On November 7th, Xiaopeng P7+was launched, which is the world's first AI car. At 24:00 that evening, more than 30000 orders were obtained, and the server was once "overwhelmed". Currently, the cycle of changes in automobiles is becoming shorter and even showing the characteristics of overlapping changes. The past changes have not yet been completed, and new changes have begun. This kind of overlapping development has become the new normal of the automotive industry, and the entire automotive industry has entered a new competitive landscape, with the latest driving factor being artificial intelligence At the recently held Global Intelligent Vehicle Industry Conference, Zhang Yongwei, Vice Chairman and Secretary General of the China Electric Vehicle Hundred People's Association, said. Starting from this year, Xiaopeng Motors has clearly defined its development direction for the next 10 years, which is to become a global AI automotive company. At Xiaopeng AI Technology Day, Xiaopeng Motors Chairman and CEO He Xiaopeng shared the Xiaopeng AI system. What is an AI car? Firstly, high-level autonomous driving assistance is required as standard, and intelligent driving technology will undoubtedly change our way of transportation. Secondly, it relies on constantly evolving AI capabilities, which is a very important point in defining AI cars, "explained He Xiaopeng." Once AI becomes the standard or foundational capability for cars, its scalability value will be very significant, which is of great significance to Xiaopeng Motors and even the entire automotive industry. "AI has become an important tool for achieving uniqueness and differentiation in automotive products. In the stage of electrification, product competition focuses more on the performance of the power system; as the three electric technologies approach maturity and gradually form universal technologies, the performance gap between new energy vehicles is becoming smaller and the user experience is gradually converging. However, AI will also promote new differentiation in automotive intelligence. Xu Luman, Deputy Secretary General of the China Electric Vehicle Hundred People's Congress, believes that differentiation will revolve around two tracks. The first track is intelligent driving, dedicated to solving the problem of how cars can "drive better"; The second track is the intelligent cockpit, which solves the problem of how to make the interior of the car "more fun and user-friendly". The newly released "AI Automotive Development Report (2024) - AI Defined Cockpit" shows that the development of AI automotive cockpits will be divided into three stages. The 1.0 stage mainly focuses on human-computer interaction to enhance user interaction experience. At this stage, cars still embody their attributes as a means of transportation; The 2.0 stage is the evolution of intelligent cockpits, which can integrate the stacked functional configurations of cockpits into atomized function pools and provide one-stop services through personalized orchestration; In the 3.0 stage, it is possible to achieve functional calling at the vehicle level, making cars intelligent partners of humans. At the same time, AI is also penetrating into the automotive manufacturing, testing, and service sectors. In terms of product development and production, efficient data processing, intelligent visual inspection, digital labeling, and other means can be used to improve development efficiency and reduce costs; In terms of product functionality, through algorithm optimization and data mining, we aim to achieve a higher level of intelligent experience; In terms of enterprise management, accelerate the promotion of comprehensive, accurate, and efficient decision-making recommendations through data analysis, intelligent sales, intelligent services, and other links. NIO's second advanced manufacturing base has a 90 kilometer 100 GB fiber optic ring network and a large amount of data collection, making it a globally leading fully digitized intelligent factory NIO founder, chairman, and CEO Li Bin told reporters that "the company started using AI tools to generate code last year, which increased production efficiency by about 30%; in the production and welding process, AI intelligent sampling is used, and the accuracy can be improved to 0.1 millimeters; there are more than 20 speakers in a car, and AI is used for intelligent audio and video detection, which is both efficient and accurate." Faced with new challenges in computing power and standards, from AI empowerment to AI definition, China's automotive industry has taken the lead in research and development innovation, user experience, ecological construction, and other aspects globally. However, the AI driven industrial intelligence transformation requires huge investment, and the competition threshold is gradually increasing. The competition is not only about cognition and speed, but also about the strength of enterprises. In the era of artificial intelligence, what the automotive industry lacks the most is intelligent computing infrastructure, not production capacity Zhang Yongwei believes that the current lack of intelligent computing infrastructure has become the primary challenge for the development of automotive AI. Intelligent computing "refers to the computing power in the field of intelligence. With the deep integration of automobiles and AI, the demand for intelligent computing power in the industry is rapidly increasing as end-to-end intelligent driving, cockpit models, and other technologies accelerate their entry into vehicles. Without a computing power cluster of thousands or even tens of thousands of cards, and without sufficient computing power, algorithm, and data teams, it is difficult for enterprises to form competitiveness in the new track, "Zhang Yongwei admitted. Currently, the total computing power of all domestic car companies is not as good as Tesla's 100EFLOPS (billions of floating point operations per second) computing power. Unlike intelligent driving, the concept of intelligent cockpit has only become widely known in the past two years. As an emerging field, the intelligent cockpit itself is complex and non standardized, with rapid technological and product iteration. The current iteration of the functions of the car cockpit and operating system requires enterprises to accelerate the establishment of standardized technical platforms, unify the operating environment and various interface standards. Wang Rong, director of the Intelligent Connected Vehicle Product and System Evaluation Room of the China Software Evaluation Center, has repeatedly mentioned the word "standard". Liu Li, CTO of Shenzhou Digital Automotive Business Group, has a deeper appreciation for the urgency of establishing standards: "Whether you are in or out of the car, you need to interact with the car, and cars also need to interact with each other. This interaction framework is completely different from the current framework of mobile app stores, and standards are urgently needed." "We have been actively promoting the adoption of local operating systems to achieve large-scale applications in recent years. The autonomy and controllability of automotive operating systems is a strategic issue," said Zhang Yongwei. How to build new competitiveness With the accelerated integration of artificial intelligence and automobiles, mainly represented by big computing power, big data, and big models, the technological highland of the automotive industry and the strategic competitive pivot of automotive enterprises are shifting towards AI driven intelligence. This requires us to focus on the value of AI technology and data to create new competitiveness Zhang Yongwei said that domestic enterprises need to start from the perspective of data and solve two core problems: on the one hand, they need to make data the core asset and element of the enterprise, create value through data, and change the current situation of insufficient data mining capabilities and underutilization of data value in automotive enterprises. On the other hand, we need to address the synergistic effects of data. In terms of training software and systems, relying solely on the data volume of a single car company is not enough. In the AI era, competitiveness relies on data stacking, and the problem of large-scale data must be solved. This requires innovative mechanisms to promote data aggregation, so that enterprises can invest and use data for platforms according to market-oriented principles, and solve the problem of small data scale at present, "said Zhang Yongwei. The development of AI cars also requires support from chips, basic software, and other cross-border technologies. The most important hardware for the development of artificial intelligence, including the development of automobiles themselves, is chips, and the demand for chips is increasing. From a strategic perspective, the development of intelligent connected vehicles in China must solve the problem of localized supply of automotive chips. Zhang Yongwei believes that it is crucial to solve the problem of localized supply of automotive chips in different fields, steps, and stages, especially in the research and manufacturing of high computing chips. The intelligent new energy vehicle industry chain covers multiple fields such as software, hardware, system integration, and artificial intelligence. The industry boundaries are facing restructuring, and in the future, automobiles will develop into green and intelligent mobile living spaces. Open cooperation and cross-border integration are the only way for automobile enterprises to develop Li Ming, General Manager of Anhui Jianghuai Automobile Group Co., Ltd., said. It is impossible for car companies to achieve the integration development strategy of artificial intelligence and automobiles. The biggest advantage of China is that it has a large number of cross-border forces that can empower and connect cars beyond the automotive industry. These forces have strong individual capabilities in technology, models, software, networks, including hardware. When these capabilities are linked to cars, they become the capabilities of cars Zhang Yongwei said. At present, many vehicle manufacturers and chip companies have begun to jointly create intelligent driving solutions, and some vehicle manufacturers have begun to build a software ecosystem for the automotive industry with leading software companies. This is an important practice to explore the co creation and symbiosis model between car companies and cross-border enterprises. (New Society)