What is the current AI Chipsets Market size?

The AI Chipsets Market is projected to register a CAGR of 39% during the forecast period (2024-2029) Read More

Who are the key players in AI Chipsets Market?

Samsung Electronics, NVIDIA Corp., Xilinx Inc., Micron Technology Inc. and Intel Corporation are the major companies operating in the AI Chipsets Market. Read More

Which is the fastest growing region in AI Chipsets Market?

Asia-Pacific is estimated to grow at the highest CAGR over the forecast period (2024-2029). Read More

Which region has the biggest share in AI Chipsets Market?

In 2024, the North America accounts for the largest market share in AI Chipsets Market. Read More

What years does this AI Chipsets Market cover?

The report covers the AI Chipsets Market historical market size for years: 2019, 2020, 2021, 2022 and 2023. The report also forecasts the AI Chipsets Market size for years: 2024, 2025, 2026, 2027, 2028 and 2029. Read More

AI Chipsets Market - Size, Share & Industry Analysis

AI Chipsets Market Size & Share Analysis - Growth Trends & Forecasts (2024 - 2029)

The AI Chipsets Market is segmented by Component (Central Processing Unit (CPU), Graphics Processing Unit (GPU), and Neural Network Processor (NNP)), by Application (Consumer Electronics, Automotive, Healthcare, Automation & Robotics), and by Geography.

AI Chipsets Industry Overview

Though some small and large global companies have influenced the market, the AI chipsets market is expected to be moderately consolidated. The market is still in its early stages of development. Some of the prominent participants in the current industry include Intel Corporation, Samsung Electronics, NVIDIA Corp., Xilinx Inc., and Micron Technology. To obtain leading positions in the AI chipsets market, these players are engaged in competitive strategic advancements, such as collaborations, new product innovations, and market expansions.
August 2021 - IBM announced a new chip, Telum, which is expected to allow IBM clients to leverage deep learning inference at scale. This chip features a centralized design enabling clients to leverage the full power of the AI processor for AI-specific workloads, making it suitable for financial services workloads, such as loan processing, clearing and settlement of trades, fraud detection, anti-money laundering, and risk analysis.