Sources familiar with the matter revealed that the CEO of UAES has joined Momenta.
The century-old automotive industry is standing at a watershed moment of transformation. The wave of electrification has passed its period of rapid expansion, and industry competition has fully shifted to the second half of intelligentization. Price wars continue to squeeze profits across the industry chain, the bottlenecks of distributed electronic and electrical architectures are becoming increasingly apparent, and software-defined vehicles are moving from concept to core competitiveness for vehicle manufacturers.
Xiong Weiming has a keen insight into industry trends. He has repeatedly pointed out in public that with the increasing penetration rate of new energy vehicles and the determination of OEMs to “go all in” on intelligentization, the underlying logic of the automotive industry is undergoing a fundamental change. “Previously, software served hardware; now it is increasingly becoming clear that hardware is serving software.” This statement accurately summarizes the characteristics of the “software-defined vehicle” era.
Xiong Weiming spearheaded a major upgrade of UAES’s Electronic and Electrical Architecture (EEA). He proposed that the new infrastructure for intelligent vehicles should be based on a cross-domain integrated “centralized computing + regionalization + SOA (Service-Oriented Architecture)” solution.
In October 2024, the Taicang New Energy Vehicle Powertrain Project, facilitated by Xiong Weiming, was officially completed. With a total investment of 5.05 billion yuan, the project is designed to produce 1.2 million drive motors and 3.6 million power modules annually, and is considered a key node in the Yangtze River Delta’s new energy vehicle industry chain.
In July 2022, under his leadership, UAES and Neusoft Reach reached a strategic cooperation agreement to jointly develop automotive basic software solutions involving SOA middleware and automated testing technologies. In 2024, he also conducted a technical inspection with senior executives of the Bosch Group to further deepen supply chain collaboration in the new energy field.
Currently, digital AI has become a highly competitive market, while physical AI is just beginning. Digital AI (such as GPT) experienced initial explosive growth because internet data is readily available and testing costs are low; while physical AI faces difficulties in data acquisition and has long testing cycles. However, the physical world “may be a much larger part,” so the successful experiences of digital AI will inevitably migrate to the physical world.
Autonomous driving is the first real-world application of physical AI. Momenta has launched the Momenta R7 World Model, a foundational model for physical AI, comprising a three-layer architecture: world model pre-training, world model simulation, and world model reinforcement learning.
Currently, Momenta possesses data from 1 million mass-produced vehicles and 100 million data points extracted from over 12 billion kilometers of real-world driving mileage. It trains its model with all the knowledge of the digital world, compressing physical common sense and causal relationships into the foundational model through massive amounts of real-world driving data videos, enabling the system to form a basic understanding of the physical world.
It took Momenta two years to deliver its first 100,000 vehicles; now, it has shortened the delivery time to less than 40 days for a similar scale of delivery. From its launch in 2017 to mass production by the end of 2025, it took eight years, but the pace has significantly accelerated after the breakthrough. In 2024, Momenta acquired all of Mercedes-Benz’s electric and gasoline vehicle business.
The core of physical AI is the mutual driving force between data scaling and business scaling. Autonomous driving is currently the only physical AI field that can achieve both of these simultaneously, and Momenta has initially run this cycle through 1 million mass-produced vehicles.
