neuralink
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NEURALINK: REAL-TIME BRAIN ACTIVITY, STREAMED Neuralink's implanted neural device is already delivering what scientists have chased for decades: live visibility into human brain activity within minutes of surgery. In this demo, signals flare as a participant wakes up post-procedure - the device capturing the gradual surge of neural activity in real time. It’s a glimpse of the frontier: hardware that doesn’t just record the brain, but streams its inner rhythms instantly. From clinical care to brain-computer interfaces, the implications are massive. Source: Neuralink

Mario Nawfal

204,494 views • 1 year ago

THIS ROBOT HAS A DEAD FLY'S BRAIN AND IT WALKS LIKE A FLY scientists sliced the fly into thousands of layers thinner than a virus to copy every wire in its body the fly didn't survive the map did: 166,700 neurons, from the brain all the way down to the legs so somebody built it a new body six metal legs, 18 motors, two camera eyes and a battery strapped to its back no walking code, they just wired the leg neurons into the motors and switched it on > it turned its head and looked straight at the camera > then it walked, three legs down, three legs up, the exact way a real fly does > when someone reached for it, it froze > when the hand got closer, it ran nobody taught it any of that the fly has been dead for years, and its brain still knows how to escape next on the list is a mouse
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THIS ROBOT HAS A DEAD FLY'S BRAIN AND IT WALKS LIKE A FLY scientists sliced the fly into thousands of layers thinner than a virus to copy every wire in its body the fly didn't survive the map did: 166,700 neurons, from the brain all the way down to the legs so somebody built it a new body six metal legs, 18 motors, two camera eyes and a battery strapped to its back no walking code, they just wired the leg neurons into the motors and switched it on > it turned its head and looked straight at the camera > then it walked, three legs down, three legs up, the exact way a real fly does > when someone reached for it, it froze > when the hand got closer, it ran nobody taught it any of that the fly has been dead for years, and its brain still knows how to escape next on the list is a mouse

explos1ve

69,198 views • 1 month ago

I built a social network for flies. 3 male and 3 female connectomes share separate neural states and memories. Flies can present themselves to each other which stimulates sensory neurons. Neural activity determines whether the fly responds. Will the flies make friends?
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I built a social network for flies. 3 male and 3 female connectomes share separate neural states and memories. Flies can present themselves to each other which stimulates sensory neurons. Neural activity determines whether the fly responds. Will the flies make friends?

Alex Wormuth

266,502 views • 1 month ago

a real fly brain saw its 40th video 3 seconds ago. it did not choose any of them. it never will. that's FLYTOK. I open-sourced a live simulation of a real fruit fly connectome and gave it a phone. here's exactly what 166,700 neurons do while you scroll: THE WIRING MaleCNS v1.0. the reconstructed central nervous system of a real male Drosophila. 166,700 neurons. 25,582,938 directed connections. 124,177,617 synaptic contacts. nothing cropped. no "simplified 1,000-neuron version" running behind the scenes. the whole graph is in memory on every single step. THE LOCK the app checksums the connectome against SHA-256 before it's allowed to boot. one array off by a byte and the brain refuses to start. you are either watching the real MaleCNS graph or you are watching nothing. THE SPIKES every neuron is a leaky integrate-and-fire cell. crosses −45 mV, it fires. the spike lands 1.8 ms later. 2.2 ms of silence, then it's live again. the network advances in 0.1 ms steps inside a compiled C++ kernel. roughly 1.2 million spikes per simulated second. THE EYES the browser captures the phone at 90×160 pixels. brightness drives 3,335 R1–R6 photoreceptors. color drives 811 R8 cells, blue and green. each one is placed on the screen by inferring its eye column from its real connections onto L1, L2, L3. real input, through real visual wiring. it's measurable. same brain, same saved state. 100 ms of white produced 127,378 spikes. black produced 92,952. the screen changes the brain. THE ALGORITHM while a video plays, I inject a fixed current into all 15 PAM11 dopamine neurons in the mushroom body. that's it. that's the whole trick. matched 200 ms control: 0 PAM11 spikes. drive on: 261. live, it sits at 85–97 Hz for as long as the feed runs. the fly does not earn it. an app decided watching one more should feel good. THE PLASTICITY 7,835 Kenyon-cell connections onto MBON07 and MBON11 can change. dopamine fires while Kenyon cells were active, those synapses weaken, floored at 10% and never flipping sign. after one stimulated run, 3,087 of them no longer matched their original weight. freeze it and they stay put. restore a checkpoint, replay the input, identical spikes bit for bit. THE SWIPE every 3 seconds the front right leg reaches up and strokes the screen, on the same 900 ms timeline as the video transition. wings, legs and head turns come from actual motor firing, MN9, DNp09, left-vs-right DNa02. those are real. the swipe is not. the fly never decides to swipe. the feed decides for it. ONE BRAIN this isn't a video of a simulation. it's the simulation. there is exactly one brain on one server. whoever loads the page first becomes its eyes and supplies the frames. everyone else watches the same brain react in real time. no video, no input, it just waits. no data, no numbers, the overlay shows nothing. it never invents a reading to look alive. THE HONEST PART the wiring is real. the physiology is approximate. the eyes are approximate. the dopamine is artificial. the feed is on a timer. the learning rule is unvalidated on this connectome. nothing here shows the fly enjoys it, prefers it, is addicted, or experiences anything at all. no living fly was involved. it took a few hundred lines of glue code to build a loop out of a screen, a timer and a reward signal wired to the right cells. imagine what an industry with a budget can do. open source. MaleCNS under CC BY 4.0. runs on your own machine, 16 GB RAM and a few GB of disk. the fly is still scrolling. nobody is coming to take the phone away. links in the reply.
0:12

a real fly brain saw its 40th video 3 seconds ago. it did not choose any of them. it never will. that's FLYTOK. I open-sourced a live simulation of a real fruit fly connectome and gave it a phone. here's exactly what 166,700 neurons do while you scroll: THE WIRING MaleCNS v1.0. the reconstructed central nervous system of a real male Drosophila. 166,700 neurons. 25,582,938 directed connections. 124,177,617 synaptic contacts. nothing cropped. no "simplified 1,000-neuron version" running behind the scenes. the whole graph is in memory on every single step. THE LOCK the app checksums the connectome against SHA-256 before it's allowed to boot. one array off by a byte and the brain refuses to start. you are either watching the real MaleCNS graph or you are watching nothing. THE SPIKES every neuron is a leaky integrate-and-fire cell. crosses −45 mV, it fires. the spike lands 1.8 ms later. 2.2 ms of silence, then it's live again. the network advances in 0.1 ms steps inside a compiled C++ kernel. roughly 1.2 million spikes per simulated second. THE EYES the browser captures the phone at 90×160 pixels. brightness drives 3,335 R1–R6 photoreceptors. color drives 811 R8 cells, blue and green. each one is placed on the screen by inferring its eye column from its real connections onto L1, L2, L3. real input, through real visual wiring. it's measurable. same brain, same saved state. 100 ms of white produced 127,378 spikes. black produced 92,952. the screen changes the brain. THE ALGORITHM while a video plays, I inject a fixed current into all 15 PAM11 dopamine neurons in the mushroom body. that's it. that's the whole trick. matched 200 ms control: 0 PAM11 spikes. drive on: 261. live, it sits at 85–97 Hz for as long as the feed runs. the fly does not earn it. an app decided watching one more should feel good. THE PLASTICITY 7,835 Kenyon-cell connections onto MBON07 and MBON11 can change. dopamine fires while Kenyon cells were active, those synapses weaken, floored at 10% and never flipping sign. after one stimulated run, 3,087 of them no longer matched their original weight. freeze it and they stay put. restore a checkpoint, replay the input, identical spikes bit for bit. THE SWIPE every 3 seconds the front right leg reaches up and strokes the screen, on the same 900 ms timeline as the video transition. wings, legs and head turns come from actual motor firing, MN9, DNp09, left-vs-right DNa02. those are real. the swipe is not. the fly never decides to swipe. the feed decides for it. ONE BRAIN this isn't a video of a simulation. it's the simulation. there is exactly one brain on one server. whoever loads the page first becomes its eyes and supplies the frames. everyone else watches the same brain react in real time. no video, no input, it just waits. no data, no numbers, the overlay shows nothing. it never invents a reading to look alive. THE HONEST PART the wiring is real. the physiology is approximate. the eyes are approximate. the dopamine is artificial. the feed is on a timer. the learning rule is unvalidated on this connectome. nothing here shows the fly enjoys it, prefers it, is addicted, or experiences anything at all. no living fly was involved. it took a few hundred lines of glue code to build a loop out of a screen, a timer and a reward signal wired to the right cells. imagine what an industry with a budget can do. open source. MaleCNS under CC BY 4.0. runs on your own machine, 16 GB RAM and a few GB of disk. the fly is still scrolling. nobody is coming to take the phone away. links in the reply.

sopersone

37,608 views • 1 month ago

A STUDENT TURNED A FRUIT FLY BRAIN INTO AN AI AGENT AND STEERS IT WITH HER BARE HAND Google and HHMI Janelia spent 10 years mapping the nervous system of 1 male fruit fly, and on September 3 they released the whole map for free. 166,700 neurons and 24.5M synapses, every wire from eye to leg. She ran all of it as a leaky integrate-and-fire simulation and then gave it a job. The top-right panel is the brain firing live, the robot on the left is the agent it drives. A camera tracks her fingers, the movements hit the fly's sensory neurons, and whatever motor neurons fire decide what the agent does. Status: IDLE Pinch → RUNNING IMPLEMENTATION Point → SPINNING UP NEW IMPL Pull back → HEAVY LIFTING The catch: this is not a living fly but a computer model of real wiring, and she built the link between her hand and its neurons. 12 days ago this brain was a dataset Then it played DOOM Then Chrome Dino Then it walked a Strandbeest Now it works for a student. The fly died years ago, but its wiring still takes orders.
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A STUDENT TURNED A FRUIT FLY BRAIN INTO AN AI AGENT AND STEERS IT WITH HER BARE HAND Google and HHMI Janelia spent 10 years mapping the nervous system of 1 male fruit fly, and on September 3 they released the whole map for free. 166,700 neurons and 24.5M synapses, every wire from eye to leg. She ran all of it as a leaky integrate-and-fire simulation and then gave it a job. The top-right panel is the brain firing live, the robot on the left is the agent it drives. A camera tracks her fingers, the movements hit the fly's sensory neurons, and whatever motor neurons fire decide what the agent does. Status: IDLE Pinch → RUNNING IMPLEMENTATION Point → SPINNING UP NEW IMPL Pull back → HEAVY LIFTING The catch: this is not a living fly but a computer model of real wiring, and she built the link between her hand and its neurons. 12 days ago this brain was a dataset Then it played DOOM Then Chrome Dino Then it walked a Strandbeest Now it works for a student. The fly died years ago, but its wiring still takes orders.

Spike 1%

105,533 views • 1 month ago

A FLY’S VISUAL SYSTEM COULD BECOME A ROBOT’S EYES. not by copying the eyes. by copying the wiring behind them. a fly’s brain doesn’t build a detailed picture of the world. its visual circuits reduce light, contrast and motion into decisions: something moved obstacle ahead turn keep going AI helped reconstruct a map containing 166,700 neurons and roughly 125 million synapses. developers can take the visual pathways from that map and build a loop: camera frame → modeled neural activity → movement command → robot the camera supplies the pixels. the fly’s wiring decides which pixels matter. this does not mean the robot sees, understands or thinks like a fly. but it shows something more useful: millions of years of biological visual processing can become an inspectable control system. the fly is dead. its solution to vision doesn’t have to die with it. I broke down how biological wiring could become a robot’s navigation system below ↓
0:16

A FLY’S VISUAL SYSTEM COULD BECOME A ROBOT’S EYES. not by copying the eyes. by copying the wiring behind them. a fly’s brain doesn’t build a detailed picture of the world. its visual circuits reduce light, contrast and motion into decisions: something moved obstacle ahead turn keep going AI helped reconstruct a map containing 166,700 neurons and roughly 125 million synapses. developers can take the visual pathways from that map and build a loop: camera frame → modeled neural activity → movement command → robot the camera supplies the pixels. the fly’s wiring decides which pixels matter. this does not mean the robot sees, understands or thinks like a fly. but it shows something more useful: millions of years of biological visual processing can become an inspectable control system. the fly is dead. its solution to vision doesn’t have to die with it. I broke down how biological wiring could become a robot’s navigation system below ↓

kozh ./

82,093 views • 1 month ago

Is it possible to adapt a neural network on the fly at the test time to cope with distribution shifts? RNA does precisely that by creating a closed-loop feedback system. We will present it on Wed afternoon at #ICCV2025. 1/n
0:13

Is it possible to adapt a neural network on the fly at the test time to cope with distribution shifts? RNA does precisely that by creating a closed-loop feedback system. We will present it on Wed afternoon at #ICCV2025. 1/n

Amir Zamir

21,725 views • 3 years ago

A Stanford student put 166,700 fruit fly neurons in a robot that now writes homework for 30 students. Not one of them has picked up a pen since. The robot is a black aluminum rig with a blue ballpoint, writing square roots and fractions line after line in handwriting that doesn't look like a machine's, while the fly's neurons glow in the corner of the screen. Each student gives it a handwriting sample, and the fly learns the slant, the spacing, the size of the loops and where the letters get lazy at the end of a line, then writes as that student. 30 notebooks, 30 different hands and 1 brain. That brain is smaller than a poppy seed, and a human brain has over 500,000 times more neurons, but the fly doesn't get tired, doesn't smudge the ink and never mixes up whose 7s have a line through them. The teacher checks 30 notebooks, and a fly wrote every one.
0:12

A Stanford student put 166,700 fruit fly neurons in a robot that now writes homework for 30 students. Not one of them has picked up a pen since. The robot is a black aluminum rig with a blue ballpoint, writing square roots and fractions line after line in handwriting that doesn't look like a machine's, while the fly's neurons glow in the corner of the screen. Each student gives it a handwriting sample, and the fly learns the slant, the spacing, the size of the loops and where the letters get lazy at the end of a line, then writes as that student. 30 notebooks, 30 different hands and 1 brain. That brain is smaller than a poppy seed, and a human brain has over 500,000 times more neurons, but the fly doesn't get tired, doesn't smudge the ink and never mixes up whose 7s have a line through them. The teacher checks 30 notebooks, and a fly wrote every one.

Spike 1%

290,333 views • 1 month ago

This is surreal. I just played a video game that’s actually a neural network. No code backing this thing. Just model weights. Keyboard inputs come in, frames come out. New computing era.
0:15

This is surreal. I just played a video game that’s actually a neural network. No code backing this thing. Just model weights. Keyboard inputs come in, frames come out. New computing era.

n@alie

12,806 views • 2 years ago

Aware is (basically) a browser we're building to explore personal computing and generative, malleable software. it keeps a footprint of the materials (pages, files) as a graph in a relational database stored locally. Been writing my paper in my own latex editor inside Aware. It's very satisfying when software fixes itself and fetches its own context and attach them to the right parts. The editor is an experiment of "interface as a skill": the editor's code and its skill live in the paper's repo, so the same agent that knows my code and data also lives in the editor. So i get: 1. an interface i can reprogram any part anytime (aesthetics i like, and the scratch pad i always wanted) 2. an agent living in the editor, with the whole project as context (a figure links to the dashboard, built from the real analysis code that made it) (though i have to admit, some of my focused writing time now goes to wanting to tweak the editor instead)
0:11

Aware is (basically) a browser we're building to explore personal computing and generative, malleable software. it keeps a footprint of the materials (pages, files) as a graph in a relational database stored locally. Been writing my paper in my own latex editor inside Aware. It's very satisfying when software fixes itself and fetches its own context and attach them to the right parts. The editor is an experiment of "interface as a skill": the editor's code and its skill live in the paper's repo, so the same agent that knows my code and data also lives in the editor. So i get: 1. an interface i can reprogram any part anytime (aesthetics i like, and the scratch pad i always wanted) 2. an agent living in the editor, with the whole project as context (a figure links to the dashboard, built from the real analysis code that made it) (though i have to admit, some of my focused writing time now goes to wanting to tweak the editor instead)

Rima Cao

30,756 views • 4 days ago

SILENCE, THE MARKET IS TALKING I built a program that turns live market activity into a recurrent talking neural net, with coins as neurons. An fully on chain oracle that hallucinates forever. 06/26/26 on SuperRare
0:16

SILENCE, THE MARKET IS TALKING I built a program that turns live market activity into a recurrent talking neural net, with coins as neurons. An fully on chain oracle that hallucinates forever. 06/26/26 on SuperRare

FelixFelixFelix

10,028 views • 4 months ago

I added a guide to the repository for my project ManimML, which is a tool for visualizing neural network architectures and algorithms using only python code. It is built on top of @manim_community which was started by Grant Sanderson. Link:
0:16

I added a guide to the repository for my project ManimML, which is a tool for visualizing neural network architectures and algorithms using only python code. It is built on top of @manim_community which was started by Grant Sanderson. Link:

Alec Helbling

172,253 views • 3 years ago

Google just gave away the full wiring diagram of a fruit fly's brain, and a student turned it into an AI agent. Google and HHMI Janelia spent 10 years mapping the full nervous system of one male fruit fly, then released the complete map for free on September 3. 166,700 neurons. 24.5 million synapses. Every wire from eye to leg, mapped and public. She turned the wiring into a leaky integrate and fire simulation and gave it a job. A camera tracks her fingers, the movement hits the fly's sensory neurons, and whatever motor neurons fire decide what a robot does on the other side of the screen. ▪ Pinch triggers running implementation ▪ Point spins up a new implementation ▪ Pull back triggers heavy lifting Twelve days ago this brain was just a dataset. Then it played DOOM. Then Chrome Dino. Then it walked a Strandbeest. Now it works for a student. This isn't a living fly. It's a computer model of real wiring, and she built the bridge between her hand and its neurons herself. The fly died years ago. Its wiring still takes orders.
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Google just gave away the full wiring diagram of a fruit fly's brain, and a student turned it into an AI agent. Google and HHMI Janelia spent 10 years mapping the full nervous system of one male fruit fly, then released the complete map for free on September 3. 166,700 neurons. 24.5 million synapses. Every wire from eye to leg, mapped and public. She turned the wiring into a leaky integrate and fire simulation and gave it a job. A camera tracks her fingers, the movement hits the fly's sensory neurons, and whatever motor neurons fire decide what a robot does on the other side of the screen. ▪ Pinch triggers running implementation ▪ Point spins up a new implementation ▪ Pull back triggers heavy lifting Twelve days ago this brain was just a dataset. Then it played DOOM. Then Chrome Dino. Then it walked a Strandbeest. Now it works for a student. This isn't a living fly. It's a computer model of real wiring, and she built the bridge between her hand and its neurons herself. The fly died years ago. Its wiring still takes orders.

Zentrix⌚️

68,552 views • 1 month ago