AMD CEO Lisa Su said on July 24 that the artificial intelligence accelerator market is expected to reach $1.4 trillion by 2030. AI accelerators are specialized chips built for AI workloads, including matrix operations used in deep learning, and are designed to handle large-scale parallel tasks with much higher efficiency and energy performance than traditional CPUs. Mainstream products in the segment include Nvidia GPUs and custom ASICs made by companies such as Broadcom. These chips form the core compute layer behind the training and inference of large language models and other advanced AI systems. The comments point to the scale AMD expects for demand in specialized AI hardware over the rest of the decade.
AMD CEO Lisa Su said on July 24 that the artificial intelligence accelerator market is expected to reach $1.4 trillion by 2030.
AI accelerators are specialized hardware designed for AI computing, including matrix operations used in deep learning. They can process massive parallel workloads with far greater efficiency and energy performance than traditional CPUs.
Mainstream categories include Nvidia GPUs and custom ASICs produced by companies such as Broadcom. These chips serve as the core compute foundation for training and inference in large AI models.
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