Video yükleniyor...

Video Yüklenemedi

Bu video yüklenirken bir sorun oluştu. Bu geçici bir ağ sorunundan kaynaklanıyor olabilir veya video kullanılamıyor olabilir.

Ana Sayfaya Dön

China's self driving robotic traffic cones can secure accident sites within 10 seconds! All controlled remotely & much quicker than doing by hand.

HOW THINGS WORK

2,387,355 subscribers

92,053 görüntüleme • 1 ay önce •via X (Twitter)

Bilim & Teknoloji

Anya Rossi• Live Now

Private livecam show

0 Yorum

Yorum bulunmuyor

Orijinal gönderinin yorumları burada görünecek

Benzer Videolar

🚌 Futuristic travel is arriving as driverless electric buses have hit the road in Jinan, east China's Shandong Province! Locals can use a mobile app to book rides on a self-driving bus, which is charged by a robotic arm. (Source: Xinhua)

🚌 Futuristic travel is arriving as driverless electric buses have hit the road in Jinan, east China's Shandong Province! Locals can use a mobile app to book rides on a self-driving bus, which is charged by a robotic arm. (Source: Xinhua)

China-Caribbean Development Center

2,470,917 görüntüleme • 9 ay önce

I will be fined 600k for doing 40 at a 30kph zoned dual carriage & yet his boda guy, who is more at greater risk of an accident, will pass by all cameras, all traffic Uganda Police Force while breaking over 5 laws but get away with nothing other than a smirk from authorities.

I will be fined 600k for doing 40 at a 30kph zoned dual carriage & yet his boda guy, who is more at greater risk of an accident, will pass by all cameras, all traffic Uganda Police Force while breaking over 5 laws but get away with nothing other than a smirk from authorities.

Buni, The Investorpreneur

48,802 görüntüleme • 1 yıl önce

Can you name this band from their one hit wonder of 1977, in less than 10 seconds? This hit went all the way to No. 1 on the Billboard Hot 100 in 1977. Written by the band themselves.

Can you name this band from their one hit wonder of 1977, in less than 10 seconds? This hit went all the way to No. 1 on the Billboard Hot 100 in 1977. Written by the band themselves.

🇺🇸Hot Pepper

73,676 görüntüleme • 9 ay önce

TWICE's goals 10 years from now on their 20th anniversary Jihyo: "Honestly, I've already accomplished so much professionally, so more than anything, I want the members to be healthy. I hope we can all happily keep doing this together. I think that's my goal." TWICE FOREVER 🥹

TWICE's goals 10 years from now on their 20th anniversary Jihyo: "Honestly, I've already accomplished so much professionally, so more than anything, I want the members to be healthy. I hope we can all happily keep doing this together. I think that's my goal." TWICE FOREVER 🥹

minaron

120,500 görüntüleme • 1 yıl önce

According to Israeli officials, more than 10 aircraft with the Israeli Air Force participated in today’s strike against the Qatari capital of Doha, utilizing over 10 munitions which all hit a building where Hamas leaders were believed to have been gathered within seconds. Prior to and following the strike, several aerial-refuelings were carried out by Boeing 707s with the “Desert Giants” of the 120th Squadron.

According to Israeli officials, more than 10 aircraft with the Israeli Air Force participated in today’s strike against the Qatari capital of Doha, utilizing over 10 munitions which all hit a building where Hamas leaders were believed to have been gathered within seconds. Prior to and following the strike, several aerial-refuelings were carried out by Boeing 707s with the “Desert Giants” of the 120th Squadron.

OSINTdefender

358,196 görüntüleme • 1 yıl önce

🇨🇳 CHINA RELEASES VIDEO OF HYPERSONIC SHIP-KILLER LAUNCHING FROM DESTROYER - U.S. CARRIERS JUST GOT A TARGETING PROBLEM THEY CAN'T SOLVE China's navy just published footage of a Type 055 destroyer launching a YJ-20 hypersonic anti-ship missile. Mach 6+ speeds. 1,000+ km range. Designed specifically to kill aircraft carriers. The footage itself is the weapon. China's not showing this for domestic propaganda. They're telling the U.S. Navy: "Your carriers can't operate in the Pacific anymore without accepting catastrophic risk." Here's the math that just changed: U.S. carrier strike group costs: ~$50 billion (carrier + escorts + aircraft) YJ-20 missile cost: ~$10 million Number of missiles needed to mission-kill a carrier: Unknown, but probably less than 20 The economics are brutal. China can build 5,000 hypersonic missiles for the price of one U.S. carrier. Even with 90% interception rates (currently impossible), they just need to saturate defenses. Hypersonic missiles at Mach 6 travel 2 km per second. The 1,000 km range means 8 minutes flight time from launch to impact. Current U.S. ship defense systems are built for subsonic and supersonic threats. Hypersonics compress decision time to seconds. The destroyer platform is what makes this devastating. China's building Type 055s in volume - eight operational, more under construction. Each can carry multiple YJ-20s. That's mobile hypersonic capability deployed across the entire Pacific. U.S. carriers project power by getting close enough to launch aircraft. But if carriers can't survive within 1,000 km of Chinese coast, they can't project power into Taiwan Strait, South China Sea, or anywhere China's destroyer fleet can reach. Pentagon's been warning about this for years. Now China's demonstrating it works and they're mass-producing the platforms. The carrier era might be ending the same way battleships ended - too expensive, too vulnerable, replaced by cheaper weapons that can kill them from beyond their effective range. China's releasing this footage right as tensions over Taiwan escalate. The message: come within range, find out what happens. Source: Open Source Intel

🇨🇳 CHINA RELEASES VIDEO OF HYPERSONIC SHIP-KILLER LAUNCHING FROM DESTROYER - U.S. CARRIERS JUST GOT A TARGETING PROBLEM THEY CAN'T SOLVE China's navy just published footage of a Type 055 destroyer launching a YJ-20 hypersonic anti-ship missile. Mach 6+ speeds. 1,000+ km range. Designed specifically to kill aircraft carriers. The footage itself is the weapon. China's not showing this for domestic propaganda. They're telling the U.S. Navy: "Your carriers can't operate in the Pacific anymore without accepting catastrophic risk." Here's the math that just changed: U.S. carrier strike group costs: ~$50 billion (carrier + escorts + aircraft) YJ-20 missile cost: ~$10 million Number of missiles needed to mission-kill a carrier: Unknown, but probably less than 20 The economics are brutal. China can build 5,000 hypersonic missiles for the price of one U.S. carrier. Even with 90% interception rates (currently impossible), they just need to saturate defenses. Hypersonic missiles at Mach 6 travel 2 km per second. The 1,000 km range means 8 minutes flight time from launch to impact. Current U.S. ship defense systems are built for subsonic and supersonic threats. Hypersonics compress decision time to seconds. The destroyer platform is what makes this devastating. China's building Type 055s in volume - eight operational, more under construction. Each can carry multiple YJ-20s. That's mobile hypersonic capability deployed across the entire Pacific. U.S. carriers project power by getting close enough to launch aircraft. But if carriers can't survive within 1,000 km of Chinese coast, they can't project power into Taiwan Strait, South China Sea, or anywhere China's destroyer fleet can reach. Pentagon's been warning about this for years. Now China's demonstrating it works and they're mass-producing the platforms. The carrier era might be ending the same way battleships ended - too expensive, too vulnerable, replaced by cheaper weapons that can kill them from beyond their effective range. China's releasing this footage right as tensions over Taiwan escalate. The message: come within range, find out what happens. Source: Open Source Intel

Mario Nawfal

121,347 görüntüleme • 9 ay önce

Today's heavy rain around 3:00 PM exposed a serious civic issue. The drainage grate on the Veerannapalya Flyover (Nagawara to Hebbal road) became completely blocked with garbage, causing severe waterlogging. Within minutes, the flyover was flooded, forcing traffic to come to a standstill and resulting in a 3–4 km traffic jam. I was at home when I noticed the heavy congestion on Google Maps. I immediately put on my raincoat and rushed to the location. By the time I arrived, Sector Cobra personnel had also reached the spot. Together, we cleared the garbage blocking the drainage grate. Within 15 minutes, the water drained away and traffic resumed smoothly. What surprised me the most was that more than 100 people were standing there watching, yet no one stepped forward to remove the debris. If just a few people had taken the initiative, thousands of commuters could have been spared from unnecessary delays. Even more concerning is the negligence of the agencies responsible for maintaining stormwater drains. Because of poor maintenance, the burden often falls on Traffic Police, Traffic Wardens, volunteers, and responsible citizens to solve problems that should have been prevented in the first place. Let's not be citizens who only complain. Whenever it is safe to do so, let's become part of the solution. Sometimes, a small act of responsibility can save thousands of people from inconvenience. A responsible city is built by responsible citizens. Let's all do our part. HENNURU TRAFFIC PS Hebbal Traffic Police Station DCP Traffic North, Bengaluru ACP Traffic Northeast ಬೆಂಗಳೂರು ಸಂಚಾರ ಪೊಲೀಸ್ BengaluruTrafficPolice Joint CP, Traffic, Bengaluru Karnataka Portfolio ThirdEye

Today's heavy rain around 3:00 PM exposed a serious civic issue. The drainage grate on the Veerannapalya Flyover (Nagawara to Hebbal road) became completely blocked with garbage, causing severe waterlogging. Within minutes, the flyover was flooded, forcing traffic to come to a standstill and resulting in a 3–4 km traffic jam. I was at home when I noticed the heavy congestion on Google Maps. I immediately put on my raincoat and rushed to the location. By the time I arrived, Sector Cobra personnel had also reached the spot. Together, we cleared the garbage blocking the drainage grate. Within 15 minutes, the water drained away and traffic resumed smoothly. What surprised me the most was that more than 100 people were standing there watching, yet no one stepped forward to remove the debris. If just a few people had taken the initiative, thousands of commuters could have been spared from unnecessary delays. Even more concerning is the negligence of the agencies responsible for maintaining stormwater drains. Because of poor maintenance, the burden often falls on Traffic Police, Traffic Wardens, volunteers, and responsible citizens to solve problems that should have been prevented in the first place. Let's not be citizens who only complain. Whenever it is safe to do so, let's become part of the solution. Sometimes, a small act of responsibility can save thousands of people from inconvenience. A responsible city is built by responsible citizens. Let's all do our part. HENNURU TRAFFIC PS Hebbal Traffic Police Station DCP Traffic North, Bengaluru ACP Traffic Northeast ಬೆಂಗಳೂರು ಸಂಚಾರ ಪೊಲೀಸ್ BengaluruTrafficPolice Joint CP, Traffic, Bengaluru Karnataka Portfolio ThirdEye

Shree ram Bishnoi

25,899 görüntüleme • 2 ay önce

Another example of Tesla Self driving better than humans. I’m following this Legacy SUV in my Cybertruck on FSD 14.2.2.1 and we feel the brakes and are like what’s going on. Then see a deer ahead in front of SUV run past road. Deer makes it across but what is funny but not funny the SUV doesn’t even tap brakes. Don’t even look liked they slowed down. You can see us slowing down behind SUV after deer crosses. This is all done by FSD. I did nothing. People often ask me if I trust FSD. I always say yes. More than humans for sure. This is one more example of seeing road conditions before humans. Bravo Tesla

Another example of Tesla Self driving better than humans. I’m following this Legacy SUV in my Cybertruck on FSD 14.2.2.1 and we feel the brakes and are like what’s going on. Then see a deer ahead in front of SUV run past road. Deer makes it across but what is funny but not funny the SUV doesn’t even tap brakes. Don’t even look liked they slowed down. You can see us slowing down behind SUV after deer crosses. This is all done by FSD. I did nothing. People often ask me if I trust FSD. I always say yes. More than humans for sure. This is one more example of seeing road conditions before humans. Bravo Tesla

Scott Dembraski

36,843 görüntüleme • 9 ay önce

I was on the tail end of a 500 mile drive back from Omaha yesterday with my 77 year old dad and we nearly had a very serious accident, possibly deadly for the other driver. Look at this older Toyota Corolla blow this light at 60mph more than 3 seconds after it turns red. If it was me driving, because I could not see the Corolla as it was occluded by the stopped cars, we would have had a head on collision or I'm mid-turn and he would have impacted my dad's side of my Cybertruck. Thankfully Tesla FSD was doing the driving and it has superhuman reaction to brake pedal application time (aka PRT = perception response time) of about 0.25s while very good human is 0.8-0.9s or average human is 1.5-2.5s. This is life saving technology and it may have saved one yesterday. Thanks to Ashok Elluswamy, Elon Musk, and the whole team behind this.

I was on the tail end of a 500 mile drive back from Omaha yesterday with my 77 year old dad and we nearly had a very serious accident, possibly deadly for the other driver. Look at this older Toyota Corolla blow this light at 60mph more than 3 seconds after it turns red. If it was me driving, because I could not see the Corolla as it was occluded by the stopped cars, we would have had a head on collision or I'm mid-turn and he would have impacted my dad's side of my Cybertruck. Thankfully Tesla FSD was doing the driving and it has superhuman reaction to brake pedal application time (aka PRT = perception response time) of about 0.25s while very good human is 0.8-0.9s or average human is 1.5-2.5s. This is life saving technology and it may have saved one yesterday. Thanks to Ashok Elluswamy, Elon Musk, and the whole team behind this.

Cody

893,268 görüntüleme • 1 ay önce

I’d strongly urge the automobile industry to make dashcams a standard safety feature in all vehicles. Too often, we see hit-and-run cases where the culprits flee without accountability. A dashcam isn’t just a gadget it’s a necessity for our own safety, protection, and proof in such situations. Chandigarh was much better back when challans were issued manually people actually feared breaking the rules. But now, most of the reckless driving you see is by outsiders. You’ll rarely find a CH-number car in such incidents; it’s usually PB, HR, or DL plates. Just imagine how many lives can be put at risk in mere seconds because of such behaviour. No offence, but vehicles like the Verna, Creta, and Thar often end up in the same bracket when it comes to rash driving

I’d strongly urge the automobile industry to make dashcams a standard safety feature in all vehicles. Too often, we see hit-and-run cases where the culprits flee without accountability. A dashcam isn’t just a gadget it’s a necessity for our own safety, protection, and proof in such situations. Chandigarh was much better back when challans were issued manually people actually feared breaking the rules. But now, most of the reckless driving you see is by outsiders. You’ll rarely find a CH-number car in such incidents; it’s usually PB, HR, or DL plates. Just imagine how many lives can be put at risk in mere seconds because of such behaviour. No offence, but vehicles like the Verna, Creta, and Thar often end up in the same bracket when it comes to rash driving

Rattan Dhillon

680,674 görüntüleme • 1 yıl önce

Are you safer with LIDAR, or are you safer with vision? This is a false dichotomy. The more pertinent question today is "do you have something, or do you have nothing?" As you can see from the clips below, vision based systems avoid countless potential collisions every day. The difference between a crash and no crash isn't what sensor suite you chose — it's whether you have any AI on your car at all. Even if we concede that LIDAR may help prevent some additional crashes, we are really debating whether it is 1% of crashes or 0.00001% of crashes. Not all crashes are super complex and require lasers to detect. Most are simple, routine, and can easily be prevented by today's vision based AI. In fact, evidence is mounting that computer vision based systems can actually outperform more traditional approaches to self-driving. Why? Because the low cost of cameras enables you to create a much larger, more varied, and more diverse dataset. If you want to have expensive custom cars that's fine, but you're going to get fewer vehicles for the same budget. Seeing what's in front of you now is actually less important than predicting what's going to happen next — and the large scale datasets used to train pure vision systems are the best for predicting what's next. Counter-intuitively, the simpler and lower cost sensor actually has properties that make it better suited for training advanced AI. Computer vision based self-driving is often framed by LIDAR proponents as "cheaping out" on the sensor suite to save money. But it's not about being cheap, it's about bringing the technology to everyone. 1.2 million people die on the road every year around the world. That's around 39 million people who've died on the roads around the world since I was born — equivalent to a city the size of Tokyo or New Delhi getting wiped off the map. The status quo is simply unacceptable, and something has to be done to fix it as soon as possible. Of the 1.2 million people that will die on the roads this year, about 40,000 will be Americans. That's about 3%. So if we moved entirely to self-driving cars in America and brought crashes down to 0, 97% of the world's crash fatalities would still be taking place as usual. Deploying a $200,000+ retrofitted self-driving car may work in a few American cities, but it is not going to make sense in most places around the world where fares are much cheaper. Most often, the choice is not between LIDAR and vision. It's between vision or nothing. The best system is the system that's there running on my car when I need it to save my life. To say that all self-driving cars must have LIDAR is to sentence most of the world to death. We can't write off computer vision if we want to make a serious dent in this problem. It's going to be a key piece of the solution. Let LIDAR based players build the best self-driving car they can, and let vision based players do the same. We need to be trying everything

Are you safer with LIDAR, or are you safer with vision? This is a false dichotomy. The more pertinent question today is "do you have something, or do you have nothing?" As you can see from the clips below, vision based systems avoid countless potential collisions every day. The difference between a crash and no crash isn't what sensor suite you chose — it's whether you have any AI on your car at all. Even if we concede that LIDAR may help prevent some additional crashes, we are really debating whether it is 1% of crashes or 0.00001% of crashes. Not all crashes are super complex and require lasers to detect. Most are simple, routine, and can easily be prevented by today's vision based AI. In fact, evidence is mounting that computer vision based systems can actually outperform more traditional approaches to self-driving. Why? Because the low cost of cameras enables you to create a much larger, more varied, and more diverse dataset. If you want to have expensive custom cars that's fine, but you're going to get fewer vehicles for the same budget. Seeing what's in front of you now is actually less important than predicting what's going to happen next — and the large scale datasets used to train pure vision systems are the best for predicting what's next. Counter-intuitively, the simpler and lower cost sensor actually has properties that make it better suited for training advanced AI. Computer vision based self-driving is often framed by LIDAR proponents as "cheaping out" on the sensor suite to save money. But it's not about being cheap, it's about bringing the technology to everyone. 1.2 million people die on the road every year around the world. That's around 39 million people who've died on the roads around the world since I was born — equivalent to a city the size of Tokyo or New Delhi getting wiped off the map. The status quo is simply unacceptable, and something has to be done to fix it as soon as possible. Of the 1.2 million people that will die on the roads this year, about 40,000 will be Americans. That's about 3%. So if we moved entirely to self-driving cars in America and brought crashes down to 0, 97% of the world's crash fatalities would still be taking place as usual. Deploying a $200,000+ retrofitted self-driving car may work in a few American cities, but it is not going to make sense in most places around the world where fares are much cheaper. Most often, the choice is not between LIDAR and vision. It's between vision or nothing. The best system is the system that's there running on my car when I need it to save my life. To say that all self-driving cars must have LIDAR is to sentence most of the world to death. We can't write off computer vision if we want to make a serious dent in this problem. It's going to be a key piece of the solution. Let LIDAR based players build the best self-driving car they can, and let vision based players do the same. We need to be trying everything

Whole Mars Catalog

45,853 görüntüleme • 1 yıl önce

Just finished a one-week trip to China. I've now "survived" all the major (~20) L2 self-driving and robotaxi vehicles in both the US and China. Some thoughts & observations: ▶️L2 self-driving I tested major brands like $Huawei, $Li, $NIO, $Xpeng, and $Xiaomi. Overall, they exceeded my expectations. The rides were not overly cautious and handled complex situations (yes, road conditions in China are very challenging!) quite well. Nothing compares to $Tsla's approach. I see imitation learning/end-to-end as the only effective approach for self-driving. While Chinese peers perform well on main roads, they struggle on frontage roads due to reliance on high-precision maps and rule-based methods (e.g. cars stopped in the middle of the road where there was no clear white lining). Chinese EVs' self-driving capabilities are far ahead of those from US and EU brands. I doubt any Chinese players can profit from L2 self-driving, not because it’s not useful, but because it’s hard to differentiate, and price wars dominate the market in China. Chinese consumers and regulators seem much more receptive to self-driving. Even with a 5/10 self-driving capability, cars are practically *hands-free(!)* Insurance-wise, for L3+ cars, OEMs bear responsibility for incidents, so OEMs avoid labeling cars as L3+. ▶️Robotaxi I tested major brands like $Didi, and $Bidu. I'd rate equal to $Waymo, and it's ahead of other peers. However, the same issue applies here: user experience is nearly perfect (in Yizhuang, Beijing), but expansion is the real question. Chinese robotaxi companies are very sophisticated. While the rest of the world focuses on technology, Chinese peers treat it as a product, considering unit economics, operations, mass production, etc. Interestingly, most companies expressed a preference NOT to operate fleets themselves. They aim to be asset-light and let fleet managers handle operations. Policy Support: China has a very clear approval process, driven by data (autonomous driving distance, fully driverless distance, intervention rate, passenger ratings, etc.). ▶️Chinese EVs In major cities like Beijing or Shanghai, EV adoption (green license plates vs. gas cars with blue license plates) seems to be 40%+. If 40% of cars on the road are EVs, then EV penetration (defined as the % of new car sales) must already be over 50%. In shopping malls, the ground floor is filled with EV showrooms—easily 10+ brands, many of which are unfamiliar Chinese brands. It appears almost too easy to make an electric car, which is a stark contrast to the US. $Xiaomi, for example, can achieve a 10% gross profit margin in its first year of operation, compared to $RIVN's -45%. Additionally, $Xiaomi cars are priced at 30% of $RIVN's price. It's fascinating to see how China transitioned from "couldn't make their own gas cars at all (only JVs)" to "dominating EVs globally." The government deserves credit for setting the direction and executing effectively. China now controls the entire supply chain, with $CATL holding 40% of the global market share. 🔹How did it happen? The success of the industry Incentives were set just right: the government provided incentives early on to make EVs and gas cars have comparable MSRPs, allowing consumers to choose based on functionality. This approach differs from how the IRA offers incentives... Perfectly competitive market: $TSLA was brought in, and competition was welcomed, unlike the US, which has a 100% import tax on Chinese EVs. Strategic regulations: License plate restrictions were used effectively; for example, taxis and minivans are required to be EVs. 🔹The challenges Despite the success, the industry faces challenges with low-margin companies and struggling stocks. The intense competition shows no sign of ending. Well-funded global OEMs and Chinese state-owned car companies continue to subsidize, leading to new EV brands emerging annually. The natural tendency in China is to race to the bottom. I think this ties back to China's history as the "world’s factory," where manufacturers price products at "cost plus" versus the US and developing countries, which price based on "affordability/value creation." 🔹The wow EV feature >Software features that surprised me the most: - Everything in the car can be voice-controlled. Not just simple tasks like playing music; users can adjust the height of the steering wheel and set the temperature easily. - Self-parking, which $Tsla has yet to release to all FSD users, is already a table stake in China (I'd rate the quality as 10/10). >Other fun hardware features: - Mini fridges in the car - Infotainment systems - IoT: remote access the car/home via cellphone - all connected together - Heads-up displays - UV-protected glass roofs: $Xiaomi took $Tsla's design, but the glass roof of the $Xiaomi car is made of double layers with silver, blocking 99.9% of UV and infrared rays...as a result, heat is no longer a problem inside the car

Just finished a one-week trip to China. I've now "survived" all the major (~20) L2 self-driving and robotaxi vehicles in both the US and China. Some thoughts & observations: ▶️L2 self-driving I tested major brands like $Huawei, $Li, $NIO, $Xpeng, and $Xiaomi. Overall, they exceeded my expectations. The rides were not overly cautious and handled complex situations (yes, road conditions in China are very challenging!) quite well. Nothing compares to $Tsla's approach. I see imitation learning/end-to-end as the only effective approach for self-driving. While Chinese peers perform well on main roads, they struggle on frontage roads due to reliance on high-precision maps and rule-based methods (e.g. cars stopped in the middle of the road where there was no clear white lining). Chinese EVs' self-driving capabilities are far ahead of those from US and EU brands. I doubt any Chinese players can profit from L2 self-driving, not because it’s not useful, but because it’s hard to differentiate, and price wars dominate the market in China. Chinese consumers and regulators seem much more receptive to self-driving. Even with a 5/10 self-driving capability, cars are practically hands-free(!) Insurance-wise, for L3+ cars, OEMs bear responsibility for incidents, so OEMs avoid labeling cars as L3+. ▶️Robotaxi I tested major brands like $Didi, and $Bidu. I'd rate equal to $Waymo, and it's ahead of other peers. However, the same issue applies here: user experience is nearly perfect (in Yizhuang, Beijing), but expansion is the real question. Chinese robotaxi companies are very sophisticated. While the rest of the world focuses on technology, Chinese peers treat it as a product, considering unit economics, operations, mass production, etc. Interestingly, most companies expressed a preference NOT to operate fleets themselves. They aim to be asset-light and let fleet managers handle operations. Policy Support: China has a very clear approval process, driven by data (autonomous driving distance, fully driverless distance, intervention rate, passenger ratings, etc.). ▶️Chinese EVs In major cities like Beijing or Shanghai, EV adoption (green license plates vs. gas cars with blue license plates) seems to be 40%+. If 40% of cars on the road are EVs, then EV penetration (defined as the % of new car sales) must already be over 50%. In shopping malls, the ground floor is filled with EV showrooms—easily 10+ brands, many of which are unfamiliar Chinese brands. It appears almost too easy to make an electric car, which is a stark contrast to the US. $Xiaomi, for example, can achieve a 10% gross profit margin in its first year of operation, compared to $RIVN's -45%. Additionally, $Xiaomi cars are priced at 30% of $RIVN's price. It's fascinating to see how China transitioned from "couldn't make their own gas cars at all (only JVs)" to "dominating EVs globally." The government deserves credit for setting the direction and executing effectively. China now controls the entire supply chain, with $CATL holding 40% of the global market share. 🔹How did it happen? The success of the industry Incentives were set just right: the government provided incentives early on to make EVs and gas cars have comparable MSRPs, allowing consumers to choose based on functionality. This approach differs from how the IRA offers incentives... Perfectly competitive market: $TSLA was brought in, and competition was welcomed, unlike the US, which has a 100% import tax on Chinese EVs. Strategic regulations: License plate restrictions were used effectively; for example, taxis and minivans are required to be EVs. 🔹The challenges Despite the success, the industry faces challenges with low-margin companies and struggling stocks. The intense competition shows no sign of ending. Well-funded global OEMs and Chinese state-owned car companies continue to subsidize, leading to new EV brands emerging annually. The natural tendency in China is to race to the bottom. I think this ties back to China's history as the "world’s factory," where manufacturers price products at "cost plus" versus the US and developing countries, which price based on "affordability/value creation." 🔹The wow EV feature >Software features that surprised me the most: - Everything in the car can be voice-controlled. Not just simple tasks like playing music; users can adjust the height of the steering wheel and set the temperature easily. - Self-parking, which $Tsla has yet to release to all FSD users, is already a table stake in China (I'd rate the quality as 10/10). >Other fun hardware features: - Mini fridges in the car - Infotainment systems - IoT: remote access the car/home via cellphone - all connected together - Heads-up displays - UV-protected glass roofs: $Xiaomi took $Tsla's design, but the glass roof of the $Xiaomi car is made of double layers with silver, blocking 99.9% of UV and infrared rays...as a result, heat is no longer a problem inside the car

Freda Duan

399,124 görüntüleme • 2 yıl önce

Robots that act like slime! 🫟 Cornell University engineers developed a robotic collective that behaves less like a machine and more like a material that flows, reshapes, and adapts without centralized control. It consists of dozens of small robots with limited individual mobility that exhibit coordinated motion when entangled. The system resembles soft matter, continuously deforming and reorganizing as it moves, driven by mechanical intelligence. Each robotic module measures 200mm long and 20mm wide, containing a small motor that oscillates between "I" and "U" shapes. These oscillations generate forces against the ground, allowing modules to inch forward and jostle together. On their own, modules move slowly and inefficiently. When they entangle into chains, they self-organize into shifting configurations that prove resilient in challenging environments. On incline surfaces, chains moved more reliably than individuals. In obstacle fields, the collective behaved like a flowing material, connections formed to maintain cohesion, then broke apart to prevent jamming. The system stays functional even when modules fail. Isolated modules emit an audible distress signal, prompting nearby modules to slow down so the straggler can reconnect. No centralized sensing or control, each module infers when it has lost contact by how much it's being jostled. Read more here: ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Robots that act like slime! 🫟 Cornell University engineers developed a robotic collective that behaves less like a machine and more like a material that flows, reshapes, and adapts without centralized control. It consists of dozens of small robots with limited individual mobility that exhibit coordinated motion when entangled. The system resembles soft matter, continuously deforming and reorganizing as it moves, driven by mechanical intelligence. Each robotic module measures 200mm long and 20mm wide, containing a small motor that oscillates between "I" and "U" shapes. These oscillations generate forces against the ground, allowing modules to inch forward and jostle together. On their own, modules move slowly and inefficiently. When they entangle into chains, they self-organize into shifting configurations that prove resilient in challenging environments. On incline surfaces, chains moved more reliably than individuals. In obstacle fields, the collective behaved like a flowing material, connections formed to maintain cohesion, then broke apart to prevent jamming. The system stays functional even when modules fail. Isolated modules emit an audible distress signal, prompting nearby modules to slow down so the straggler can reconnect. No centralized sensing or control, each module infers when it has lost contact by how much it's being jostled. Read more here: ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Lukas Ziegler

13,026 görüntüleme • 4 ay önce

I think the future of AI-assisted anime is not video models, but image continuity models like GPT Image 2.5. Predicting the next frame conditioned on the previous frame gives you much better control than predicting the next few seconds of video. You also don't need to predict all 24 frames every second. Since anime is basically layered animation, you can keep the same image for 5seconds while only the hand is waving or the eyes are blinking. Frame by frame prediction is also the nature of 2D anime. I've never really get the idea with turning everything into ultra-smooth 60 FPS animation. The problem with this model right now is that the 'invisible watermark' is too visible, which is really annoying. When you do chained generations, the watermark keeps stacking up to the point where it actually makes the project worse. It also has very poor color consistency.

I think the future of AI-assisted anime is not video models, but image continuity models like GPT Image 2.5. Predicting the next frame conditioned on the previous frame gives you much better control than predicting the next few seconds of video. You also don't need to predict all 24 frames every second. Since anime is basically layered animation, you can keep the same image for 5seconds while only the hand is waving or the eyes are blinking. Frame by frame prediction is also the nature of 2D anime. I've never really get the idea with turning everything into ultra-smooth 60 FPS animation. The problem with this model right now is that the 'invisible watermark' is too visible, which is really annoying. When you do chained generations, the watermark keeps stacking up to the point where it actually makes the project worse. It also has very poor color consistency.

Linaqruf

12,591 görüntüleme • 10 gün önce

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.

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 💎

1,801,196 görüntüleme • 15 gün önce

Created with Seedance 2.0 on BudgetPixel AI Prompt:Create a highly detailed, cinematic 15-second animated video set in a lively modern city completely operated by anthropomorphic animals. Use polished feature-film-quality 3D animation, expressive but natural animal movements, realistic fur simulation, vibrant environments, smooth camera motion, and consistent character design throughout. 0–3 seconds — Bear Police Officers Open with a wide establishing shot of a busy downtown intersection during a bright morning. Two large brown bears wear neat navy police uniforms with badges and caps. One bear confidently directs traffic with clear hand signals while the other stands beside a police car with flashing lights. Animal pedestrians cross the street naturally in the background. 3–6 seconds — Penguin Ice Cream Shop Use a smooth whip-pan transition to a colorful vintage ice cream truck. Two cheerful penguins wearing small aprons and bow ties serve ice cream cones through the window. A rabbit customer receives a tall strawberry cone while other animals wait in line. Include playful expressions, realistic melting ice cream, and small natural movements. 6–10 seconds — Monkey Bus Driver Transition as the ice cream truck passes in front of the camera, revealing a city bus. A friendly monkey in a professional driver’s uniform drives confidently through the busy street. Rabbits, deer, foxes, and pandas sit inside as passengers. Show the monkey checking the mirror, turning the steering wheel, and stopping smoothly at a bus stop. 10–13 seconds — Busy Animal City The camera follows the bus through the city, revealing raccoons cleaning the sidewalks, squirrels selling fruit at a street market, giraffes working near tall buildings, and birds delivering letters between rooftops. The city should feel organized, energetic, and full of believable activity. 13–15 seconds — Grand Final Shot End with a fast cinematic crane shot rising above the central city square, showing hundreds of animals working, shopping, driving, and socializing together. A fountain sits in the center while the animal city stretches into the distance under warm golden sunlight. Style: premium cinematic 3D animation, playful family-friendly comedy, highly detailed fur and clothing, expressive faces, natural body movement, realistic lighting and shadows, colorful urban production design, smooth transitions, dynamic tracking shots, shallow depth of field, 4K, 24fps, widescreen composition. Avoid: character duplication, changing uniforms, distorted paws, extra limbs, floating objects, unreadable signs, unnatural walking, chaotic traffic, stiff animation, low-detail backgrounds, sudden scene changes, text overlays, logos, subtitles, or watermarks.

Created with Seedance 2.0 on BudgetPixel AI Prompt:Create a highly detailed, cinematic 15-second animated video set in a lively modern city completely operated by anthropomorphic animals. Use polished feature-film-quality 3D animation, expressive but natural animal movements, realistic fur simulation, vibrant environments, smooth camera motion, and consistent character design throughout. 0–3 seconds — Bear Police Officers Open with a wide establishing shot of a busy downtown intersection during a bright morning. Two large brown bears wear neat navy police uniforms with badges and caps. One bear confidently directs traffic with clear hand signals while the other stands beside a police car with flashing lights. Animal pedestrians cross the street naturally in the background. 3–6 seconds — Penguin Ice Cream Shop Use a smooth whip-pan transition to a colorful vintage ice cream truck. Two cheerful penguins wearing small aprons and bow ties serve ice cream cones through the window. A rabbit customer receives a tall strawberry cone while other animals wait in line. Include playful expressions, realistic melting ice cream, and small natural movements. 6–10 seconds — Monkey Bus Driver Transition as the ice cream truck passes in front of the camera, revealing a city bus. A friendly monkey in a professional driver’s uniform drives confidently through the busy street. Rabbits, deer, foxes, and pandas sit inside as passengers. Show the monkey checking the mirror, turning the steering wheel, and stopping smoothly at a bus stop. 10–13 seconds — Busy Animal City The camera follows the bus through the city, revealing raccoons cleaning the sidewalks, squirrels selling fruit at a street market, giraffes working near tall buildings, and birds delivering letters between rooftops. The city should feel organized, energetic, and full of believable activity. 13–15 seconds — Grand Final Shot End with a fast cinematic crane shot rising above the central city square, showing hundreds of animals working, shopping, driving, and socializing together. A fountain sits in the center while the animal city stretches into the distance under warm golden sunlight. Style: premium cinematic 3D animation, playful family-friendly comedy, highly detailed fur and clothing, expressive faces, natural body movement, realistic lighting and shadows, colorful urban production design, smooth transitions, dynamic tracking shots, shallow depth of field, 4K, 24fps, widescreen composition. Avoid: character duplication, changing uniforms, distorted paws, extra limbs, floating objects, unreadable signs, unnatural walking, chaotic traffic, stiff animation, low-detail backgrounds, sudden scene changes, text overlays, logos, subtitles, or watermarks.

Sarah Parker

58,693 görüntüleme • 2 ay önce

DOM3 is made from HTML, CSS and Javascript, closer to a document than a canvas. It's a strange contemporary material that shapes much of our digital lives. The rhythm of endless creation and deletion in DOM3 is a self-driving version of what happens when you browse the web. "The Document Object Model (DOM) connects web pages to scripts or programming languages by representing the structure of a document—such as the HTML representing a web page—in memory." A html element, and a rectangle on a canvas, are not the same thing. It's a different material. Even if it all ends up controlling the same pixels, the process is different. The html element kind of actually exists, in this abstract context of a document object model. And in memory, in the moment. If it was possible to measure its weight, it would be heavier than a pixel on a canvas.

DOM3 is made from HTML, CSS and Javascript, closer to a document than a canvas. It's a strange contemporary material that shapes much of our digital lives. The rhythm of endless creation and deletion in DOM3 is a self-driving version of what happens when you browse the web. "The Document Object Model (DOM) connects web pages to scripts or programming languages by representing the structure of a document—such as the HTML representing a web page—in memory." A html element, and a rectangle on a canvas, are not the same thing. It's a different material. Even if it all ends up controlling the same pixels, the process is different. The html element kind of actually exists, in this abstract context of a document object model. And in memory, in the moment. If it was possible to measure its weight, it would be heavier than a pixel on a canvas.

Leander Herzog

11,484 görüntüleme • 1 yıl önce

It takes GRIT and sacrifice to play Div 1 Soccer. Self reflect and ask yourself these questions: 1. Will you get up for early AM lifts and not just drag yourself there but arrive happy and energized, eager to work and motivate your teammates? 2. Are you ready to miss family events—weddings, birthdays and be separated from your parents for longer than you ever have before? 3. Can you manage every aspect of your life for the first time by yourself, before you even throw in the rigors and demands of a sport? 4. Can you survive in an environment where you are defined by your sport and have very little social life existence outside of athletic and academic obligations? 5. Can you handle the mental challenge of going from the super star to possibly bottom of the roster, sitting on the bench, and/or not traveling with the team? 6. Will you be genuinely happy for your roommate who is getting all the playing time and attention while you’re getting none? If all answers are a resounding YES than you are built for this, but it’s not for everyone. And actually not for most. If it was easy, everyone would be doing it. College Soccer Truth ™ ECNL/GA/Recruiting/College Soccer

It takes GRIT and sacrifice to play Div 1 Soccer. Self reflect and ask yourself these questions: 1. Will you get up for early AM lifts and not just drag yourself there but arrive happy and energized, eager to work and motivate your teammates? 2. Are you ready to miss family events—weddings, birthdays and be separated from your parents for longer than you ever have before? 3. Can you manage every aspect of your life for the first time by yourself, before you even throw in the rigors and demands of a sport? 4. Can you survive in an environment where you are defined by your sport and have very little social life existence outside of athletic and academic obligations? 5. Can you handle the mental challenge of going from the super star to possibly bottom of the roster, sitting on the bench, and/or not traveling with the team? 6. Will you be genuinely happy for your roommate who is getting all the playing time and attention while you’re getting none? If all answers are a resounding YES than you are built for this, but it’s not for everyone. And actually not for most. If it was easy, everyone would be doing it. College Soccer Truth ™ ECNL/GA/Recruiting/College Soccer

Marsha Lycan

25,939 görüntüleme • 1 yıl önce