With respect to consumption, the report entails details about volume share and valuation, while deciphering the price trends over the forecast period. Information regarding import and export patterns across various geographies is provided in the report. Speaking of production, the study discusses the manufacturing of product, raw material procurement cost, and profit margins amassed by the key Deep Learning Chipsets market players, along with variations in unit cost offered by these manufacturers in several regions. More importantly, the report encompasses a detailed projection about the consumption and production patterns displayed by the Deep Learning Chipsets market in the upcoming years.

Artificial intelligence (AI) technology is progressing at a rapid pace, as is the application of the technology to solve real-world problems. While the market for chipsets to address deep learning training and inference workloads is still a new one, the landscape is changing quickly – in the past year, more than 60 companies of all sizes have announced some sort of deep learning chipset or intellectual property (IP) design. A new report from Tractica finds that virtually every prominent name in the technology industry has acknowledged the need for hardware acceleration of AI algorithms and the semiconductor industry has responded by offering a wide variety of solutions. Tractica forecasts that the market for deep learning chipsets will increase from $1.6 billion in 2017 to $66.3 billion by 2025. System-on-a-chip (SoC) accelerators such as those found in mobile devices will lead the market in terms of sheer volumes by the end of the forecast period, followed by application-specific integrated circuits (ASICs) and graphics processing units (GPUs).