Pony.ai Launches PonyWorld 2.0, a Self-Improving Physical AI Engine for Autonomous Driving - New world model upgrade enables AI to diagnose its own weaknesses, guide targeted data collection, and support the next phase of large-scale L4 commercialization GUANGZHOU, China, April 10, 2026 /PRNewswire/ -- Pony AI Inc. ("Pony.ai") (NASDAQ: PONY; HKEX: 2026), a global leader in the large-scale commercialization of autonomous driving technology, today announced the launch of PonyWorld 2.0, the latest upgrade to its proprietary world model and a major advancement in the core training system behind the company's autonomous driving stack. PonyWorld 2.0's most important advance is its ability to diagnose its own weaknesses and guide targeted improvement. The upgrade brings three core capabilities: self-diagnosis, targeted data collection in scenarios where the model still falls short, and more efficient training focused on the hardest cases. The launch comes as the autonomous driving industry enters a new commercial phase. The challenge is no longer just proving that driverless technology works. It is now about improving performance quickly and consistently enough to support broader deployment, stronger unit economics, and sustained technical leadership. Since 2020, Pony.ai has been building PonyWorld not as a basic simulation tool for generating synthetic data, but as a full reinforcement learning training system spanning cloud-side training and vehicle-side deployment. As the system matured, improving the capabilities of Pony.ai's "Virtual Driver" increasingly came to depend on improving the world model that trains it, particularly its ability to represent real-world dynamics and interactions with sufficient accuracy and realism. "PonyWorld 2.0 is an important step toward a more self-improving approach to autonomous driving development," said Dr. Tiancheng Lou, Founder and CTO of Pony.ai. "As AI systems become more capable, they can play a larger role not only in learning to drive, but also in guiding their own improvement —