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THIS ROBOT LAYS 1,000 BRICKS AN HOUR — A DAY'S WORK FOR A HUMAN, DONE IN UNDER 30 MINUTES. 🧱🤖 A skilled bricklayer places around 300-500 bricks in a full, exhausting day — about 40-60 an hour when things are going well. This machine does over 1,000 an hour....

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DN_DEGEN

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231,071 次观看 • 1 天前 •via X (Twitter)

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THIS ROBOT JUST MADE A $6,000 DEMOLITION CREW OBSOLETE. WITH ITS BARE HANDS. Interior demo: $400/day per worker. Three workers. Five days of dust, noise, and complaints. $6,000 — and that’s before you even rent the dumpster. Now watch the clip. A yellow-and-black humanoid stands inside an apartment, ankle-deep in rubble. It winds up and drives both arms straight through a brick wall like it’s punching through cardboard. Chunks fly. Dust fills the room. The wall cracks from floor to ceiling. And it doesn’t stop. If you’ve ever swung a sledgehammer for an hour, you know what that does to a human body. Wrists numb by lunch. Shoulders destroyed by 3 PM. Do that for 20 years and your lungs pay the price. This machine has no lungs. No hard hat. No insurance. No sick days. No “boss, I need Friday off.” One machine shows up every day and keeps swinging until the building is empty. The honest catch: the arm speed in this clip looks juiced, so half the comments are going to scream CGI. But demolition robots already exist on tracks. The missing piece was putting that capability on two legs and sending it inside a living room. You’re watching that happen right now. Ten years ago, “robots in construction” meant a machine behind a fence that you drove past on the highway. Now one is standing on someone’s broken tiles, doing the work three people used to split. Your kids might never know what swinging a sledgehammer for eight hours feels like. And honestly? They won’t miss it. Would you let this thing gut your apartment while you’re at work?
0:10

THIS ROBOT JUST MADE A $6,000 DEMOLITION CREW OBSOLETE. WITH ITS BARE HANDS. Interior demo: $400/day per worker. Three workers. Five days of dust, noise, and complaints. $6,000 — and that’s before you even rent the dumpster. Now watch the clip. A yellow-and-black humanoid stands inside an apartment, ankle-deep in rubble. It winds up and drives both arms straight through a brick wall like it’s punching through cardboard. Chunks fly. Dust fills the room. The wall cracks from floor to ceiling. And it doesn’t stop. If you’ve ever swung a sledgehammer for an hour, you know what that does to a human body. Wrists numb by lunch. Shoulders destroyed by 3 PM. Do that for 20 years and your lungs pay the price. This machine has no lungs. No hard hat. No insurance. No sick days. No “boss, I need Friday off.” One machine shows up every day and keeps swinging until the building is empty. The honest catch: the arm speed in this clip looks juiced, so half the comments are going to scream CGI. But demolition robots already exist on tracks. The missing piece was putting that capability on two legs and sending it inside a living room. You’re watching that happen right now. Ten years ago, “robots in construction” meant a machine behind a fence that you drove past on the highway. Now one is standing on someone’s broken tiles, doing the work three people used to split. Your kids might never know what swinging a sledgehammer for eight hours feels like. And honestly? They won’t miss it. Would you let this thing gut your apartment while you’re at work?

DN_DEGEN

60,102 次观看 • 23 天前

40 hours of human work. That’s what this humanoid could save every month! A construction company is already testing a Unitree G1 on a real job site, using the robot for site inspections, 360° imaging, data collection and progress monitoring. The robot starts at around $13,500, while the company says its deployment can save roughly 40 hours of work every month. That adds up to around 480 hours a year from a machine that costs a fraction of traditional industrial equipment. The interesting part is that this isn't about replacing an entire construction worker. It's about removing hundreds of repetitive hours from the workflow, including walking inspection routes, documenting progress and collecting information across the site. Humans can then spend their time on decisions and tasks that actually require them. This is where humanoid robots become economically interesting. Construction sites are already designed around human movement, so a robot with two arms, two legs and a human-sized body can potentially work in the same spaces without rebuilding the entire environment. Every additional task it learns turns those same hardware costs into more productive hours. And the economics get even more interesting as prices fall and production scales. A robot that saves 480 hours per year doesn't need to be perfect or replace a full-time employee to justify its existence. It just needs to reliably take over the boring, repetitive work that companies are already paying humans to do. 480 hours saved. Thousands of dollars in hardware. One construction site. This is how humanoids will enter the workforce, not by replacing everyone overnight, but by quietly taking over the hours nobody wants to spend.
0:11

40 hours of human work. That’s what this humanoid could save every month! A construction company is already testing a Unitree G1 on a real job site, using the robot for site inspections, 360° imaging, data collection and progress monitoring. The robot starts at around $13,500, while the company says its deployment can save roughly 40 hours of work every month. That adds up to around 480 hours a year from a machine that costs a fraction of traditional industrial equipment. The interesting part is that this isn't about replacing an entire construction worker. It's about removing hundreds of repetitive hours from the workflow, including walking inspection routes, documenting progress and collecting information across the site. Humans can then spend their time on decisions and tasks that actually require them. This is where humanoid robots become economically interesting. Construction sites are already designed around human movement, so a robot with two arms, two legs and a human-sized body can potentially work in the same spaces without rebuilding the entire environment. Every additional task it learns turns those same hardware costs into more productive hours. And the economics get even more interesting as prices fall and production scales. A robot that saves 480 hours per year doesn't need to be perfect or replace a full-time employee to justify its existence. It just needs to reliably take over the boring, repetitive work that companies are already paying humans to do. 480 hours saved. Thousands of dollars in hardware. One construction site. This is how humanoids will enter the workforce, not by replacing everyone overnight, but by quietly taking over the hours nobody wants to spend.

Future Memo

18,925 次观看 • 18 天前

"Rome wasn't built in a day, but they were laying bricks every hour." This is the case for Ouroboros Leios, a major Cardano upgrade that has been in development for more than 2 years. So far, the Leios team has delivered: - 679,138 lines of code - 3,140 GitHub commits - Around‑the‑clock work from 35+ global contributors When Leios switches on, it’s set to boost Cardano’s throughput by 30–50x, targeting roughly 100–1,000 transactions per second. This means near‑instant settlement and massive scalability without sacrificing decentralization. This simulation video isn’t sped up. It shows transactions moving across the network in real time. Years of R&D are about to make Cardano ready for global scale.
0:17

"Rome wasn't built in a day, but they were laying bricks every hour." This is the case for Ouroboros Leios, a major Cardano upgrade that has been in development for more than 2 years. So far, the Leios team has delivered: - 679,138 lines of code - 3,140 GitHub commits - Around‑the‑clock work from 35+ global contributors When Leios switches on, it’s set to boost Cardano’s throughput by 30–50x, targeting roughly 100–1,000 transactions per second. This means near‑instant settlement and massive scalability without sacrificing decentralization. This simulation video isn’t sped up. It shows transactions moving across the network in real time. Years of R&D are about to make Cardano ready for global scale.

Adastack.io

10,652 次观看 • 7 个月前

Figure 03 just finished an 8-hour work livestream, imperfect, but already good enough to replace a lot of repetitive warehouse labor. 🤖 Brett Adcock put a team of F.03 robots on a factory-style package sorting task for a full shift. The job was simple and brutal: detect the barcode, pick the package, flip it label-side down, place it on the conveyor, repeat. Soft poly bags, rigid boxes, moving belts, messy orientations. That is exactly the kind of boring physical work factories pay humans to do all day. Early in the stream, the system handled 230 packages in 10 minutes. That is roughly 2.6 seconds per item — already in human-speed territory for this narrow workflow. The more important part: it was not one robot pretending to work all day. It was a team of Figure 03 robots keeping the line running. When one robot ran low on battery, it left the station and another robot stepped in. That is the real factory signal: not just autonomy, but shift continuity. F.03 is rated for about 5 hours of runtime, so the 8-hour result depends on fleet orchestration, charging, and handoff. That matters more than a single clean demo. The stream was not perfect. There were pauses, hesitations, missed orientations, and small recovery moments. Good. A perfect short clip hides failure. An 8-hour livestream exposes the parts that actually matter: endurance, recovery, throughput, and whether the robot can stay useful after the novelty wears off. Figure says this was fully autonomous on Helix-02, with zero human intervention. For logistics and manufacturing, that is the threshold worth watching. Not “can it do one impressive task?” Can it keep doing the boring task for an entire shift? Figure is not showing a general human replacement yet. But for structured, repetitive factory work, the gap just got much smaller. The timing is also interesting: Figure says BotQ has already delivered 350+ F.03 units and reached a 1 robot/hour production cadence. And F.04 is now in full design lock, with parts starting to ship. The next test is obvious. 8 hours was the proof of endurance. 24/7 is the proof of labor economics.
0:25

Figure 03 just finished an 8-hour work livestream, imperfect, but already good enough to replace a lot of repetitive warehouse labor. 🤖 Brett Adcock put a team of F.03 robots on a factory-style package sorting task for a full shift. The job was simple and brutal: detect the barcode, pick the package, flip it label-side down, place it on the conveyor, repeat. Soft poly bags, rigid boxes, moving belts, messy orientations. That is exactly the kind of boring physical work factories pay humans to do all day. Early in the stream, the system handled 230 packages in 10 minutes. That is roughly 2.6 seconds per item — already in human-speed territory for this narrow workflow. The more important part: it was not one robot pretending to work all day. It was a team of Figure 03 robots keeping the line running. When one robot ran low on battery, it left the station and another robot stepped in. That is the real factory signal: not just autonomy, but shift continuity. F.03 is rated for about 5 hours of runtime, so the 8-hour result depends on fleet orchestration, charging, and handoff. That matters more than a single clean demo. The stream was not perfect. There were pauses, hesitations, missed orientations, and small recovery moments. Good. A perfect short clip hides failure. An 8-hour livestream exposes the parts that actually matter: endurance, recovery, throughput, and whether the robot can stay useful after the novelty wears off. Figure says this was fully autonomous on Helix-02, with zero human intervention. For logistics and manufacturing, that is the threshold worth watching. Not “can it do one impressive task?” Can it keep doing the boring task for an entire shift? Figure is not showing a general human replacement yet. But for structured, repetitive factory work, the gap just got much smaller. The timing is also interesting: Figure says BotQ has already delivered 350+ F.03 units and reached a 1 robot/hour production cadence. And F.04 is now in full design lock, with parts starting to ship. The next test is obvious. 8 hours was the proof of endurance. 24/7 is the proof of labor economics.

RoboHub🤖

16,818 次观看 • 4 个月前

The main goal of Judeomasonry is to destroy the science of polygenism, and they've almost been completely successful at it. Almost. Have you ever noticed something oomfies? That when you train your body to naturally sleep at an hour, the next day you want to sleep an hour after that? And again for the next day until the whole thing goes out of whack? The more naturally you try to adapt, the more consistent it is -- roughly a 1 hour slip each day. You're not abnormal, you've probably self-selected by reading this far. Not everyone has a 24 hour sleep cycle on this planet, even though all animals and plants have this correct circadian rhythm. A lot of us have a 25 hour sleep cycle. This fact has been buried in peer review with fake "new results", but the initial paper that verified this is perfectly valid. I am talking about the Aschoff-Wever bunker experiments that spanned 20 years and consistently turned up with the same result for the self-selecting participants: A ~25 hour sleep cycle. The moment you try to replicate this with the general public it'll smooth over a bimodal distribution. Some people have a circadian rhythm synchronised to Earth. The rest of us? We seem to be synchronised closer to Mars, which has a 24.7 hour day cycle. How can this be? I'll leave that question to you my sleepy oomfies. As for me, I bid you goodnight. 💙
0:15

The main goal of Judeomasonry is to destroy the science of polygenism, and they've almost been completely successful at it. Almost. Have you ever noticed something oomfies? That when you train your body to naturally sleep at an hour, the next day you want to sleep an hour after that? And again for the next day until the whole thing goes out of whack? The more naturally you try to adapt, the more consistent it is -- roughly a 1 hour slip each day. You're not abnormal, you've probably self-selected by reading this far. Not everyone has a 24 hour sleep cycle on this planet, even though all animals and plants have this correct circadian rhythm. A lot of us have a 25 hour sleep cycle. This fact has been buried in peer review with fake "new results", but the initial paper that verified this is perfectly valid. I am talking about the Aschoff-Wever bunker experiments that spanned 20 years and consistently turned up with the same result for the self-selecting participants: A ~25 hour sleep cycle. The moment you try to replicate this with the general public it'll smooth over a bimodal distribution. Some people have a circadian rhythm synchronised to Earth. The rest of us? We seem to be synchronised closer to Mars, which has a 24.7 hour day cycle. How can this be? I'll leave that question to you my sleepy oomfies. As for me, I bid you goodnight. 💙

Korobochka (コロボ) 🇦🇺✝️🇷🇺

34,467 次观看 • 7 个月前

We were taught the derivative as a formula to memorise. A definition to recite. A rule to apply. Something that "gives you the slope." But nobody told us what the formula was actually saying. Every symbol is a sentence. Every fraction is a question. Every limit is a story about getting closer and closer to something you can never quite touch. The top of the fraction? That's a change. A difference. A before and after. The bottom? That's how long you waited to see it. The limit? That's you, zooming in, refusing to settle for an approximation - chasing the truth all the way down to an interval so small it almost disappears. Put it all together, and you get the most honest question in calculus: How fast is something changing - right now, in this exact instant? Not on average. Not over a minute. Not eventually. Right now. That's it. That's the derivative. It's not a trick. It's not a rule. It's a beautifully precise way of asking a very human question: what's happening, in this moment? We spent years solving these. Maybe it's time we actually understood them.
0:12

We were taught the derivative as a formula to memorise. A definition to recite. A rule to apply. Something that "gives you the slope." But nobody told us what the formula was actually saying. Every symbol is a sentence. Every fraction is a question. Every limit is a story about getting closer and closer to something you can never quite touch. The top of the fraction? That's a change. A difference. A before and after. The bottom? That's how long you waited to see it. The limit? That's you, zooming in, refusing to settle for an approximation - chasing the truth all the way down to an interval so small it almost disappears. Put it all together, and you get the most honest question in calculus: How fast is something changing - right now, in this exact instant? Not on average. Not over a minute. Not eventually. Right now. That's it. That's the derivative. It's not a trick. It's not a rule. It's a beautifully precise way of asking a very human question: what's happening, in this moment? We spent years solving these. Maybe it's time we actually understood them.

The Math Flow

22,498 次观看 • 4 个月前

Beat in a photo today, ahead before and after the line made for tough watching. Slow start to the year by my standards first to admit it, we are currently in a small loss over the six weeks, people love to hate when things not going so well. I don’t tip bullshit night before prices. I don’t charge a single penny, never will. I don’t do promo or affiliate. I post one horse a day and never chase. I hope those who are praying on the LNAP downfall are there when it’s 11 winning naps in a row and 100k followers. This flat season is gonna be huge no doubt.
0:19

Beat in a photo today, ahead before and after the line made for tough watching. Slow start to the year by my standards first to admit it, we are currently in a small loss over the six weeks, people love to hate when things not going so well. I don’t tip bullshit night before prices. I don’t charge a single penny, never will. I don’t do promo or affiliate. I post one horse a day and never chase. I hope those who are praying on the LNAP downfall are there when it’s 11 winning naps in a row and 100k followers. This flat season is gonna be huge no doubt.

LNAP

12,436 次观看 • 7 个月前

THE FIRST WAVE ON THE BEACH WON’T BE HUMAN ANYMORE. Multi-legged robots don’t need the beach cleared first. That’s the entire point. Ukraine already ran the real version of this. An uncrewed boat dropped a robot on a beach. It opened fire with a remote machine gun before a single soldier landed. China’s done it too. PLA footage from October 2025 showed robot dogs paired with drones in a live amphibious landing drill near Taiwan. The real mission set: underwater beach surveys, mine detection, coastal mapping. Jobs that used to send Navy SEALs in first. This is now an official vehicle category for defense contractors — beach landings, amphibious recon, route clearance through the surf zone. The honest catch: this is mostly recon and mine-clearance, not an armed assault unit yet. Beaches used to be cleared by soldiers. Now it’s machines. Would you trust a robot to scout the beach before you land on it?
0:18

THE FIRST WAVE ON THE BEACH WON’T BE HUMAN ANYMORE. Multi-legged robots don’t need the beach cleared first. That’s the entire point. Ukraine already ran the real version of this. An uncrewed boat dropped a robot on a beach. It opened fire with a remote machine gun before a single soldier landed. China’s done it too. PLA footage from October 2025 showed robot dogs paired with drones in a live amphibious landing drill near Taiwan. The real mission set: underwater beach surveys, mine detection, coastal mapping. Jobs that used to send Navy SEALs in first. This is now an official vehicle category for defense contractors — beach landings, amphibious recon, route clearance through the surf zone. The honest catch: this is mostly recon and mine-clearance, not an armed assault unit yet. Beaches used to be cleared by soldiers. Now it’s machines. Would you trust a robot to scout the beach before you land on it?

DN_DEGEN

99,131 次观看 • 1 个月前

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
0:16

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

1,115,104 次观看 • 9 个月前

THE STREET ADDRESS ON THE BANNER IS THE ONLY REAL THING HERE A girl waits in line at a food tent, phone in hand, chatting with the cashier over the counter. Behind her: hand-lettered menu boards, a "SOLD OUT :(" sign, and a full suite number printed on the banner like it belongs to a real receipt. None of it happened - not the order, not the laugh from behind the register, not her standing at that counter. - A precise address is a harder tell than a face A generic food stand reads as generic - nobody can check it. This one prints an exact suite number nobody adds for style, only to ground a transaction that never happened inside a business that can actually be looked up. That detail either belongs to someone with no idea this exists, or points nowhere at all - and either way, it's checkable by tomorrow. A location this specific isn't an accident. It's the same choice the pipeline in the article below makes on purpose, tool by tool, until five characters feel like they were always standing somewhere real.
0:10

THE STREET ADDRESS ON THE BANNER IS THE ONLY REAL THING HERE A girl waits in line at a food tent, phone in hand, chatting with the cashier over the counter. Behind her: hand-lettered menu boards, a "SOLD OUT :(" sign, and a full suite number printed on the banner like it belongs to a real receipt. None of it happened - not the order, not the laugh from behind the register, not her standing at that counter. - A precise address is a harder tell than a face A generic food stand reads as generic - nobody can check it. This one prints an exact suite number nobody adds for style, only to ground a transaction that never happened inside a business that can actually be looked up. That detail either belongs to someone with no idea this exists, or points nowhere at all - and either way, it's checkable by tomorrow. A location this specific isn't an accident. It's the same choice the pipeline in the article below makes on purpose, tool by tool, until five characters feel like they were always standing somewhere real.

capONE 💎

1,801,613 次观看 • 21 天前

This Nvidia GPU farm sits in a spare room and prints $18,000 a month Ten cards running 24 hours a day, seven days a week. The setup cost $120,000 to build but it paid for itself in seven months. It does not mine crypto. It rents compute to AI companies that need processing power right now. Companies pay by the hour and the demand never stops. At full capacity the farm pulls $18,000 a month after electricity costs. The owner does not touch it. It just runs. Nvidia GPUs are the most in-demand piece of hardware on the planet right now. The companies that figured this out two years ago are already sitting on serious passive income. The barrier to entry is high but the people inside are not leaving. Follow if you want to understand where the real AI money is actually going.
0:11

This Nvidia GPU farm sits in a spare room and prints $18,000 a month Ten cards running 24 hours a day, seven days a week. The setup cost $120,000 to build but it paid for itself in seven months. It does not mine crypto. It rents compute to AI companies that need processing power right now. Companies pay by the hour and the demand never stops. At full capacity the farm pulls $18,000 a month after electricity costs. The owner does not touch it. It just runs. Nvidia GPUs are the most in-demand piece of hardware on the planet right now. The companies that figured this out two years ago are already sitting on serious passive income. The barrier to entry is high but the people inside are not leaving. Follow if you want to understand where the real AI money is actually going.

winkle.

22,626 次观看 • 3 个月前

I MADE MY AI AGENT 10X FASTER WITHOUT CHANGING THE MODEL not a smarter model, not a bigger context window, not another clever prompt the same kind of AI that designs vaccines for viruses we have not even met yet was spending two minutes opening the wrong files just to hand me a brief from three months ago the problem was never capability, it was the scaffolding that piled up around my agent by accident, folder by folder an agent does not think in your categories, it searches from scratch every single time, and your tidy human folders are a maze to it the fix was almost stupidly small, one index file at the root of each big folder and a few numbers in front of the folder names slowest task dropped from 2 minutes to 26 seconds, fastest ones hit 10, zero model changes capability is cheap when the scaffolding around it is broken the article breaks down the whole system in 15 minutes ↓
0:11

I MADE MY AI AGENT 10X FASTER WITHOUT CHANGING THE MODEL not a smarter model, not a bigger context window, not another clever prompt the same kind of AI that designs vaccines for viruses we have not even met yet was spending two minutes opening the wrong files just to hand me a brief from three months ago the problem was never capability, it was the scaffolding that piled up around my agent by accident, folder by folder an agent does not think in your categories, it searches from scratch every single time, and your tidy human folders are a maze to it the fix was almost stupidly small, one index file at the root of each big folder and a few numbers in front of the folder names slowest task dropped from 2 minutes to 26 seconds, fastest ones hit 10, zero model changes capability is cheap when the scaffolding around it is broken the article breaks down the whole system in 15 minutes ↓

shmidt

36,479 次观看 • 3 个月前

This work makes a humanoid robot do simple parkour moves by looking with a depth camera and choosing the right move on the fly. The big deal is that it turns lots of small human moves into long, real-time robot behavior, without hand-coding every transition or retraining for each new course. A humanoid robot is usually good at steady walking, but it often fails when it has to do fast moves like jumping up, vaulting, or rolling, and then keep going to the next obstacle. The hard part is that you cannot easily collect training data for every possible obstacle shape, distance, and mistake, so robots end up learning a few moves that only work in a narrow setup. This work starts from short clips of real human parkour moves, like stepping over, vaulting, climbing, and rolling. It uses motion matching, which is basically a smart “pick the next clip that fits best right now” search, to stitch those short clips into a long, smooth plan that looks like a human doing a whole course. Then it trains a controller with reinforcement learning (RL), which means the robot learns by trial and error to copy that plan while staying balanced and not falling. After training separate expert controllers for different moves, it compresses them into 1 controller that uses only onboard depth sensing and a simple “go this fast in this direction” command. In real tests on a Unitree G1 humanoid, it can clear multiple obstacles in a row, adapt when obstacles get moved, and climb a wall up to 1.25m.
0:05

This work makes a humanoid robot do simple parkour moves by looking with a depth camera and choosing the right move on the fly. The big deal is that it turns lots of small human moves into long, real-time robot behavior, without hand-coding every transition or retraining for each new course. A humanoid robot is usually good at steady walking, but it often fails when it has to do fast moves like jumping up, vaulting, or rolling, and then keep going to the next obstacle. The hard part is that you cannot easily collect training data for every possible obstacle shape, distance, and mistake, so robots end up learning a few moves that only work in a narrow setup. This work starts from short clips of real human parkour moves, like stepping over, vaulting, climbing, and rolling. It uses motion matching, which is basically a smart “pick the next clip that fits best right now” search, to stitch those short clips into a long, smooth plan that looks like a human doing a whole course. Then it trains a controller with reinforcement learning (RL), which means the robot learns by trial and error to copy that plan while staying balanced and not falling. After training separate expert controllers for different moves, it compresses them into 1 controller that uses only onboard depth sensing and a simple “go this fast in this direction” command. In real tests on a Unitree G1 humanoid, it can clear multiple obstacles in a row, adapt when obstacles get moved, and climb a wall up to 1.25m.

Rohan Paul

37,121 次观看 • 7 个月前

⚠️ FRAMERS, THAT HOUSE YOU'RE BUILDING BY HAND IS BEING BUILT BY A ROBOT CREW SOMEWHERE ELSE RIGHT NOW A dozen Tesla Optimus units just framed an entire house from the foundation up, no scaffolding crew, no framing contractor, nobody standing around waiting on materials. Framing is one of the hardest jobs on a site. You're balancing on trusses, reading blueprints on the fly, and timing every cut so the whole structure lines up by the time the roof goes on. It's the kind of work people spend years getting good at. Now watch what's happening in the footage. The robots are climbing the frame, setting studs, running the roof trusses, and doing it as a full crew, the way an actual framing team would, except none of them stop for lunch and none of them call in hurt. Nobody expected robots to learn a full trade before they learned to walk normally. They're already building the house. If you still think construction is years away from automation, the frame is already up.
0:15

⚠️ FRAMERS, THAT HOUSE YOU'RE BUILDING BY HAND IS BEING BUILT BY A ROBOT CREW SOMEWHERE ELSE RIGHT NOW A dozen Tesla Optimus units just framed an entire house from the foundation up, no scaffolding crew, no framing contractor, nobody standing around waiting on materials. Framing is one of the hardest jobs on a site. You're balancing on trusses, reading blueprints on the fly, and timing every cut so the whole structure lines up by the time the roof goes on. It's the kind of work people spend years getting good at. Now watch what's happening in the footage. The robots are climbing the frame, setting studs, running the roof trusses, and doing it as a full crew, the way an actual framing team would, except none of them stop for lunch and none of them call in hurt. Nobody expected robots to learn a full trade before they learned to walk normally. They're already building the house. If you still think construction is years away from automation, the frame is already up.

V0LYX

365,499 次观看 • 1 个月前

How to make near-unfair progress in the gym: - 4 to 6 reps, heavy, to failure or one off it - Add weight before you add anything else - Same handful of lifts, week after week, going up - Rest three minutes so the next set is actually hard - Chase the number in the logbook, never the pump - Five lifts, out in under an hour - Two proper rest days a week, minimum - Hit each muscle two or three times over the week, not once into the ground - Eat the animal, especially the fat - Get your protein up and your fussiness down - Sleep like it is part of the programme, because it is Do this and you'll be the person others quietly wonder about in a year. Boringly simple, and almost nobody has the patience to be this unimpressive for long enough.
0:17

How to make near-unfair progress in the gym: - 4 to 6 reps, heavy, to failure or one off it - Add weight before you add anything else - Same handful of lifts, week after week, going up - Rest three minutes so the next set is actually hard - Chase the number in the logbook, never the pump - Five lifts, out in under an hour - Two proper rest days a week, minimum - Hit each muscle two or three times over the week, not once into the ground - Eat the animal, especially the fat - Get your protein up and your fussiness down - Sleep like it is part of the programme, because it is Do this and you'll be the person others quietly wonder about in a year. Boringly simple, and almost nobody has the patience to be this unimpressive for long enough.

Sama Hoole

102,165 次观看 • 2 个月前

The #1 trader on Polymarket isn't even human - it's a bot sitting on $23.6M. And a real person just declared war on it. swisstony built that $23.6M all-time off 203,391 predictions. No human clicks that many bets. It's a machine, running around the clock, parked at the top of the leaderboard. Now a real guy is coming for the crown. Djdjdjekekek - joined in June, already $5.9M, from zero to that in 8 weeks - fired a public shot: "Swisstony been camping top-1 for a lil too long. Keep an eye on my next bet, lil bro." Man vs machine, live on the leaderboard. The bot never sleeps and never tilts. The human has to actually read the board and size up with nerve. The throne's been quiet for a while. For the first time, it actually looks contested.
0:18

The #1 trader on Polymarket isn't even human - it's a bot sitting on $23.6M. And a real person just declared war on it. swisstony built that $23.6M all-time off 203,391 predictions. No human clicks that many bets. It's a machine, running around the clock, parked at the top of the leaderboard. Now a real guy is coming for the crown. Djdjdjekekek - joined in June, already $5.9M, from zero to that in 8 weeks - fired a public shot: "Swisstony been camping top-1 for a lil too long. Keep an eye on my next bet, lil bro." Man vs machine, live on the leaderboard. The bot never sleeps and never tilts. The human has to actually read the board and size up with nerve. The throne's been quiet for a while. For the first time, it actually looks contested.

Polykinder

12,193 次观看 • 1 个月前

This is the view from Hindukush heights in Chitral. Graced by the likes of Diana, Robert de Niro and countless polo champions. The hotel looks over a beautiful valley, but also the chitral airport. Which costs the government of KPK eight million a rupees to keep functional every month. Flights from islamabad to here would take one hour. The airport used to have five flights a day from across the country. Then it had one a day. Then it had a flight a week. For the past three years there are no flights because PIA doesn’t have the money for proper small aircraft. So it takes a 12 hour bus journey across mountain roads to get here.
0:12

This is the view from Hindukush heights in Chitral. Graced by the likes of Diana, Robert de Niro and countless polo champions. The hotel looks over a beautiful valley, but also the chitral airport. Which costs the government of KPK eight million a rupees to keep functional every month. Flights from islamabad to here would take one hour. The airport used to have five flights a day from across the country. Then it had one a day. Then it had a flight a week. For the past three years there are no flights because PIA doesn’t have the money for proper small aircraft. So it takes a 12 hour bus journey across mountain roads to get here.

Abdul Moiz Jaferii

30,673 次观看 • 5 个月前

⚠️ THIS IS THE LAST GENERATION OF HUMAN LINE COOKS Optimus switched on chef mode in a real restaurant kitchen and did something no one wants to admit out loud: – ran a full wok station without a single mistake – plated faster than your best sous chef on a slammed Friday – never got tired, never called in sick, never asked for a raise That decade you spent learning knife skills, timing, plating under pressure? It just watched you do it once and copied it perfectly. While chefs keep telling themselves "AI will never understand flavor, passion, creativity"... the robot is already standing at the stove, running the line, and it doesn't need to sleep between shifts. This isn't years away. It's already in the kitchen. The only question left is whether it's in yours yet.
0:15

⚠️ THIS IS THE LAST GENERATION OF HUMAN LINE COOKS Optimus switched on chef mode in a real restaurant kitchen and did something no one wants to admit out loud: – ran a full wok station without a single mistake – plated faster than your best sous chef on a slammed Friday – never got tired, never called in sick, never asked for a raise That decade you spent learning knife skills, timing, plating under pressure? It just watched you do it once and copied it perfectly. While chefs keep telling themselves "AI will never understand flavor, passion, creativity"... the robot is already standing at the stove, running the line, and it doesn't need to sleep between shifts. This isn't years away. It's already in the kitchen. The only question left is whether it's in yours yet.

Shredder

110,513 次观看 • 2 个月前

So, by now I'm sure you saw the AI fanart recreation of the Princess Mononoke trailer. It got a LOT of feedback, mostly from people telling the creator what a terrible thing he did and how AI assisted workflows can never be used for anything good or meaningful and most of all that it can never be used for art. That's such nonsense. Of course it can. If it's wielded by artists and great storytellers, great things will come of it. If you hand a violin to someone on the street they'll be able to make it make sounds.. if you hand it to a talented musician it becomes a conveyer of thoughts, emotion and art. Here's a small scene from Mononoke that I did an AI take on.. it's far from perfect and to animate this properly would require much more work. The AI workflows we have today are lacking so many control elements. But to think those things won't come.. come on. Of course they will. But most importantly, in a way where they don't overtake the art completely, but instead acts like an "amplifier" of the artists using the tools. This technology will be in most of our creative tools in the very near future with full controllability. Oh and I never liked the idea of turning old disney classics into live-action films, or doing the same with the beautiful work of Studio Ghibli. But for the purpose of this post I hope you'll forgive me ;-) #art #animation
0:10

So, by now I'm sure you saw the AI fanart recreation of the Princess Mononoke trailer. It got a LOT of feedback, mostly from people telling the creator what a terrible thing he did and how AI assisted workflows can never be used for anything good or meaningful and most of all that it can never be used for art. That's such nonsense. Of course it can. If it's wielded by artists and great storytellers, great things will come of it. If you hand a violin to someone on the street they'll be able to make it make sounds.. if you hand it to a talented musician it becomes a conveyer of thoughts, emotion and art. Here's a small scene from Mononoke that I did an AI take on.. it's far from perfect and to animate this properly would require much more work. The AI workflows we have today are lacking so many control elements. But to think those things won't come.. come on. Of course they will. But most importantly, in a way where they don't overtake the art completely, but instead acts like an "amplifier" of the artists using the tools. This technology will be in most of our creative tools in the very near future with full controllability. Oh and I never liked the idea of turning old disney classics into live-action films, or doing the same with the beautiful work of Studio Ghibli. But for the purpose of this post I hope you'll forgive me ;-) #art #animation

Martin Nebelong

18,377 次观看 • 2 年前