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Ai+transportationCompared 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.AI+ film and television (important aspect: Wensheng video)

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.AI application explosion! The development of AI technology has brought new development opportunities to various industries.AI+ dianshang

Compared 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.Concept stocks: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.