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AI+ dianshangCompared with traditional chips, AI chips have more efficient parallel computing capability, powerful floating-point computing capability, power consumption and energy saving performance, and low latency. The existence of AI chip can meet the requirements of large-scale data processing and complex model training. AI chips also have a downstream industrial chain. A large number of enterprises apply AI chips to smart phones and smart devices, self-driving cars, data centers and cloud computing, edge computing and the Internet of Things. With the expansion of application scenarios, AI chips will also play an increasingly important role in the future wave of technology.Application of AI in other fields

AI chip is an integrated circuit chip, which is specially used to deal with a large number of computing tasks in artificial intelligence applications, including machine learning, deep learning and other tasks related to AI algorithm.AI refers to the use of AI technology to enhance and improve the efficiency and quality of education. AI education includes personalized learning content push, intelligent teaching, auxiliary evaluation, special education, educational resource management, virtual reality (VR) and augmented reality (AR), evaluation and feedback automation, and intelligent tutoring system. The application of AI technology is gradually conceiving the traditional teaching mode, which brings more opportunities and challenges to schools and teachers. In fact, many universities have designed many achievements in AI+ higher education. For example, Beijing University of Posts and Telecommunications's big model-enabled intelligent programming teaching application platform "code", Beijing Normal University's innovative "AI+" classroom teaching intelligent evaluation, and Huazhong University of Science and Technology's intelligent academic early warning and collaborative assistance mechanism.In the future, we hope to see the integration of reality and reality and a new teaching paradigm of "teacher, student and machine" interaction.

Take intelligent driving as an example. In the process of intelligent driving, under the machine learning and deep learning, the AI algorithm has the driving strategy of the vehicle. AI algorithm can predict the trajectory of other vehicles by further processing and analyzing the perceived information. At the same time, according to the analysis of the current situation of the vehicle, the next step is completed by controlling braking, acceleration and steering.Gao Xinxing, Yutong Optics, Desai Siwei, Qianfang Technology, Qiming Information, Digital Zhengtong, Jiadu Technology, Siwei Tuxin, Zhonghaida, Wanji Technology, Dahua Co., Huayang Group, Baolong Technology, Jingwei HengrunConcept stocks: