The main reasons why artificial intelligence depends on chips are as follows:
Computing power requirements: The implementation of artificial intelligence requires a large amount of computing and processing power, and chips, as the core components of computers, directly affect the performance and performance of artificial intelligence. Performance indicators such as the computing power, memory bandwidth, and data transfer speed of the chip will have a significant impact on the computing speed and accuracy of artificial intelligence.
Algorithm requirements: Artificial intelligence algorithms require a large number of matrix operations and deep learning, which requires the chip to have high-performance processing power and sufficient memory bandwidth to ensure the efficiency and accuracy of the operation. If the performance of the chip is insufficient, it will lead to slower computing speed and even inability to complete complex computing tasks, which will affect the application effect of artificial intelligence.
Energy consumption and cost: The performance and power consumption of chips are also important considerations for the development of artificial intelligence. With the popularization of artificial intelligence applications, the requirements for energy consumption and cost are also increasing. Therefore, how to reduce power consumption and cost, and improve the performance and efficiency of chips are also problems that need to be solved in the development of artificial intelligence.