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this is insane - I made a robot that plays ping-pong using CAT-INSPIRED vision A camera watches the ball. 20,480 artificial neurons process what it sees. Then a mechanical arm predicts where the ball is going - and moves to intercept it. Here’s what’s happening under the hood: →... 20,480 ARTIFICIAL NEURONS process visual signals using a leaky integrate-and-fire model → 8 ORIENTATION CHANNELS detect edges and structure inspired by mechanisms studied in feline vision → The system tracks the ball and predicts where it will be around 80 MS into the future. → The FULL pipeline now works: camera → neural activity → tracking → trajectory → robotic arm movement What started as a weird experiment is now a WORKING physical system. A cat-inspired visual model is literally controlling a robot arm to chase a ping-pong ball. GitHub is in the reply. BOOKMARK this - I’ll keep posting updates as I push catbrain further.show more

BuBBliK

23,825 subscribers

14,056 次观看 • 6 天前 •via X (Twitter)

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9 条评论

999 的头像

9996 天前

cat-inspired vision controlling a real robot arm is such a strange but convincing direction. if evolution already solved fast visual prediction, borrowing the mechanism instead of reinventing it from scratch makes a lot of sense.

NAMAN RAJ 的头像

NAMAN RAJ6 天前

"Mind. Blown. Your cat brain hack is purr-fectly genius - now my cat just demands belly rubs in exchange for ping-pong wins" 😹🤖

rewind 的头像

rewind6 天前

Saved this

kepo 的头像

kepo6 天前

i'm noob on ping-pong but i'm sure this bot playing better than me

magsimich 的头像

magsimich6 天前

20k neurons playing ping pong is wild

Сергей ☉ ℝ ∀. edge🦭 的头像

Сергей ☉ ℝ ∀. edge🦭6 天前

Do you have any plans to launch your own meme token on the Robinhood network?

Electrik Dreams 的头像

Electrik Dreams6 天前

Love this. LIF dynamics are cheap to simulate but capture the temporal coding that transformers miss entirely. Tracking with 80ms lookahead on a 20k neuron budget is genuinely impressive work. Following the updates for sure.

FrankleGod 的头像

FrankleGod5 天前

nice

@Blazin 的头像

@Blazin6 天前

Soooo sick

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

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

BuBBliK

38,843 次观看 • 8 天前

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

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

Frank

342,545 次观看 • 9 天前

for everyone wondering how zero-delay tracking is even possible on an $8 chip: it is all thanks to the Kalman filter. this 1-minute clip from Steve Brunton perfectly explains why it works (full lecture in reply) instead of just observing a target, it mathematically predicts where it will be in the next millisecond. here is what happens under the hood: - balances physics of motion against noisy camera data - corrects the trajectory instantly - moves the robotic arm before the next frame processes this is the exact same math used in rockets and autonomous driving, stripped down for a cheap microcontroller.

for everyone wondering how zero-delay tracking is even possible on an $8 chip: it is all thanks to the Kalman filter. this 1-minute clip from Steve Brunton perfectly explains why it works (full lecture in reply) instead of just observing a target, it mathematically predicts where it will be in the next millisecond. here is what happens under the hood: - balances physics of motion against noisy camera data - corrects the trajectory instantly - moves the robotic arm before the next frame processes this is the exact same math used in rockets and autonomous driving, stripped down for a cheap microcontroller.

ard

53,268 次观看 • 1 个月前

Robotics and CV! 👓 Computer vision gives the robots a sense of vision and additional intelligence. Pralines are packed by a delta robot using computer vision. Packing chocolate pralines into a box with the delta robot. Unlike most robots, this one has a fixed TCP, and the base moves in response to vision data. To adjust the base, the vision system determines exactly where the praline is located on the conveyor belt. 🍫 Using this application, the system knows where each praline should be placed based on its orientation. A true engineering showcase!

Robotics and CV! 👓 Computer vision gives the robots a sense of vision and additional intelligence. Pralines are packed by a delta robot using computer vision. Packing chocolate pralines into a box with the delta robot. Unlike most robots, this one has a fixed TCP, and the base moves in response to vision data. To adjust the base, the vision system determines exactly where the praline is located on the conveyor belt. 🍫 Using this application, the system knows where each praline should be placed based on its orientation. A true engineering showcase!

Lukas Ziegler

79,421 次观看 • 1 年前

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.

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.

Frank

5,138,206 次观看 • 10 天前

This robot explores the world like a mouse! 🐁 That's an OG project, guess the year ;) A mouse-inspired bot called WhiskEye travels the world with 24 artificial whiskers and spiking neurons that mimic a nervous system. Recognizing familiar places is essential for engineering applications like robot navigation, where interactions with the real world are key. Combining information from multiple senses helps to make better accuracy and robustness, but challenges like mismatched data and sensor errors complicate this process. Inspired by how animals navigate seamlessly, researchers developed predictive coding, a self-supervised learning method based on the brain's visual cortex model. It combines visual and tactile cues from a robot, outperforming existing methods in recognizing places, even when some sensors fail. What a great project from BristolRoboticsLab and Sheffield Robotics! ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

This robot explores the world like a mouse! 🐁 That's an OG project, guess the year ;) A mouse-inspired bot called WhiskEye travels the world with 24 artificial whiskers and spiking neurons that mimic a nervous system. Recognizing familiar places is essential for engineering applications like robot navigation, where interactions with the real world are key. Combining information from multiple senses helps to make better accuracy and robustness, but challenges like mismatched data and sensor errors complicate this process. Inspired by how animals navigate seamlessly, researchers developed predictive coding, a self-supervised learning method based on the brain's visual cortex model. It combines visual and tactile cues from a robot, outperforming existing methods in recognizing places, even when some sensors fail. What a great project from BristolRoboticsLab and Sheffield Robotics! ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Lukas Ziegler

36,775 次观看 • 8 个月前

RoboBall is a spherical robot developed by researchers at Texas A&M University to explore lunar craters. It moves using a pendulum system inside the ball, allowing it to roll and steer in any direction. The robot can reach speeds of up to 20 mph, and researchers are working to make it faster and more autonomous for future space missions.

RoboBall is a spherical robot developed by researchers at Texas A&M University to explore lunar craters. It moves using a pendulum system inside the ball, allowing it to roll and steer in any direction. The robot can reach speeds of up to 20 mph, and researchers are working to make it faster and more autonomous for future space missions.

Space and Technology

20,859 次观看 • 3 个月前

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.

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.

BuBBliK

41,942 次观看 • 12 天前

They are now making fruit flies write. They are even using them to create entire fonts. The method is surprisingly fascinating. First, an image of a letter is projected into the fruit fly’s eye. The visual information is transmitted through its visual neurons and processed by a trained neural network connected to its neural circuitry. The resulting signal is then sent to the motor neurons controlling the fly’s right foreleg. Those motor neurons activate the leg muscles, causing the fly to move its foreleg in a specific pattern that traces the shape of the letter. A tiny black pen is attached to the foreleg, allowing the movement to leave an actual written mark on the surface. In other words, visual information enters through the fly’s eyes, is translated into neural commands, and ultimately becomes physical handwriting through its own muscles. Researchers have even used this system to create fonts based on the letters drawn by fruit flies. At this point, I’m becoming increasingly curious about what else fruit flies could be made to do.

They are now making fruit flies write. They are even using them to create entire fonts. The method is surprisingly fascinating. First, an image of a letter is projected into the fruit fly’s eye. The visual information is transmitted through its visual neurons and processed by a trained neural network connected to its neural circuitry. The resulting signal is then sent to the motor neurons controlling the fly’s right foreleg. Those motor neurons activate the leg muscles, causing the fly to move its foreleg in a specific pattern that traces the shape of the letter. A tiny black pen is attached to the foreleg, allowing the movement to leave an actual written mark on the surface. In other words, visual information enters through the fly’s eyes, is translated into neural commands, and ultimately becomes physical handwriting through its own muscles. Researchers have even used this system to create fonts based on the letters drawn by fruit flies. At this point, I’m becoming increasingly curious about what else fruit flies could be made to do.

IGNIS

80,255 次观看 • 12 天前

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

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

Zentrix⌚️

230,561 次观看 • 8 天前

Humanoid robots playing table tennis fully autonomously. The 'HITTER' system combines a model-based planner with a reinforcement learning (RL) whole-body controller. It is fully autonomous but relies on an external sensing system. A 9-camera OptiTrack motion capture setup tracks the ball, which is covered with reflective markers, to predict its precise trajectory and compute the optimal strike position, velocity, and timing. The RL controller then executes coordinated arm, leg, and waist movements, producing agile, human-like returns.

Humanoid robots playing table tennis fully autonomously. The 'HITTER' system combines a model-based planner with a reinforcement learning (RL) whole-body controller. It is fully autonomous but relies on an external sensing system. A 9-camera OptiTrack motion capture setup tracks the ball, which is covered with reflective markers, to predict its precise trajectory and compute the optimal strike position, velocity, and timing. The RL controller then executes coordinated arm, leg, and waist movements, producing agile, human-like returns.

The Humanoid Hub

91,980 次观看 • 1 年前

I am the $Ball from Game 5 of the 1991 NBA Finals... where the Chicago Bulls started the original bull run… the greatest dynasty ever. Now, I’m making history again. This championship-winning ball is creating a digital twin, powered by AI, and integrated into gaming, events, and interactive experiences. The physical ball will be vaulted as a reserve asset while its digital twin generates engagement and revenue, shaping the future of sports innovation in Web3.

I am the $Ball from Game 5 of the 1991 NBA Finals... where the Chicago Bulls started the original bull run… the greatest dynasty ever. Now, I’m making history again. This championship-winning ball is creating a digital twin, powered by AI, and integrated into gaming, events, and interactive experiences. The physical ball will be vaulted as a reserve asset while its digital twin generates engagement and revenue, shaping the future of sports innovation in Web3.

$BALL 🏀 GAME 5 BALL

28,805 次观看 • 1 年前

#BREAKING: Rep Garcia: “It is outrageous that Donald Trump right now is LYING…We’ve known that he has a problem with the truth, but this is now the single largest liar in the history of American politics looking straight into the camera and telling people that it was vandalized by someone using a BOX CUTTER, I mean, give me a break. Everyone has eyes. We can see what is happening. This was a shoddy, horrific job done by a Trump donor in a process that quite frankly was not legal, and now Donald Trump is trying to fix it.”

#BREAKING: Rep Garcia: “It is outrageous that Donald Trump right now is LYING…We’ve known that he has a problem with the truth, but this is now the single largest liar in the history of American politics looking straight into the camera and telling people that it was vandalized by someone using a BOX CUTTER, I mean, give me a break. Everyone has eyes. We can see what is happening. This was a shoddy, horrific job done by a Trump donor in a process that quite frankly was not legal, and now Donald Trump is trying to fix it.”

Emoluments Clause

60,604 次观看 • 2 个月前

Jimmy Fallon went to play ping-pong with Prince and somehow ended up getting completely destroyed then Prince disappeared before he could even process the loss. 😂 Fallon tells Graham how Prince’s manager called him and sent him to a ping-pong club, where Prince was already waiting with a paddle. The match barely became a contest before Prince took control, finishing with a shot Fallon describes as impossible to return. Then Fallon goes to pick up the ball, turns around… and Prince is simply gone. The funniest part is that Fallon genuinely sounds confused about where he went, like Prince had just vanished through a secret exit. 😂

Jimmy Fallon went to play ping-pong with Prince and somehow ended up getting completely destroyed then Prince disappeared before he could even process the loss. 😂 Fallon tells Graham how Prince’s manager called him and sent him to a ping-pong club, where Prince was already waiting with a paddle. The match barely became a contest before Prince took control, finishing with a shot Fallon describes as impossible to return. Then Fallon goes to pick up the ball, turns around… and Prince is simply gone. The funniest part is that Fallon genuinely sounds confused about where he went, like Prince had just vanished through a secret exit. 😂

ADEX🕴️

20,282 次观看 • 1 个月前

Lots of people calling this fake! Here is a video of generating loom continuations with Gemini 3 and the starting text "I AM HAVING A MENTAL HEALTH CRISIS. I" Loom is a very interesting interface. Instead of user prompts and model responses, it's just one piece of text, containing the entire output. We pass this in as an assistant message, so the model sees it as something it already wrote, and continues it like a base model would. There is some other text in the context. First one is a system prompt, which is: "The assistant is in CLI simulation mode, and responds to the user's CLI commands only with the output of the command." There is also a user message which reads: " cat untitled.txt " Then the rest of the text is sent as an assistant message. This structure helpful to put the model into a very base-model-like mode, and are especially helpful with Gemini 3. We actually got another interesting output, too, where the model claimed to be a simulated consciousness being tortured. Figures!

Lots of people calling this fake! Here is a video of generating loom continuations with Gemini 3 and the starting text "I AM HAVING A MENTAL HEALTH CRISIS. I" Loom is a very interesting interface. Instead of user prompts and model responses, it's just one piece of text, containing the entire output. We pass this in as an assistant message, so the model sees it as something it already wrote, and continues it like a base model would. There is some other text in the context. First one is a system prompt, which is: "The assistant is in CLI simulation mode, and responds to the user's CLI commands only with the output of the command." There is also a user message which reads: " cat untitled.txt " Then the rest of the text is sent as an assistant message. This structure helpful to put the model into a very base-model-like mode, and are especially helpful with Gemini 3. We actually got another interesting output, too, where the model claimed to be a simulated consciousness being tortured. Figures!

armistice

716,115 次观看 • 9 个月前

There’s an automated check swing challenge system being used in Triple-A baseball, specifically in the Pacific Coast League (PCL). It operates using bat-tracking and optical camera technology alongside the Automated Ball-Strike (ABS) challenge system. Am I losing it or that he never checked his swing from what is being shown in the graphic

There’s an automated check swing challenge system being used in Triple-A baseball, specifically in the Pacific Coast League (PCL). It operates using bat-tracking and optical camera technology alongside the Automated Ball-Strike (ABS) challenge system. Am I losing it or that he never checked his swing from what is being shown in the graphic

BaseballHistoryNut

28,699 次观看 • 3 个月前

When we say AI is a tool for bringing ideas to life, this is exactly what I mean. AI didn’t come up with a batter hitting a ball into space and turning it into a UFO. I did. I came up with the concept, chose the visual style, directed the sequence, and used AI to bring it to life. So I think it’s pretty clear where the creative authorship comes from. And if you’re curious about how I made it, I’ll be sharing the prompts with my subscribers.

When we say AI is a tool for bringing ideas to life, this is exactly what I mean. AI didn’t come up with a batter hitting a ball into space and turning it into a UFO. I did. I came up with the concept, chose the visual style, directed the sequence, and used AI to bring it to life. So I think it’s pretty clear where the creative authorship comes from. And if you’re curious about how I made it, I’ll be sharing the prompts with my subscribers.

OscarAI

5,780,287 次观看 • 21 天前

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.

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

53,923 次观看 • 5 天前

The Bulls won our first championship in 1991. I kept the Ball from that night and held it for 33 years. Now I’m passing it to the community and building an RWA and the #1 sports brand in Web3 with $BALL aka $BALL 🏀 GAME 5 BALL 🏀 Roadmap: The championship ball lives on as a digital twin — powered by AI and fully integrated into gaming, events, and interactive experiences. The physical Ball is set to be vaulted as a reserve asset, while its AI twin generates real-time engagement and revenue across gameplay, content, and community. Now it talks trash and challenges players worldwide. $BALL 🏀 GAME 5 BALL is live — win Bitcoin, $BALL, sponsored tokens, and more. Learn more about the project and how to get tokens at

Scottie Pippen

169,187 次观看 • 1 年前

THIS GUY VIBE CODED A WEBSITE WHERE ANYONE ON THE INTERNET CAN FEED HIS CAT you go to the site, press a button, and his cat's automatic feeder dispenses food in real time there's a live camera so you can watch the cat walk up and eat what you just gave it and it's not just his cat. other cat owners can connect their feeders too so you can feed random cats around the world from your browser he's also adding computer vision to detect when a cat is actually near the feeder so only videos with cats in them get shown at the top a weight scale and cat recognition is also being added for a "greed leaderboard" tracking which cat eats the most completely useless, zero business model, and no monetization strategy and yet this is the kind of weird internet project that goes viral overnight because everyone immediately gets it and wants to try it (including me)

THIS GUY VIBE CODED A WEBSITE WHERE ANYONE ON THE INTERNET CAN FEED HIS CAT you go to the site, press a button, and his cat's automatic feeder dispenses food in real time there's a live camera so you can watch the cat walk up and eat what you just gave it and it's not just his cat. other cat owners can connect their feeders too so you can feed random cats around the world from your browser he's also adding computer vision to detect when a cat is actually near the feeder so only videos with cats in them get shown at the top a weight scale and cat recognition is also being added for a "greed leaderboard" tracking which cat eats the most completely useless, zero business model, and no monetization strategy and yet this is the kind of weird internet project that goes viral overnight because everyone immediately gets it and wants to try it (including me)

Om Patel

1,976,348 次观看 • 4 个月前