North America Deep Learning Chip Market Research to 2027 | Get Free Trial Access

Deep Learning Chip Market 2020 Global Industry research report explores analysis of historical data along with size, share, growth, demand, revenue and forecast of the global Deep Learning Chip and estimates the future trend of market on the basis of this detailed study. The study shares market performance both in terms of volume and revenue and this factor which is useful & helpful to the business.

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Driving factor such as the rising investments in deep learning chip start-ups is propelling the growth of the . Further, the increasing adoption of cloud-based computing across several industries is anticipated to boost the deep learning chip market growth in the near future. 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 industries in artificial intelligence and its capabilities to transform business processes. Some of the important developments in the start-up landscape include, in May 2019, Hailo Technologies Ltd. an Israeli private limited company launched the first of their deep learning processors named Hailo i-8 chips. This chip is expected to provide 26 tera operations per second (TOPS). In November 2019, Intel Corporation grew its prominence in artificial intelligence with the launch of its Nervana Neural Network processors for deep learning.

The deep learning chip market is segmented on the basis of chip type into GPU, ASIC, FPGA, CPU, and Others. During the forecast period of 2019 to 2027, the GPU chip type is anticipated to be the largest contributor in the deep learning chip market. However, the ASIC segment is projected to be the fastest-growing chip type with the highest CAGR over the forecast period.

The US dominated the deep learning chip market in 2018 and is expected to dominate the market with the highest share in the North America region through the forecast period. The US holds major share of the total spending in the deep learning chip technology. The growth in the deep learning chip market in the US is mainly driven by considerable growth of tech start-ups each year, which are funded by several capitalists, thereby increasing the scope of the market. The companies in the market are developing a dedicated platform for AI and its sub-sets. For instance, in March 2017, Mythic, a US-based AI platform provider, launched an AI platform that provides the benefits of processing analog/digital calculations in memory, which leads to improved performance, power life, and accuracy of various devices. The above-mentioned factors are, therefore, contributing to the growth of the deep learning chip market in the country. The figure given below highlights the revenue share of the Mexico in the deep learning chip market in the forecast period:

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NORTH AMERICA DEEP LEARNING - CHIP MARKET SEGMENTATION

NORTH AMERICA DEEP LEARNING - By Chip Type

GPU
ASIC
FPGA
CPU
Others

NORTH AMERICA DEEP LEARNING - By Technology

System-on-Chip
System-in-Package
Multi-chip Module
Others

NORTH AMERICA DEEP LEARNING - By Industry Vertical

Media & Advertising
BFSI
IT & Telecom
Retail
Healthcare
Automotive & Transportation
Others

NORTH AMERICA DEEP LEARNING - By Country

US
Canada
Mexico

Deep Learning Chip Market - Companies Mentioned

Advanced Micro Devices, Inc.
Amazon.com, Inc.
Huawei Technologies Co., Ltd.
Baidu, Inc.
Alphabet Inc. (Google)
Intel Corporation
NVIDIA Corporation
Qualcomm Technologies, Inc.
Samsung Electronics Co. Ltd.
Xilinx Inc.

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