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BYD, the world’s largest EV maker headquartered in Shenzhen, has launched large-scale pre-production testing of its L3 autonomous driving system on city roads. So far, the system has completed over 150,000 kilometers of real-world testing on Shenzhen roads, covering highways, as well as night driving, rain, and construction zones.... show more

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30,179 просмотров • 8 месяцев назад •via X (Twitter)

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NEWS: BYD has unveiled an advanced driver-assist system called "God's Eye" that it plans to install on its entire model line-up including its $9,600 Seagull hatchback. "BYD wants to democratize self-driving tech. BYD had previously only offered such features, which enable cars to navigate highway traffic autonomously under human drivers' supervision, in models priced from $30,000." “God’s Eye was developed in-house by BYD and will equip the automaker’s mass-market models with features commonly only found on upscale EVs such as remote parking via smartphones and autonomous overtaking on roads."

NEWS: BYD has unveiled an advanced driver-assist system called "God's Eye" that it plans to install on its entire model line-up including its $9,600 Seagull hatchback. "BYD wants to democratize self-driving tech. BYD had previously only offered such features, which enable cars to navigate highway traffic autonomously under human drivers' supervision, in models priced from $30,000." “God’s Eye was developed in-house by BYD and will equip the automaker’s mass-market models with features commonly only found on upscale EVs such as remote parking via smartphones and autonomous overtaking on roads."

Sawyer Merritt

652,090 просмотров • 1 год назад

Ahead of the big brand day, I'm pleased to share that following its successful rollout in China this March, XPENG's Next Generation Pilot (NGP) intelligent driving system powered by VLA 2.0 technology will launch in Europe in early 2027. We've been testing on European roads for quite some time and results are pretty positive as in the video. I will also be testing it on the Munich road later today. Your turn Xianming Liu ! And we're not stopping there. We look forward to working with European partners to bring XPENG Robotaxi fleet powered by the same foundation model to local markets. Together, we'll accelerate the future of autonomous mobility.

Xiaopeng He

2,250,598 просмотров • 1 месяц назад

🚀 Tesla just hit another major Tesla Robotaxi milestone! FutureAzA highlighted that a production Cybercab with no steering wheel or pedals has now been spotted driving on public roads in Austin during supervised testing. On top of that, the Cybercab has been added to the Texas Connected Autonomous Vehicles Registry, and Tesla continues expanding testing, safety training, and operations. Tesla also hired former Intel executive Gary Jiang to help lead its Terafab chip project in Austin. Taken together, these aren't just small updates. They look like more signs that Tesla is preparing to scale Robotaxi and AI infrastructure at the same time. $TSLA

🚀 Tesla just hit another major Tesla Robotaxi milestone! FutureAzA highlighted that a production Cybercab with no steering wheel or pedals has now been spotted driving on public roads in Austin during supervised testing. On top of that, the Cybercab has been added to the Texas Connected Autonomous Vehicles Registry, and Tesla continues expanding testing, safety training, and operations. Tesla also hired former Intel executive Gary Jiang to help lead its Terafab chip project in Austin. Taken together, these aren't just small updates. They look like more signs that Tesla is preparing to scale Robotaxi and AI infrastructure at the same time. $TSLA

Herbert Ong

31,528 просмотров • 1 месяц назад

NEWS: The first EV from Sony and Honda’s joint venture has started pre-production in Ohio. • Two trims: $89,900 and $102,900 USD • 40 sensors & cameras for semi-autonomous driving assistance: 18 cameras, 1 LiDAR, 9 radars, and 12 ultrasonics. Will enable Level 3 autonomous driving in specific conditions in the future • 300 miles of EPA range • 91-kWh battery • Exterior display on the vehicle's front hood/bumper area (video below) • Native NACS charge port. Up to 150kW charging speed • 194" long • Equipped with Snapdragon Ride Platform SoC*2 as its brain. 800 TOPS computing power • Yoke steering wheel • Dolby Atmos sound system • Panoramic Screen • Name of EV: Afeela • Deliveries start in the first half of 2026. Pricier Signature trim will start deliveries in 2026. 2027 for the less expensive version.

NEWS: The first EV from Sony and Honda’s joint venture has started pre-production in Ohio. • Two trims: $89,900 and $102,900 USD • 40 sensors & cameras for semi-autonomous driving assistance: 18 cameras, 1 LiDAR, 9 radars, and 12 ultrasonics. Will enable Level 3 autonomous driving in specific conditions in the future • 300 miles of EPA range • 91-kWh battery • Exterior display on the vehicle's front hood/bumper area (video below) • Native NACS charge port. Up to 150kW charging speed • 194" long • Equipped with Snapdragon Ride Platform SoC*2 as its brain. 800 TOPS computing power • Yoke steering wheel • Dolby Atmos sound system • Panoramic Screen • Name of EV: Afeela • Deliveries start in the first half of 2026. Pricier Signature trim will start deliveries in 2026. 2027 for the less expensive version.

Sawyer Merritt

132,832 просмотров • 1 год назад

BREAKING NEWS: SHENZHEN JUST MADE WORLD’S FASTEST CAR A BYD car broke records to become the fastest production car in the world. The Yangwang U9 achieved a speed of 496.22 kilometers an hour, which is 308.4 mph, at a car testing center in Germany. While jetfighters and specialist racecars can go faster, this is the fastest speed achieved by a factory produced car that people can actually buy. How much gas did it use? None. The BYD Yangwang U9 Xtreme contains four electric motors to give it extreme thrust and special tyres designed to move at 500 kilometers an hour. Built in Shenzhen, China, it can also do the other cool stuff associated with Chinese cars – it can turn on the spot, jump over potholes and so on. But perhaps the most remarkable thing is that the BYD U9 was a concept just two years ago – and is now breaking world records. Pretty good for a toddler of 24 months.

BREAKING NEWS: SHENZHEN JUST MADE WORLD’S FASTEST CAR A BYD car broke records to become the fastest production car in the world. The Yangwang U9 achieved a speed of 496.22 kilometers an hour, which is 308.4 mph, at a car testing center in Germany. While jetfighters and specialist racecars can go faster, this is the fastest speed achieved by a factory produced car that people can actually buy. How much gas did it use? None. The BYD Yangwang U9 Xtreme contains four electric motors to give it extreme thrust and special tyres designed to move at 500 kilometers an hour. Built in Shenzhen, China, it can also do the other cool stuff associated with Chinese cars – it can turn on the spot, jump over potholes and so on. But perhaps the most remarkable thing is that the BYD U9 was a concept just two years ago – and is now breaking world records. Pretty good for a toddler of 24 months.

Nury Vittachi

20,566 просмотров • 11 месяцев назад

Autonomous driving through tight, dynamic, stochastic, and adversarial traffic-dynamics on sub-urban roads in India, as well as through partially unstructured environments. This demos showcases the robustness of our motion planning and decision making algorithmic frameworks in enabling #autonomousdriving through seamlessly through such traffic and environmental scenarios. The vehicle starts from a generic open environment at the temple, where there are no traffic-rules to abide by. It then exits the region and assumes a generic autonomous navigation behaviour, negotiating complex traffic scenes. At various points it can be seen that the other vehicles (bikes, autos, bicyclists, and cars) didn't abide by any traffic-rule and moved in crisscross fashion, presenting adversarial scenarios, challenging our autonomous vehicle at Swaayatt Robots to take care of the collision avoidance. This classical motion planning and decision making algorithmic framework is being further scaled up with deep #reinforcementlearning, which will practically solve the sub-urban traffic-dynamics and environment negotiation for #autonomousvehicles in India and throughout the world as well. This demo was done at the Kankali Kali Mata mandir in the city of Bhopal. This demo was a culmination of our prior works and demos: off-roads, on-roads, bidirectional traffic negotiation in single lane roads, and toll-plaza navigation. We have taken up the arduous task of solving the Level-4 autonomous driving by the end of 2024, globally. #machinelearning #deeplearning

Autonomous driving through tight, dynamic, stochastic, and adversarial traffic-dynamics on sub-urban roads in India, as well as through partially unstructured environments. This demos showcases the robustness of our motion planning and decision making algorithmic frameworks in enabling #autonomousdriving through seamlessly through such traffic and environmental scenarios. The vehicle starts from a generic open environment at the temple, where there are no traffic-rules to abide by. It then exits the region and assumes a generic autonomous navigation behaviour, negotiating complex traffic scenes. At various points it can be seen that the other vehicles (bikes, autos, bicyclists, and cars) didn't abide by any traffic-rule and moved in crisscross fashion, presenting adversarial scenarios, challenging our autonomous vehicle at Swaayatt Robots to take care of the collision avoidance. This classical motion planning and decision making algorithmic framework is being further scaled up with deep #reinforcementlearning, which will practically solve the sub-urban traffic-dynamics and environment negotiation for #autonomousvehicles in India and throughout the world as well. This demo was done at the Kankali Kali Mata mandir in the city of Bhopal. This demo was a culmination of our prior works and demos: off-roads, on-roads, bidirectional traffic negotiation in single lane roads, and toll-plaza navigation. We have taken up the arduous task of solving the Level-4 autonomous driving by the end of 2024, globally. #machinelearning #deeplearning

Sanjeev Sharma

186,291 просмотров • 2 лет назад

NEWS: Tesla is officially testing FSD in The Boring Company's Vegas Loop tunnel system. “We’ve started to test,” Steve Hill, CEO of the Las Vegas Convention & Visitors Authority. No passengers have been in vehicles during the testing. In the future, the Boring Company will remove safety drivers from the front seat during testing, Hill said, but there is no telling when that will take place, as it will depend on when Tesla and the Boring Company can demonstrate to the LVCVA that it is safe to do so. Hill said that the vehicles are currently being tested in self-driving mode inside the tunnels, “experiencing the environment,” as “they find spots that are difficult for them.” The rock walls of the tunnels, Hill said, combined with the bright, colorful lights in the passageways create some “interesting but odd lighting” for Tesla’s self-driving system. The tunnels should make for a “much easier environment” for autonomous vehicles than the open roads of Austin, because in the tunnels, the Boring Company has complete control over what and who enters, Hill said - Fortune (video below is not on FSD)

NEWS: Tesla is officially testing FSD in The Boring Company's Vegas Loop tunnel system. “We’ve started to test,” Steve Hill, CEO of the Las Vegas Convention & Visitors Authority. No passengers have been in vehicles during the testing. In the future, the Boring Company will remove safety drivers from the front seat during testing, Hill said, but there is no telling when that will take place, as it will depend on when Tesla and the Boring Company can demonstrate to the LVCVA that it is safe to do so. Hill said that the vehicles are currently being tested in self-driving mode inside the tunnels, “experiencing the environment,” as “they find spots that are difficult for them.” The rock walls of the tunnels, Hill said, combined with the bright, colorful lights in the passageways create some “interesting but odd lighting” for Tesla’s self-driving system. The tunnels should make for a “much easier environment” for autonomous vehicles than the open roads of Austin, because in the tunnels, the Boring Company has complete control over what and who enters, Hill said - Fortune (video below is not on FSD)

Sawyer Merritt

180,713 просмотров • 1 год назад

Delighted to share that an initiative conceived and brought to digital life as WCD Minister, has been honoured with the National Award for e-Governance 2024 (GOLD) at the 27th National Conference on e-Governance. Since its inception in March 2021, in response to PM Narendra Modi's clarion call for a SuPoshit Bharat, the Poshan Tracker has emerged as the largest nutrition surveillance system in the world, enabling real-time tracking of health-related Govt schemes and driving transparency & efficiency at the grassroot level. It has profoundly improved maternal and child health across the nation. Congratulations to TEAM Ministry of WCD for this well-deserved recognition, and kudos to everyone who has been part of this transformative journey.

Delighted to share that an initiative conceived and brought to digital life as WCD Minister, has been honoured with the National Award for e-Governance 2024 (GOLD) at the 27th National Conference on e-Governance. Since its inception in March 2021, in response to PM Narendra Modi's clarion call for a SuPoshit Bharat, the Poshan Tracker has emerged as the largest nutrition surveillance system in the world, enabling real-time tracking of health-related Govt schemes and driving transparency & efficiency at the grassroot level. It has profoundly improved maternal and child health across the nation. Congratulations to TEAM Ministry of WCD for this well-deserved recognition, and kudos to everyone who has been part of this transformative journey.

Smriti Z Irani

16,917 просмотров • 2 лет назад

NEWS: BYD has launched its next-generation battery energy storage system. It has a unit capacity of 14.5 MWh, the highest globally to date. The energy storage system achieves an ultra-large capacity of 10 MWh within a space equivalent to a 20-foot container, BYD said. For a 1 GWh storage plant, it will cut the number of required units by more than half, reduce land use by one-third, and trim cell count by 76%, according to the manufacturer. It uses BYD’s self-developed 2,710 Ah Blade Battery cell, which the company claims is the largest energy storage cell in the world. "This next-generation cell delivers three times the capacity of conventional storage batteries, boasts a cycle life of over 10,000 cycles, and reduces the total lifecycle cost per kilowatt-hour to below $0.014 – a milestone that could reshape the economics of large-scale storage." BYD says it can cut project-level levelized costs (LCOS) by 21.7%. For a typical 1 GWh installation, total costs related to equipment procurement, transportation, and installation are expected to drop by around 30%. In addition, BYD has launched its new GC Flux grid-forming inverter solution, which covers the 2.5–10 MW capacity range. According to BYD, the inverter boasts a performance level approximately 38% higher than common industry standards and a maximum power density of 1,474 kW/㎡, which is around 130% above typical values in today’s market. The system provides an overload capacity of up to 3x for 10 seconds and reaches a peak efficiency of 99.35%.

NEWS: BYD has launched its next-generation battery energy storage system. It has a unit capacity of 14.5 MWh, the highest globally to date. The energy storage system achieves an ultra-large capacity of 10 MWh within a space equivalent to a 20-foot container, BYD said. For a 1 GWh storage plant, it will cut the number of required units by more than half, reduce land use by one-third, and trim cell count by 76%, according to the manufacturer. It uses BYD’s self-developed 2,710 Ah Blade Battery cell, which the company claims is the largest energy storage cell in the world. "This next-generation cell delivers three times the capacity of conventional storage batteries, boasts a cycle life of over 10,000 cycles, and reduces the total lifecycle cost per kilowatt-hour to below $0.014 – a milestone that could reshape the economics of large-scale storage." BYD says it can cut project-level levelized costs (LCOS) by 21.7%. For a typical 1 GWh installation, total costs related to equipment procurement, transportation, and installation are expected to drop by around 30%. In addition, BYD has launched its new GC Flux grid-forming inverter solution, which covers the 2.5–10 MW capacity range. According to BYD, the inverter boasts a performance level approximately 38% higher than common industry standards and a maximum power density of 1,474 kW/㎡, which is around 130% above typical values in today’s market. The system provides an overload capacity of up to 3x for 10 seconds and reaches a peak efficiency of 99.35%.

Sawyer Merritt

384,738 просмотров • 11 месяцев назад

Today we're unveiling something truly extraordinary—one of the coolest and most transformative technologies: Mixed Reality Testing (MRT). Since launching Waabi World four years ago, we've been building towards this pivotal moment - bringing our virtual testing capabilities into the physical world to fundamentally transform what's possible in autonomous vehicle development. For over 100 years, closed-course testing has been the staple of vehicle safety testing. But creating scenarios on a physical test track resembles elaborate movie-stunts—it’s difficult to reproduce tests consistently, those tests do not capture the diversity of the real-world, and the range of safety-critical scenarios we can test is very limited because of the risk of damaging equipment or, worse, endangering lives. MRT changes everything! In the same way that augmented reality goggles blend the physical world with a virtual world, MRT enables the Waabi Driver to drive autonomously down a physical test track while simultaneously experiencing numerous intelligent, simulated actors that coexist in this hybrid reality and react to each other and to the physical world in naturalistic ways. All this is possible by leveraging Onboard Waabi World, a version of Waabi's neural simulator that runs in a few milliseconds on the onboard compute. As Onboard Waabi World generates new scenarios, the real physical sensor readings are modified instantaneously so the Waabi Driver can react to the blend of real and virtual elements while driving in the physical world. This fusion creates a first-of-its-kind reality that unlocks unlimited testing possibilities previously impossible to achieve safely or practically. Traffic jams can materialize instantly, motorcycles can weave between lanes, crowds of pedestrians can jaywalk unpredictably, children can dart into the street from behind parked cars, animals can wander across the road, debris can appear in lanes creating hazardous obstacles. The possibilities are endless. This breakthrough eliminates all traditional constraints of closed-course testing. We can do exponentially more tests than ever before and in a continuous fashion, with extraordinary levels of diversity and realism. Most importantly, we can push the boundaries of safety testing without real-world consequences. MRT represents the culmination of years of work toward safe, scalable autonomous deployment. It's been central to our testing approach for over two years and fundamental to achieving feature-complete autonomous driving capabilities earlier this year. But this is just the beginning. MRT’s impact extends beyond self-driving trucks – we’re laying the foundation for a future where any physical AI system can be tested and validated safely - from robotaxis to humanoid robots, manufacturing automation to healthcare robotics. Learn about Mixed Reality Testing:

Today we're unveiling something truly extraordinary—one of the coolest and most transformative technologies: Mixed Reality Testing (MRT). Since launching Waabi World four years ago, we've been building towards this pivotal moment - bringing our virtual testing capabilities into the physical world to fundamentally transform what's possible in autonomous vehicle development. For over 100 years, closed-course testing has been the staple of vehicle safety testing. But creating scenarios on a physical test track resembles elaborate movie-stunts—it’s difficult to reproduce tests consistently, those tests do not capture the diversity of the real-world, and the range of safety-critical scenarios we can test is very limited because of the risk of damaging equipment or, worse, endangering lives. MRT changes everything! In the same way that augmented reality goggles blend the physical world with a virtual world, MRT enables the Waabi Driver to drive autonomously down a physical test track while simultaneously experiencing numerous intelligent, simulated actors that coexist in this hybrid reality and react to each other and to the physical world in naturalistic ways. All this is possible by leveraging Onboard Waabi World, a version of Waabi's neural simulator that runs in a few milliseconds on the onboard compute. As Onboard Waabi World generates new scenarios, the real physical sensor readings are modified instantaneously so the Waabi Driver can react to the blend of real and virtual elements while driving in the physical world. This fusion creates a first-of-its-kind reality that unlocks unlimited testing possibilities previously impossible to achieve safely or practically. Traffic jams can materialize instantly, motorcycles can weave between lanes, crowds of pedestrians can jaywalk unpredictably, children can dart into the street from behind parked cars, animals can wander across the road, debris can appear in lanes creating hazardous obstacles. The possibilities are endless. This breakthrough eliminates all traditional constraints of closed-course testing. We can do exponentially more tests than ever before and in a continuous fashion, with extraordinary levels of diversity and realism. Most importantly, we can push the boundaries of safety testing without real-world consequences. MRT represents the culmination of years of work toward safe, scalable autonomous deployment. It's been central to our testing approach for over two years and fundamental to achieving feature-complete autonomous driving capabilities earlier this year. But this is just the beginning. MRT’s impact extends beyond self-driving trucks – we’re laying the foundation for a future where any physical AI system can be tested and validated safely - from robotaxis to humanoid robots, manufacturing automation to healthcare robotics. Learn about Mixed Reality Testing:

Raquel Urtasun

13,106 просмотров • 1 год назад

Autonomous driving through very dense dynamic traffic, with extremely tight-complex-stochastic traffic-dynamics on sub-urban roads, connecting to an open ground, with absolutely zero traffic-rules. This is the most heavily cluttered environment where we have tested our #autonomousdriving technology, presenting many of the adversarial negotiation scenarios as well, throughout the autonomous navigation task. This demo was done at the Mata Baglamukhi Madir campus in the city of Nalkheda, in MP, India, and was done in the presence of heavy police forces deployed that day on the ground, as can be seen in our demo. Our autonomous vehicle starts from the temple with a generic open environment, with zero traffic rules, with very narrow corridors created out of barricades for vehicles movement by the security forces. In the corridor no two vehicles can pass through at the same time, and our vehicle was tasked with driving through this corridor, while negotiating its way from any traffic, two-wheelers, or pedestrians it faces, with dense presence of bikes and cars on either side, presenting a very challenging environment for #autonomousvehicles. The vehicle exits the open area, and then assumes generic dual lane navigation, avoiding both static and dynamic obstacles, before encountering a police check-post, where the vehicle is supposed to wait if the barricade is closed, and proceed if open. Upon exiting the checkpost, the vehicle negotiates a traffic-intersection with stochastic and adversarial driving behaviour of other vehicles on the road. Our vehicle continuously faced heavily cluttered traffic scene, where entities on the road can execute a random driving pattern, making the decision making task very challenging. We did the demo over a period of two days, successfully executing multiple (30+) trials in this setting. This demo was again a culmination of our prior works and demos: Kankali Kali Mata demo, on-roads, bidirectional negotiation capability on single lane roads, and open environment Level-5 negotiation capability as showcased in our Toll-Plaza demo. We again scaled up classical decision making and motion planning algorithmic framework, to adapt to such a level of density of obstacles on the road. This framework is further being scaled up with #reinforcementlearning and unsupervised #deeplearning at Swaayatt Robots. We will again do a demo in the month of June here, showcasing autonomously acquired skills to pave the way for Level-5 autonomous driving, and to solve the Level-4 autonomy problem by the end of 2024. #MachineLearning

Autonomous driving through very dense dynamic traffic, with extremely tight-complex-stochastic traffic-dynamics on sub-urban roads, connecting to an open ground, with absolutely zero traffic-rules. This is the most heavily cluttered environment where we have tested our #autonomousdriving technology, presenting many of the adversarial negotiation scenarios as well, throughout the autonomous navigation task. This demo was done at the Mata Baglamukhi Madir campus in the city of Nalkheda, in MP, India, and was done in the presence of heavy police forces deployed that day on the ground, as can be seen in our demo. Our autonomous vehicle starts from the temple with a generic open environment, with zero traffic rules, with very narrow corridors created out of barricades for vehicles movement by the security forces. In the corridor no two vehicles can pass through at the same time, and our vehicle was tasked with driving through this corridor, while negotiating its way from any traffic, two-wheelers, or pedestrians it faces, with dense presence of bikes and cars on either side, presenting a very challenging environment for #autonomousvehicles. The vehicle exits the open area, and then assumes generic dual lane navigation, avoiding both static and dynamic obstacles, before encountering a police check-post, where the vehicle is supposed to wait if the barricade is closed, and proceed if open. Upon exiting the checkpost, the vehicle negotiates a traffic-intersection with stochastic and adversarial driving behaviour of other vehicles on the road. Our vehicle continuously faced heavily cluttered traffic scene, where entities on the road can execute a random driving pattern, making the decision making task very challenging. We did the demo over a period of two days, successfully executing multiple (30+) trials in this setting. This demo was again a culmination of our prior works and demos: Kankali Kali Mata demo, on-roads, bidirectional negotiation capability on single lane roads, and open environment Level-5 negotiation capability as showcased in our Toll-Plaza demo. We again scaled up classical decision making and motion planning algorithmic framework, to adapt to such a level of density of obstacles on the road. This framework is further being scaled up with #reinforcementlearning and unsupervised #deeplearning at Swaayatt Robots. We will again do a demo in the month of June here, showcasing autonomously acquired skills to pave the way for Level-5 autonomous driving, and to solve the Level-4 autonomy problem by the end of 2024. #MachineLearning

Sanjeev Sharma

332,974 просмотров • 2 лет назад

NEWS: NVIDIA just announced Alpamayo, what CEO Jensen Huang calls the world’s first thinking, reasoning autonomous vehicle AI, launching on U.S. roads later this year, starting with the Mercedes CLA. Jensen: "It's trained end-to-end. Literally from camera in to actuation out; It reasons what action it is about to take, the reason by which is came about that action, and the trajectory." Alpamayo introduces Vision-Language-Action (VLA) models, which enable self-driving systems to interpret what they see, reason about complex driving scenarios, and generate driving actions. The platform includes large reasoning models, simulation tools for testing rare and edge-case scenarios, and open datasets for training and validation. NVIDIA says the approach improves transparency, safety, and robustness in autonomous systems, particularly in complex real-world environments, and supports progress toward higher levels of vehicle autonomy: "With a 10-billion-parameter architecture, Alpamayo 1 uses video input to generate trajectories alongside reasoning traces, showing the logic behind each decision. Developers can adapt Alpamayo 1 into smaller runtime models for vehicle development, or use it as a foundation for AV development tools such as reasoning-based evaluators and auto-labeling systems. Alpamayo 1 provides open model weights and open-source inferencing scripts. Future models in the family will feature larger parameter counts, more detailed reasoning capabilities, more input and output flexibility, and options for commercial usage."

NEWS: NVIDIA just announced Alpamayo, what CEO Jensen Huang calls the world’s first thinking, reasoning autonomous vehicle AI, launching on U.S. roads later this year, starting with the Mercedes CLA. Jensen: "It's trained end-to-end. Literally from camera in to actuation out; It reasons what action it is about to take, the reason by which is came about that action, and the trajectory." Alpamayo introduces Vision-Language-Action (VLA) models, which enable self-driving systems to interpret what they see, reason about complex driving scenarios, and generate driving actions. The platform includes large reasoning models, simulation tools for testing rare and edge-case scenarios, and open datasets for training and validation. NVIDIA says the approach improves transparency, safety, and robustness in autonomous systems, particularly in complex real-world environments, and supports progress toward higher levels of vehicle autonomy: "With a 10-billion-parameter architecture, Alpamayo 1 uses video input to generate trajectories alongside reasoning traces, showing the logic behind each decision. Developers can adapt Alpamayo 1 into smaller runtime models for vehicle development, or use it as a foundation for AV development tools such as reasoning-based evaluators and auto-labeling systems. Alpamayo 1 provides open model weights and open-source inferencing scripts. Future models in the family will feature larger parameter counts, more detailed reasoning capabilities, more input and output flexibility, and options for commercial usage."

Sawyer Merritt

1,604,362 просмотров • 7 месяцев назад

🚨🇩🇪 BREAKING: Germany Launches Massive NATO Medical Drill Amid War Fears. Germany has conducted its largest medical exercise in decades as NATO prepares for the possibility of large-scale conflict. The Quadriga 2026 drill simulated evacuating wounded troops from Lithuania to hospitals across Germany, testing how the system would handle mass casualties in a high-intensity war scenario. Experts warn the system could face up to 1,000 casualties per day, with growing concerns over drone warfare injuries and attacks on medical units. The exercise is designed to expose weaknesses, and test whether Germany is truly ready. Source: DW

🚨🇩🇪 BREAKING: Germany Launches Massive NATO Medical Drill Amid War Fears. Germany has conducted its largest medical exercise in decades as NATO prepares for the possibility of large-scale conflict. The Quadriga 2026 drill simulated evacuating wounded troops from Lithuania to hospitals across Germany, testing how the system would handle mass casualties in a high-intensity war scenario. Experts warn the system could face up to 1,000 casualties per day, with growing concerns over drone warfare injuries and attacks on medical units. The exercise is designed to expose weaknesses, and test whether Germany is truly ready. Source: DW

Defence Index

15,646 просмотров • 4 месяцев назад

France Minister of Transportation on Tesla's FSD in new video: "The safety trade-offs are not yet sufficient to authorize it as it currently stands. All the more so since this system is not a self-driving system; So what are our concerns? Without going into overly technical detail, there are several. First example: we've found that the system allows for speeding. Another example: according to the data we have, the system doesn't guarantee an optimal level of driver attention in urban settings and during the most complex maneuvers, such as lane changes, intersections, or roundabouts. So what are the next steps? We're currently continuing our technical discussions with the Netherlands, other European states, and Tesla to refine our analysis. Last week, a representative from the Ministry of Transport's services traveled to the Netherlands. I want to emphasize this: France supports these technologies, and their deployment must happen within a framework of trust that allows us to evaluate the systems and determine what adjustments FSD needs to guarantee a high level of safety. This autumn, I will also be bringing together the French autonomous vehicle ecosystem to present the levers that will accelerate the deployment of this technology and to set a direction for the coming years. In France, we're fortunate to have world-class automakers and automotive suppliers, as well as some of the best engineers in the world in artificial intelligence and digital technology. We have real cards to play, and we're ready to play them — but never at the expense of safety on our roads."

France Minister of Transportation on Tesla's FSD in new video: "The safety trade-offs are not yet sufficient to authorize it as it currently stands. All the more so since this system is not a self-driving system; So what are our concerns? Without going into overly technical detail, there are several. First example: we've found that the system allows for speeding. Another example: according to the data we have, the system doesn't guarantee an optimal level of driver attention in urban settings and during the most complex maneuvers, such as lane changes, intersections, or roundabouts. So what are the next steps? We're currently continuing our technical discussions with the Netherlands, other European states, and Tesla to refine our analysis. Last week, a representative from the Ministry of Transport's services traveled to the Netherlands. I want to emphasize this: France supports these technologies, and their deployment must happen within a framework of trust that allows us to evaluate the systems and determine what adjustments FSD needs to guarantee a high level of safety. This autumn, I will also be bringing together the French autonomous vehicle ecosystem to present the levers that will accelerate the deployment of this technology and to set a direction for the coming years. In France, we're fortunate to have world-class automakers and automotive suppliers, as well as some of the best engineers in the world in artificial intelligence and digital technology. We have real cards to play, and we're ready to play them — but never at the expense of safety on our roads."

Sawyer Merritt

708,926 просмотров • 1 месяц назад

A member in our chat group shared his initial experience with FSD. He just downloaded v13.2.6 after returning back to Shenzhen, China before he took several test drives with FSD engaged and accumulated over 100 km FSD mileage. He is so impressed by the flawless zero-disengagement or zero-intervention drives. He invited his friend, an Xpeng X9 owner, to test it as well. The friend uses XPeng’s latest NGP autonomous driving system all the time. Obviously he is a very savvy ADAS observer in China. After the test drive, his verdict is: FSD is “invincible”. The foundational capabilities of FSD are far better than those of other systems in China. Let that sink in.

A member in our chat group shared his initial experience with FSD. He just downloaded v13.2.6 after returning back to Shenzhen, China before he took several test drives with FSD engaged and accumulated over 100 km FSD mileage. He is so impressed by the flawless zero-disengagement or zero-intervention drives. He invited his friend, an Xpeng X9 owner, to test it as well. The friend uses XPeng’s latest NGP autonomous driving system all the time. Obviously he is a very savvy ADAS observer in China. After the test drive, his verdict is: FSD is “invincible”. The foundational capabilities of FSD are far better than those of other systems in China. Let that sink in.

Ray

165,143 просмотров • 1 год назад

Russia puts a fully self-driving train on open city rails No driver in the cab. No one is pressing buttons at every stop. Just a train that thinks for itself. Moscow is now testing the Lastochka with Level 4 automation – the highest grade. That means the train: 🟠 drives itself 🟠 opens and closes doors 🟠 brakes automatically 🟠 detects obstacles on the tracks A human operator sits in a control center and watches over up to 4 trains at once. They only step in if something goes wrong. For comparison, a lower-level version (with a driver still onboard for safety) has already been carrying passengers since August 2024. What makes this unique? Most self-driving trains in the world run in closed tunnels. This one operates on open infrastructure—streets, crossings, and real-world chaos. 📍And the system is 100% Russian-made.

Russia puts a fully self-driving train on open city rails No driver in the cab. No one is pressing buttons at every stop. Just a train that thinks for itself. Moscow is now testing the Lastochka with Level 4 automation – the highest grade. That means the train: 🟠 drives itself 🟠 opens and closes doors 🟠 brakes automatically 🟠 detects obstacles on the tracks A human operator sits in a control center and watches over up to 4 trains at once. They only step in if something goes wrong. For comparison, a lower-level version (with a driver still onboard for safety) has already been carrying passengers since August 2024. What makes this unique? Most self-driving trains in the world run in closed tunnels. This one operates on open infrastructure—streets, crossings, and real-world chaos. 📍And the system is 100% Russian-made.

Sputnik

15,775 просмотров • 20 дней назад

BREAKING - EARLY EXCLUSIVE: XPENG Partners with Google Maps to Fuel Global Expansion The global autonomous driving landscape is becoming even more competitive! XPENG has announced a milestone global partnership with Google Maps, bringing a complete refresh of its in-car navigation and advanced driver assistance systems (ADAS). This major upgrade will come standard in the newly debuted XPENG L03. At the official launch event for the L03 in Munich, Germany, XPENG Chairman and CEO He Xiaopeng announced that the Next-Gen AI SUV Coupe will launch simultaneously in 64 countries and regions. XPENG is building its native in-car navigation system using Google Maps’ Auto SDK for vehicles outside China, which I’m sure MANY of you will be excited about. First in APAC to Adopt Google Maps Auto SDK XPENG is the first automaker from the APAC region to ship a vehicle with Google Maps Auto SDK integration. Instead of using your smartphone for basic screen mirroring, drivers get a native, custom in-car map application designed entirely by XPENG and powered directly by Google Maps. This integration brings: Real-time precision: Live traffic-aware guidance and highly accurate place search. Smart EV routing: Direct in-car EV energy estimation and trip planning. Native control: Full compatibility with voice control and multi-screen display transfer. Laying the Foundation for Global Autonomous Driving This partnership goes beyond finding directions. XPENG is officially utilizing Google Maps' in-vehicle Map Data Services to support its flagship full-scenario ADAS, Next Generation Pilot (NGP), as well as its foundational assist system, XPILOT ASSIST. To scale XPENG's advanced driving systems internationally, future applications of NGP (VLA 2.0) must rely on highly accurate map data and navigation maneuvers. Google Map Data Services will serve as the cornerstone for this phased global rollout, excluding markets in the Commonwealth of Independent States (CIS). Think of it as a fusion of XPENG’s technology with Google Maps Technology to get a more robust, intelligent, powerful, and safe autonomous driving experience. Overseas users of the XPENG L03 will be the very first to experience this upgraded, Google-powered native navigation system. My Thoughts I personally love and use Google Maps, so I’m glad to see this partnership, and I find it really neat how XPENG and Google Maps technology will work together. What are your thoughts and questions on XPENG integrating Google Maps natively to power its global self-driving tech? Let me know in the replies, and I will try to find the answers to your questions.

BREAKING - EARLY EXCLUSIVE: XPENG Partners with Google Maps to Fuel Global Expansion The global autonomous driving landscape is becoming even more competitive! XPENG has announced a milestone global partnership with Google Maps, bringing a complete refresh of its in-car navigation and advanced driver assistance systems (ADAS). This major upgrade will come standard in the newly debuted XPENG L03. At the official launch event for the L03 in Munich, Germany, XPENG Chairman and CEO He Xiaopeng announced that the Next-Gen AI SUV Coupe will launch simultaneously in 64 countries and regions. XPENG is building its native in-car navigation system using Google Maps’ Auto SDK for vehicles outside China, which I’m sure MANY of you will be excited about. First in APAC to Adopt Google Maps Auto SDK XPENG is the first automaker from the APAC region to ship a vehicle with Google Maps Auto SDK integration. Instead of using your smartphone for basic screen mirroring, drivers get a native, custom in-car map application designed entirely by XPENG and powered directly by Google Maps. This integration brings: Real-time precision: Live traffic-aware guidance and highly accurate place search. Smart EV routing: Direct in-car EV energy estimation and trip planning. Native control: Full compatibility with voice control and multi-screen display transfer. Laying the Foundation for Global Autonomous Driving This partnership goes beyond finding directions. XPENG is officially utilizing Google Maps' in-vehicle Map Data Services to support its flagship full-scenario ADAS, Next Generation Pilot (NGP), as well as its foundational assist system, XPILOT ASSIST. To scale XPENG's advanced driving systems internationally, future applications of NGP (VLA 2.0) must rely on highly accurate map data and navigation maneuvers. Google Map Data Services will serve as the cornerstone for this phased global rollout, excluding markets in the Commonwealth of Independent States (CIS). Think of it as a fusion of XPENG’s technology with Google Maps Technology to get a more robust, intelligent, powerful, and safe autonomous driving experience. Overseas users of the XPENG L03 will be the very first to experience this upgraded, Google-powered native navigation system. My Thoughts I personally love and use Google Maps, so I’m glad to see this partnership, and I find it really neat how XPENG and Google Maps technology will work together. What are your thoughts and questions on XPENG integrating Google Maps natively to power its global self-driving tech? Let me know in the replies, and I will try to find the answers to your questions.

M. Brandon Lee | THIS IS TECH TODAY

65,878 просмотров • 1 месяц назад