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Deep Learning Chipsets Market Entry Strategies, Countermeasures of Economic Impact and Marketing Channels to 2025

Global Deep Learning Chipsets Market Size Growth Rate by Type - CPUs, GPUs, FPGAs

 

Pune, India -- (SBWIRE) -- 10/19/2018 -- Overview of Deep Learning Chipsets Market
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 study report on global Deep Learning Chipsets Market market throws light on the crucial trends and dynamics impacting the development of the market, including the restraints, drivers, and opportunities. A number of analysis tools such as Porter's five forces analysis and SWOT analysis have been employed to provide an accurate understanding of this market.

By geography: -
United States, Europe, China, Japan, Other Regions.

Top Market Players:
Google, Intel,, Facebook, IBM, Xilinx, AMD, NVIDIA, ARM, Qualcomm, Graphcore, BrainChip, Mobileye, Wave Computing, CEVA, Movidius, Nervana Systems, Amazon, Cerebras Systems.

Major Types of Deep Learning Chipsets Market covered are:
CPUs
GPUs
FPGAs
ASICs
SoC Accelerators
Others

Major Applications of Deep Learning Chipsets Market covered are:
Automotive
Smart Cameras
Robots
Drones
Mobile Phones
Others

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Market Scenario:
The report further highlights the development trends in the global Deep Learning Chipsets market. Factors that are driving the market growth and fueling its segments are also analyzed in the report. The report also highlights on its applications, types, deployments, components, developments of this market.

Global Deep Learning Chipsets Market Research Report 2018:
A) Deep Learning Chipsets Market Overview
B) Global Deep Learning Chipsets Market Competition by Manufacturers
C) Global Deep Learning Chipsets Capacity, Production, Revenue (Value) by Region
D) Global Deep Learning Chipsets Supply (Production), Consumption, Export, Import by Region
E) Global Deep Learning Chipsets Production, Revenue (Value), Price Trend by Type
F) Global Deep Learning Chipsets Market Analysis by Application
G) Global Deep Learning Chipsets Manufacturers Profiles/Analysis
H) Deep Learning Chipsets Manufacturing Cost Analysis
I) Industrial Chain, Sourcing Strategy and Downstream Buyers
J) Deep Learning Chipsets Strategy Analysis, Distributors/Traders

Key Reasons to Purchase:
A) To gain insightful analyses of the market and have comprehensive understanding of the global Deep Learning Chipsets market and its commercial landscape.
B) Assess the Deep Learning Chipsets production processes, major issues, and solutions to mitigate the development risk.
C) To understand the most affecting driving and restraining forces in the Deep Learning Chipsets market and its impact in the global market.
D) Learn about the market strategies that are being adopted by leading respective organizations.
E) To understand the future outlook and prospects for Deep Learning Chipsets market.

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Lastly, this report covers the market scene and its development prospects over the coming years, the Report likewise short manages the item life cycle, contrasting it with the significant items from crosswise over ventures that had just been popularized points of interest the potential for different applications, examining about late item advancements and gives a diagram on potential territorial pieces of the pie.

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