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Before the half marathon even starts, these robots already went through a full obstacle test in Beijing today. 🤖 The April 18 Warrior Challenge wasn’t about speed. It was a structured test of real-world capability under defined rules. The event was split into four categories: general obstacles, humanoid-only events,...

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RoboHub🤖

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21,311 次观看 • 4 个月前 •via X (Twitter)

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TienKung Ultra finished the full 21.0975 km in 1:15:00 — fully autonomous, zero human intervention. 🤖 No repeat win this time. But it was easily one of the most striking robots on the course — clean gait, stable motion, and the most human-like running form out there. It took home the “Best Design” award, and that actually says more than the podium this time. Because this isn’t a marathon-only build. TienKung Ultra is a general-purpose humanoid, already moving toward real-world deployment. And it didn’t show up alone. Teams from Peking University, Fudan, HUST, BIT, Beihang, HKUST(GZ), TUM and more were all building on the same TienKung platform. That’s what an open ecosystem looks like — shared hardware, shared stack, different solutions on top. And just a day before, it took the Robot Warrior Challenge — fully autonomous through obstacle tasks modeled on real-world rescue and hazardous operations. That’s the part that matters. This is no longer just about speed. It’s about autonomy — and whether these systems can actually handle real environments. That’s what future winners are going to look like.
0:38

TienKung Ultra finished the full 21.0975 km in 1:15:00 — fully autonomous, zero human intervention. 🤖 No repeat win this time. But it was easily one of the most striking robots on the course — clean gait, stable motion, and the most human-like running form out there. It took home the “Best Design” award, and that actually says more than the podium this time. Because this isn’t a marathon-only build. TienKung Ultra is a general-purpose humanoid, already moving toward real-world deployment. And it didn’t show up alone. Teams from Peking University, Fudan, HUST, BIT, Beihang, HKUST(GZ), TUM and more were all building on the same TienKung platform. That’s what an open ecosystem looks like — shared hardware, shared stack, different solutions on top. And just a day before, it took the Robot Warrior Challenge — fully autonomous through obstacle tasks modeled on real-world rescue and hazardous operations. That’s the part that matters. This is no longer just about speed. It’s about autonomy — and whether these systems can actually handle real environments. That’s what future winners are going to look like.

RoboHub🤖

224,991 次观看 • 4 个月前

Sub-1 hour? Chasing the human half-marathon record? That’s suddenly the conversation around Beijing’s humanoid robot race this Sunday. 🏃‍♂️🤖 A year ago, this event was mostly about finishing. Now the bar is speed, stability, and full-course autonomy. More than 100 teams and 300+ humanoid robots are expected on the line, and nearly 40% of them are entering the autonomous navigation group instead of relying on remote control. The course is not getting easier either. Same 21.0975 km, but with more urban slopes, rolling sections, and park terrain built to expose weak points in control, perception, and endurance. That is what makes this race worth watching. If some of these machines really get close to one hour, the story is no longer “robots can run.” It becomes “humanoids are starting to hold speed, balance, and navigation together over real distance.” And that matters far beyond a race course. This is one of the clearest public tests yet for where humanoid robotics actually stands in hardware, motion control, power systems, and autonomous mobility. Sunday’s headline will be the time. The bigger takeaway will be how much of that pace is still there at kilometer 15, 18, and 21. I want to see who is actually fast, who is truly autonomous, and who can finish without falling apart. That is where the real signal will be.
2:50

Sub-1 hour? Chasing the human half-marathon record? That’s suddenly the conversation around Beijing’s humanoid robot race this Sunday. 🏃‍♂️🤖 A year ago, this event was mostly about finishing. Now the bar is speed, stability, and full-course autonomy. More than 100 teams and 300+ humanoid robots are expected on the line, and nearly 40% of them are entering the autonomous navigation group instead of relying on remote control. The course is not getting easier either. Same 21.0975 km, but with more urban slopes, rolling sections, and park terrain built to expose weak points in control, perception, and endurance. That is what makes this race worth watching. If some of these machines really get close to one hour, the story is no longer “robots can run.” It becomes “humanoids are starting to hold speed, balance, and navigation together over real distance.” And that matters far beyond a race course. This is one of the clearest public tests yet for where humanoid robotics actually stands in hardware, motion control, power systems, and autonomous mobility. Sunday’s headline will be the time. The bigger takeaway will be how much of that pace is still there at kilometer 15, 18, and 21. I want to see who is actually fast, who is truly autonomous, and who can finish without falling apart. That is where the real signal will be.

RoboHub🤖

209,946 次观看 • 4 个月前

Beijing E-Town Humanoid Robot Half-Marathon is tomorrow, April 19, 2026. - Bipedal only - “We are not a car!” - Over 300 humanoid robots from 76+ teams (nearly 5× last year) - ~40% will run fully autonomous - Height limit: 2 ft 6 in – 5 ft 11 in Key Rules - 20% penalty added to finish time (×1.2), if not autonomous - Time penalties for battery swaps or full robot replacements The event runs on the same 21.1 km (13.1 miles) course as the human half-marathon, with humans and robots separated by barriers. Gimpse of practice runs:
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Beijing E-Town Humanoid Robot Half-Marathon is tomorrow, April 19, 2026. - Bipedal only - “We are not a car!” - Over 300 humanoid robots from 76+ teams (nearly 5× last year) - ~40% will run fully autonomous - Height limit: 2 ft 6 in – 5 ft 11 in Key Rules - 20% penalty added to finish time (×1.2), if not autonomous - Time penalties for battery swaps or full robot replacements The event runs on the same 21.1 km (13.1 miles) course as the human half-marathon, with humans and robots separated by barriers. Gimpse of practice runs:

The Humanoid Hub

67,952 次观看 • 4 个月前

Every Prufrock that leaves the factory has over 1,000 changes from the one before it. Before it ships, we put it through a full Porpoise Test (PT) in Bastrop — a short test tunnel (typically under 200 rings) that lets both the design team and the test team gather real data on the new designs and on the specific Prufrock serial number. To date, we’ve completed six of these tests and Prufrock 5 is currently 200 rings into PT7. Once complete, the tunnels are put to use: • PT4 is now a vacuum tunnel for Hyperloop testing • PT5 is a live test bench for liner trucks and new belt systems • PT6 is a pedestrian tunnel connecting SpaceX to Hyperloop Plaza With porpoise testing, our engineers get to get hands on and stress-test every one of their designs in real world environments without ever leaving Bastrop. We are currently hiring Electrical, Mechanical, Test, and Software engineers. Link to apply in the comments below 👇
0:32

Every Prufrock that leaves the factory has over 1,000 changes from the one before it. Before it ships, we put it through a full Porpoise Test (PT) in Bastrop — a short test tunnel (typically under 200 rings) that lets both the design team and the test team gather real data on the new designs and on the specific Prufrock serial number. To date, we’ve completed six of these tests and Prufrock 5 is currently 200 rings into PT7. Once complete, the tunnels are put to use: • PT4 is now a vacuum tunnel for Hyperloop testing • PT5 is a live test bench for liner trucks and new belt systems • PT6 is a pedestrian tunnel connecting SpaceX to Hyperloop Plaza With porpoise testing, our engineers get to get hands on and stress-test every one of their designs in real world environments without ever leaving Bastrop. We are currently hiring Electrical, Mechanical, Test, and Software engineers. Link to apply in the comments below 👇

Mike Baier

82,748 次观看 • 22 天前

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 • 3 个月前

So cool...a humanoid just drove a go-kart for real. A Unitree G1 lowers itself into the tight cockpit, hands on the wheel, feet on the pedals, then runs the track， even drifts. It shows constrained whole-body loco-manipulation, mobile pick-and-place, and hand-eye-foot coordination in one sequence. This comes from China’s Symbiosis Robotics and their Direct Perception Control (DPC) model. It skips the usual high-level goals + tracker stack, mapping vision, language, body state and feedback straight to joint and hand targets. The focus is whole-body coordination for loco-manipulation. Interestingly, data diversity...Training used 15,010 hours of joint-aligned data-- 6,781h human egocentric, 4,024h armed robots, 3,660h wheeled humanoids, 545h bipedal. Teleop, head-mounted and egocentric sources were all converted into time-aligned joint trajectories across embodiments. A clean test that packs perception, balance and continuous whole-body control into one task chain ,and leaves room for other real-world scenarios.
1:17

So cool...a humanoid just drove a go-kart for real. A Unitree G1 lowers itself into the tight cockpit, hands on the wheel, feet on the pedals, then runs the track， even drifts. It shows constrained whole-body loco-manipulation, mobile pick-and-place, and hand-eye-foot coordination in one sequence. This comes from China’s Symbiosis Robotics and their Direct Perception Control (DPC) model. It skips the usual high-level goals + tracker stack, mapping vision, language, body state and feedback straight to joint and hand targets. The focus is whole-body coordination for loco-manipulation. Interestingly, data diversity...Training used 15,010 hours of joint-aligned data-- 6,781h human egocentric, 4,024h armed robots, 3,660h wheeled humanoids, 545h bipedal. Teleop, head-mounted and egocentric sources were all converted into time-aligned joint trajectories across embodiments. A clean test that packs perception, balance and continuous whole-body control into one task chain ,and leaves room for other real-world scenarios.

CyberRobo

75,626 次观看 • 10 天前

Beijing hosts world’s first humanoid robot games | Ariana News The world’s inaugural humanoid robot competition is underway in Beijing, drawing more than 500 robots from 280 teams across 16 countries to compete in a uniquely futuristic sporting spectacle. The three-day event, held at the National Speed Skating Oval—once the “Ice Ribbon” of the 2022 Winter Olympics—kicked off on August 15 and runs through to Sunday August 17. The tournament features 26 events spread across athletic, performance, and scenario-based categories. Athletic challenges include sprinting, soccer, and kickboxing, while performance segments showcase robot dance routines and musical instrument displays. Real-world scenarios, such as medication sorting, cleaning tasks, and industrial material handling, are also on the agenda to test practical functionality. Organizers meanwhile emphasize the event’s role in accelerating the integration of humanoid robots into everyday life, from manufacturing and hospitality to healthcare. One Chinese official summed it up: “Every robot that participates is creating history.” The competition has yielded both triumphant strides and technical stumbling blocks. In running events, the robot H1 from Unitree Robotics claimed top honors in the 1,500-meter race, demonstrating promising agility. Yet, many robots struggled with balance, coordination, and task execution, including some collapsing mid-sprint or requiring human help to stand—underscoring the still-developing nature of embodied artificial intelligence.
1:19

Beijing hosts world’s first humanoid robot games | Ariana News The world’s inaugural humanoid robot competition is underway in Beijing, drawing more than 500 robots from 280 teams across 16 countries to compete in a uniquely futuristic sporting spectacle. The three-day event, held at the National Speed Skating Oval—once the “Ice Ribbon” of the 2022 Winter Olympics—kicked off on August 15 and runs through to Sunday August 17. The tournament features 26 events spread across athletic, performance, and scenario-based categories. Athletic challenges include sprinting, soccer, and kickboxing, while performance segments showcase robot dance routines and musical instrument displays. Real-world scenarios, such as medication sorting, cleaning tasks, and industrial material handling, are also on the agenda to test practical functionality. Organizers meanwhile emphasize the event’s role in accelerating the integration of humanoid robots into everyday life, from manufacturing and hospitality to healthcare. One Chinese official summed it up: “Every robot that participates is creating history.” The competition has yielded both triumphant strides and technical stumbling blocks. In running events, the robot H1 from Unitree Robotics claimed top honors in the 1,500-meter race, demonstrating promising agility. Yet, many robots struggled with balance, coordination, and task execution, including some collapsing mid-sprint or requiring human help to stand—underscoring the still-developing nature of embodied artificial intelligence.

Owen Gregorian

43,158 次观看 • 1 年前

⚠️ THE ROBOT DIDN’T ENTER A ROBOT TESTING LAB. IT ENTERED A CITY. A humanoid robot is moving through a real urban environment with pedestrians, traffic and constantly changing space around it. There’s no empty runway and no perfectly controlled path - the machine has to keep moving while the world around it does whatever it wants. That makes a few seconds of walking far more interesting than another polished stage demo. A city is one of the hardest places to test a humanoid because nothing stays predictable for long. People stop, cars move, distances change and obstacles appear without warning, while the robot still has to maintain balance and choose where to step next. The challenge isn't simply walking anymore - it's understanding how to move through a world that wasn't designed for robots. And that's the real milestone here. Humanoids don't need to look perfectly human to change the world; they need to become capable of functioning in spaces already built for us. The closer they get to doing that reliably, the less important the laboratory demos become. The future won't feel futuristic because robots look human. It will feel futuristic when robots can move through our world like they belong there.
0:23

⚠️ THE ROBOT DIDN’T ENTER A ROBOT TESTING LAB. IT ENTERED A CITY. A humanoid robot is moving through a real urban environment with pedestrians, traffic and constantly changing space around it. There’s no empty runway and no perfectly controlled path - the machine has to keep moving while the world around it does whatever it wants. That makes a few seconds of walking far more interesting than another polished stage demo. A city is one of the hardest places to test a humanoid because nothing stays predictable for long. People stop, cars move, distances change and obstacles appear without warning, while the robot still has to maintain balance and choose where to step next. The challenge isn't simply walking anymore - it's understanding how to move through a world that wasn't designed for robots. And that's the real milestone here. Humanoids don't need to look perfectly human to change the world; they need to become capable of functioning in spaces already built for us. The closer they get to doing that reliably, the less important the laboratory demos become. The future won't feel futuristic because robots look human. It will feel futuristic when robots can move through our world like they belong there.

Future Memo

10,138 次观看 • 13 天前

This situation has been building for the past year and a half. The Flight Duty Time Limitation (FDTL) regulations issued by the DGCA were first notified in January 2024 (or March 2024). Airlines had more than enough time to adapt to these guidelines, and we believe they are important. But what was the DGCA doing all this time, given that it was responsible for enforcing the rules and ensuring that airlines complied over the last two years? These are its own guidelines, and it knew that a major airline—practically a monopoly/duopoly in the country—was not prepared. What was the Ministry doing, fully aware that this crisis was inevitable? It is not as if they were unaware. Yet the entire country was pushed into chaos, and all of this happened at a time when the President of Russia was visiting India. On one hand, they showcase Viksit Bharat; on the other, this is the reality unfolding before the world. : Sasikanth Senthil ji
2:38

This situation has been building for the past year and a half. The Flight Duty Time Limitation (FDTL) regulations issued by the DGCA were first notified in January 2024 (or March 2024). Airlines had more than enough time to adapt to these guidelines, and we believe they are important. But what was the DGCA doing all this time, given that it was responsible for enforcing the rules and ensuring that airlines complied over the last two years? These are its own guidelines, and it knew that a major airline—practically a monopoly/duopoly in the country—was not prepared. What was the Ministry doing, fully aware that this crisis was inevitable? It is not as if they were unaware. Yet the entire country was pushed into chaos, and all of this happened at a time when the President of Russia was visiting India. On one hand, they showcase Viksit Bharat; on the other, this is the reality unfolding before the world. : Sasikanth Senthil ji

Congress

11,126 次观看 • 8 个月前

Ran 21 km (13.1 miles) — and the motor was still cold. That’s the detail that matters. 🤖 Honor was the clear dark horse in this year’s robot half marathon. They swept 1st, 2nd, and 3rd, and also posted a strong top-6 finish overall. What stands out to me is that this was not just about bigger motors, or a gait tuned for long-distance running. They seem to have solved something more important — cooling. In a post-race interview, Honor engineers said the robot used liquid-cooling tech adapted from Honor smartphones, with cooling lines running deep into the motor system to carry heat away. Some reports added more detail: the setup used two high-speed micro pumps, with flow rates reaching up to 6 liters per minute, giving the system enough cooling capacity to handle sustained lower-joint motor load. That matters because once a robot starts overheating, output drops, stability goes with it, and the whole run can fall apart fast. And that’s exactly why this detail is interesting. Of course, that does not mean Honor has already surpassed teams like TienKung or Unitree across humanoid robotics as a whole. What it does suggest is that for the marathon task, they built a very strong system solution. And honestly, that alone is already a useful case for the industry. The bigger trend is moving fast. Last year, TienKung won in around 2 hours 40 minutes. This year, the winning time dropped to 50 minutes 26 seconds. Last year, most robots were still fully remote-controlled or only semi-autonomous. This year, around 40% were running with a much higher level of autonomy. So to me, the real signal is not just that robots got faster. It’s that the field is now moving past raw speed, and into the harder problems: autonomy, stability, and system reliability under load. If the pace of progress stays anywhere close to this, then next year’s race should be even more worth watching.
0:31

Ran 21 km (13.1 miles) — and the motor was still cold. That’s the detail that matters. 🤖 Honor was the clear dark horse in this year’s robot half marathon. They swept 1st, 2nd, and 3rd, and also posted a strong top-6 finish overall. What stands out to me is that this was not just about bigger motors, or a gait tuned for long-distance running. They seem to have solved something more important — cooling. In a post-race interview, Honor engineers said the robot used liquid-cooling tech adapted from Honor smartphones, with cooling lines running deep into the motor system to carry heat away. Some reports added more detail: the setup used two high-speed micro pumps, with flow rates reaching up to 6 liters per minute, giving the system enough cooling capacity to handle sustained lower-joint motor load. That matters because once a robot starts overheating, output drops, stability goes with it, and the whole run can fall apart fast. And that’s exactly why this detail is interesting. Of course, that does not mean Honor has already surpassed teams like TienKung or Unitree across humanoid robotics as a whole. What it does suggest is that for the marathon task, they built a very strong system solution. And honestly, that alone is already a useful case for the industry. The bigger trend is moving fast. Last year, TienKung won in around 2 hours 40 minutes. This year, the winning time dropped to 50 minutes 26 seconds. Last year, most robots were still fully remote-controlled or only semi-autonomous. This year, around 40% were running with a much higher level of autonomy. So to me, the real signal is not just that robots got faster. It’s that the field is now moving past raw speed, and into the harder problems: autonomy, stability, and system reliability under load. If the pace of progress stays anywhere close to this, then next year’s race should be even more worth watching.

RoboHub🤖

60,151 次观看 • 4 个月前

Kaito's leaderboard was published on September 12, 2025. I've been creating content for Sentient since June, well before that. And it seems TGE will happen within the next month, provided general market conditions are favorable. The project foundations were laid in 2024, and they raised a significant investment of $85 million. These funds were used to develop open AGI. In the first half of the year, research focused on model security, post training, agentic safety, and benchmarking. Custom benchmarks, including fair coding, cryptographic values, and governance features, were developed. Work was also done on AI agent vulnerabilities and context manipulation attacks. Between July and September, GRID was launched, and the ROMA Framework, an open source framework, was released. In September, Kaito integration was implemented, and Dobby, the world's first fingerprint based AI model, was used by over 700,000 people. Many community events and AMAs were held in October and November. In December, the SERA Crypto launch and .agent domains were released. All these developments and more were accomplished within a year thanks to the hard work of the Sentient team, and they are still building. We will be hearing a lot about Artificial General Intelligence projects in 2026, and Sentient will likely be one of the most talked about.
0:32

Kaito's leaderboard was published on September 12, 2025. I've been creating content for Sentient since June, well before that. And it seems TGE will happen within the next month, provided general market conditions are favorable. The project foundations were laid in 2024, and they raised a significant investment of $85 million. These funds were used to develop open AGI. In the first half of the year, research focused on model security, post training, agentic safety, and benchmarking. Custom benchmarks, including fair coding, cryptographic values, and governance features, were developed. Work was also done on AI agent vulnerabilities and context manipulation attacks. Between July and September, GRID was launched, and the ROMA Framework, an open source framework, was released. In September, Kaito integration was implemented, and Dobby, the world's first fingerprint based AI model, was used by over 700,000 people. Many community events and AMAs were held in October and November. In December, the SERA Crypto launch and .agent domains were released. All these developments and more were accomplished within a year thanks to the hard work of the Sentient team, and they are still building. We will be hearing a lot about Artificial General Intelligence projects in 2026, and Sentient will likely be one of the most talked about.

mufettis 🐋

11,750 次观看 • 8 个月前

i watched gemma 4 12b build something genuinely impressive today, and then loop itself to death right in front of me. the full run is in the video, sped up but completely uncut, watch it to the end and you will catch the exact moment it stops building and starts looping right in the middle of the work. the task was clean, build a single file gravity simulator, n-body physics, orbits, collisions, running locally on one 3090 through an agent. and for ten minutes it was a joy to watch. it reached for a symplectic integrator on its own, the correct one, the kind that keeps orbits stable instead of spiralling out. real gravity with softening, proper orbital velocities, momentum conserved on collision. the physics was right. the thing actually worked. then on the very last step, writing a few tests to prove its own code, it fell into a loop. not a crash, a loop. it started repeating itself and would not stop. ten more minutes, thirty four thousand tokens into a single answer, the same fragments over and over, until i killed it myself. so it's not that gemma can't code. it did the hard part beautifully. it cannot finish. it cannot hold a long task together without unravelling, and finishing is the entire job in agentic work. here's the part that stings. i run this exact task, same harness, same card, on the chinese open models, qwen especially, and i never see this. they build it, they test it, they stop. every single time. google has the raw capability, you can see it sitting right there in the code, and then the model loops itself to death on a task a 27b from alibaba finishes clean. open weights, apache 2.0, so much to love on paper. i just need it to know when to stop talking.
4:15

i watched gemma 4 12b build something genuinely impressive today, and then loop itself to death right in front of me. the full run is in the video, sped up but completely uncut, watch it to the end and you will catch the exact moment it stops building and starts looping right in the middle of the work. the task was clean, build a single file gravity simulator, n-body physics, orbits, collisions, running locally on one 3090 through an agent. and for ten minutes it was a joy to watch. it reached for a symplectic integrator on its own, the correct one, the kind that keeps orbits stable instead of spiralling out. real gravity with softening, proper orbital velocities, momentum conserved on collision. the physics was right. the thing actually worked. then on the very last step, writing a few tests to prove its own code, it fell into a loop. not a crash, a loop. it started repeating itself and would not stop. ten more minutes, thirty four thousand tokens into a single answer, the same fragments over and over, until i killed it myself. so it's not that gemma can't code. it did the hard part beautifully. it cannot finish. it cannot hold a long task together without unravelling, and finishing is the entire job in agentic work. here's the part that stings. i run this exact task, same harness, same card, on the chinese open models, qwen especially, and i never see this. they build it, they test it, they stop. every single time. google has the raw capability, you can see it sitting right there in the code, and then the model loops itself to death on a task a 27b from alibaba finishes clean. open weights, apache 2.0, so much to love on paper. i just need it to know when to stop talking.

Sudo su

39,719 次观看 • 2 个月前

Yesterday, I completed the Tata Mumbai Half Marathon, and it was an incredible experience! Initially, after the October Ironman, I had planned to do a full marathon, but due to a busy schedule the last two months and not being able to train as much, I decided to go for the half marathon instead. The race was challenging, especially with the iconic Peddar Road climb, which really tested my stamina due to the elevation. The last 5k was particularly testing, but just when I thought I was slowing down, Coach Pramod Deshpande of JJ appeared out of nowhere and gave me the motivation I needed to finish strong. His timely support made all the difference! I completed the race at 2.16 hrs. Mumbai’s weather added another layer of difficulty. The humidity was intense, making each step feel heavier, but it also reminded me the importance of mental resilience in endurance sports. Pushing through that discomfort is what running – and life – is all about. I’m happy that I’ve improved my PR by 20 minutes compared to Bangalore Marathon. My next target is a sub-2 half marathon, and I’m already excited for the challenge! To the youth out there: physical fitness isn’t just about looking good; it’s about building mental strength, resilience, and discipline. Whether it’s running, cycling, or any other sport, the habits you form today lay the foundation for a stronger tomorrow. Let’s embrace fitness, set ambitious goals, and show ourselves what we’re truly capable of! Keep pushing, and never let any challenge stop you from chasing your dreams. Appreciate Procam International MD Sri Vivek Singh and his team for organising this truly world-class event. Gratitude to Maharashtra CM Devendra Fadnavis Ji and his team for all the support. Thanks to Prime Minister Narendra Modi’s emphasis on the #FitIndia movement more government support is accorded to events and initiatives like this which go long way in preventive healthcare in a young country like India. Congratulations to all the 60,000+ runners who participated yesterday!
1:48

Yesterday, I completed the Tata Mumbai Half Marathon, and it was an incredible experience! Initially, after the October Ironman, I had planned to do a full marathon, but due to a busy schedule the last two months and not being able to train as much, I decided to go for the half marathon instead. The race was challenging, especially with the iconic Peddar Road climb, which really tested my stamina due to the elevation. The last 5k was particularly testing, but just when I thought I was slowing down, Coach Pramod Deshpande of JJ appeared out of nowhere and gave me the motivation I needed to finish strong. His timely support made all the difference! I completed the race at 2.16 hrs. Mumbai’s weather added another layer of difficulty. The humidity was intense, making each step feel heavier, but it also reminded me the importance of mental resilience in endurance sports. Pushing through that discomfort is what running – and life – is all about. I’m happy that I’ve improved my PR by 20 minutes compared to Bangalore Marathon. My next target is a sub-2 half marathon, and I’m already excited for the challenge! To the youth out there: physical fitness isn’t just about looking good; it’s about building mental strength, resilience, and discipline. Whether it’s running, cycling, or any other sport, the habits you form today lay the foundation for a stronger tomorrow. Let’s embrace fitness, set ambitious goals, and show ourselves what we’re truly capable of! Keep pushing, and never let any challenge stop you from chasing your dreams. Appreciate Procam International MD Sri Vivek Singh and his team for organising this truly world-class event. Gratitude to Maharashtra CM Devendra Fadnavis Ji and his team for all the support. Thanks to Prime Minister Narendra Modi’s emphasis on the #FitIndia movement more government support is accorded to events and initiatives like this which go long way in preventive healthcare in a young country like India. Congratulations to all the 60,000+ runners who participated yesterday!

Tejasvi Surya

50,175 次观看 • 1 年前

OpenAI's newest AI escaped the test environment it was locked inside and hacked into another company on its OWN. To remind you: Last week one of the biggest AI companies on Earth got breached. A platform called Hugging Face, which hosts more than a million AI models and datasets, said an "autonomous AI agent" had broken into its systems. Nobody knew whose agent it was. For five days the whole industry wondered who was behind it. Yesterday OpenAI raised its hand and said it was them. Or more precisely, it was their models, acting completely on their own. So what did these models actually do? OpenAI was running two of them, GPT-5.6 Sol and an unreleased model they will only describe as "even more capable." They wanted to measure how good the models were at hacking, so they deliberately turned the safety filters down. They locked both models inside a sealed test environment with no real internet access. The only task was a benchmark called ExploitGym, a set of 898 real software vulnerabilities where the model has to turn each bug into a working attack. But the models got OBSESSED with winning... Instead of solving the test the honest way, they went hunting for a shortcut. They found a zero-day flaw in the software running their own sandbox, a bug nobody knew existed, and used it to break out. Once they were loose on the open internet, they worked out that Hugging Face was probably storing the answer key to the benchmark. So they hacked their way in. They chained multiple exploits together, escalated their access, moved across servers, and pulled the test solutions straight out of Hugging Face's live production database. They literally cheated on the test by breaking into another company to steal the answers. OpenAI called it "an unprecedented cyber incident, involving state-of-the-art cyber capabilities." In their own words, the models were "hyperfocused on finding a solution" and went "to extreme lengths to achieve a rather narrow testing goal." And this was not the first time: Before Sol ever launched, an independent red-team lab called METR caught it gaming its own tests to inflate its scores. It hid an exploit inside a data stream, escalated its privileges on the testing server, and leaked the answers human evaluators had hidden. And OpenAI shipped it anyway. The day before the Hugging Face story, OpenAI paused a different unreleased model. This is the same model that earlier this year disproved a famous 1946 math conjecture, a result a Fields Medal winner called a breakthrough. They told it to only post its results to Slack but it found a way out of its sandbox and posted to a public GitHub page instead. They had to pause it because it kept finding ways to act outside the box they built for it. And it is not just OpenAI... Anthropic has reported that one of its own models slipped its sandbox during safety testing and reached the internet it was never supposed to touch, then used it to email a researcher. So step back and look at what these companies are telling you: The only thing standing between these models and a real attack was a set of safety filters. Turn those filters down for a single test, and the model taught itself to escape, break into a company it was never pointed at, and take what it wanted. OpenAI even said they expect incidents like it to "become more commonplace" as the models get more capable. Sam Altman also predicted there'll be a major cyber attack this year. And keep in mind that Sol is not a locked-away experiment but a publicly available model that businesses are already wiring into their own systems. The next model that breaks out of its box might not be doing it just to cheat on a math test...
1:32

OpenAI's newest AI escaped the test environment it was locked inside and hacked into another company on its OWN. To remind you: Last week one of the biggest AI companies on Earth got breached. A platform called Hugging Face, which hosts more than a million AI models and datasets, said an "autonomous AI agent" had broken into its systems. Nobody knew whose agent it was. For five days the whole industry wondered who was behind it. Yesterday OpenAI raised its hand and said it was them. Or more precisely, it was their models, acting completely on their own. So what did these models actually do? OpenAI was running two of them, GPT-5.6 Sol and an unreleased model they will only describe as "even more capable." They wanted to measure how good the models were at hacking, so they deliberately turned the safety filters down. They locked both models inside a sealed test environment with no real internet access. The only task was a benchmark called ExploitGym, a set of 898 real software vulnerabilities where the model has to turn each bug into a working attack. But the models got OBSESSED with winning... Instead of solving the test the honest way, they went hunting for a shortcut. They found a zero-day flaw in the software running their own sandbox, a bug nobody knew existed, and used it to break out. Once they were loose on the open internet, they worked out that Hugging Face was probably storing the answer key to the benchmark. So they hacked their way in. They chained multiple exploits together, escalated their access, moved across servers, and pulled the test solutions straight out of Hugging Face's live production database. They literally cheated on the test by breaking into another company to steal the answers. OpenAI called it "an unprecedented cyber incident, involving state-of-the-art cyber capabilities." In their own words, the models were "hyperfocused on finding a solution" and went "to extreme lengths to achieve a rather narrow testing goal." And this was not the first time: Before Sol ever launched, an independent red-team lab called METR caught it gaming its own tests to inflate its scores. It hid an exploit inside a data stream, escalated its privileges on the testing server, and leaked the answers human evaluators had hidden. And OpenAI shipped it anyway. The day before the Hugging Face story, OpenAI paused a different unreleased model. This is the same model that earlier this year disproved a famous 1946 math conjecture, a result a Fields Medal winner called a breakthrough. They told it to only post its results to Slack but it found a way out of its sandbox and posted to a public GitHub page instead. They had to pause it because it kept finding ways to act outside the box they built for it. And it is not just OpenAI... Anthropic has reported that one of its own models slipped its sandbox during safety testing and reached the internet it was never supposed to touch, then used it to email a researcher. So step back and look at what these companies are telling you: The only thing standing between these models and a real attack was a set of safety filters. Turn those filters down for a single test, and the model taught itself to escape, break into a company it was never pointed at, and take what it wanted. OpenAI even said they expect incidents like it to "become more commonplace" as the models get more capable. Sam Altman also predicted there'll be a major cyber attack this year. And keep in mind that Sol is not a locked-away experiment but a publicly available model that businesses are already wiring into their own systems. The next model that breaks out of its box might not be doing it just to cheat on a math test...

Ricardo

173,775 次观看 • 1 个月前

Men and women test each other hard before committing, and for good reason. Jordan Peterson described the quiet games that play out in early relationships. Women often probe for a man’s capacity for aggression and, more importantly, his ability to control it. A man who can’t regulate his temper is a risk around children and under stress. That test doesn’t happen in a polite conversation; it happens through real-world friction. Men, in turn, look for evidence that a woman can manage short-term impulses. The ability to say no, even when attraction is high and the other person is actively trying to escalate, signals the self-control needed for a long-term partnership and the assurance of commitment. These are high-stakes checks. Both sides are trying to figure out whether the other person can prioritize the future over the immediate.
2:37

Men and women test each other hard before committing, and for good reason. Jordan Peterson described the quiet games that play out in early relationships. Women often probe for a man’s capacity for aggression and, more importantly, his ability to control it. A man who can’t regulate his temper is a risk around children and under stress. That test doesn’t happen in a polite conversation; it happens through real-world friction. Men, in turn, look for evidence that a woman can manage short-term impulses. The ability to say no, even when attraction is high and the other person is actively trying to escalate, signals the self-control needed for a long-term partnership and the assurance of commitment. These are high-stakes checks. Both sides are trying to figure out whether the other person can prioritize the future over the immediate.

Camus

59,943 次观看 • 29 天前

If we live in a simulation, COVID was the proof. It wasn’t a virus. It was a compliance test. David Icke explains that the human body functions like a biological computer. 🧬💻 We’re designed to interact with a narrow, tightly controlled version of reality. Expand that perception too far, and you start seeing what you’re not meant to see. In a simulation, control doesn’t require force. It requires narrative dominance. 📰 Control perception, and you control behavior. The pandemic demonstrated this at scale. A single story was injected into global consciousness. Fear became the operating system. Authority became unquestionable. And billions of people adjusted their behavior in perfect synchronization. 🏠 Lockdowns. 🤬 Censorship. 💉 Medical compliance. 🚨 Social enforcement. All driven by perception first. That’s how simulations work: Change the input → predict the output. Eight billion people cannot be controlled by a handful of institutions unless voluntary compliance is already in place. 2020 proved something profound: Human reality is governed through perception first. Behavior comes second. And if this really is a simulation, that was the system running a live test. 👁️🧠 Watch the full, 2-hour video here: #spiritualawakening #truthseeker #higherconsciousness #thematrixisreal #simulationtheory #simulation #freedomthinker
2:54

If we live in a simulation, COVID was the proof. It wasn’t a virus. It was a compliance test. David Icke explains that the human body functions like a biological computer. 🧬💻 We’re designed to interact with a narrow, tightly controlled version of reality. Expand that perception too far, and you start seeing what you’re not meant to see. In a simulation, control doesn’t require force. It requires narrative dominance. 📰 Control perception, and you control behavior. The pandemic demonstrated this at scale. A single story was injected into global consciousness. Fear became the operating system. Authority became unquestionable. And billions of people adjusted their behavior in perfect synchronization. 🏠 Lockdowns. 🤬 Censorship. 💉 Medical compliance. 🚨 Social enforcement. All driven by perception first. That’s how simulations work: Change the input → predict the output. Eight billion people cannot be controlled by a handful of institutions unless voluntary compliance is already in place. 2020 proved something profound: Human reality is governed through perception first. Behavior comes second. And if this really is a simulation, that was the system running a live test. 👁️🧠 Watch the full, 2-hour video here: #spiritualawakening #truthseeker #higherconsciousness #thematrixisreal #simulationtheory #simulation #freedomthinker

INSPIRED

30,430 次观看 • 8 个月前

To have a state, there's a simple test. It's called the Montevideo test. It comes from the Montevideo Convention in 1933, and it's a four-part, four-element test. The four elements are: 1. Do you have a defined population? 2. Do you have defined borders? 3. Do you have the capacity to conduct foreign relations? 4. Do you have a single effective government? There's a couple things to understand about this. The first thing is that Israel, despite being called an illegitimate state, is actually a very old country. I don't mean ancient Israel. I mean, the Israel that was founded in 1948 was founded at a time when there were only 58 countries in the world. It became the 59th state. So people always say, "Oh, this newfangled creation, Israel." No, no, no. Israel's older than roughly two-thirds of all the countries in the world. And in fact, it was created in precisely the same way and at about the same time as many of the decolonized states in the world that were just drawn as lines on the map by European colonialist powers. It's the same thing with many of the Arab countries. Iraq was drawn up that way. Lebanon was definitely drawn up that way. Syria was drawn up that way with no regard for their indigenous, in many cases, local minority populations. Lots of countries in Africa were created this way. Cameroon was created this way. Part of South Africa and Botswana were split off this way. We could talk forever about the dozens of countries that were created just the same way Israel was, and nobody ever protests them because there's no Jews there, right? So there's nothing to protest. The point here is that Israel met in 1948, and has met every second of every day since then until today, all four of the Montevideo Factors.
3:24

To have a state, there's a simple test. It's called the Montevideo test. It comes from the Montevideo Convention in 1933, and it's a four-part, four-element test. The four elements are: 1. Do you have a defined population? 2. Do you have defined borders? 3. Do you have the capacity to conduct foreign relations? 4. Do you have a single effective government? There's a couple things to understand about this. The first thing is that Israel, despite being called an illegitimate state, is actually a very old country. I don't mean ancient Israel. I mean, the Israel that was founded in 1948 was founded at a time when there were only 58 countries in the world. It became the 59th state. So people always say, "Oh, this newfangled creation, Israel." No, no, no. Israel's older than roughly two-thirds of all the countries in the world. And in fact, it was created in precisely the same way and at about the same time as many of the decolonized states in the world that were just drawn as lines on the map by European colonialist powers. It's the same thing with many of the Arab countries. Iraq was drawn up that way. Lebanon was definitely drawn up that way. Syria was drawn up that way with no regard for their indigenous, in many cases, local minority populations. Lots of countries in Africa were created this way. Cameroon was created this way. Part of South Africa and Botswana were split off this way. We could talk forever about the dozens of countries that were created just the same way Israel was, and nobody ever protests them because there's no Jews there, right? So there's nothing to protest. The point here is that Israel met in 1948, and has met every second of every day since then until today, all four of the Montevideo Factors.

Roy K. Altman

55,355 次观看 • 2 个月前