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Deep Learning Chip Market by Chip Type (GPU, ASIC, FPGA, CPU, and Others), Technology (System-on-chip, System-in-package, Multi-chip module, and Others), and Industry Vertical (Media & Advertising, BFSI, IT & Telecom, Retail, Healthcare, Automotive & Transportation, and Others) - Global Opportunity Analysis and Industry Forecast, 2018-2025

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SE_182558
Pages: 360
Jul 2018 | 1758 Views
 
Author's : Akshay Jadhav & Prasad Kakade
Tables: 118
Charts: 73
 

Deep Learning Chip Market Overview:

Deep learning is a sub-set of machine learning, which is a sub-set of artificial intelligence (AI) that is achieved to perform tasks related to AI. Deep learning works as a brain, which has been penetrating in several industries around the world. This technology is achieved with software, such as computer vision, voice recognition, speech synthesis, machine translation, game playing, drug discovery, and robotics. Deep learning chips are specialized Silicon chips, which incorporate AI and machine learning technology.

Emergence of quantum computing and enhanced implementation of deep learning chips in robotics drive the growth of the global deep learning chip market considerably. In addition, emergence of autonomous robotics-robots that develop and control themselves autonomously-is anticipated to provide potential growth opportunities for the market. However, dearth of skilled workforce is one of the major restraints of the market. Most of the tasks, such as testing, bug fixing, cloud implementation, and others, are taken over by deep learning chips; however, delivery of such tasks lacks essential skillsets.

The major companies profiled in the report include AMD (Advanced Micro Devices), Google, Inc., Intel Corporation, NVIDIA, Baidu, Bitmain Technologies, Qualcomm, Amazon, Xilinx,  and Samsung.

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The global deep learning chipset market is segmented based on chip type, industry vertical, technology, and geography. By chip type, the market is categorized into graphics processing unit (GPU), application-specific integrated circuit (ASIC), field-programmable gate array (FPGA), central processing unit (CPU), and others. System-on-chip, system-in-package, multi-chip module, and others are the technologies taken into consideration. The industry verticals taken into account in the study include media & advertising, BFSI, IT & telecom, retail, healthcare, automotive & transportation, and others.

Geographically, the deep learning chip industry is sub-segmented into North America, Europe, Asia-Pacific, and LAMEA.

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The significant impacting factors in the global deep learning chip industry include increase in demand for smart homes and smart cities, rise in investments in AI startups, emergence of quantum computing, growth in the number of AI applications, dearth of skilled workforce, increase in adoption of deep learning chips in the developing regions, and development of smarter robots. Each of these factors is anticipated to have a definite impact on the deep learning chipset market during the forecast period.

Increase in Demand for Smart Homes and Smart Cities

AI provides impetus to initiate smart city programs in developing countries, such as India. Tools and technologies that are artificially intelligent possess a massive potential to transform interconnected digital homes and smart cities. Furthermore, creation of a chip that embeds an inbuilt AI network has emerged as an opportunity for the deep learning chip market.  

Rise in Investments in AI Startups

Multiple countries, especially the U.S., witness a considerable growth in tech start-ups every year, which are backed by various venture capitalists and venture capitals, thus increasing the market scope. Various key players have been innovating to build a dedicated platform; for instance, Mythic’s platform has an advantage of processing  digital/analog calculations in memory, which results in enhanced performance, accuracy, and power life. Furthermore, surge in need to integrate video surveillance and AI and rise in government spending for cyber security solutions that are integrated with real-time analytics and AI are anticipated to boost the growth of the deep learning chipset market.

Emergence of Quantum Computing

Quantum computers take seconds to complete a calculation that would otherwise take thousands of years; for instance, Google has a quantum computer that is 100 million times faster than today’s computing systems. Quantum computers are an innovative transformation of artificial intelligence, big data, and machine learning. Thus, emergence of quantum computing has fueled the growth of the deep learning chipset market. Furthermore, processor performance has improved around five times since Intel's introduction of the Pentium processors. Firstly, because of the smaller size of transistors, which has collapsed from 800 nm to 16 nm. This enables to create processors with billions of transistors, which operate in the gigahertz range and increase the computational power drastically. Secondly, owing to the improved graphic processing units (GPUs) over the traditional central processing units (CPUs). Hence, a single processor performs complex calculations in seconds, which during the 90s would have required multiple lifetimes. With the help of the internet's size and scale, deep learning handles large data sets at a very low cost. These factors have been helping to drive the growth of the global deep learning chip industry.

Dearth of Skilled Workforce

AI consists of complex algorithms for its development. In addition, management of AI and automated systems is difficult at times. This requires exceptional software engineering skills and a notable experience to deal with distributed and concurrent programming or debugging with communication protocols. However, many regions, particularly the emerging economies, lack people with such skills. Hence, dearth of a skilled workforce is a prominent restraining force of the deep learning chip industry.

Increased Adoption of Deep Learning Chips in the Developing Regions

Recent developments in the emerging economies, such as China and India, across various industry verticals, which include media & advertising, finance, retail, healthcare, automotive & transportation, and others, have created a major growth potential for AI. The time and cost benefits provided by AI are the major growth factors leading to its increased adoption in the developing regions. All these factors together fuel the growth of the market.

Development of Smarter Robots

Many players have been building superior robot brains, which would enable machines to operate autonomously by deployment; for instance, Rethink Robotics’ Baxter is a research robot, which is trained accordingly. Similarly, human-like robots are invented by Hanson Robotics, which carry a peculiar conversation and recall personal history. Furthermore, development of smarter virtual assistants is opportunistic for the overall market. A notable illustration is Jarvis Corp, which is a start-up in the conceptual phases. It has been building a virtual assistant that answers questions by accessing the internet and acting as an internet server and acts as a control for connected devices.

Key Benefits

  • This study comprises an analytical depiction of the global deep learning chip market size with current trends and future estimations to depict the imminent investment pockets.
  • The overall deep learning chip industry potential is determined to understand the profitable trends to gain a stronger foothold.
  • The report presents information related to key drivers, restraints, and opportunities with a detailed impact analysis.
  • The current deep learning chip market is quantitatively analyzed from 2018 to 2025 to benchmark the financial competency.
  • Porter’s Five Forces analysis illustrates the potency of the buyers and suppliers in the global deep learning chip market.
  • The report includes the deep learning chip market share of key vendors and deep learning chip market trends.

Deep Learning Chip Market Key Segments:

By Chip Type

  • GPU
  • ASIC
  • FPGA
  • CPU
  • Others

By Technology

  • System-on-chip (SoC)
  • System-in-package (SIP)
  • Multi-chip module
  • Others

By Industry Vertical

  • Media & advertising
  • BFSI
  • IT & telecom
  • Retail
  • Healthcare
  • Automotive & transportation
  • Others

By Region

  • North America
    • U.S.
    • Canada
    • Mexico
  • Europe
    • UK
    • Germany
    • France
    • Russia
    • Rest of Europe
  • Asia-Pacific
    • China
    • Japan
    • India
    • Australia
    • Rest of Asia-Pacific
  • LAMEA
    • Latin America
    • Middle East
    • Africa

Key Market Players Profiled

  • AMD (Advanced Micro Devices)
  • Google, Inc.
  • Intel Corporation
  • NVIDIA
  • Baidu
  • Bitmain Technologies
  • Qualcomm
  • Amazon
  • Xilinx
  • Samsung
 

Chapter: 1: INTRODUCTION

1.1. REPORT DESCRIPTION
1.2. KEY BENEFITS FOR STAKEHOLDERS
1.3. KEY MARKET SEGMENTS
1.4. RESEARCH METHODOLOGY

1.4.1. Primary research
1.4.2. Secondary research
1.4.3. Analyst tools and models

Chapter: 2: EXECUTIVE SUMMARY

2.1. CXO PERSPECTIVE

Chapter: 3: MARKET OVERVIEW

3.1. MARKET DEFINITION AND SCOPE
3.2. KEY FINDINGS

3.2.1. Top impacting factors
3.2.2. Top investment pockets
3.2.3. Top winning strategies

3.3. PORTER’S FIVE FORCES ANALYSIS

3.3.1. Moderate-to-high bargaining power of suppliers
3.3.2. Moderate-to-high threat of new entrants
3.3.3. Low-to-Moderate threat of substitutes
3.3.4. High-to-moderate intensity of rivalry
3.3.5. High-to-moderate bargaining power of buyers

3.4. MARKET SHARE ANALYSIS (2017)
3.5. MARKET DYNAMICS

3.5.1. Drivers

3.5.1.1. Increase in demand for smart homes & smart cities
3.5.1.2. Rise in investments in AI startups
3.5.1.3. Emergence of quantum computing
3.5.1.4. Growth in number of AI applications

3.5.2. Restraints

3.5.2.1. Dearth of skilled workforce

3.5.3. Opportunities

3.5.3.1. Increased adoption of deep learning chips in the developing regions
3.5.3.2. Development of smarter robots

Chapter: 4: DEEP LEARNING CHIP MARKET, BY CHIP TYPE

4.1. OVERVIEW
4.2. GPU

4.2.1. Key market trends, growth factors and opportunities
4.2.2. Market size and forecast, by region
4.2.3. Market analysis by country

4.3. ASIC

4.3.1. Key market trends, growth factors, and opportunities
4.3.2. Market size and forecast, by region
4.3.3. Market analysis by country

4.4. FPGA

4.4.1. Key market trends, growth factors, and opportunities
4.4.2. Market size and forecast, by region
4.4.3. Market analysis by country

4.5. CPU

4.5.1. Key market trends, growth factors, and opportunities
4.5.2. Market size and forecast, by region
4.5.3. Market analysis by country

4.6. OTHERS (NPU & HYBRID CHIP)

4.6.1. Key market trends, growth factors, and opportunities
4.6.2. Market size and forecast, by region
4.6.3. Market analysis by country

Chapter: 5: DEEP LEARNING CHIP MARKET, BY TECHNOLOGY

5.1. OVERVIEW
5.2. SYSTEM-ON-CHIP (SOC)

5.2.1. Key market trends, growth factors and opportunities
5.2.2. Market size and forecast, by region
5.2.3. Market analysis by country

5.3. SYSTEM-IN-PACKAGE (SIP)

5.3.1. Key market trends, growth factors, and opportunities
5.3.2. Market size and forecast, by region
5.3.3. Market analysis by country

5.4. MULTI-CHIP MODULE

5.4.1. Key market trends, growth factors, and opportunities
5.4.2. Market size and forecast, by region
5.4.3. Market analysis by country

5.5. OTHERS (PACKAGE IN PACKAGE, TSV)

5.5.1. Key market trends, growth factors, and opportunities
5.5.2. Market size and forecast, by region
5.5.3. Market analysis by country

Chapter: 6: DEEP LEARNING CHIP MARKET, BY INDUSTRY VERTICAL

6.1. OVERVIEW
6.2. MEDIA & ADVERTISING

6.2.1. Key market trends, growth factors and opportunities
6.2.2. Market size and forecast, by region
6.2.3. Market analysis by country

6.3. BFSI

6.3.1. Key market trends, growth factors and opportunities
6.3.2. Market size and forecast, by region
6.3.3. Market analysis by country

6.4. IT & TELECOM

6.4.1. Key market trends, growth factors and opportunities
6.4.2. Market size and forecast, by region
6.4.3. Market analysis by country

6.5. RETAIL

6.5.1. Key market trends, growth factors and opportunities
6.5.2. Market size and forecast, by region
6.5.3. Market analysis by country

6.6. HEALTHCARE

6.6.1. Key market trends, growth factors and opportunities
6.6.2. Market size and forecast, by region
6.6.3. Market analysis by country

6.7. AUTOMOTIVE

6.7.1. Key market trends, growth factors and opportunities
6.7.2. Market size and forecast, by region
6.7.3. Market analysis by country

6.8. OTHERS

6.8.1. Key market trends, growth factors and opportunities
6.8.2. Market size and forecast, by region
6.8.3. Market analysis by country

Chapter: 7: DEEP LEARNING CHIP MARKET, BY REGION

7.1. OVERVIEW
7.2. NORTH AMERICA

7.2.1. Key market trends, growth factors, and opportunities
7.2.2. Market size and forecast, by chip type
7.2.3. Market size and forecast, by technology
7.2.4. Market size and forecast, by industry vertical
7.2.5. Market analysis by country

7.2.5.1. U.S.

7.2.5.1.1. Market size and forecast, by chip type
7.2.5.1.2. Market size and forecast, by technology
7.2.5.1.3. Market size and forecast, by industry vertical

7.2.5.2. Canada

7.2.5.2.1. Market size and forecast, by chip type
7.2.5.2.2. Market size and forecast, by technology
7.2.5.2.3. Market size and forecast, by industry vertical

7.2.5.3. Mexico

7.2.5.3.1. Market size and forecast, by chip type
7.2.5.3.2. Market size and forecast, by technology
7.2.5.3.3. Market size and forecast, by industry vertical

7.3. EUROPE

7.3.1. Key market trends, growth factors, and opportunities
7.3.2. Market size and forecast, by chip type
7.3.3. Market size and forecast, by technology
7.3.4. Market size and forecast, by industry vertical
7.3.5. Market analysis by country

7.3.5.1. U.K.

7.3.5.1.1. Market size and forecast, by chip type
7.3.5.1.2. Market size and forecast, by technology
7.3.5.1.3. Market size and forecast, by industry vertical

7.3.5.2. Germany

7.3.5.2.1. Market size and forecast, by chip type
7.3.5.2.2. Market size and forecast, by technology
7.3.5.2.3. Market size and forecast, by industry vertical

7.3.5.3. France

7.3.5.3.1. Market size and forecast, by chip type
7.3.5.3.2. Market size and forecast, by technology
7.3.5.3.3. Market size and forecast, by industry vertical

7.3.5.4. Russia

7.3.5.4.1. Market size and forecast, by chip type
7.3.5.4.2. Market size and forecast, by technology
7.3.5.4.3. Market size and forecast, by industry vertical

7.3.5.5. Rest of Europe

7.3.5.5.1. Market size and forecast, by chip type
7.3.5.5.2. Market size and forecast, by technology
7.3.5.5.3. Market size and forecast, by industry vertical

7.4. ASIA-PACIFIC

7.4.1. Key market trends, growth factors, and opportunities
7.4.2. Market size and forecast, by chip type
7.4.3. Market size and forecast, by technology
7.4.4. Market size and forecast, by industry vertical
7.4.5. Market analysis by country

7.4.5.1. China

7.4.5.1.1. Market size and forecast, by chip type
7.4.5.1.2. Market size and forecast, by technology
7.4.5.1.3. Market size and forecast, by industry vertical

7.4.5.2. Japan

7.4.5.2.1. Market size and forecast, by chip type
7.4.5.2.2. Market size and forecast, by technology
7.4.5.2.3. Market size and forecast, by industry vertical

7.4.5.3. India

7.4.5.3.1. Market size and forecast, by chip type
7.4.5.3.2. Market size and forecast, by technology
7.4.5.3.3. Market size and forecast, by industry vertical

7.4.5.4. Australia

7.4.5.4.1. Market size and forecast, by chip type
7.4.5.4.2. Market size and forecast, by technology
7.4.5.4.3. Market size and forecast, by industry vertical

7.4.5.5. Rest of Asia-Pacific

7.4.5.5.1. Market size and forecast, by chip type
7.4.5.5.2. Market size and forecast, by technology
7.4.5.5.3. Market size and forecast, by industry vertical

7.5. LAMEA

7.5.1. Key market trends, growth factors, and opportunities
7.5.2. Market size and forecast, by chip type
7.5.3. Market size and forecast, by technology
7.5.4. Market size and forecast, by industry vertical
7.5.5. Market analysis by country

7.5.5.1. Latin America

7.5.5.1.1. Market size and forecast, by chip type
7.5.5.1.2. Market size and forecast, by technology
7.5.5.1.3. Market size and forecast, by industry vertical

7.5.5.2. Middle East

7.5.5.2.1. Market size and forecast, by chip type
7.5.5.2.2. Market size and forecast, by technology
7.5.5.2.3. Market size and forecast, by industry vertical

7.5.5.3. Africa

7.5.5.3.1. Market size and forecast, by chip type
7.5.5.3.2. Market size and forecast, by technology
7.5.5.3.3. Market size and forecast, by industry vertical

Chapter: 8: COMPANY PROFILES

8.1. ALPHABET INC. (GOOGLE INC.)

8.1.1. Company overview
8.1.2. Company snapshot
8.1.3. Operating business segments
8.1.4. Product portfolio
8.1.5. Business performance
8.1.6. Key strategic moves and developments
8.1.7. Technological insights and key architecture

8.2. AMAZON.COM, INC.

8.2.1. Company overview
8.2.2. Company snapshot
8.2.3. Operating business segments
8.2.4. Product portfolio
8.2.5. Business performance
8.2.6. Key strategic moves and developments
8.2.7. Technological insights and key architecture

8.3. ADVANCED MICRO DEVICES, INC.

8.3.1. Company overview
8.3.2. Company snapshot
8.3.3. Operating business segments
8.3.4. Product portfolio
8.3.5. Business performance
8.3.6. Key strategic moves and developments
8.3.7. Technological insights and key architecture

8.4. BAIDU, INC.

8.4.1. Company overview
8.4.2. Company snapshot
8.4.3. Operating business segments
8.4.4. Product portfolio
8.4.5. Business performance
8.4.6. Key strategic moves and developments
8.4.7. Technological insights and key architecture

8.5. BITMAIN TECHNOLOGIES LTD.

8.5.1. Company overview
8.5.2. Company snapshot
8.5.3. Product portfolio
8.5.4. Key strategic moves and developments
8.5.5. Technological insights and key architecture

8.6. INTEL CORPORATION

8.6.1. Company overview
8.6.2. Company snapshot
8.6.3. Operating business segments
8.6.4. Product portfolio
8.6.5. Business performance
8.6.6. Key strategic moves and developments
8.6.7. Technological insights and key architecture

8.7. NVIDIA CORPORATION

8.7.1. Company overview
8.7.2. Company snapshot
8.7.3. Operating business segments
8.7.4. Product portfolio
8.7.5. Business performance
8.7.6. Key strategic moves and developments
8.7.7. Technological insights and key architecture

8.8. QUALCOMM INCORPORATED

8.8.1. Company overview
8.8.2. Company snapshot
8.8.3. Operating business segments
8.8.4. Product portfolio
8.8.5. Business performance
8.8.6. Key strategic moves and developments
8.8.7. Technological insights and key architecture

8.9. SAMSUNG ELECTRONICS CO. LTD.

8.9.1. Company overview
8.9.2. Company snapshot
8.9.3. Operating business segments
8.9.4. Product portfolio
8.9.5. Business performance
8.9.6. Key strategic moves and developments
8.9.7. Technological insights and key architecture

8.10. XILINX, INC.

8.10.1. Company overview
8.10.2. Company snapshot
8.10.3. Operating business segments
8.10.4. Product portfolio
8.10.5. Business performance
8.10.6. Key strategic moves and developments
8.10.7. Technological insights and key architecture

LIST OF TABLES

TABLE 01. GLOBAL DEEP LEARNING CHIP MARKET, BY CHIP TYPE, 2017-2025($MILLION)
TABLE 02. DEEP LEARNING CHIP MARKET REVENUE FOR GPU, BY REGION 2017-2025 ($MILLION)
TABLE 03. DEEP LEARNING CHIP MARKET REVENUE FOR ASIC, BY REGION 2017-2025 ($MILLION)
TABLE 04. DEEP LEARNING CHIP MARKET REVENUE FOR FPGA, BY REGION 2017-2025 ($MILLION)
TABLE 05. DEEP LEARNING CHIP MARKET REVENUE FOR CPU, BY REGION 2017-2025 ($MILLION)
TABLE 06. DEEP LEARNING CHIP MARKET REVENUE FOR OTHERS, BY REGION 2017-2025 ($MILLION)
TABLE 07. GLOBAL DEEP LEARNING CHIP MARKET, BY TECHNOLOGY, 2017-2025($MILLION)
TABLE 08. DEEP LEARNING CHIP MARKET REVENUE FOR SYSTEM-ON-CHIP (SOC), BY REGION 2017-2025 ($MILLION)
TABLE 09. DEEP LEARNING CHIP MARKET REVENUE FOR SYSTEM-IN-PACKAGE (SIP), BY REGION 2017-2025 ($MILLION)
TABLE 10. DEEP LEARNING CHIP MARKET REVENUE FOR MULTI-CHIP MODULE, BY REGION 2017-2025 ($MILLION)
TABLE 11. DEEP LEARNING CHIP MARKET REVENUE FOR OTHERS, BY REGION 2017-2025 ($MILLION)
TABLE 12. GLOBAL DEEP LEARNING CHIP MARKET, BY INDUTRY VERTICAL, 2017-2025 ($MILLION)
TABLE 13. DEEP LEARNING CHIP MARKET REVENUE FOR MEDIA & ADVERTISING, BY REGION, 2017-2025 ($MILLION)
TABLE 14. DEEP LEARNING CHIP MARKET REVENUE FOR BFSI, BY REGION 2017-2025 ($MILLION)
TABLE 15. DEEP LEARNING CHIP MARKET REVENUE FOR IT & TELECOM, BY REGION, 2017-2025 ($MILLION)
TABLE 16. DEEP LEARNING CHIP MARKET REVENUE FOR RETAIL, BY REGION, 2017-2025 ($MILLION)
TABLE 17. DEEP LEARNING CHIP MARKET REVENUE FOR HEALTHCARE, BY REGION 2017-2025 ($MILLION)
TABLE 18. DEEP LEARNING CHIP MARKET REVENUE FOR AUTOMOTIVE, BY REGION 2017-2025 ($MILLION)
TABLE 19. DEEP LEARNING CHIP MARKET REVENUE FOR OTHERS, BY REGION, 2017-2025 ($MILLION)
TABLE 20. GLOBAL DEEP LEARNING CHIP MARKET, BY REGION, 2017-2025 ($MILLION)
TABLE 21. NORTH AMERICAN DEEP LEARNING CHIP MARKET, BY CHIP TYPE, 2017-2025 ($MILLION)
TABLE 22. NORTH AMERICAN DEEP LEARNING CHIP MARKET, BY TECHNOLOGY, 2017-2025 ($MILLION)
TABLE 23. NORTH AMERICAN DEEP LEARNING CHIP MARKET, BY INDUSTRY VERTICAL, 2017-2025 ($MILLION)
TABLE 24. U. S. DEEP LEARNING CHIP MARKET, BY CHIP TYPE, 2017-2025 ($MILLION)
TABLE 25. U. S. DEEP LEARNING CHIP MARKET, BY TECHNOLOGY, 2017-2025 ($MILLION)
TABLE 26. U.S. DEEP LEARNING CHIP MARKET, BY INDUSTRY VERTICAL, 2017-2025 ($MILLION)
TABLE 27. CANADA DEEP LEARNING CHIP MARKET, BY CHIP TYPE, 2017-2025 ($MILLION)
TABLE 28. CANADA DEEP LEARNING CHIP MARKET, BY TECHNOLOGY, 2017-2025 ($MILLION)
TABLE 29. CANADA DEEP LEARNING CHIP MARKET, BY INDUSTRY VERTICAL, 2017-2025 ($MILLION)
TABLE 30. MEXICO DEEP LEARNING CHIP MARKET, BY CHIP TYPE, 2017-2025 ($MILLION)
TABLE 31. MEXICO DEEP LEARNING CHIP MARKET, BY TECHNOLOGY, 2017-2025 ($MILLION)
TABLE 32. MEXICO DEEP LEARNING CHIP MARKET, BY INDUSTRY VERTICAL, 2017-2025 ($MILLION)
TABLE 33. EUROPEAN DEEP LEARNING CHIP MARKET, BY CHIP TYPE, 2017-2025 ($MILLION)
TABLE 34. EUROPEAN DEEP LEARNING CHIP MARKET, BY TECHNOLOGY, 2017-2025 ($MILLION)
TABLE 35. EUROPEAN DEEP LEARNING CHIP MARKET, BY INDUSTRY VERTICAL, 2017-2025 ($MILLION)
TABLE 36. U.K. DEEP LEARNING CHIP MARKET, BY CHIP TYPE, 2017-2025 ($MILLION)
TABLE 37. U.K. DEEP LEARNING CHIP MARKET, BY TECHNOLOGY, 2017-2025 ($MILLION)
TABLE 38. U.K. DEEP LEARNING CHIP MARKET, BY INDUSTRY VERTICAL, 2017-2025 ($MILLION)
TABLE 39. GERMANY DEEP LEARNING CHIP MARKET, BY CHIP TYPE, 2017-2025 ($MILLION)
TABLE 40. GERMANY DEEP LEARNING CHIP MARKET, BY TECHNOLOGY, 2017-2025 ($MILLION)
TABLE 41. GERMANY DEEP LEARNING CHIP MARKET, BY INDUSTRY VERTICAL, 2017-2025 ($MILLION)
TABLE 42. FRANCE DEEP LEARNING CHIP MARKET, BY CHIP TYPE, 2017-2025 ($MILLION)
TABLE 43. FRANCE DEEP LEARNING CHIP MARKET, BY TECHNOLOGY, 2017-2025 ($MILLION)
TABLE 44. FRANCE DEEP LEARNING CHIP MARKET, BY INDUSTRY VERTICAL, 2017-2025 ($MILLION)
TABLE 45. RUSSIA DEEP LEARNING CHIP MARKET, BY CHIP TYPE, 2017-2025 ($MILLION)
TABLE 46. RUSSIA DEEP LEARNING CHIP MARKET, BY TECHNOLOGY, 2017-2025 ($MILLION)
TABLE 47. RUSSIA DEEP LEARNING CHIP MARKET, BY INDUSTRY VERTICAL, 2017-2025 ($MILLION)
TABLE 48. REST OF EUROPE DEEP LEARNING CHIP MARKET, BY CHIP TYPE, 2017-2025 ($MILLION)
TABLE 49. REST OF EUROPE DEEP LEARNING CHIP MARKET, BY TECHNOLOGY, 2017-2025 ($MILLION)
TABLE 50. REST OF EUROPE DEEP LEARNING CHIP MARKET, BY INDUSTRY VERTICAL, 2017-2025 ($MILLION)
TABLE 51. ASIA-PACIFIC DEEP LEARNING CHIP MARKET, BY CHIP TYPE, 2017-2025 ($MILLION)
TABLE 52. ASIA-PACIFIC DEEP LEARNING CHIP MARKET, BY TECHNOLOGY, 2017-2025 ($MILLION)
TABLE 53. ASIA-PACIFIC DEEP LEARNING CHIP MARKET, BY INDUSTRY VERTICAL, 2017-2025 ($MILLION)
TABLE 54. CHINA DEEP LEARNING CHIP MARKET, BY CHIP TYPE, 2017-2025 ($MILLION)
TABLE 55. CHINA DEEP LEARNING CHIP MARKET, BY TECHNOLOGY, 2017-2025 ($MILLION)
TABLE 56. CHINA DEEP LEARNING CHIP MARKET, BY INDUSTRY VERTICAL, 2017-2025 ($MILLION)
TABLE 57. JAPAN DEEP LEARNING CHIP MARKET, BY CHIP TYPE, 2017-2025 ($MILLION)
TABLE 58. JAPAN DEEP LEARNING CHIP MARKET, BY TECHNOLOGY, 2017-2025 ($MILLION)
TABLE 59. JAPAN DEEP LEARNING CHIP MARKET, BY INDUSTRY VERTICAL, 2017-2025 ($MILLION)
TABLE 60. INDIA DEEP LEARNING CHIP MARKET, BY CHIP TYPE, 2017-2025 ($MILLION)
TABLE 61. INDIA DEEP LEARNING CHIP MARKET, BY TECHNOLOGY, 2017-2025 ($MILLION)
TABLE 62. INDIA DEEP LEARNING CHIP MARKET, BY INDUSTRY VERTICAL, 2017-2025 ($MILLION)
TABLE 63. AUSTRALIA DEEP LEARNING CHIP MARKET, BY CHIP TYPE, 2017-2025 ($MILLION)
TABLE 64. AUSTRALIA DEEP LEARNING CHIP MARKET, BY TECHNOLOGY, 2017-2025 ($MILLION)
TABLE 65. AUSTRALIA DEEP LEARNING CHIP MARKET, BY INDUSTRY VERTICAL, 2017-2025 ($MILLION)
TABLE 66. REST OF ASIA-PACIFIC DEEP LEARNING CHIP MARKET, BY CHIP TYPE, 2017-2025 ($MILLION)
TABLE 67. REST OF ASIA-PACIFIC DEEP LEARNING CHIP MARKET, BY TECHNOLOGY, 2017-2025 ($MILLION)
TABLE 68. REST OF ASIA-PACIFIC DEEP LEARNING CHIP MARKET, BY INDUSTRY VERTICAL, 2017-2025 ($MILLION)
TABLE 69. LAMEA DEEP LEARNING CHIP MARKET, BY CHIP TYPE, 2017-2025 ($MILLION)
TABLE 70. LAMEA DEEP LEARNING CHIP MARKET, BY TECHNOLOGY, 2017-2025 ($MILLION)
TABLE 71. LAMEA DEEP LEARNING CHIP MARKET, BY INDUSTRY VERTICAL, 2017-2025 ($MILLION)
TABLE 72. LATIN AMERICA DEEP LEARNING CHIP MARKET, BY CHIP TYPE, 2017-2025 ($MILLION)
TABLE 73. LATIN AMERICA DEEP LEARNING CHIP MARKET, BY TECHNOLOGY, 2017-2025 ($MILLION)
TABLE 74. LATIN AMERICA DEEP LEARNING CHIP MARKET, BY INDUSTRY VERTICAL, 2017-2025 ($MILLION)
TABLE 75. MIDDLE EAST DEEP LEARNING CHIP MARKET, BY CHIP TYPE, 2017-2025 ($MILLION)
TABLE 76. MIDDLE EAST DEEP LEARNING CHIP MARKET, BY TECHNOLOGY, 2017-2025 ($MILLION)
TABLE 77. MIDDLE EAST DEEP LEARNING CHIP MARKET, BY INDUSTRY VERTICAL, 2017-2025 ($MILLION)
TABLE 78. AFRICA DEEP LEARNING CHIP MARKET, BY CHIP TYPE, 2017-2025 ($MILLION)
TABLE 79. AFRICA DEEP LEARNING CHIP MARKET, BY TECHNOLOGY, 2017-2025 ($MILLION)
TABLE 80. AFRICA DEEP LEARNING CHIP MARKET, BY INDUSTRY VERTICAL, 2017-2025 ($MILLION)
TABLE 81. ALPHABET: COMPANY SNAPSHOT
TABLE 82. ALPHABET: OPERATING SEGMENTS
TABLE 83. ALPHABET: PRODUCT PORTFOLIO
TABLE 84. ALPHABET: TECHNOLOGICAL INSIGHTS AND KEY ARCHITECTURES
TABLE 85. AMAZON.COM: COMPANY SNAPSHOT
TABLE 86. AMAZON.COM: OPERATING SEGMENTS
TABLE 87. AMAZON.COM: PRODUCT PORTFOLIO
TABLE 88. AMAZON.COM: TECHNOLOGICAL INSIGHTS AND KEY ARCHITECTURES
TABLE 89. AMD: COMPANY SNAPSHOT
TABLE 90. AMD: OPERATING SEGMENTS
TABLE 91. AMD: PRODUCT PORTFOLIO
TABLE 92. AMD: TECHNOLOGICAL INSIGHTS AND KEY ARCHITECTURES
TABLE 93. AMAZON.COM: COMPANY SNAPSHOT
TABLE 94. AMAZON.COM: OPERATING SEGMENTS
TABLE 95. AMAZON.COM: PRODUCT PORTFOLIO
TABLE 96. BAIDU: TECHNOLOGICAL INSIGHTS AND KEY ARCHITECTURES
TABLE 97. BITMAIN TECHNOLOGIES: COMPANY SNAPSHOT
TABLE 98. BITMAIN TECHNOLOGIES: PRODUCT PORTFOLIO
TABLE 99. BITMAIN TECHNOLOGIES: TECHNOLOGICAL INSIGHTS AND KEY ARCHITECTURES
TABLE 100. INTEL: COMPANY SNAPSHOT
TABLE 101. INTEL: OPERATING SEGMENTS
TABLE 102. INTEL: PRODUCT PORTFOLIO
TABLE 103. INTEL: TECHNOLOGICAL INSIGHTS AND KEY ARCHITECTURES
TABLE 104. NVIDIA: COMPANY SNAPSHOT
TABLE 105. NVIDIA: OPERATING SEGMENTS
TABLE 106. NVIDIA: PRODUCT PORTFOLIO
TABLE 107. NVIDIA: TECHNOLOGICAL INSIGHTS AND KEY ARCHITECTURES
TABLE 108. QUALCOMM: COMPANY SNAPSHOT
TABLE 109. QUALCOMM: OPERATING SEGMENTS
TABLE 110. QUALCOMM: PRODUCT PORTFOLIO
TABLE 111. QUALCOMM: TECHNOLOGICAL INSIGHTS AND KEY ARCHITECTURES
TABLE 112. SAMSUNG: COMPANY SNAPSHOT
TABLE 113. SAMSUNG: OPERATING SEGMENTS
TABLE 114. SAMSUNG: PRODUCT PORTFOLIO
TABLE 115. SAMSUNG: TECHNOLOGICAL INSIGHTS AND KEY ARCHITECTURES
TABLE 116. XILINX: COMPANY SNAPSHOT
TABLE 117. XILINX: PRODUCT PORTFOLIO
TABLE 118. XILINX: TECHNOLOGICAL INSIGHTS AND KEY ARCHITECTURES

LIST OF FIGURES

FIGURE 01. KEY MARKET SEGMENTS
FIGURE 02. EXECUTIVE SUMMARY
FIGURE 03. EXECUTIVE SUMMARY
FIGURE 04. TOP IMPACTING FACTORS
FIGURE 05. TOP INVESTMENT POCKETS
FIGURE 06. TOP WINNING STRATEGIES, 2017-2025 (%)
FIGURE 07. TOP COMPANIES AND THEIR STRATEGIES
FIGURE 08. MARKET SHARE ANALYSIS (2017)
FIGURE 09. GLOBAL DEEP LEARNING CHIP MARKET SHARE, BY CHIP TYPE, 2017-2025 (%)
FIGURE 10. COMPARATIVE SHARE ANALYSIS OF DEEP LEARNING CHIP MARKET FOR GPU, BY COUNTRY, 2017 & 2025 (%)
FIGURE 11. COMPARATIVE SHARE ANALYSIS OF DEEP LEARNING CHIP MARKET FOR ASIC, BY COUNTRY, 2017 & 2025 (%)
FIGURE 12. COMPARATIVE SHARE ANALYSIS OF DEEP LEARNING CHIP MARKET FOR FPGA, BY COUNTRY, 2017 & 2025 (%)
FIGURE 13. COMPARATIVE SHARE ANALYSIS OF DEEP LEARNING CHIP MARKET FOR CPU, BY COUNTRY, 2017 & 2025 (%)
FIGURE 14. COMPARATIVE SHARE ANALYSIS OF DEEP LEARNING CHIP MARKET FOR OTHERS, BY COUNTRY, 2017 & 2025 (%)
FIGURE 15. GLOBAL DEEP LEARNING CHIP MARKET SHARE, BY TECHNOLOGY, 2017-2025 (%)
FIGURE 16. COMPARATIVE SHARE ANALYSIS OF DEEP LEARNING CHIP MARKET FOR SYSTEM-ON-CHIP (SOC), BY COUNTRY, 2017 & 2025 (%)
FIGURE 17. COMPARATIVE SHARE ANALYSIS OF DEEP LEARNING CHIP MARKET FOR SYSTEM-IN-PACKAGE (SIP), BY COUNTRY, 2017 & 2025 (%)
FIGURE 18. COMPARATIVE SHARE ANALYSIS OF DEEP LEARNING CHIP MARKET FOR MULTI-CHIP MODULE, BY COUNTRY, 2017 & 2025 (%)
FIGURE 19. COMPARATIVE SHARE ANALYSIS OF DEEP LEARNING CHIP MARKET FOR OTHERS, BY COUNTRY, 2017 & 2025 (%)
FIGURE 20. GLOBAL DEEP LEARNING CHIP MARKET SHARE, BY INDUSTRY VERTICAL, 2017-2025 (%)
FIGURE 21. COMPARATIVE SHARE ANALYSIS OF DEEP LEARNING CHIP MARKET FOR MEDIA & ADVERTISING, BY COUNTRY, 2017 & 2025 (%)
FIGURE 22. COMPARATIVE SHARE ANALYSIS OF DEEP LEARNING CHIP MARKET FOR BFSI, BY COUNTRY, 2017 & 2025 (%)
FIGURE 23. COMPARATIVE SHARE ANALYSIS OF DEEP LEARNING CHIP MARKET FOR IT & TELECOM, BY COUNTRY, 2017 & 2025 (%)
FIGURE 24. COMPARATIVE SHARE ANALYSIS OF DEEP LEARNING CHIP MARKET FOR RETAIL, BY COUNTRY, 2017 & 2025 (%)
FIGURE 25. COMPARATIVE SHARE ANALYSIS OF DEEP LEARNING CHIP MARKET FOR HEALTHCARE, BY COUNTRY, 2017 & 2025 (%)
FIGURE 26. COMPARATIVE SHARE ANALYSIS OF DEEP LEARNING CHIP MARKET FOR AUTOMOTIVE, BY COUNTRY, 2017 & 2025 (%)
FIGURE 27. COMPARATIVE SHARE ANALYSIS OF DEEP LEARNING CHIP MARKET FOR OTHERS, BY COUNTRY, 2017 & 2025 (%)
FIGURE 28. DEEP LEARNING CHIP MARKET, BY REGION, 2017-2025 (%)
FIGURE 29. COMPARATIVE SHARE ANALYSIS OF DEEP LEARNING CHIP MARKET, BY COUNTRY, 2017-2025 (%)
FIGURE 30. U. S. DEEP LEARNING CHIP MARKET, 2017-2025 ($MILLION)
FIGURE 31. CANADA DEEP LEARNING CHIP MARKET, 2017-2025 ($MILLION)
FIGURE 32. MEXICO DEEP LEARNING CHIP MARKET, 2017-2025 ($MILLION)
FIGURE 33. COMPARATIVE SHARE ANALYSIS OF DEEP LEARNING CHIP MARKET, BY COUNTRY, 2017-2025 (%)
FIGURE 34. U.K. DEEP LEARNING CHIP MARKET, 2017-2025 ($MILLION)
FIGURE 35. GERMANY DEEP LEARNING CHIP MARKET, 2017-2025 ($MILLION)
FIGURE 36. FRANCE DEEP LEARNING CHIP MARKET, 2017-2025 ($MILLION)
FIGURE 37. RUSSIA DEEP LEARNING CHIP MARKET, 2017-2025 ($MILLION)
FIGURE 38. REST OF EUROPE DEEP LEARNING CHIP MARKET, 2017-2025 ($MILLION)
FIGURE 39. COMPARATIVE SHARE ANALYSIS OF DEEP LEARNING CHIP MARKET, BY COUNTRY, 2017-2025 (%)
FIGURE 40. CHINA DEEP LEARNING CHIP MARKET, 2017-2025 ($MILLION)
FIGURE 41. JAPAN DEEP LEARNING CHIP MARKET, 2017-2025 ($MILLION)
FIGURE 42. INDIA DEEP LEARNING CHIP MARKET, 2017-2025 ($MILLION)
FIGURE 43. AUSTRALIA DEEP LEARNING CHIP MARKET, 2017-2025 ($MILLION)
FIGURE 44. REST OF ASIA-PACIFIC DEEP LEARNING CHIP MARKET, 2017-2025 ($MILLION)
FIGURE 45. COMPARATIVE SHARE ANALYSIS OF DEEP LEARNING CHIP MARKET, BY COUNTRY, 2017-2025 (%)
FIGURE 46. LATIN AMERICA DEEP LEARNING CHIP MARKET, 2017-2025 ($MILLION)
FIGURE 47. MIDDLE EAST DEEP LEARNING CHIP MARKET, 2017-2025 ($MILLION)
FIGURE 48. AFRICA DEEP LEARNING CHIP MARKET, 2017-2025 ($MILLION)
FIGURE 49. ALPHABET: NET SALES, 2015-2017 ($MILLION)
FIGURE 50. ALPHABET: REVENUE SHARE BY SEGMENT, 2017 (%)
FIGURE 51. ALPHABET: REVENUE SHARE BY GEOGRAPHY, 2017 (%)
FIGURE 52. AMAZON.COM: NET SALES, 2015-2017 ($MILLION)
FIGURE 53. AMAZON.COM: REVENUE SHARE BY SEGMENT, 2017 (%)
FIGURE 54. AMAZON.COM: REVENUE SHARE BY GEOGRAPHY, 2017 (%)
FIGURE 55. AMD: NET SALES, 2015-2017 ($MILLION)
FIGURE 56. AMD: REVENUE SHARE BY SEGMENT, 2017 (%)
FIGURE 57. AMD: REVENUE SHARE BY GEOGRAPHY, 2017 (%)
FIGURE 58. BAIDU: NET SALES, 2015-2017 ($MILLION)
FIGURE 59. BAIDU: REVENUE SHARE BY SEGMENT, 2017 (%)
FIGURE 60. INTEL: NET SALES, 2015-2017 ($MILLION)
FIGURE 61. INTEL: REVENUE SHARE BY SEGMENT, 2017 (%)
FIGURE 62. INTEL: REVENUE SHARE BY GEOGRAPHY, 2017 (%)
FIGURE 63. NVIDIA: NET SALES, 2015-2017 ($MILLION)
FIGURE 64. NVIDIA: REVENUE SHARE BY SEGMENT, 2017 (%)
FIGURE 65. NVIDIA: REVENUE SHARE BY GEOGRAPHY, 2017 (%)
FIGURE 66. QUALCOMM: NET SALES, 2015-2017 ($MILLION)
FIGURE 67. QUALCOMM: REVENUE SHARE BY SEGMENT, 2017 (%)
FIGURE 68. SAMSUNG: NET SALES, 2015-2017 ($MILLION)
FIGURE 69. SAMSUNG: REVENUE SHARE BY SEGMENT, 2017 (%)
FIGURE 70. SAMSUNG: REVENUE SHARE BY GEOGRAPHY, 2017 (%)
FIGURE 71. XILINX: NET SALES, 2015-2017 ($MILLION)
FIGURE 72. XILINX: REVENUE SHARE BY PRODUCT, 2017 (%)
FIGURE 73. XILINX: REVENUE SHARE BY GEOGRAPHY, 2017 (%)

 

The global deep learning chip market holds a high potential for the semiconductor industry. The current business scenario has been witnessing an increase in the demand for deep learning chips, particularly in the developing regions, such as China, India, and others. Companies in this industry adopt various innovative techniques to provide customers with advanced and innovative product offerings.

Emergence of quantum computing and increase in implementation of deep learning chips in robotics drive the growth of the global deep learning chip market considerably. In addition, emergence of autonomous robotics-robots that develop and control themselves autonomously-is anticipated to provide potential growth opportunities for the market. However, dearth of skilled workforce is one of the major restraints of the market. Most of the tasks, such as testing, bug fixing, cloud implementation, and others, are taken over by deep learning chips; however, delivery of such tasks lacks essential skillsets.

Among the geographical regions, North America exhibits the highest adoption of deep learning chips. On the other hand, the Asia-Pacific region is expected to grow at a faster pace, predicting lucrative growth.

AMD (Advanced Micro Devices), Google, Inc., Intel Corporation, NVIDIA, Baidu, Bitmain Technologies, Qualcomm, Amazon, Xilinx, and Samsung are the key market players that occupy a significant revenue share in the global deep learning chip market.

 

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