Maharashtra, India -- (SBWire) -- 10/18/2018 --Deep Learning Chipsets Market

Summary

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. 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 range of solutions.

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The edge computing market, where AI computation is done on the device, is expected to represent more than three-quarters of the total market opportunity, with the balance being in cloud/data center environments. Mobile phones will be a major driver of the edge market, and other prominent edge categories include automotive, smart cameras, robots, and drones.

This Deep Learning Chipsets market research report provides the existing competitive analysis of some of the major players profiled in the market, which includes: Google, Intel, Xilinx, AMD, NVIDIA, ARM, Qualcomm, IBM, Graphcore, BrainChip, Mobileye, Wave Computing, CEVA, Movidius, Nervana Systems, Amazon, Cerebras Systems, Facebook.

Key Regions for this market: North America, Europe, APAC, Latin America, and the Middle East & Africa.

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Global Deep Learning Chipsets Market: Type Outlook: CPUs, GPUs, FPGAs, ASICs, SoC Accelerators, Others.

Global Deep Learning Chipsets Market: Application Outlook: Automotive, Smart Cameras, Robots, Drones, Mobile Phones, Others.

Technological Advancements

The latest and advanced technologies used in the Deep Learning Chipsets Market can be helpful for collaborative seminars, meetings, lectures, and training for industry professionals. Furthermore, in order to introduce advanced products or solutions, leading competitors are expected to concentrate on product innovation through continuous investments in product development.

Key questions answered in the report include:

What will the market size and the growth rate by the end of the forecast period?
What are the key industry trends impacting the growth of the market?
What are the key factors driving and restraining the Deep Learning Chipsetsmarket?
What are the challenges to market growth?
What are the market opportunities and threats faced by the key players in the market?
Who are the leading competitors functioning in the market for Deep Learning Chipsets?
What are the key outcomes of Porter's five forces analysis of the Deep Learning Chipsetsmarket?
The study objectives of this report are:

To analyze global Deep Learning Chipsets status, future forecast, growth opportunity, key market and key players.

To present the Deep Learning Chipsets development in United States, Europe and China.

To strategically profile the key players and comprehensively analyze their development plan and strategies.

To define, describe and forecast the market by product type, market and key regions.

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In this study, the years considered to estimate the market size of Deep Learning Chipsets are as follows:

History Year: 2013-2017

Base Year: 2017

Estimated Year: 2018

Forecast Year 2018 to 2025

For the data information by region, company, type and application, 2017 is considered as the base year. Whenever data information was unavailable for the base year, the prior year has been considered.