


Gartner predicts that global AI chip revenue will reach US$53 billion by 2023 and US$119.4 billion by 2027
News on August 24, according to the latest forecast from market research company Gartner, Global hardware sales revenue for AI is expected to increase by 20.9% year-on-year in 2023, reaching 53.4 billion US dollars (currently approximately 388.752 billion yuan) .
According to Gartner, the growth of generative AI and the widespread use of various AI-based applications in data centers, edge infrastructure and endpoint devices will require the use of GPUs and optimized semiconductor devices for deployment , which will drive the production and deployment of artificial intelligence chips
The content that needs to be rewritten is: ▲ Figure source consulting firm
Gartner estimates that AI semiconductor revenue Will continue to maintain double-digit growth during the forecast period, will grow 25.6% in 2024, reaching 67.1 billion US dollars (notes on this site: currently about 488.488 billion yuan), by 2027, AI chip revenue is expected to be higher than 2023 The market size has more than doubled in 2016, reaching US$119.4 billion (currently approximately RMB 869.232 billion).
What needs to be rewritten is: ▲ Figure source consulting company
Gartner said that as the use of AI workloads in enterprises matures, many more of industries and IT organizations will deploy systems containing AI chips. In terms of the consumer electronics market, Gartner estimates that the value of AI-enabled application processors for devices will reach US$1.2 billion by the end of 2023 (currently approximately 8.736 billion yuan), compared with US$558 million in 2022 (currently approximately 4.062 billion yuan) Yuan RMB).
Gartner believes that the need for efficient and optimized designs that support cost-effective execution of AI workloads will lead to an increase in the deployment of custom-designed AI chips. For many organizations, large-scale deployment of custom AI chips will replace the current dominant chip architecture, Discrete GPUs, for a variety of AI workloads based on generative AI technologies.
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