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A REGULAR PHONE JUST REPLACED A $50,000 SURVEILLANCE SYSTEM Point it at an intersection and the screen boxes things on its own: car, person, stop sign, traffic light, umbrella, bench, bicycle, motorcycle, a boat out on the lake. Every target gets an ID and a confidence score. T-001 BOAT...

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shmidt

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12,096 görüntüleme • 1 ay önce •via X (Twitter)

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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
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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

951,210 görüntüleme • 1 ay önce

WHAT ARE YOU DOING IN THIS SITUATION…? You’re stuck in traffic, already irritated… cars barely moving. Now here comes the person that was tailgating you earlier 👀 They hop out their car… walk straight up to your passenger window…hit on it once then throw a rock through it… One bad decision and this turns from “annoying traffic moment” into a full-blown situation. He waited for traffic like it was a scheduled fight 😂. As a man, are you stepping out the car?
0:17

WHAT ARE YOU DOING IN THIS SITUATION…? You’re stuck in traffic, already irritated… cars barely moving. Now here comes the person that was tailgating you earlier 👀 They hop out their car… walk straight up to your passenger window…hit on it once then throw a rock through it… One bad decision and this turns from “annoying traffic moment” into a full-blown situation. He waited for traffic like it was a scheduled fight 😂. As a man, are you stepping out the car?

𝐌𝐑. 𝐖𝐇𝐈𝐓𝐄 ™

61,799 görüntüleme • 5 ay önce

166,000 neurons from a dead fruit fly now hunt drones from a bedroom desk. A white drone the size of a palm lifts off the carpet, and a black 3D-printed turret on the desk swings after it, with the fly's brain working its 2 stepper motors, 1 camera and 2 barrels through a nest of rainbow wires on a breadboard. That brain sits in the top-left corner of the screen and flares every time the drone jerks. A Patriot interceptor costs about $4 million, and armies are firing them at drones worth a fraction of that. This brain is smaller than a poppy seed, and Google put it online for free 2 weeks ago. Then someone gave it a job it was built for. Most of a fly's brain exists to see motion, and this brain is male, and male flies spend their lives chasing whatever moves. The drone climbs past the ceiling fan and the crosshair climbs with it, then drops when it drops. For 18 seconds it never loses the drone. In the last shot the drone flies home to the guy holding the controller, and the crosshair follows it right onto his chest. It spent its whole life dodging swatters. Now it's the one aiming.
0:17

166,000 neurons from a dead fruit fly now hunt drones from a bedroom desk. A white drone the size of a palm lifts off the carpet, and a black 3D-printed turret on the desk swings after it, with the fly's brain working its 2 stepper motors, 1 camera and 2 barrels through a nest of rainbow wires on a breadboard. That brain sits in the top-left corner of the screen and flares every time the drone jerks. A Patriot interceptor costs about $4 million, and armies are firing them at drones worth a fraction of that. This brain is smaller than a poppy seed, and Google put it online for free 2 weeks ago. Then someone gave it a job it was built for. Most of a fly's brain exists to see motion, and this brain is male, and male flies spend their lives chasing whatever moves. The drone climbs past the ceiling fan and the crosshair climbs with it, then drops when it drops. For 18 seconds it never loses the drone. In the last shot the drone flies home to the guy holding the controller, and the crosshair follows it right onto his chest. It spent its whole life dodging swatters. Now it's the one aiming.

Spike 1%

32,405 görüntüleme • 2 gün önce

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.
0:10

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 görüntüleme • 4 ay önce

This is everyone’s worst nightmare on the road. The woman in the green truck was flying at 80 mph, completely out of it, and left a white car totaled with its passengers in shock. Just a reminder that you can do everything right and still get wiped out by someone else.
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This is everyone’s worst nightmare on the road. The woman in the green truck was flying at 80 mph, completely out of it, and left a white car totaled with its passengers in shock. Just a reminder that you can do everything right and still get wiped out by someone else.

Desiree

3,467,783 görüntüleme • 6 ay önce

Running cold email campaigns just became a whole lot easier Smartlead now runs an MCP server, which in plain terms means Claude can read and act on your live campaign data directly instead of working off a spreadsheet that went stale the moment you exported it. The workflow is worth walking through properly, because it is shorter than people expect. You generate an API key inside your account, point Claude at the server once, and from then on you ask for what you want in a sentence. Here is a prompt worth stealing in full: "Fetch all Smartlead clients, then get today's performance for each: emails sent, replied, positive replies, unique lead count. Compute reply rate per client, run a top and bottom performer analysis, format it as a daily client performance report, and post it to Slack." One paste, and it pulls live figures for every account, does the arithmetic, ranks the strongest and the weakest, and delivers the finished thing into the channel your team already sits in, before anyone has logged on for the day. Be clear about the division of labour, because it is what makes this useful rather than a novelty. Smartlead is the engine holding the campaigns, the mailboxes, the warmup and the reply data, and Claude is simply the interface you operate all of it through, so nothing about your sending changes and everything about how you interrogate it does. The effect people underestimate is on the questions you start asking. Once a report costs you a sentence rather than an afternoon, you stop rationing the ones that used to feel like too much trouble, and problems that used to surface on a Friday start surfacing on a Tuesday. Connect it with Claude through MCP and run one prompt against your own account today.
0:10

Running cold email campaigns just became a whole lot easier Smartlead now runs an MCP server, which in plain terms means Claude can read and act on your live campaign data directly instead of working off a spreadsheet that went stale the moment you exported it. The workflow is worth walking through properly, because it is shorter than people expect. You generate an API key inside your account, point Claude at the server once, and from then on you ask for what you want in a sentence. Here is a prompt worth stealing in full: "Fetch all Smartlead clients, then get today's performance for each: emails sent, replied, positive replies, unique lead count. Compute reply rate per client, run a top and bottom performer analysis, format it as a daily client performance report, and post it to Slack." One paste, and it pulls live figures for every account, does the arithmetic, ranks the strongest and the weakest, and delivers the finished thing into the channel your team already sits in, before anyone has logged on for the day. Be clear about the division of labour, because it is what makes this useful rather than a novelty. Smartlead is the engine holding the campaigns, the mailboxes, the warmup and the reply data, and Claude is simply the interface you operate all of it through, so nothing about your sending changes and everything about how you interrogate it does. The effect people underestimate is on the questions you start asking. Once a report costs you a sentence rather than an afternoon, you stop rationing the ones that used to feel like too much trouble, and problems that used to surface on a Friday start surfacing on a Tuesday. Connect it with Claude through MCP and run one prompt against your own account today.

Tim

21,666 görüntüleme • 1 gün önce

Today I had my first demo drive in a Tesla. It was also my first time ever sitting in one. This was the first car I’ve ever sat in the driver’s seat of where I didn’t touch the steering wheel for over 20 miles. Before I even got to the car, the people who had demoed it before me were an older married couple who were absolutely euphoric. They thought it was so cool that the car could drive itself. The Tesla employee told me this happens all the time. People come back from demo drives and tell the next test driver that they’re about to have an amazing experience. Little did I know, I’d end up carrying on the torch to the next couple demoing it after me. There was a ton of construction where I demoed the car, and FSD handled the entire drive extremely well. And yes, it can go through a drive-thru and stop at each window. The only thing I had to do was tap the pedal because it wouldn’t leave on its own, but it was still wild seeing the AI stop perfectly at the second window and wait. There are a million things I could write about why a Tesla feels like a better car and how much more it offers compared to a regular car. But for now, I’ll stick to FSD. There were only two moments that made me a little uneasy. The first was pretty minor. The car slightly hesitated going up a driveway, but quickly made up its mind. The second was more noticeable. I didn’t realize the car was nagging me. Once I touched the steering wheel, nothing happened, so I pulled it right a little harder, then let go. After that, the car turned left and crossed a double yellow on a backroad. (and yes I know you can sue the volume knob) I’m not totally sure if it was trying to pull over or what it was doing. I wanted to see how it would handle the situation, but there were cars coming, so I took over and corrected it. One of the coolest moments was when I thought FSD was glitching because it came to a complete stop in the middle of a busy road. Then I looked around and realized why. On the right side, there was a bicyclist waiting at a yellow crosswalk. The cars behind me didn’t honk, and the Tesla stopping actually incentivized another car in the right lane to stop and let him pass. The car is almost too nice to pedestrians, because 99.999% of humans would’ve blown through that, especially with no flashing light. For 99.9% of the drive, the car navigated confidently and smoothly. It was a real “feel the AGI” moment. Please do not let the media, the general public, or anyone else convince you that this technology is just some kind of auto assist or glorified cruise control. This is undoubtedly getting extremely close to feeling superhuman. You still have to pay attention to the road, but after experiencing it myself, I’d be shocked if HW4 Teslas aren’t unsupervised within the next couple years. The car was extremely smooth. There was no harsh braking, and it even avoided something in the road that I didn’t see. Driving with FSD made me realize I probably wasn’t driving as well as I could be. Hopefully, eventually, everyone’s car can be as mindful as a Tesla. I’ve never seen a brand so far removed from the public’s sentiment. I’m so happy I ordered one.
0:14

Today I had my first demo drive in a Tesla. It was also my first time ever sitting in one. This was the first car I’ve ever sat in the driver’s seat of where I didn’t touch the steering wheel for over 20 miles. Before I even got to the car, the people who had demoed it before me were an older married couple who were absolutely euphoric. They thought it was so cool that the car could drive itself. The Tesla employee told me this happens all the time. People come back from demo drives and tell the next test driver that they’re about to have an amazing experience. Little did I know, I’d end up carrying on the torch to the next couple demoing it after me. There was a ton of construction where I demoed the car, and FSD handled the entire drive extremely well. And yes, it can go through a drive-thru and stop at each window. The only thing I had to do was tap the pedal because it wouldn’t leave on its own, but it was still wild seeing the AI stop perfectly at the second window and wait. There are a million things I could write about why a Tesla feels like a better car and how much more it offers compared to a regular car. But for now, I’ll stick to FSD. There were only two moments that made me a little uneasy. The first was pretty minor. The car slightly hesitated going up a driveway, but quickly made up its mind. The second was more noticeable. I didn’t realize the car was nagging me. Once I touched the steering wheel, nothing happened, so I pulled it right a little harder, then let go. After that, the car turned left and crossed a double yellow on a backroad. (and yes I know you can sue the volume knob) I’m not totally sure if it was trying to pull over or what it was doing. I wanted to see how it would handle the situation, but there were cars coming, so I took over and corrected it. One of the coolest moments was when I thought FSD was glitching because it came to a complete stop in the middle of a busy road. Then I looked around and realized why. On the right side, there was a bicyclist waiting at a yellow crosswalk. The cars behind me didn’t honk, and the Tesla stopping actually incentivized another car in the right lane to stop and let him pass. The car is almost too nice to pedestrians, because 99.999% of humans would’ve blown through that, especially with no flashing light. For 99.9% of the drive, the car navigated confidently and smoothly. It was a real “feel the AGI” moment. Please do not let the media, the general public, or anyone else convince you that this technology is just some kind of auto assist or glorified cruise control. This is undoubtedly getting extremely close to feeling superhuman. You still have to pay attention to the road, but after experiencing it myself, I’d be shocked if HW4 Teslas aren’t unsupervised within the next couple years. The car was extremely smooth. There was no harsh braking, and it even avoided something in the road that I didn’t see. Driving with FSD made me realize I probably wasn’t driving as well as I could be. Hopefully, eventually, everyone’s car can be as mindful as a Tesla. I’ve never seen a brand so far removed from the public’s sentiment. I’m so happy I ordered one.

Chris

18,824 görüntüleme • 2 ay önce

🚨 Florida crash caught on video. A witness says he pulled out his phone after a green Tacoma nearly hit him and started driving wildly through traffic. Seconds later… The driver never hit the brakes and slammed straight into a car stopped in traffic. The man filming said he had a feeling something bad was about to happen… He just didn’t expect it to end like this. At this point you have to ask: What is going on with drivers lately? ⬇️ 🇺🇸
0:18

🚨 Florida crash caught on video. A witness says he pulled out his phone after a green Tacoma nearly hit him and started driving wildly through traffic. Seconds later… The driver never hit the brakes and slammed straight into a car stopped in traffic. The man filming said he had a feeling something bad was about to happen… He just didn’t expect it to end like this. At this point you have to ask: What is going on with drivers lately? ⬇️ 🇺🇸

Tony Lane 🇺🇸

95,028 görüntüleme • 6 ay önce

I FOUND A FORMAT THAT GETS 6M+ VIEWS WITH A GIRL WHO NEVER TAKES HER TOP OFF. 17 SECONDS. SHE PULLS IT, TIES IT, ADJUSTS IT, LIFTS IT. EVERY FRAME LOOKS LIKE THE NEXT ONE IS THE REVEAL. THERE IS NO REVEAL. THAT'S WHY YOU'RE ON YOUR THIRD LOOP. Thread. Girl leaning against a tree. Dark tank top, jeans, cross necklace. Her hands are on her shirt and they never leave. She ties the bottom in a knot, shows a strip of stomach. Unties it. Pulls a strap. Adjusts. Every movement is one tug away from something the platform would delete. 0:03. She pulls the fabric tight across her chest. Camera framed on her torso, face barely in shot. You're not watching a person, you're watching hands and fabric and the gap between them. 0:08. She pulls the strap off her shoulder, lets it hang. The top shifts. For half a second you think this is it. It's not. She pulls it back up and your brain resets the clock. 0:14. Still adjusting. Hands on the neckline, pulling it down, gathering it back up. The cross necklace sits right above the edge of the top the entire time. A tiny gold reminder of modesty hanging directly over the thing you're waiting to see. The camera never shows her full face. Crop the face and she stops being a person and starts being a countdown. 17 seconds. Every other video we've broken down is under 10. This one runs long because the payoff is always "the next second." You watch 17 waiting for 18. Second 18 is the loop. She never takes it off. She never needed to. She just needed you to think she was about to.
0:17

I FOUND A FORMAT THAT GETS 6M+ VIEWS WITH A GIRL WHO NEVER TAKES HER TOP OFF. 17 SECONDS. SHE PULLS IT, TIES IT, ADJUSTS IT, LIFTS IT. EVERY FRAME LOOKS LIKE THE NEXT ONE IS THE REVEAL. THERE IS NO REVEAL. THAT'S WHY YOU'RE ON YOUR THIRD LOOP. Thread. Girl leaning against a tree. Dark tank top, jeans, cross necklace. Her hands are on her shirt and they never leave. She ties the bottom in a knot, shows a strip of stomach. Unties it. Pulls a strap. Adjusts. Every movement is one tug away from something the platform would delete. 0:03. She pulls the fabric tight across her chest. Camera framed on her torso, face barely in shot. You're not watching a person, you're watching hands and fabric and the gap between them. 0:08. She pulls the strap off her shoulder, lets it hang. The top shifts. For half a second you think this is it. It's not. She pulls it back up and your brain resets the clock. 0:14. Still adjusting. Hands on the neckline, pulling it down, gathering it back up. The cross necklace sits right above the edge of the top the entire time. A tiny gold reminder of modesty hanging directly over the thing you're waiting to see. The camera never shows her full face. Crop the face and she stops being a person and starts being a countdown. 17 seconds. Every other video we've broken down is under 10. This one runs long because the payoff is always "the next second." You watch 17 waiting for 18. Second 18 is the loop. She never takes it off. She never needed to. She just needed you to think she was about to.

framexin

41,040 görüntüleme • 1 ay önce

There is a room in Málaga that was built to be the closest thing on earth to standing inside heaven. It is called the camarín of the Virgin of Victory, and it is hidden at the top of a tower inside the Santuario de la Victoria. To reach it, you climb and the ascent is the entire point... The building you are climbing through was completed in 1700, and it was designed as a single argument made in stone. At the bottom lies a crypt: a black chamber crowded with white plaster skeletons, a meditation on death and the brevity of life. From there a staircase rises, and as you climb it the light grows stronger and the imagery changes from bones to saints. The architects of the time understood this ascent as the soul's own journey, the dark crypt as the stage of penitence, the staircase as the stage of spiritual progress, and the room at the very top as the final stage: the union of the soul with the divine. That room at the top is the camarín, and its dome is one of the most extraordinary interiors in Spain... Every surface is covered in white and gold plasterwork. There is no empty space anywhere. The Baroque called this horror vacui, the horror of the void: the conviction that a space meant to represent heaven should not contain a single bare patch of stone. Out of that plasterwork emerge angels, flowers, birds, and mirrors. The mirrors are not decoration alone. They catch the light pouring in through the windows of the drum and throw it around the chamber, so that the gold seems to move and the whole room appears to shimmer and breathe. This wonder was built by people who believed that if you wanted to show a human being what heaven might feel like, you did not describe it to them. You built a room, and you let them climb into it... -- -- -- If you enjoyed this, I write a weekly newsletter read by over 50,000 people who love rediscovering the beauty of the past. You can join us here: If you'd like to support my work, a paid subscription is what makes it possible.
0:13

There is a room in Málaga that was built to be the closest thing on earth to standing inside heaven. It is called the camarín of the Virgin of Victory, and it is hidden at the top of a tower inside the Santuario de la Victoria. To reach it, you climb and the ascent is the entire point... The building you are climbing through was completed in 1700, and it was designed as a single argument made in stone. At the bottom lies a crypt: a black chamber crowded with white plaster skeletons, a meditation on death and the brevity of life. From there a staircase rises, and as you climb it the light grows stronger and the imagery changes from bones to saints. The architects of the time understood this ascent as the soul's own journey, the dark crypt as the stage of penitence, the staircase as the stage of spiritual progress, and the room at the very top as the final stage: the union of the soul with the divine. That room at the top is the camarín, and its dome is one of the most extraordinary interiors in Spain... Every surface is covered in white and gold plasterwork. There is no empty space anywhere. The Baroque called this horror vacui, the horror of the void: the conviction that a space meant to represent heaven should not contain a single bare patch of stone. Out of that plasterwork emerge angels, flowers, birds, and mirrors. The mirrors are not decoration alone. They catch the light pouring in through the windows of the drum and throw it around the chamber, so that the gold seems to move and the whole room appears to shimmer and breathe. This wonder was built by people who believed that if you wanted to show a human being what heaven might feel like, you did not describe it to them. You built a room, and you let them climb into it... -- -- -- If you enjoyed this, I write a weekly newsletter read by over 50,000 people who love rediscovering the beauty of the past. You can join us here: If you'd like to support my work, a paid subscription is what makes it possible.

James Lucas

69,389 görüntüleme • 3 ay önce

sorry, they just did WHAT someone gave a machine one disease name, the leading cause of blindness in the developed world with 1.5 million americans already in its path, and it came back pointing at a drug that has sat in pharmacies for years under a different label: 551 papers read in 30 minutes against the 294 hours a human would have needed, and the loop that did it is public on GitHub most agent setups answer one question at a time, so the ceiling on the work is the quality of the question you happened to think of this one was handed a single question and wrote the second one itself. turns out that follow-up is where the real find was: a target called ABCA1, upregulated threefold, in an experiment no human ordered i read the whole paper looking for the trick, and the trick is structural. that is the second question, and it is the gap between an assistant and a factory: - hand the loop a field rather than a task: it was given a disease, and choosing the mechanism was part of its job - make it rank before it spends: 151 papers in, ten candidate mechanisms out, scored against each other before anything touched a bench - split reading from judging, so the agent that forms the theory is a different agent from the one grading it - close every cycle on physical reality: the verdict was an experiment, and another model's opinion was never allowed to stand in for one - feed each result back as the next question rather than a log line, which is the step almost nobody builds - search what already passed inspection first: the winner was an approved compound with a safety file already on record - write down what the round learned before opening the next one, so round two starts where round one stopped my read, and i think it is the uncomfortable one: reading was the entire bottleneck in that field, and everybody spent the decade optimising the writing. people ran every physical experiment here, the analysis agent needs a domain expert writing its prompts, and the authors decline to call this the leap it resembles. the thinking got replaced, and the hands did not so the question i cannot answer for my own setup: which step of your loop still stops dead until you sit down and type something bookmark this one. the four parts that turn one model into a line that runs like this, the queue, the rooms, the write permissions and the gate, are built file by file in the piece below ↓
0:15

sorry, they just did WHAT someone gave a machine one disease name, the leading cause of blindness in the developed world with 1.5 million americans already in its path, and it came back pointing at a drug that has sat in pharmacies for years under a different label: 551 papers read in 30 minutes against the 294 hours a human would have needed, and the loop that did it is public on GitHub most agent setups answer one question at a time, so the ceiling on the work is the quality of the question you happened to think of this one was handed a single question and wrote the second one itself. turns out that follow-up is where the real find was: a target called ABCA1, upregulated threefold, in an experiment no human ordered i read the whole paper looking for the trick, and the trick is structural. that is the second question, and it is the gap between an assistant and a factory: - hand the loop a field rather than a task: it was given a disease, and choosing the mechanism was part of its job - make it rank before it spends: 151 papers in, ten candidate mechanisms out, scored against each other before anything touched a bench - split reading from judging, so the agent that forms the theory is a different agent from the one grading it - close every cycle on physical reality: the verdict was an experiment, and another model's opinion was never allowed to stand in for one - feed each result back as the next question rather than a log line, which is the step almost nobody builds - search what already passed inspection first: the winner was an approved compound with a safety file already on record - write down what the round learned before opening the next one, so round two starts where round one stopped my read, and i think it is the uncomfortable one: reading was the entire bottleneck in that field, and everybody spent the decade optimising the writing. people ran every physical experiment here, the analysis agent needs a domain expert writing its prompts, and the authors decline to call this the leap it resembles. the thinking got replaced, and the hands did not so the question i cannot answer for my own setup: which step of your loop still stops dead until you sit down and type something bookmark this one. the four parts that turn one model into a line that runs like this, the queue, the rooms, the write permissions and the gate, are built file by file in the piece below ↓

Argona

32,475 görüntüleme • 1 ay önce

Stop renting a chatbot and calling it your company’s brain. Utopia is the first open-source enterprise world model I’ve seen that actually treats knowledge like a system, not a vibe. It's a Self-hosted, open source and built around the one question every other knowledge base ignores: when. Every fact in it carries a start date and an end date. Nothing gets overwritten. When something changes, the correction closes the old version and opens a new one. The history stays intact. So the graph isn't a snapshot anymore. It's a recording you can rewind. You drag a timeline on the screen and watch the whole thing redraw itself to show what was true on that date. Who owned what. What the policy said before it changed. All of it, replayable. And every fact points back to the exact sentence it came from. Nothing gets in without a receipt. Here's the part that got me. The whole thing is one binary and one Postgres database. That's it. No Elasticsearch, no separate vector service and no message queue. Most RAG stacks are six services duct-taped together. This is two. It even runs fully offline on an air-gapped network with any model you want.
0:16

Stop renting a chatbot and calling it your company’s brain. Utopia is the first open-source enterprise world model I’ve seen that actually treats knowledge like a system, not a vibe. It's a Self-hosted, open source and built around the one question every other knowledge base ignores: when. Every fact in it carries a start date and an end date. Nothing gets overwritten. When something changes, the correction closes the old version and opens a new one. The history stays intact. So the graph isn't a snapshot anymore. It's a recording you can rewind. You drag a timeline on the screen and watch the whole thing redraw itself to show what was true on that date. Who owned what. What the policy said before it changed. All of it, replayable. And every fact points back to the exact sentence it came from. Nothing gets in without a receipt. Here's the part that got me. The whole thing is one binary and one Postgres database. That's it. No Elasticsearch, no separate vector service and no message queue. Most RAG stacks are six services duct-taped together. This is two. It even runs fully offline on an air-gapped network with any model you want.

Hasan Toor

174,689 görüntüleme • 17 gün önce

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

41,985 görüntüleme • 3 gün önce

first ray tracing demo on Bend2! looks unimpressive til you realize there's no shader nor opengl buffers on EVERY frame, it: - allocates a "quadtree JSON" with 1 million objects (??) - ray-traces over it, using a Python-ish marcher - renders every pixel to the screen - collects the entire structure and it still renders at ~80 FPS on 1024x1024 with no leaks and no stop-the-world garbage collection. it just keeps going again this is not optimized in any sensible way. this is rendering 3d graphics by allocating a massive JSON on every frame and then ray tracing and consuming it whole inside the Apple M4 GPU. and somehow it works I'm soo happy I finally have time to play with my creation 🥺
0:15

first ray tracing demo on Bend2! looks unimpressive til you realize there's no shader nor opengl buffers on EVERY frame, it: - allocates a "quadtree JSON" with 1 million objects (??) - ray-traces over it, using a Python-ish marcher - renders every pixel to the screen - collects the entire structure and it still renders at ~80 FPS on 1024x1024 with no leaks and no stop-the-world garbage collection. it just keeps going again this is not optimized in any sensible way. this is rendering 3d graphics by allocating a massive JSON on every frame and then ray tracing and consuming it whole inside the Apple M4 GPU. and somehow it works I'm soo happy I finally have time to play with my creation 🥺

Taelin

60,151 görüntüleme • 10 gün önce

A 20-year-old student from China, Li Hao, built an AI speed radar with Claude alone and sold it to a city district for $317,000 He wrote the whole thing in 9 days, spending about $20 on Claude API calls He set an old camera on his balcony, pointed it at the intersection below, and let Claude watch the road Claude tags every car, motorbike and pedestrian in real time, 653 in five minutes, and flags anyone over the limit The moment a car speeds, Claude clips the video, reads the license plate, matches the owner, and emails the fine on its own A normal radar takes one photo and misses half the time. Claude records full video, so there is nothing to dispute, and the fines go out with no operator He walked into the district office with a flash drive and asked for 10 minutes. he left with a contract Every Claude config he used is in the article
0:10

A 20-year-old student from China, Li Hao, built an AI speed radar with Claude alone and sold it to a city district for $317,000 He wrote the whole thing in 9 days, spending about $20 on Claude API calls He set an old camera on his balcony, pointed it at the intersection below, and let Claude watch the road Claude tags every car, motorbike and pedestrian in real time, 653 in five minutes, and flags anyone over the limit The moment a car speeds, Claude clips the video, reads the license plate, matches the owner, and emails the fine on its own A normal radar takes one photo and misses half the time. Claude records full video, so there is nothing to dispute, and the fines go out with no operator He walked into the district office with a flash drive and asked for 10 minutes. he left with a contract Every Claude config he used is in the article

Fokki

332,797 görüntüleme • 2 ay önce

iPhone Takes a Photo of You Every 5 Seconds While you’re using your iPhone, it takes a photo of you every 5 seconds. More precisely - when you pick up or put down your iPhone, and also when it’s unlocked and sits motionless for a long time, the Face ID sensors take pictures every 5 seconds. You can see this through the infrared lens: it looks like the iPhone is taking a photo in the dark with a flash. Even if you cover the sensor, it will still keep trying to take a picture. In reality, of course, the iPhone isn’t taking photos. It scans your face to figure out whether you’re looking at it. In Face ID settings this mode is called Attention Awareness. You’re working on your iPhone, it’s charging, you get a call - and the iPhone “takes pictures” with the Face ID camera. As soon as it realizes you’re looking at it, the ringtone gets quieter. The same thing works with alarms and other notifications. This is not actually taking photos - it’s the TrueDepth infrared sensors scanning your face for the Attention Aware Features. How to turn this off on iPhone. You need to disable Attention Aware Features. Method 1 (main one): 1. Open Settings. 2. Tap Face ID & Passcode. 3. Enter your passcode. 4. Find Attention Aware Features and turn it off. Method 2 (via Accessibility): 1. Open Settings → Accessibility. 2. Tap Face ID & Attention. 3. Turn off Attention Aware Features. After that, your iPhone will stop automatically lowering the volume of calls, alarms, and notifications when you’re looking at the screen, and it won’t scan your face as actively for “attention.”
0:17

iPhone Takes a Photo of You Every 5 Seconds While you’re using your iPhone, it takes a photo of you every 5 seconds. More precisely - when you pick up or put down your iPhone, and also when it’s unlocked and sits motionless for a long time, the Face ID sensors take pictures every 5 seconds. You can see this through the infrared lens: it looks like the iPhone is taking a photo in the dark with a flash. Even if you cover the sensor, it will still keep trying to take a picture. In reality, of course, the iPhone isn’t taking photos. It scans your face to figure out whether you’re looking at it. In Face ID settings this mode is called Attention Awareness. You’re working on your iPhone, it’s charging, you get a call - and the iPhone “takes pictures” with the Face ID camera. As soon as it realizes you’re looking at it, the ringtone gets quieter. The same thing works with alarms and other notifications. This is not actually taking photos - it’s the TrueDepth infrared sensors scanning your face for the Attention Aware Features. How to turn this off on iPhone. You need to disable Attention Aware Features. Method 1 (main one): 1. Open Settings. 2. Tap Face ID & Passcode. 3. Enter your passcode. 4. Find Attention Aware Features and turn it off. Method 2 (via Accessibility): 1. Open Settings → Accessibility. 2. Tap Face ID & Attention. 3. Turn off Attention Aware Features. After that, your iPhone will stop automatically lowering the volume of calls, alarms, and notifications when you’re looking at the screen, and it won’t scan your face as actively for “attention.”

Officer's Notes

18,831 görüntüleme • 12 gün önce

She's 21. She makes $22,000 a month doing nothing, but filming her own life - the gym, the surf, the climbing, the run and letting AI do the rest. She's not a model. She doesn't sell a course. She just lives a full life on camera and every single hobby is a brand category that's desperate for content. The surf clip is a wakeboard brand's ad. The climbing gym wants the bouldering footage. The track session is an activewear drop. The smoothie after is a supplement post. She'd be doing all of it anyway. The only thing she changed was pointing the phone the right way and letting AI turn one week of her actual life into a month of content for the brands behind it. Here's the mechanism. She films her week - no script, no shoot day, just her life. AI cuts it into 20+ reels, writes every caption in each brand's voice, builds the calendar, sends the report that renews the deal. The part that used to need an editor, a writer, a strategist, and a manager is now one chat window. She kept the only thing AI can't do: actually being there, living it. Seven brands across her hobbies. ~$3,200 each. $22,000 a month - at 21, from a phone and a $40 stack of AI. Her cost doesn't move whether she has one brand or ten. That's the whole business. Everyone her age is filming the exact same life and posting it for free, calling it a personal brand. She pointed hers at the brands that pay and let the system carry the 90% that used to cost a five-person agency. This is the part that should sting: the footage was never the hard part, she'd have shot it regardless. The team around it was. And that team just collapsed into a subscription. The full playbook - niches, how to find brands, how to close them is right below. Save it before someone half your motivation reads it first👇
0:14

She's 21. She makes $22,000 a month doing nothing, but filming her own life - the gym, the surf, the climbing, the run and letting AI do the rest. She's not a model. She doesn't sell a course. She just lives a full life on camera and every single hobby is a brand category that's desperate for content. The surf clip is a wakeboard brand's ad. The climbing gym wants the bouldering footage. The track session is an activewear drop. The smoothie after is a supplement post. She'd be doing all of it anyway. The only thing she changed was pointing the phone the right way and letting AI turn one week of her actual life into a month of content for the brands behind it. Here's the mechanism. She films her week - no script, no shoot day, just her life. AI cuts it into 20+ reels, writes every caption in each brand's voice, builds the calendar, sends the report that renews the deal. The part that used to need an editor, a writer, a strategist, and a manager is now one chat window. She kept the only thing AI can't do: actually being there, living it. Seven brands across her hobbies. ~$3,200 each. $22,000 a month - at 21, from a phone and a $40 stack of AI. Her cost doesn't move whether she has one brand or ten. That's the whole business. Everyone her age is filming the exact same life and posting it for free, calling it a personal brand. She pointed hers at the brands that pay and let the system carry the 90% that used to cost a five-person agency. This is the part that should sting: the footage was never the hard part, she'd have shot it regardless. The team around it was. And that team just collapsed into a subscription. The full playbook - niches, how to find brands, how to close them is right below. Save it before someone half your motivation reads it first👇

Rich

32,535 görüntüleme • 2 ay önce

this is more useful than my entire degree Elon Musk's rocket company signed a $60,000,000,000 deal for Cursor in June, and eight days ago the two of them put a worker on sale for $200 a month: it gets its own computer in the cloud, signs into your accounts, clicks through your real apps, and hands back finished work instead of a draft for you to paste i ran one against my receipts folder on sunday and got back 14 filed, 2 it held because they needed a card number, and a saved method i never wrote myself Grok Bot is the one you train by doing your own job in front of it, and the whole handover fits in four messages tonight: 1. write out one job you did today the way you would brief a new hire: what has to be finished, which sites and files to work from, what to hand back, and where it stops and asks you 2. let it run once on something safe to get wrong, then correct the result until it is worth your name 3. say "save what we just did as a skill", and add the one rule about what always needs your approval 4. say "run that skill every weekday at 8 and post the result here. if the source is missing, tell me instead of using yesterday's numbers" xAI wrote that order into its own manual: one real job, then the saved method, then the clock. a schedule sitting on top of a method nobody checked replaces two hours of your clicking with two hours of your mistake turns out you never get to pick the brain, and that is the part i would argue about: the manual says there is no model picker for members or admins, no plan to add one, and the bill follows whichever model answered bookmark this, then open the piece below: which jobs deserve a worker of their own, and which ones quietly burn the seat ↓
0:15

this is more useful than my entire degree Elon Musk's rocket company signed a $60,000,000,000 deal for Cursor in June, and eight days ago the two of them put a worker on sale for $200 a month: it gets its own computer in the cloud, signs into your accounts, clicks through your real apps, and hands back finished work instead of a draft for you to paste i ran one against my receipts folder on sunday and got back 14 filed, 2 it held because they needed a card number, and a saved method i never wrote myself Grok Bot is the one you train by doing your own job in front of it, and the whole handover fits in four messages tonight: 1. write out one job you did today the way you would brief a new hire: what has to be finished, which sites and files to work from, what to hand back, and where it stops and asks you 2. let it run once on something safe to get wrong, then correct the result until it is worth your name 3. say "save what we just did as a skill", and add the one rule about what always needs your approval 4. say "run that skill every weekday at 8 and post the result here. if the source is missing, tell me instead of using yesterday's numbers" xAI wrote that order into its own manual: one real job, then the saved method, then the clock. a schedule sitting on top of a method nobody checked replaces two hours of your clicking with two hours of your mistake turns out you never get to pick the brain, and that is the part i would argue about: the manual says there is no model picker for members or admins, no plan to add one, and the bill follows whichever model answered bookmark this, then open the piece below: which jobs deserve a worker of their own, and which ones quietly burn the seat ↓

Argona

21,946 görüntüleme • 1 ay önce