What is the difference between an embedded processor and an AI chip?
With the birth of AlphaGo, "deep learning" has become increasingly popular, and artificial intelligence has begun to evolve from intelligent tools to smart machines. The original MCU has been unable to meet the high-speed massive data computing requirements for deep learning, and the AI chip came into being. The embedded chip field is now facing a new round of opportunities for AI chips.
Some people think that there is no AI chip, and it may be considered that the AI chip is only a function extension of the original embedded processor. However, I don't know that as the function of the embedded processor continues to expand, it has changed qualitatively. Since the era of artificial intelligence entering the deep learning of machines, the hardware acceleration of the original MCU has been unable to meet the requirements of high-speed massive numerical calculations and the inter-cloud interaction requirements of big data. In this way, in the embedded field, there are two chipsets with MCU and AI chips that are fundamentally different. The former is an intelligent control chip that satisfies the intelligence of the tool (in terms of control); the latter is a computing chip that satisfies the deep learning of intelligent machines (in terms of calculation).
In the future, in the field of artificial intelligence, two areas of intelligent tools and intelligent machines will gradually be formed. At present, the field of intelligent tools has matured, and the field of intelligent machines relies on AI chips, neural networks, deep learning, and inter-cloud interactions to gradually move toward strong artificial intelligence. Since the era of artificial intelligence entering the deep learning of machines, the hardware acceleration of the original MCU has been unable to meet the requirements of high-speed massive numerical calculations and the inter-cloud interaction requirements of big data. As the functions of embedded processors continue to expand, they have undergone qualitative changes.
In the embedded field, there are two chipsets with MCU and AI chips that are fundamentally different. The former is an intelligent control chip that satisfies the intelligence of the tool (in terms of control); the latter is a computing chip that satisfies the deep learning of intelligent machines (in terms of calculation). In the future, in the field of artificial intelligence, two areas of intelligent tools and intelligent machines will gradually be formed.
Taking face recognition as an example, real-time face recognition for access control may use the MCU+ graphics accelerator solution. However, in order to identify specific faces from many people in real time, it is necessary to introduce deep learning and continuously improve their recognition ability; in order to compare with many faces, it also needs to interact with cloud big data, no matter how brilliant MCU can not bear such a heavy responsibility. .Perhaps "deep learning" and "cloud interaction" are two important features of the AI chip.
Andreas Nuernberger, a professor at the University of Magdeburg in Germany, said: "I agree with the idea that there is no artificial intelligence chip. Now the development of the chip has accelerated the process of deep learning. Previously, there was such deep learning in terms of images. You now call them artificial intelligence chips, but this is a product that is produced for a specific purpose. I think the Internet of Things can make the process more reliable and ensure that these networks and hardware react faster more reliable and more dynamic. I think these are the real worlds of smart hardware, but they are costly because you need more complex infrastructure and more technology, which is different from before."
At present, the competition in the field of AI chips is fierce. It may be difficult to form a unified structural system at the moment. However, after gradually improving, as a new recruit in the embedded field, it complements and complements the MCU in the field of artificial intelligence. They cannot be replaced by each other and have different technological development directions. MCUs and AI processors are used in different fields, and both have great potential for development.
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