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The XPENG P7+ incorporates XPENG's visual-based ADAS advanced AI-defined smart driving solutions, offering expert driver-class handling even in challenging driving scenarios! #XPENGP7Plus #FutureMobility

656,653 次观看 • 1 年前 •via X (Twitter)

2 条评论

IoT Automotive News 的头像
IoT Automotive News1 年前

Awesome 👌

Conner 的头像
Conner1 年前

But its Chinese.

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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 次观看 • 26 天前

NEWS: Waymo has released a new blog post detailing their AI strategy and how it’s allowing them to bring service to more riders faster. "Achieving demonstrably safe AI — where safety is proven, not just promised — requires a holistic approach. Beyond a smart and capable Driver, you also need a closed-loop, realistic Simulator to train and rigorously test the Driver in a myriad of challenging situations, and a sharp Critic to evaluate the Driver's performance and identify areas for improvement." Waymo says that autonomous driving isn’t just a matter of building a “smart driver,” but rather creating a full AI ecosystem centered on safety from the ground up. At the core is the Waymo Foundation Model, a unified world-model that powers all major components of Waymo’s autonomous stack (Driver, Simulator, Critic). "By using a “Think Fast/Think Slow” architecture (combining rapid sensor-fusion with deep semantic reasoning), this system enables the car to detect complex and rare road scenarios (e.g. a burning vehicle ahead), reason about them, and choose safe behavior. Waymo trains large “Teacher” AI-models for driving, simulation, and evaluation, then distills them into smaller, efficient “Student” models suitable for real-world deployment, while keeping safety validation tightly integrated. The result is a continuous “flywheel” of learning: driving data (real and simulated) generate feedback, which leads to refinements, more simulation, more data, and only when safety checks pass is new code deployed. Having already exceeded 100 million fully autonomous miles, Waymo reports a more than ten-fold reduction in severe-injury crashes compared to human drivers." Full blog post:

Sawyer Merritt

83,625 次观看 • 8 个月前