deep learning chip Market

The global deep learning chip market accounted for US$ 2.04 Bn in 2018 and is expected to grow at a CAGR of 30.0% over the forecast period 2019-2027, to account for US$ 21.31 Bn in 2027.

The increasing investments in deep learning chip start-ups, prominence of quantum computing, and real time consumer behavior insights & increased operational efficiency are few of the factors driving the deep learning chip market worldwide. However, lack of infrastructure & technology know-how in third world countries and dearth of skilled workforce may restrain the future growth of market. Despite these limitations, rising adoption of cloud-based computing across industries is anticipated to offer ample growth opportunities for the players operating in the deep learning chip market during the forecast period.

Deep learning chips are being utilized extensively in numerous areas ranging from cloud computing applications to digital assistants and self-driving/autonomous vehicles. With ever increasing use cases of AI and the evolving market landscape, the advancements in present chips have become a necessity. Deep learning chip is majorly used in data center training market where NVIDIA is a market leader. However, the demand for application-specific custom deep learning chips and inference on edge and data center are the fast-growing segments in deep learning chip market, and many new startups are coming up to tap this market. The innovative technologies and solutions offered by these start-ups are going to intensify the competition in the deep learning chip market. The funding scenario is looking good for these startups majorly due to huge interest of global industries in artificial intelligence and its capabilities to transform business processes. Few of the noteworthy startups are mention in the table below with a brief on the technology they are working. The upcoming chips are expected to have higher performance per unit of power versus traditional CPUs and GPUs offered by market giants like by Intel and NVIDIA respectively.

The market for deep learning chip has been segmented on the basis of chip type, technology, industry vertical, and geography. The deep learning chip market based on chip type is led by GPU segment and is expected to continue its dominance in the forecast period. The deep learning chip market on the basis of technology is segmented into system-on-chip, system-in-package, multi-chip module, others. The System-on-Chip technology led the deep learning chip market and it is anticipated to continue its dominance during the forecast period. The market for deep learning chip by industry vertical is further segmented into media & advertising, BFSI, it & telecom, retail, healthcare, automotive & transportation, and others. The BFSI sector is expected to hold the lion’s share in the year 2018 and is expected to continue its dominance till 2027.
 
The overall deep learning chip market size has been derived using both primary and secondary source. The research process begins with exhaustive secondary research using internal and external sources to obtain qualitative and quantitative information related to the deep learning chip market. It also provides the overview and forecast for the global deep learning chip market based on all the segmentation provided with respect to five major reasons such as North America, Europe, Asia-Pacific, the Middle East and Africa, and South America. Also, primary interviews were conducted with industry participants and commentators in order to validate data and analysis. The participants who typically take part in such a process include industry expert such as VPs, business development managers, market intelligence managers, and national sales managers, and external consultant such as valuation experts, research analysts and key opinion leaders specializing in the deep learning chip market. Some of the players present in deep learning chip market are Advanced Micro Devices, Inc., Amazon Web Services, Inc., Huawei Technologies Co., Ltd., Baidu, Inc., Google, Inc., Intel Corporation, NVIDIA Corporation, Qualcomm Technologies, Inc., Samsung Electronics Co. Ltd., and Xilinx Inc. among others.