Global Deep Learning Chipset Market Growth Analysis of all Industry Key Players Like NVIDIA, Intel, IBM, Qualcomm, KnuEdge, Xilinx, Google and Others 2018 - 2023

Deep Learning Technology is driving the evolution of artificial intelligence (AI) and has become one of the hottest topics of discussion within the technology world and beyond. Given the rate at which deep learning is progressing, some industry observers are predicting it will bring about a doomsday scenario, while others strive for a time when the technology can transform business processes and create new business models through scalable, more efficient automation and predictive capabilities. The current market climate is ripe for innovation in hardware in general, and chipsets more specifically.

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Scope of the Report:
This report focuses on the Deep Learning Chipset in global market, especially in North America, Europe and Asia-Pacific, South America, Middle East and Africa. This report categorizes the market based on manufacturers, regions, type and application.
United States has the largest global export quantity and manufacturers in Deep Learning Chipset market, while the EU is the second sales volume market for Deep Learning Chipset in 2016.
In the industry, NVIDIA profits most in 2016 and recent years, while Intel and IBM ranked 2 and 3.The market share of them is 26.72%, 20.57% and 12.56% in 2016.The gap of market share is keep on enlarged due to different strategy.
Deep Learning Chipset technology is not mature now, and new enterprises can not surpass existing famous brands on reputation or design in the short term. So, the study group recommends the new entrants need to be considered carefully before enter into this field.
The worldwide market for Deep Learning Chipset is expected to grow at a CAGR of roughly 39.1% over the next five years, will reach 6310 million US$ in 2023, from 870 million US$ in 2017, according to a new GIR (Global Info Research) study.

Market Segment by Manufacturers, this report covers
NVIDIA
Intel
IBM
Qualcomm
CEVA
KnuEdge
AMD
Xilinx
ARM
Google
Graphcore
TeraDeep
Wave Computing
BrainChip

Market Segment by Regions, regional analysis covers
North America (United States, Canada and Mexico)
Europe (Germany, France, UK, Russia and Italy)
Asia-Pacific (China, Japan, Korea, India and Southeast Asia)
South America (Brazil, Argentina, Colombia etc.)
Middle East and Africa (Saudi Arabia, UAE, Egypt, Nigeria and South Africa)

Market Segment by Type, covers
Graphics Processing Units (GPUs)
Central Processing Units (CPUs)
Application Specific Integrated Circuits (ASICs)
Field Programmable Gate Arrays (FPGAs)
Others

Market Segment by Applications, can be divided into
Consumer
Aerospace, Military & Defense
Automotive
Industrial
Medical
Others

There are 15 Chapters to deeply display the global Deep Learning Chipset market.
Chapter 1, to describe Deep Learning Chipset Introduction, product scope, market overview, market opportunities, market risk, market driving force;
Chapter 2, to analyze the top manufacturers of Deep Learning Chipset, with sales, revenue, and price of Deep Learning Chipset, in 2016 and 2017;
Chapter 3, to display the competitive situation among the top manufacturers, with sales, revenue and market share in 2016 and 2017;
Chapter 4, to show the global market by regions, with sales, revenue and market share of Deep Learning Chipset, for each region, from 2013 to 2018;
Chapter 5, 6, 7, 8 and 9, to analyze the market by countries, by type, by application and by manufacturers, with sales, revenue and market share by key countries in these regions;
Chapter 10 and 11, to show the market by type and application, with sales market share and growth rate by type, application, from 2013 to 2018;
Chapter 12, Deep Learning Chipset market forecast, by regions, type and application, with sales and revenue, from 2018 to 2023;
Chapter 13, 14 and 15, to describe Deep Learning Chipset sales channel, distributors, traders, dealers, Research Findings and Conclusion, appendix and data source

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Table of Contents

1 Market Overview
1.1 Deep Learning Chipset Introduction
1.2 Market Analysis by Type
1.2.1 Graphics Processing Units (GPUs)
1.2.2 Central Processing Units (CPUs)
1.2.3 Application Specific Integrated Circuits (ASICs)
1.2.4 Field Programmable Gate Arrays (FPGAs)
1.2.5 Others
1.3 Market Analysis by Applications
1.3.1 Consumer
1.3.2 Aerospace, Military & Defense
1.3.3 Automotive
1.3.4 Industrial
1.3.5 Medical
1.3.6 Others
1.4 Market Analysis by Regions
1.4.1 North America (United States, Canada and Mexico)
1.4.1.1 United States Market States and Outlook (2013-2023)
1.4.1.2 Canada Market States and Outlook (2013-2023)
1.4.1.3 Mexico Market States and Outlook (2013-2023)
1.4.2 Europe (Germany, France, UK, Russia and Italy)
1.4.2.1 Germany Market States and Outlook (2013-2023)
1.4.2.2 France Market States and Outlook (2013-2023)
1.4.2.3 UK Market States and Outlook (2013-2023)
1.4.2.4 Russia Market States and Outlook (2013-2023)
1.4.2.5 Italy Market States and Outlook (2013-2023)
1.4.3 Asia-Pacific (China, Japan, Korea, India and Southeast Asia)
1.4.3.1 China Market States and Outlook (2013-2023)
1.4.3.2 Japan Market States and Outlook (2013-2023)
1.4.3.3 Korea Market States and Outlook (2013-2023)
1.4.3.4 India Market States and Outlook (2013-2023)
1.4.3.5 Southeast Asia Market States and Outlook (2013-2023)
1.4.4 South America, Middle East and Africa
1.4.4.1 Brazil Market States and Outlook (2013-2023)
1.4.4.2 Egypt Market States and Outlook (2013-2023)
1.4.4.3 Saudi Arabia Market States and Outlook (2013-2023)
1.4.4.4 South Africa Market States and Outlook (2013-2023)
1.4.4.5 Nigeria Market States and Outlook (2013-2023)
1.5 Market Dynamics
1.5.1 Market Opportunities
1.5.2 Market Risk
1.5.3 Market Driving Force

2 Manufacturers Profiles
2.1 NVIDIA
2.1.1 Business Overview
2.1.2 Deep Learning Chipset Type and Applications
2.1.2.1 Product A
2.1.2.2 Product B
2.1.3 NVIDIA Deep Learning Chipset Sales, Price, Revenue, Gross Margin and Market Share (2016-2017)
2.2 Intel
2.2.1 Business Overview
2.2.2 Deep Learning Chipset Type and Applications
2.2.2.1 Product A
2.2.2.2 Product B
2.2.3 Intel Deep Learning Chipset Sales, Price, Revenue, Gross Margin and Market Share (2016-2017)
2.3 IBM
2.3.1 Business Overview
2.3.2 Deep Learning Chipset Type and Applications
2.3.2.1 Product A
2.3.2.2 Product B
2.3.3 IBM Deep Learning Chipset Sales, Price, Revenue, Gross Margin and Market Share (2016-2017)
2.4 Qualcomm
2.4.1 Business Overview
2.4.2 Deep Learning Chipset Type and Applications
2.4.2.1 Product A
2.4.2.2 Product B
2.4.3 Qualcomm Deep Learning Chipset Sales, Price, Revenue, Gross Margin and Market Share (2016-2017)
2.5 CEVA
2.5.1 Business Overview
2.5.2 Deep Learning Chipset Type and Applications
2.5.2.1 Product A
2.5.2.2 Product B
2.5.3 CEVA Deep Learning Chipset Sales, Price, Revenue, Gross Margin and Market Share (2016-2017)
2.6 KnuEdge
2.6.1 Business Overview
2.6.2 Deep Learning Chipset Type and Applications
2.6.2.1 Product A
2.6.2.2 Product B
2.6.3 KnuEdge Deep Learning Chipset Sales, Price, Revenue, Gross Margin and Market Share (2016-2017)
2.7 AMD
2.7.1 Business Overview
2.7.2 Deep Learning Chipset Type and Applications
2.7.2.1 Product A
2.7.2.2 Product B
2.7.3 AMD Deep Learning Chipset Sales, Price, Revenue, Gross Margin and Market Share (2016-2017)
2.8 Xilinx
2.8.1 Business Overview
2.8.2 Deep Learning Chipset Type and Applications
2.8.2.1 Product A
2.8.2.2 Product B
2.8.3 Xilinx Deep Learning Chipset Sales, Price, Revenue, Gross Margin and Market Share (2016-2017)
2.9 ARM
2.9.1 Business Overview
2.9.2 Deep Learning Chipset Type and Applications
2.9.2.1 Product A
2.9.2.2 Product B
2.9.3 ARM Deep Learning Chipset Sales, Price, Revenue, Gross Margin and Market Share (2016-2017)
2.10 Google
2.10.1 Business Overview
2.10.2 Deep Learning Chipset Type and Applications
2.10.2.1 Product A
2.10.2.2 Product B
2.10.3 Google Deep Learning Chipset Sales, Price, Revenue, Gross Margin and Market Share (2016-2017)
2.11 Graphcore
2.11.1 Business Overview
2.11.2 Deep Learning Chipset Type and Applications
2.11.2.1 Product A
2.11.2.2 Product B
2.11.3 Graphcore Deep Learning Chipset Sales, Price, Revenue, Gross Margin and Market Share (2016-2017)
2.12 TeraDeep
2.12.1 Business Overview
2.12.2 Deep Learning Chipset Type and Applications
2.12.2.1 Product A
2.12.2.2 Product B
2.12.3 TeraDeep Deep Learning Chipset Sales, Price, Revenue, Gross Margin and Market Share (2016-2017)
2.13 Wave Computing
2.13.1 Business Overview
2.13.2 Deep Learning Chipset Type and Applications
2.13.2.1 Product A
2.13.2.2 Product B
2.13.3 Wave Computing Deep Learning Chipset Sales, Price, Revenue, Gross Margin and Market Share (2016-2017)
2.14 BrainChip
2.14.1 Business Overview
2.14.2 Deep Learning Chipset Type and Applications
2.14.2.1 Product A
2.14.2.2 Product B
2.14.3 BrainChip Deep Learning Chipset Sales, Price, Revenue, Gross Margin and Market Share (2016-2017)

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3 Global Deep Learning Chipset Sales, Revenue, Market Share and Competition by Manufacturer (2016-2017)
3.1 Global Deep Learning Chipset Sales and Market Share by Manufacturer (2016-2017)
3.2 Global Deep Learning Chipset Revenue and Market Share by Manufacturer (2016-2017)
3.3 Market Concentration Rate
3.3.1 Top 3 Deep Learning Chipset Manufacturer Market Share in 2017
3.3.2 Top 6 Deep Learning Chipset Manufacturer Market Share in 2017
3.4 Market Competition Trend

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