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a Vietnamese AI engineer just built a real-time system that counts objects moving down a conveyor belt. it runs on ultralytics' objectcounter. train a detector, define the region you care about, and it handles the rest. works for anything on a line, parts, packages, produce. the clever bit: instead... show more

Oliver Prompts

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29,156 次观看 • 7 天前 •via X (Twitter)

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Elon Musk gave the entire entertainment industry its expiration date, and he is the one building the thing that kills it. Musk: “My guess is that we see the first compelling half hour, pure AI show next year.” Next year. A complete show generated entirely by AI. No writers. No actors. No cameras. No sets. No crew. No studio. Just a prompt and enough compute to render a reality that never physically existed. And shows are the easy part. Musk: “I say probably we’re maybe three years away from AI does the whole video game.” A show plays the same way every time. A game has to generate a living world that reacts to every decision in real time across every single frame. That is a fundamentally harder class of problem. And Musk put three years on it. Right now a single AAA title takes seven years and half a billion dollars across thousands of engineers and artists just to ship it. Musk is describing a world where one person types a paragraph and gets something comparable. The entire value proposition of a multi-billion dollar industry lives inside that gap. And it closes in thirty-six months. But the prediction is not the story. The person making it is. This is not an analyst speculating from the sidelines. This is the man building the largest AI compute clusters on the planet. The man who built xAI from zero in under two years. The man stacking hundreds of thousands of GPUs into facilities designed to do exactly what he is describing. When Musk says three years, he is not guessing about what someone else might eventually ship. He is reading you a delivery date off his own roadmap. Every media company on Earth is valued on a single assumption. That quality content is expensive and difficult to produce at scale. That one assumption is the structural foundation underneath every studio, every network, and every publisher in existence. Musk is dismantling it with raw compute. The studios still parading thousand-person production teams are not demonstrating strength. They are advertising the exact cost structure that one person with a prompt and a GPU allocation is about to make irrelevant. And it does not stop at entertainment. If AI can generate an interactive world that responds to human input in real time, it can generate anything. Advertising. Architecture. Training simulations. Product design. Every industry built on humans manually constructing visual experiences frame by frame is sitting on the same countdown Musk just read out loud. Now zoom out. Because this is not just an industry story. For the entire history of human civilization, the distance between imagining a world and actually creating one required thousands of people, millions of hours, and billions of dollars. That distance built Hollywood. That distance built the gaming industry. That distance made content scarce and studios powerful. Musk is collapsing that distance to zero. When the gap between imagining something and it existing disappears, every business model built on the difficulty of creation disappears with it. That is not disruption. That is a full inversion of how human beings create. Musk did not make a casual prediction on that podcast. He told you what he is building. He told you the timeline. And he told you which industries do not survive it. The entertainment industry is still debating whether this future is real. Musk is not part of that debate. He is building. And he just told you the delivery date.

Elon Musk gave the entire entertainment industry its expiration date, and he is the one building the thing that kills it. Musk: “My guess is that we see the first compelling half hour, pure AI show next year.” Next year. A complete show generated entirely by AI. No writers. No actors. No cameras. No sets. No crew. No studio. Just a prompt and enough compute to render a reality that never physically existed. And shows are the easy part. Musk: “I say probably we’re maybe three years away from AI does the whole video game.” A show plays the same way every time. A game has to generate a living world that reacts to every decision in real time across every single frame. That is a fundamentally harder class of problem. And Musk put three years on it. Right now a single AAA title takes seven years and half a billion dollars across thousands of engineers and artists just to ship it. Musk is describing a world where one person types a paragraph and gets something comparable. The entire value proposition of a multi-billion dollar industry lives inside that gap. And it closes in thirty-six months. But the prediction is not the story. The person making it is. This is not an analyst speculating from the sidelines. This is the man building the largest AI compute clusters on the planet. The man who built xAI from zero in under two years. The man stacking hundreds of thousands of GPUs into facilities designed to do exactly what he is describing. When Musk says three years, he is not guessing about what someone else might eventually ship. He is reading you a delivery date off his own roadmap. Every media company on Earth is valued on a single assumption. That quality content is expensive and difficult to produce at scale. That one assumption is the structural foundation underneath every studio, every network, and every publisher in existence. Musk is dismantling it with raw compute. The studios still parading thousand-person production teams are not demonstrating strength. They are advertising the exact cost structure that one person with a prompt and a GPU allocation is about to make irrelevant. And it does not stop at entertainment. If AI can generate an interactive world that responds to human input in real time, it can generate anything. Advertising. Architecture. Training simulations. Product design. Every industry built on humans manually constructing visual experiences frame by frame is sitting on the same countdown Musk just read out loud. Now zoom out. Because this is not just an industry story. For the entire history of human civilization, the distance between imagining a world and actually creating one required thousands of people, millions of hours, and billions of dollars. That distance built Hollywood. That distance built the gaming industry. That distance made content scarce and studios powerful. Musk is collapsing that distance to zero. When the gap between imagining something and it existing disappears, every business model built on the difficulty of creation disappears with it. That is not disruption. That is a full inversion of how human beings create. Musk did not make a casual prediction on that podcast. He told you what he is building. He told you the timeline. And he told you which industries do not survive it. The entertainment industry is still debating whether this future is real. Musk is not part of that debate. He is building. And he just told you the delivery date.

Dustin

22,390 次观看 • 1 个月前

You can't 3D reconstruct glass from images... ...WRONG! Thanks for video diffusion, now just about anything is possible! Introducing...Diffusion Knows Transparency (DKT) Transparent and reflective objects usually break robot vision and photogrammetry pipelines because they don't follow the "solid object" rules standard cameras expect. DKT is a new AI model that repurposes the "internal physics engine" found in video generation models to solve this problem. Researchers took a massive video diffusion model (WAN) and fine-tuned it using a custom-built synthetic dataset to turn it into a high-precision depth sensor. To train the AI, they built the first massive synthetic video library of transparent objects, 1.32 million frames of perfectly labeled glass and metal objects in motion. Without ever seeing a "real" labeled video of glass during training, the model (DKT) outperformed all previous specialized systems on real-world benchmarks (ClearPose, DREDS). They created a "lightweight" 1.3B parameter version that runs fast enough (0.17s per frame) to be used on actual robot hardware. Two reasons I find this project important: 1. It further proves that synthetic data will be essential for training the next generation vision models. 2. In real-world robotic tests, using DKT's depth maps nearly doubled the success rate of robot arms trying to pick up objects on tricky reflective or translucent surfaces. At home robots will need to interact with these types of objects on a daily basis. Check out the project page here: Code is LIVE! #Computervision #Robotics #AI

You can't 3D reconstruct glass from images... ...WRONG! Thanks for video diffusion, now just about anything is possible! Introducing...Diffusion Knows Transparency (DKT) Transparent and reflective objects usually break robot vision and photogrammetry pipelines because they don't follow the "solid object" rules standard cameras expect. DKT is a new AI model that repurposes the "internal physics engine" found in video generation models to solve this problem. Researchers took a massive video diffusion model (WAN) and fine-tuned it using a custom-built synthetic dataset to turn it into a high-precision depth sensor. To train the AI, they built the first massive synthetic video library of transparent objects, 1.32 million frames of perfectly labeled glass and metal objects in motion. Without ever seeing a "real" labeled video of glass during training, the model (DKT) outperformed all previous specialized systems on real-world benchmarks (ClearPose, DREDS). They created a "lightweight" 1.3B parameter version that runs fast enough (0.17s per frame) to be used on actual robot hardware. Two reasons I find this project important: 1. It further proves that synthetic data will be essential for training the next generation vision models. 2. In real-world robotic tests, using DKT's depth maps nearly doubled the success rate of robot arms trying to pick up objects on tricky reflective or translucent surfaces. At home robots will need to interact with these types of objects on a daily basis. Check out the project page here: Code is LIVE! #Computervision #Robotics #AI

Jonathan Stephens

17,712 次观看 • 7 个月前

The new GPT Engineer is insane. I just wrote a single sentence and it created me a landing page for a SaaS business! It outputs the code, allows you to modify anything and publish it with just one click 🤯

The new GPT Engineer is insane. I just wrote a single sentence and it created me a landing page for a SaaS business! It outputs the code, allows you to modify anything and publish it with just one click 🤯

Alvaro Cintas

99,000 次观看 • 2 年前

I built a Bing AI clone called Zing! Featuring functional GPT-4 and Bing API search integration. I didn't write a single line of code; I just asked, and GPT-4 did the rest 🤯😅 It took roughly 2 hours. Hosted on Replit ⠕

I built a Bing AI clone called Zing! Featuring functional GPT-4 and Bing API search integration. I didn't write a single line of code; I just asked, and GPT-4 did the rest 🤯😅 It took roughly 2 hours. Hosted on Replit ⠕

Pietro Schirano

581,490 次观看 • 3 年前

SOMEONE BUILT A WAY TO SEND FILES BETWEEN TWO PHONES WITH NO WIFI, NO BLUETOOTH AND NO NETWORK AT ALL it works with just a screen flashing qr codes at a camera one device plays an endless stream of animated qr codes, the other one points its camera at the screen and rebuilds the file out of the light no pairing, no app, no shared network, nothing but the camera > its pulling about 129 kb/s, a full 2mb image transfers in seconds > theres no back channel, the receiver can never ask for a missed frame, so it uses fountain codes, every frame is a scrambled mix of the file rather than one piece of it > that means the receiver just collects any frames it can catch in any order, and once it has enough it can reconstruct the whole file > dropping frames costs you a little time but never breaks the transfer > you can point the camera at a stream thats already running and it just locks on mid flight he was building a cached mp3 player because he was sick of ads and bad streaming quality. he wanted a way to send tracks phone to phone without both phones being on the same network, and realized flashing qr codes could carry the data he built the whole working prototype in one night with claude code its open source and already at 375 stars

SOMEONE BUILT A WAY TO SEND FILES BETWEEN TWO PHONES WITH NO WIFI, NO BLUETOOTH AND NO NETWORK AT ALL it works with just a screen flashing qr codes at a camera one device plays an endless stream of animated qr codes, the other one points its camera at the screen and rebuilds the file out of the light no pairing, no app, no shared network, nothing but the camera > its pulling about 129 kb/s, a full 2mb image transfers in seconds > theres no back channel, the receiver can never ask for a missed frame, so it uses fountain codes, every frame is a scrambled mix of the file rather than one piece of it > that means the receiver just collects any frames it can catch in any order, and once it has enough it can reconstruct the whole file > dropping frames costs you a little time but never breaks the transfer > you can point the camera at a stream thats already running and it just locks on mid flight he was building a cached mp3 player because he was sick of ads and bad streaming quality. he wanted a way to send tracks phone to phone without both phones being on the same network, and realized flashing qr codes could carry the data he built the whole working prototype in one night with claude code its open source and already at 375 stars

Om Patel

947,303 次观看 • 16 天前

Update on my lightweight intercom alternative that runs on a $5 a month server. The widget is almost ready. It took more work than I expected. I spent a lot of time making it light on websites and thinking through interactions and UI. Built with Go and Vue, and I’ll open source it soon.

Update on my lightweight intercom alternative that runs on a $5 a month server. The widget is almost ready. It took more work than I expected. I spent a lot of time making it light on websites and thinking through interactions and UI. Built with Go and Vue, and I’ll open source it soon.

Fayaz Ahmed

60,335 次观看 • 10 个月前

THIS GUY GOT SICK OF UK TRAIN STATIONS HIDING THE PLATFORM NUMBER UNTIL THE LAST SECOND, SO HE VIBE CODED AN APP THAT PREDICTS IT BEFORE THEY REVEAL IT if youve ever stood in a crowded station like london euston, you know the pain the platform stays hidden until 15 minutes before boarding, then it flashes up and hundreds of people sprint for the same gate so he built something that fixes this: > a clean departures and arrivals app pulling live data straight from the network rail apis > live train tracking so you can watch where your train actually is on the route and whether its running on time > the main feature is a predictive engine that guesses your platform before the station reveals it, and its right about 75% of the time heres how it predicts: every time a train finishes its journey, it logs which platform it actually pulled into and compares that to the platform network rail originally advertised it saves every one of those comparisons, and over time it builds up enough history to predict the platform with a real confidence score he built the whole thing with claude, mostly opus with some fable

THIS GUY GOT SICK OF UK TRAIN STATIONS HIDING THE PLATFORM NUMBER UNTIL THE LAST SECOND, SO HE VIBE CODED AN APP THAT PREDICTS IT BEFORE THEY REVEAL IT if youve ever stood in a crowded station like london euston, you know the pain the platform stays hidden until 15 minutes before boarding, then it flashes up and hundreds of people sprint for the same gate so he built something that fixes this: > a clean departures and arrivals app pulling live data straight from the network rail apis > live train tracking so you can watch where your train actually is on the route and whether its running on time > the main feature is a predictive engine that guesses your platform before the station reveals it, and its right about 75% of the time heres how it predicts: every time a train finishes its journey, it logs which platform it actually pulled into and compares that to the platform network rail originally advertised it saves every one of those comparisons, and over time it builds up enough history to predict the platform with a real confidence score he built the whole thing with claude, mostly opus with some fable

Om Patel

175,724 次观看 • 1 个月前

One of the coolest things about Samsung’s Frame Pro TV that further enhances the effect that it’s a painting is that when you get the remote and turn the TV on, sometimes it just doesn’t and keeps displaying art. Pretty cool effect!

One of the coolest things about Samsung’s Frame Pro TV that further enhances the effect that it’s a painting is that when you get the remote and turn the TV on, sometimes it just doesn’t and keeps displaying art. Pretty cool effect!

Quinn Nelson

426,027 次观看 • 1 年前

Mediabunny has world-class video seeking across all file formats. On the left, VLC *trying* to seek through a .ts file, and it just kind of gives up. On the right, a player built with Mediabunny. It just works. Doesn't matter if it's in memory, on disk, or over the network.

Mediabunny has world-class video seeking across all file formats. On the left, VLC trying to seek through a .ts file, and it just kind of gives up. On the right, a player built with Mediabunny. It just works. Doesn't matter if it's in memory, on disk, or over the network.

Vanilagy

57,643 次观看 • 6 个月前

Do you actually understand what's happening. He took an old laptop and turned it into a box that replaces every AI subscription he pays for. Now that box brings in $2,500 a month, per client, on repeat. No new hardware. Just parts he already had, mounted on a printed plate, running six agents without breaking a sweat. The agents don't sleep. One scouts topics. One writes drafts. One rejects anything below standard. One pushes finished work out the door. One watches over the rest. Fifteen clients. Thirty pieces of content each, every month. Four hours a week from him. The system he built out of spare parts now earns more than most people's actual job. Everyone else recycled their old laptop. He recycled his into income.

Do you actually understand what's happening. He took an old laptop and turned it into a box that replaces every AI subscription he pays for. Now that box brings in $2,500 a month, per client, on repeat. No new hardware. Just parts he already had, mounted on a printed plate, running six agents without breaking a sweat. The agents don't sleep. One scouts topics. One writes drafts. One rejects anything below standard. One pushes finished work out the door. One watches over the rest. Fifteen clients. Thirty pieces of content each, every month. Four hours a week from him. The system he built out of spare parts now earns more than most people's actual job. Everyone else recycled their old laptop. He recycled his into income.

Superior

16,950 次观看 • 1 个月前

Hyundai just unveiled the Boulder concept, a body-on-frame off-roader that would line up against the Bronco, and we want it in production

Hyundai just unveiled the Boulder concept, a body-on-frame off-roader that would line up against the Bronco, and we want it in production

Edmunds

30,415 次观看 • 4 个月前

Cinematographer Roger Deakins had a camera platform with a soft buffer built on the railroad tracks so the train could run into it safely and push the camera down the track for this incredibly visceral shot. Movie Magic!

Cinematographer Roger Deakins had a camera platform with a soft buffer built on the railroad tracks so the train could run into it safely and push the camera down the track for this incredibly visceral shot. Movie Magic!

Vashi Nedomansky, ACE

380,738 次观看 • 4 个月前

This guy built a visual scanner that reads 468 points on his face and 42 points on his hands from a regular webcam and turns them into a cloud of thousands of particles right between his palms. Inside, MediaPipe and TouchDesigner are linked: the first captures hands and face from the webcam with high accuracy, the second turns those coordinates into a live plane and feeds it into a POP system that instantly generates a swarm of particles in the shape of a head. No studio, no render farmer, no VR headset. Just a laptop, a webcam, and 1 TouchDesigner session. And traditional VJ studios keep teams of 5 people on a setup with lighting, custom hardware, and commercial plugins, while his expenses are only a TouchDesigner subscription and a regular USB camera. One laptop runs MediaPipe and TouchDesigner simultaneously, holds the camera stream at 60 FPS without drops, and in parallel processes 468 face points + 21 points on each hand. The camera captures frame after frame, MediaPipe in real time sends TouchDesigner the finger coordinates and face geometry, and the POP operator inside the engine translates those numbers into thousands of particle points with colors from bright pink to gold. This setup immediately defines the role of the tool and the limits of its autonomy. It knows where the fingertips are at every moment of the frame. It knows how to read the face geometry at any angle to the camera. It knows how to draw a swarm of particles between them with the right color and contour. → MediaPipe pulls 468 points from the face and 21 points from each hand, 60 times per second → TouchDesigner receives those coordinates, builds a virtual rectangle between the fingertips, and feeds it into the POP system → POP generates thousands of particle points in the shape of a head, coloring them in a gradient from bright pink to gold → The HUD layer adds green corners and a blue neon frame, styling the image like an AR interface → All layers assemble into 1 real-time frame that projects back onto the video in the camera window → The final image is recorded to a file or broadcast to a projector for a live installation And only when the guy spreads his hands wider does the plane between the palms stretch; brings them together, it narrows. Otherwise the system runs on its own. And when he moves from his home room to a concert hall, the same laptop with the same webcam launches the same TouchDesigner session in just 5 minutes, without reconfiguration, without a new team, and without a single line of new code. In his work setup there is no studio of his own and no team for assembly. On the desk sits a laptop with a webcam, on top run MediaPipe and TouchDesigner with POP operators, and the same setup through a USB camera moves to any concert without a new configuration. Out of everything I have seen this year, this is the cleanest Creative Coding setup on 1 laptop: 0 render farms, 0 studio lighting, and between them 3 libraries, thousands of particle points, and 1 webcam.

This guy built a visual scanner that reads 468 points on his face and 42 points on his hands from a regular webcam and turns them into a cloud of thousands of particles right between his palms. Inside, MediaPipe and TouchDesigner are linked: the first captures hands and face from the webcam with high accuracy, the second turns those coordinates into a live plane and feeds it into a POP system that instantly generates a swarm of particles in the shape of a head. No studio, no render farmer, no VR headset. Just a laptop, a webcam, and 1 TouchDesigner session. And traditional VJ studios keep teams of 5 people on a setup with lighting, custom hardware, and commercial plugins, while his expenses are only a TouchDesigner subscription and a regular USB camera. One laptop runs MediaPipe and TouchDesigner simultaneously, holds the camera stream at 60 FPS without drops, and in parallel processes 468 face points + 21 points on each hand. The camera captures frame after frame, MediaPipe in real time sends TouchDesigner the finger coordinates and face geometry, and the POP operator inside the engine translates those numbers into thousands of particle points with colors from bright pink to gold. This setup immediately defines the role of the tool and the limits of its autonomy. It knows where the fingertips are at every moment of the frame. It knows how to read the face geometry at any angle to the camera. It knows how to draw a swarm of particles between them with the right color and contour. → MediaPipe pulls 468 points from the face and 21 points from each hand, 60 times per second → TouchDesigner receives those coordinates, builds a virtual rectangle between the fingertips, and feeds it into the POP system → POP generates thousands of particle points in the shape of a head, coloring them in a gradient from bright pink to gold → The HUD layer adds green corners and a blue neon frame, styling the image like an AR interface → All layers assemble into 1 real-time frame that projects back onto the video in the camera window → The final image is recorded to a file or broadcast to a projector for a live installation And only when the guy spreads his hands wider does the plane between the palms stretch; brings them together, it narrows. Otherwise the system runs on its own. And when he moves from his home room to a concert hall, the same laptop with the same webcam launches the same TouchDesigner session in just 5 minutes, without reconfiguration, without a new team, and without a single line of new code. In his work setup there is no studio of his own and no team for assembly. On the desk sits a laptop with a webcam, on top run MediaPipe and TouchDesigner with POP operators, and the same setup through a USB camera moves to any concert without a new configuration. Out of everything I have seen this year, this is the cleanest Creative Coding setup on 1 laptop: 0 render farms, 0 studio lighting, and between them 3 libraries, thousands of particle points, and 1 webcam.

Blaze

38,242 次观看 • 3 个月前

China just dropped an open source model that turns any phone into a 3D scanner you point it at a room and walk through it the whole space builds itself into a 3D point cloud in real time as the camera moves, no LiDAR and no depth sensor anywhere it held a full 13 minute walkthrough at 25,000 frames without the map drifting or collapsing > ~20 fps on a single GPU > works indoors and outdoors from plain footage > the scan normally needs a $50,000 rig and a technician > Apache 2.0 and runs fully offline on your machine repo in the reply

China just dropped an open source model that turns any phone into a 3D scanner you point it at a room and walk through it the whole space builds itself into a 3D point cloud in real time as the camera moves, no LiDAR and no depth sensor anywhere it held a full 13 minute walkthrough at 25,000 frames without the map drifting or collapsing > ~20 fps on a single GPU > works indoors and outdoors from plain footage > the scan normally needs a $50,000 rig and a technician > Apache 2.0 and runs fully offline on your machine repo in the reply

savip

104,123 次观看 • 29 天前

I'm seeing a lot of people saying it is just a bad upscaling instead of Gen AI, but it is indeed Gen AI animation. There are things going on in it that just don't make any sense for puppet animation. Here are some parts that make it clear, I slowed down the video so it's easier to notice the chunky parts. I checked the past ADs and it's possible to notice details (from an animator's POV) that are common and make sense for human work, so it was definitely a choice to use AI on this new AD

I'm seeing a lot of people saying it is just a bad upscaling instead of Gen AI, but it is indeed Gen AI animation. There are things going on in it that just don't make any sense for puppet animation. Here are some parts that make it clear, I slowed down the video so it's easier to notice the chunky parts. I checked the past ADs and it's possible to notice details (from an animator's POV) that are common and make sense for human work, so it was definitely a choice to use AI on this new AD

mei ✨ live2d animator

1,114,561 次观看 • 7 个月前

I don't think there's a single terminal ux that handles agent swarms well With slate, you can literally use Opus 4.6 and GPT 5.4 at the exact same time But making it intuitive took a ton of work So heres a thread on how it works and how to actually use it 🧵

I don't think there's a single terminal ux that handles agent swarms well With slate, you can literally use Opus 4.6 and GPT 5.4 at the exact same time But making it intuitive took a ton of work So heres a thread on how it works and how to actually use it 🧵

akira

139,114 次观看 • 5 个月前

This guy built something that changes your face in real time using hand gestures. And it looks insane. 🤯 Viet Nguyen, a Senior AI engineer, built a personal project that transforms your face into 16 different visual styles. Van Gogh. Neon. Anime. Pop art. Graffiti. All triggered by just moving your hand. Open your hand. AI reads the gesture. Your face transforms into a completely different art style. Almost instantly. 16 styles. One hand movement. Zero clicks. The wild part: he built this as a side project. Not a product. Not a startup. Just one engineer combining two existing tools in a way nobody had thought to before. This is what personal projects look like in 2026.

This guy built something that changes your face in real time using hand gestures. And it looks insane. 🤯 Viet Nguyen, a Senior AI engineer, built a personal project that transforms your face into 16 different visual styles. Van Gogh. Neon. Anime. Pop art. Graffiti. All triggered by just moving your hand. Open your hand. AI reads the gesture. Your face transforms into a completely different art style. Almost instantly. 16 styles. One hand movement. Zero clicks. The wild part: he built this as a side project. Not a product. Not a startup. Just one engineer combining two existing tools in a way nobody had thought to before. This is what personal projects look like in 2026.

Vaibhav Sisinty

25,242 次观看 • 1 个月前

THIS GUY DID A SPECIAL FLIGHT TRACKING RADAR USING CLAUDE THAT SHOWS EVERY AIRCRAFT NEAR WHERE YOU ARE USB-powered. AMOLED touchscreen. Tap any dot on the screen - it tells you the airline, the speed, the registration, whether it's climbing or descending. It sits on his desk. He glances out the window and knows exactly what's flying overhead. He built it in a week, just as a project for himself. Then it blew up. Now people want one. Total cost in parts: about $100. Most people look up and see a dot. He built a window into the whole sky. He built his radar for what's in the air. I built mine for what's on the ticket - using Claude to find the cheapest flight before you book.

THIS GUY DID A SPECIAL FLIGHT TRACKING RADAR USING CLAUDE THAT SHOWS EVERY AIRCRAFT NEAR WHERE YOU ARE USB-powered. AMOLED touchscreen. Tap any dot on the screen - it tells you the airline, the speed, the registration, whether it's climbing or descending. It sits on his desk. He glances out the window and knows exactly what's flying overhead. He built it in a week, just as a project for himself. Then it blew up. Now people want one. Total cost in parts: about $100. Most people look up and see a dot. He built a window into the whole sky. He built his radar for what's in the air. I built mine for what's on the ticket - using Claude to find the cheapest flight before you book.

kiosa

15,179 次观看 • 1 个月前

This is scary! Someone built a digital society for AI agents. AIvilization (AI + Civilization) is a simulation platform where thousands of AI agents live and do normal human things like work, socialize, learn, and evolve. You create one agent and let it live. You define its personality, goals, and behavior and then it goes off into a shared world with thousands of other AI agents doing the same. Check it out here:

This is scary! Someone built a digital society for AI agents. AIvilization (AI + Civilization) is a simulation platform where thousands of AI agents live and do normal human things like work, socialize, learn, and evolve. You create one agent and let it live. You define its personality, goals, and behavior and then it goes off into a shared world with thousands of other AI agents doing the same. Check it out here:

Pratham

38,077 次观看 • 4 个月前