The technological impact of AI on the semiconductor industry: Changes in chip structure

Artificial intelligence has become the hottest topic now, it seems that AI can greatly change our social status quo and bring science and technology into a new era. I think this change is definitely, all walks of life will have some earth-shaking changes. It's like with guns, swords become fitness equipment. With cars, equestrian became a competitive sport. As a tool to implement AI, the chip must first make changes for AI.

1, The change of chip structure

With the continuous improvement of the industry's demand for computing power, more and more computing platforms began to introduce a variety of different computing units such as CPU, GPU, ASIC, FPGA to accelerate calculation, thus, heterogeneous computing came into being. The core point of Heterogenous computing is the word "heterogeneous Heterogenous computing", which is to use different process architectures, different instruction sets, and hardware with different functions to improve the computing power level. In the SoC market, traditional high-performance Gpus, cpus or FPGas have significantly migrated to heterogeneous platforms. Heterogeneous computing represents a major trend in the semiconductor market, enabling AI and machine learning to be deployed at scale in countless applications across various industry segments.

Most major microcontroller vendors have publicly announced that even MCUS (Micro Controller units) will be affected by AI. St, Renesas Electronics and NXP have announced a new family of MCUS designed to support the huge demand for optimized edge devices in the iot world. These components will have machine learning capabilities optimized for high efficiency, low power consumption and low cost.

2，ASIC optimization components are rolled out to networks and endpoints

Amid the rise of the AI market, the ASIC market is booming, driven by several start-ups. It aims to provide a completely new architecture in terms of processing power and memory interface, challenging traditional architectures (CPU, GPU, FPGA, DSP) in terms of optimized performance.

The business model of each company can be very different, for example, the independent coprocessor market, the highly integrated ip core market. Although the size of the market is different, and there is a lot of uncertainty about the development of the industry, a lot of money and opportunity are poured into research and development efforts to improve processor power and speed. When disruptive technologies spawn new markets, there are bound to be many opportunities and challenges. The integrated circuit market for artificial intelligence is bound to consolidate. This means that in the next 10 years, new industry giants will be born, but only a few companies may survive.

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