$Pony AI(PONY.US)

1) Emerging automakers, with their advantages in vehicles and data, along with strong R&D awareness, are rapidly improving their autonomous driving capabilities (e.g., TESLA, XPeng, Li Auto, Xiaomi). Meanwhile, traditional automakers like BYD are also developing their own autonomous driving systems. Automakers with slower progress can collaborate with ecosystems like Huawei and Horizon Robotics to directly acquire first-class, deployable autonomous driving capabilities (Huawei has pledged not to manufacture cars but to act as a supplier). Will pure autonomous driving software algorithm developers still have commercial space to acquire automaker clients in the future?

2) If the future vision is not to sell algorithms to automakers but to operate their own robotaxi fleets, it's worth noting that emerging automakers have already made significant breakthroughs and deployments in urban NOA. Once urban NOA becomes fully mature in the next 2-3 years, will these automakers consider operating their own robotaxi fleets to gather more data? After all, producing more vehicles can reduce per-unit costs, and the collected data can further enhance autonomous driving capabilities. A robotaxi fleet also naturally serves as brand promotion and consumer outreach—a win-win scenario. Pure autonomous driving software algorithm developers cannot manufacture vehicles, face higher vehicle procurement costs, have less historical data, and lack experience in heavy-asset, heavy-operation businesses. How will they compete with robotaxi fleets backed by automakers? (Note: The impact of robotaxis on internet ride-hailing platforms like Uber and DiDi is also a topic worth discussing.)

3) For robotaxis to achieve large-scale commercial deployment, there will likely be national/industry 准入 standards. Without standards, large-scale deployment is unlikely. Logically, only after standards are established can companies that meet them operate robotaxi businesses. One major hurdle for autonomous driving deployment today is unclear boundaries—when accidents occur, it's unclear who is responsible. If national/industry standards are implemented, they would help clarify these boundaries: algorithm providers are responsible for accidents within the boundaries, but not for those outside. Further, clear 准入 standards and boundaries would significantly lower the barrier for autonomous driving companies to enter the robotaxi market. With everyone developing to meet the standards, at least 5-10 companies could compete, quickly leveling technological differences (as long as standards are met). Robotaxis would then become an industry reliant on government relations, heavy assets, and operations. Companies would invest capex in vehicles and operational teams, and with little differentiation in algorithms, price wars could erupt quickly. For instance, if Company A prices for an 8% annualized return, Company B might lower it to 5% to capture market share—still above interest rates but quickly driving returns down to survival levels with no 超额 profits.