- AI Research Reports
Deep learning (DL) is slowly moving past its hype cycle as proof-of-concept (PoC) AI applications developed in the past two years go into production. AI chipset customers have become more sophisticated in terms of chipset needs for AI application acceleration and are asking for specific benchmarks when talking to vendors. Customers’ needs for chipsets are coming to the forefront, forcing chipset companies to rethink the applicability of their technology. All prominent chip companies, such as Intel, NVIDIA, and Qualcomm, have invested heavily in AI. Cloud companies have started rolling out graphics processing units (GPUs), field-programmable gate arrays (FPGAs), and application-specific integrated circuits (ASICs), giving developers a choice for AI acceleration. Omdia forecasts that global revenue for DL chipsets will increase from $11.4bn in 2019 to $71.2bn by 2025.
This Omdia Market Report assesses the industry dynamics, technology issues, and market opportunity surrounding DL chipsets, including CPUs, GPUs, FPGAs, ASICs, and SoC accelerators. As an update to Omdia’s 2019 Deep Learning Chipsets report, it captures the state of this fast-moving chipset market. Global market forecasts, segmented by chipset type, compute capacity, power consumption, market sector, and training versus inference, extend through 2025. Omdia also provides profiles of 23 key industry players.