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Deep Learning Market by Offering (Hardware, Software, and Services), Application (Image Recognition, Signal Recognition, Data Mining), End-User Industry (Security, Marketing, Healthcare, Fintech, Automotive, Law), and Geography - Global Forecast to 2023

 

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MarketsandMarkets
マーケッツアンドマーケッツ
2018年3月US$4,950
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幅広い市場に関する調査レポートを出版しているマーケッツアンドマーケッツ(MarketsandMarkets)のディープラーニング市場に関する調査レポートです。

“Deep learning market projected to grow at a CAGR of 41.7% during forecast period”

According to the new market research report on deep learning, this market is expected to be worth USD 3.18 billion in 2018 and is likely to reach USD 18.16 billion by 2023, at a CAGR of 41.7% from 2018 to 2023. The growth of the deep learning market can be attributed to improving computing power and declining hardware cost. However, the lack of technical expertise and absence of standards and protocols, and increasing complexity in hardware due to complex algorithm used in deep learning technology are restraining the growth of the deep learning market.

“Market for services to grow at highest CAGR from 2018 to 2023”

The market for services is expected to grow at the highest CAGR from 2018 to 2023. Deep learning technology is highly complex in nature requiring the implementation of sophisticated algorithms. Deep learning systems require installation; training; and support and maintenance services. Installation services allow the software to be integrated with the analytics side to enable data retrieval and generate desired result through computation. The use of computer systems for DL/AI further increases the amount of work involved in installation.

“Processor held largest market size in 2017”

In terms of hardware, processor held the largest size of the deep learning market in 2017. Companies in industries such as healthcare and finance are investing in machine learning infrastructure. High parallel processing capabilities and improved computing power have resulted in the high adoption of GPUs in various DL applications.

“Deep learning market for manufacturing industry to witness highest growth between 2018 and 2023”

The market for the manufacturing industry is expected to witness the highest growth during the forecast period. Deep learning technology is used in industrial robots, machine vision systems, and others to improve the process and product quality, minimize cycle time, and increase the efficiency of the manufacturing process as a whole.

“Deep learning market in APAC expected to grow at highest CAGR”

This report covers the deep learning market in North America, Europe, APAC, and RoW. Rise in the adoption of deep learning technology in APAC could be attributed to the increasing applications of deep learning in media & advertising, finance, and retail sectors, among others, in technologically advancing countries such as India, China, and Japan. Growing e-commerce, online streaming, and increasing internet penetration have resulted in the growth of marketing industries. In the security vertical, with increasing incidents of cyberattacks and a growing cyber-war in the region, organizations and governments are focusing on robust defense infrastructure.

Breakdown of profiles of primary participants:

• By Company Type: Tier 1 = 55%, Tier 2 = 35%, and Tier 3 = 10%
• By Designation: C-Level Executives = 55%, Directors = 30%, and Others = 15%
• By Region: North America = 60%, Europe = 20%, APAC = 15%, and RoW = 5%

Companies that are profiled in this report are NVIDIA (US), Intel (US), Xilinx (US), Samsung Electronics (South Korea), Micron Technology (US), Qualcomm (US), IBM (US), Google (US), Microsoft (US), and AWS (US). Some of the key start-ups included in this report are Graphcore (UK), Mythic (US), Adapteva (US), and Koniku (US).

Research Coverage

The report describes various offerings associated with deep learning and related developments across industry verticals and regions. It aims at estimating the size and growth potential of this market across segments such as offerings (hardware, software, and services), applications, end-user industries, and geographies. Furthermore, the report includes an in-depth competitive analysis of the key players in the market, along with their company profiles, recent developments, and key market strategies.

Reasons to Buy the Report

• The report includes the market statistics pertaining to various segments, along with their respective revenue.
• The report details the major drivers, restraints, challenges, and opportunities pertaining to the deep learning market.
• The report provides illustrative segmentation, analysis, and forecast for the deep learning market by offering, application, end-user industry, and geography to give an overall view of the deep learning market.
• The report provides a detailed competitive landscape including key players and their ranking.
 



目次

1 INTRODUCTION 18
1.1 STUDY OBJECTIVES 18
1.2 DEFINITION 18
1.3 STUDY SCOPE 19
1.3.1 MARKETS COVERED 19
1.3.2 YEARS CONSIDERED FOR THIS STUDY 20
1.4 CURRENCY 20
1.5 STAKEHOLDERS 20
2 RESEARCH METHODOLOGY 21
2.1 RESEARCH DATA 21
2.1.1 SECONDARY AND PRIMARY RESEARCH 22
2.1.1.1 Key industry insights 23
2.1.2 SECONDARY DATA 23
2.1.2.1 Major secondary sources 23
2.1.2.2 Secondary sources 24
2.1.3 PRIMARY DATA 24
2.1.3.1 Primary interviews with experts 24
2.1.3.2 Breakdown of primaries 25
2.1.3.3 Primary sources 25
2.2 MARKET SIZE ESTIMATION 26
2.2.1 BOTTOM-UP APPROACH 26
2.2.1.1 Approach for capturing market share by bottom-up analysis
(demand side) 26
2.2.2 TOP-DOWN APPROACH 27
2.2.2.1 Approach for capturing market share by top-down analysis
(supply side) 27
2.3 MARKET BREAKDOWN AND DATA TRIANGULATION 29
2.4 RESEARCH ASSUMPTIONS 30
3 EXECUTIVE SUMMARY 31
4 PREMIUM INSIGHTS 37
4.1 ATTRACTIVE OPPORTUNITIES IN DEEP LEARNING MARKET 37
4.2 DEEP LEARNING MARKET, BY OFFERING 38
4.3 DEEP LEARNING MARKET, BY HARDWARE 38
4.4 DEEP LEARNING MARKET IN APAC, BY END-USER INDUSTRY AND COUNTRY 39
4.5 DEEP LEARNING MARKET, BY COUNTRY 40
5 MARKET OVERVIEW 41
5.1 INTRODUCTION 41
5.2 MARKET DYNAMICS 41
5.2.1 DRIVERS 42
5.2.1.1 Improving computing power and declining hardware cost 42
5.2.1.2 Increasing adoption of cloud-based technology 42
5.2.1.3 Deep learning usage in big data analytics 43
5.2.1.4 Growing AI adoption in customer-centric services 43
5.2.2 RESTRAINTS 44
5.2.2.1 Increasing complexity in hardware due to complex algorithm used in deep learning technology 44
5.2.2.2 Lack of technical expertise and absence of standards and protocols 44
5.2.3 OPPORTUNITIES 45
5.2.3.1 Presence of limited structured data to increase demand for deep learning solutions 45
5.2.3.2 Cumulative spending in healthcare, travel, tourism, and hospitality industries 45
5.2.4 CHALLENGES 45
5.2.4.1 Lack of flexibility and multitasking 45
5.2.4.2 Deployment of DL for applications such as NLP in regional dialects 45
5.3 VALUE CHAIN ANALYSIS 46
5.4 SOME OF THE PROMINENT ML LIBRARIES (SOFTWARE FRAMEWORKS) 48
6 DEEP LEARNING MARKET, BY OFFERING 49
6.1 INTRODUCTION 50
6.2 HARDWARE 52
6.2.1 PROCESSOR 52
6.2.2 MEMORY 54
6.2.3 NETWORK 55
6.3 SOFTWARE 56
6.3.1 SOLUTION (SOFTWARE FRAMEWORK/SDK) 57
6.3.2 PLATFORM/API 57
6.4 SERVICES 59
6.4.1 INSTALLATION 60
6.4.2 TRAINING 60
6.4.3 SUPPORT & MAINTENANCE 60
7 DEEP LEARNING MARKET, BY APPLICATION 62
7.1 INTRODUCTION 63
7.2 IMAGE RECOGNITION 64
7.3 SIGNAL RECOGNITION 65
7.4 DATA MINING 66
7.5 OTHERS (RECOMMENDER SYSTEM AND DRUG DISCOVERY) 67
8 DEEP LEARNING MARKET, BY END-USER INDUSTRY 69
8.1 INTRODUCTION 70
8.2 HEALTHCARE 72
8.2.1 PATIENT DATA & RISK ANALYSIS 74
8.2.2 LIFESTYLE MANAGEMENT & MONITORING 75
8.2.3 PRECISION MEDICINE 75
8.2.4 INPATIENT CARE & HOSPITAL MANAGEMENT 75
8.2.5 MEDICAL IMAGING & DIAGNOSTICS 75
8.2.6 DRUG DISCOVERY 76
8.2.7 VIRTUAL ASSISTANT 76
8.2.8 WEARABLES 76
8.2.9 RESEARCH 76
8.3 MANUFACTURING 77
8.3.1 MATERIAL MOVEMENT 79
8.3.2 PREDICTIVE MAINTENANCE AND MACHINERY INSPECTION 79
8.3.3 PRODUCTION PLANNING 80
8.3.4 FIELD SERVICES 80
8.3.5 RECLAMATION 80
8.3.6 QUALITY CONTROL 80
8.4 AUTOMOTIVE 81
8.4.1 AUTONOMOUS DRIVING 83
8.4.2 HUMAN–MACHINE INTERFACE 84
8.4.3 SEMIAUTONOMOUS DRIVING 84
8.5 AGRICULTURE 84
8.5.1 PRECISION FARMING 87
8.5.2 LIVESTOCK MONITORING 87
8.5.3 DRONE ANALYTICS 87
8.5.4 AGRICULTURAL ROBOTS 87
8.5.5 OTHERS 88
8.6 RETAIL 88
8.6.1 PRODUCT RECOMMENDATION AND PLANNING 90
8.6.2 CUSTOMER RELATIONSHIP MANAGEMENT 90
8.6.3 VISUAL SEARCH 90
8.6.4 VIRTUAL ASSISTANT 90
8.6.5 PRICE OPTIMIZATION 91
8.6.6 PAYMENT SERVICES MANAGEMENT 91
8.6.7 SUPPLY CHAIN MANAGEMENT AND DEMAND PLANNING 91
8.6.8 OTHERS 91
8.7 SECURITY 92
8.7.1 IDENTITY AND ACCESS MANAGEMENT (IAM) 94
8.7.2 RISK AND COMPLIANCE MANAGEMENT 94
8.7.3 ENCRYPTION 95
8.7.4 DATA LOSS PREVENTION 95
8.7.5 UNIFIED THREAT MANAGEMENT 95
8.7.6 ANTIVIRUS/ANTIMALWARE 95
8.7.7 INTRUSION DETECTION/PREVENTION SYSTEMS 95
8.7.8 OTHERS 96
8.8 HUMAN RESOURCES 96
8.8.1 VIRTUAL ASSISTANT 98
8.8.2 SENTIMENT ANALYSIS 98
8.8.3 SCHEDULING GROUP MEETINGS AND INTERVIEWS 98
8.8.4 PERSONALIZED LEARNING AND DEVELOPMENT 99
8.8.5 APPLICANT TRACKING & ASSESSMENT 99
8.8.6 EMPLOYEE ENGAGEMENT 99
8.8.7 RESUME ANALYSIS 99
8.9 MARKETING 99
8.9.1 SOCIAL MEDIA ADVERTISING 102
8.9.2 SEARCH ADVERTISING 102
8.9.3 DYNAMIC PRICING 102
8.9.4 VIRTUAL ASSISTANT 102
8.9.5 CONTENT CURATION 102
8.9.6 SALES & MARKETING AUTOMATION 102
8.9.7 ANALYTICS PLATFORM 103
8.9.8 OTHERS 103
8.10 LAW 103
8.10.1 EDISCOVERY 104
8.10.2 LEGAL RESEARCH 104
8.10.3 CONTRACT ANALYSIS 105
8.10.4 CASE PREDICTION 105
8.10.5 COMPLIANCE 105
8.10.6 OTHERS 105
8.11 FINTECH 105
8.11.1 VIRTUAL ASSISTANT 107
8.11.2 BUSINESS ANALYTICS AND REPORTING 107
8.11.3 CUSTOMER BEHAVIOR ANALYTICS 107
8.11.4 OTHERS 108
9 GEOGRAPHIC ANALYSIS 109
9.1 INTRODUCTION 110
9.2 NORTH AMERICA 112
9.2.1 US 114
9.2.2 CANADA 115
9.2.3 MEXICO 116

9.3 EUROPE 118
9.3.1 UK 120
9.3.2 GERMANY 121
9.3.3 FRANCE 122
9.3.4 ITALY 124
9.3.5 SPAIN 124
9.3.6 REST OF EUROPE 125
9.4 APAC 126
9.4.1 CHINA 128
9.4.2 JAPAN 130
9.4.3 SOUTH KOREA 131
9.4.4 INDIA 131
9.4.5 REST OF APAC 133
9.5 ROW 134
9.5.1 MIDDLE EAST AND AFRICA 135
9.5.2 SOUTH AMERICA 137
10 COMPETITIVE LANDSCAPE 138
10.1 OVERVIEW 138
10.2 RANKING ANALYSIS: DEEP LEARNING MARKET 139
10.3 COMPETITIVE SITUATION AND TREND 141
10.3.1 NEW PRODUCT DEVELOPMENTS AND LAUNCHES 142
10.3.2 COLLABORATIONS AND PARTNERSHIPS 147
10.3.3 ACQUISITIONS 150
10.3.4 OTHERS 152
11 COMPANY PROFILES 154
(Business Overview, Products Offered, Recent Developments, SWOT Analysis, and MnM View)*
11.1 KEY PLAYERS 154
11.1.1 AMAZON WEB SERVICES (AWS) 154
11.1.2 GOOGLE 158
11.1.3 IBM 161
11.1.4 INTEL 165
11.1.5 MICRON TECHNOLOGY 169
11.1.6 MICROSOFT 172
11.1.7 NVIDIA 175
11.1.8 QUALCOMM 180
11.1.9 SAMSUNG ELECTRONICS 184
11.1.10 SENSORY INC. 187
11.1.11 SKYMIND 189
11.1.12 XILINX 191

11.2 OTHER COMPANIES 195
11.2.1 AMD 195
11.2.2 GENERAL VISION 195
11.2.3 GRAPHCORE 196
11.2.4 MELLANOX TECHNOLOGIES 196
11.2.5 HUAWEI TECHNOLOGIES 197
11.2.6 FUJITSU 197
11.2.7 BAIDU 198
11.2.8 MYTHIC 198
11.2.9 ADAPTEVA, INC. 199
11.2.10 KONIKU 199
11.2.11 TENSTORRENT 199
*Details on Business Overview, Products Offered, Recent Developments, SWOT Analysis, and MnM View might not be captured in case of unlisted companies.
12 APPENDIX 200
12.1 INSIGHTS OF INDUSTRY EXPERTS 200
12.2 DISCUSSION GUIDE 201
12.3 KNOWLEDGE STORE: MARKETSANDMARKETS’ SUBSCRIPTION PORTAL 204
12.4 INTRODUCING RT: REAL-TIME MARKET INTELLIGENCE 206
12.5 AVAILABLE CUSTOMIZATIONS 208
12.6 RELATED REPORTS 209
12.7 AUTHOR DETAILS 210

 

LIST OF TABLES

TABLE 1 PRICE COMPARISON: AI CHIPSETS (LEADING COMPANIES) 42
TABLE 2 COMPANIES OFFERING CLOUD SERVICES FOR DEEP/MACHINE LEARNING 43
TABLE 3 MACHINE LEARNING LIBRARIES BY VARIOUS MARKET PLAYERS (2015–2017) 48
TABLE 4 DEEP LEARNING MARKET, BY OFFERING, 2015–2023 (USD MILLION) 51
TABLE 5 INDUSTRY PLAYERS IN DEEP LEARNING MARKET, 2017 51
TABLE 6 DEEP LEARNING MARKET, BY HARDWARE, 2015–2023 (USD MILLION) 52
TABLE 7 DEEP LEARNING MARKET, BY PROCESSOR, 2015–2023 (USD MILLION) 53
TABLE 8 DEEP LEARNING MARKET, BY PROCESSOR, 2015–2023 (THOUSAND UNITS) 54
TABLE 9 DEEP LEARNING HARDWARE MARKET, BY APPLICATION,
2015–2023 (USD MILLION) 55
TABLE 10 DEEP LEARNING HARDWARE MARKET, BY END-USER INDUSTRY,
2015–2023 (USD MILLION) 56
TABLE 11 DEEP LEARNING MARKET, BY SOFTWARE, 2015–2023 (USD MILLION) 57
TABLE 12 DEEP LEARNING SOFTWARE MARKET, BY APPLICATION,
2015–2023 (USD MILLION) 58
TABLE 13 DEEP LEARNING SOFTWARE MARKET, BY END-USER INDUSTRY,
2015–2023 (USD MILLION) 59
TABLE 14 DEEP LEARNING MARKET, BY SERVICE, 2015–2023 (USD MILLION) 60
TABLE 15 DEEP LEARNING SERVICE MARKET, BY APPLICATION, 2015–2023 (USD MILLION) 61
TABLE 16 DEEP LEARNING SERVICE MARKET, BY END-USER INDUSTRY,
2015–2023 (USD MILLION) 61
TABLE 17 DEEP LEARNING MARKET, BY APPLICATION, 2015–2023 (USD MILLION) 64
TABLE 18 DEEP LEARNING MARKET FOR IMAGE RECOGNITION, BY OFFERING,
2015–2023 (USD MILLION) 65
TABLE 19 DEEP LEARNING MARKET FOR SIGNAL RECOGNITION, BY OFFERING,
2015–2023 (USD MILLION) 66
TABLE 20 DEEP LEARNING MARKET FOR DATA MINING, BY OFFERING,
2015–2023 (USD MILLION) 67
TABLE 21 DEEP LEARNING MARKET FOR OTHERS, BY OFFERING, 2015–2023 (USD MILLION) 68
TABLE 22 DEEP LEARNING MARKET, BY END-USER INDUSTRY, 2015–2023 (USD MILLION) 72
TABLE 23 DEEP LEARNING MARKET FOR HEALTHCARE, BY OFFERING,
2015–2023 (USD MILLION) 73
TABLE 24 DEEP LEARNING MARKET FOR HEALTHCARE, BY APPLICATION,
2015–2023 (USD MILLION) 74
TABLE 25 DEEP LEARNING MARKET FOR MANUFACTURING, BY OFFERING,
2015–2023 (USD MILLION) 78
TABLE 26 DEEP LEARNING MARKET FOR MANUFACTURING, BY APPLICATION,
2015–2023 (USD MILLION) 79
TABLE 27 DEEP LEARNING MARKET FOR AUTOMOTIVE, BY OFFERING,
2015–2023 (USD MILLION) 82
TABLE 28 DEEP LEARNING MARKET FOR AUTOMOTIVE, BY APPLICATION,
2015–2023 (USD MILLION) 83
TABLE 29 DEEP LEARNING MARKET FOR AGRICULTURE, BY OFFERING,
2015–2023 (USD MILLION) 85
TABLE 30 DEEP LEARNING MARKET FOR AGRICULTURE, BY APPLICATION,
2015–2023 (USD MILLION) 86
TABLE 31 DEEP LEARNING MARKET FOR RETAIL, BY OFFERING, 2015–2023 (USD MILLION) 89
TABLE 32 DEEP LEARNING MARKET FOR RETAIL, BY APPLICATION,
2015–2023 (USD MILLION) 89
TABLE 33 DEEP LEARNING MARKET FOR SECURITY, BY OFFERING,
2015–2023 (USD MILLION) 92
TABLE 34 DEEP LEARNING MARKET FOR SECURITY, BY APPLICATION,
2015–2023 (USD MILLION) 94
TABLE 35 DEEP LEARNING MARKET FOR HR, BY OFFERING, 2015–2023 (USD MILLION) 96
TABLE 36 DEEP LEARNING MARKET FOR HR, BY APPLICATION, 2015–2023 (USD MILLION) 98
TABLE 37 DEEP LEARNING MARKET FOR MARKETING, BY OFFERING,
2015–2023 (USD MILLION) 100
TABLE 38 DEEP LEARNING MARKET FOR MARKETING, BY APPLICATION,
2015–2023 (USD MILLION) 101
TABLE 39 DEEP LEARNING MARKET FOR LAW, BY OFFERING, 2015–2023 (USD MILLION) 103
TABLE 40 DEEP LEARNING MARKET FOR LAW, BY APPLICATION, 2015–2023 (USD MILLION) 104
TABLE 41 DEEP LEARNING MARKET FOR FINTECH, BY OFFERING,
2015–2023 (USD MILLION) 106
TABLE 42 DEEP LEARNING MARKET FOR FINTECH, BY APPLICATION,
2015–2023 (USD MILLION) 107
TABLE 43 DEEP LEARNING MARKET, BY REGION, 2015–2023 (USD MILLION) 111
TABLE 44 DEEP LEARNING MARKET IN NORTH AMERICA, BY COUNTRY,
2015–2023 (USD MILLION) 114
TABLE 45 DEEP LEARNING MARKET IN US, BY END-USER INDUSTRY,
2015–2023 (USD MILLION) 115
TABLE 46 DEEP LEARNING MARKET IN CANADA, BY END-USER INDUSTRY,
2015–2023 (USD MILLION) 116
TABLE 47 DEEP LEARNING MARKET IN MEXICO, BY END-USER INDUSTRY,
2015–2023 (USD MILLION) 117
TABLE 48 DEEP LEARNING MARKET IN EUROPE, BY COUNTRY, 2015–2023 (USD MILLION) 120
TABLE 49 DEEP LEARNING MARKET IN UK, BY END-USER INDUSTRY,
2015–2023 (USD MILLION) 121
TABLE 50 DEEP LEARNING MARKET IN GERMANY, BY END-USER INDUSTRY,
2015–2023 (USD MILLION) 122
TABLE 51 DEEP LEARNING MARKET IN FRANCE, BY END-USER INDUSTRY,
2015–2023 (USD MILLION) 123
TABLE 52 DEEP LEARNING MARKET IN ITALY, BY END-USER INDUSTRY,
2015–2023 (USD MILLION) 124
TABLE 53 DEEP LEARNING MARKET IN SPAIN, BY END-USER INDUSTRY,
2015–2023 (USD MILLION) 125
TABLE 54 DEEP LEARNING MARKET IN REST OF EUROPE, BY END-USER INDUSTRY,
2015–2023 (USD MILLION) 126
TABLE 55 DEEP LEARNING MARKET IN APAC, BY COUNTRY, 2015–2023 (USD MILLION) 128
TABLE 56 DEEP LEARNING MARKET IN CHINA, BY END-USER INDUSTRY,
2015–2023 (USD MILLION) 129
TABLE 57 DEEP LEARNING MARKET IN JAPAN, BY END-USER INDUSTRY,
2015–2023 (USD MILLION) 130
TABLE 58 DEEP LEARNING MARKET IN SOUTH KOREA, BY END-USER INDUSTRY,
2015–2023 (USD MILLION) 131
TABLE 59 DEEP LEARNING MARKET IN INDIA, BY END-USER INDUSTRY,
2015–2023 (USD MILLION) 132
TABLE 60 DEEP LEARNING MARKET IN REST OF APAC, BY END-USER INDUSTRY,
2015–2023 (USD MILLION) 133
TABLE 61 DEEP LEARNING MARKET IN ROW, BY REGION, 2015–2023 (USD MILLION) 135
TABLE 62 DEEP LEARNING MARKET IN MIDDLE EAST AND AFRICA, BY END-USER INDUSTRY, 2015–2023 (USD MILLION) 136
TABLE 63 DEEP LEARNING MARKET IN SOUTH AMERICA, BY END-USER INDUSTRY,
2015–2023 (USD MILLION) 137
TABLE 64 RANKING OF KEY COMPANIES IN DEEP LEARNING MARKET (2017) 139
TABLE 65 NEW PRODUCT DEVELOPMENTS AND LAUNCHES (2015–2017) 142
TABLE 66 COLLABORATIONS AND PARTNERSHIPS (2015–2017) 147
TABLE 67 ACQUISITIONS (2015–2017) 150
TABLE 68 OTHERS (2015–2017) 152

 

LIST OF FIGURES

FIGURE 1 DEEP LEARNING MARKET SEGMENTATION 19
FIGURE 2 DEEP LEARNING MARKET: RESEARCH DESIGN 21
FIGURE 3 MARKET SIZE ESTIMATION METHODOLOGY: BOTTOM-UP APPROACH 27
FIGURE 4 MARKET SIZE ESTIMATION METHODOLOGY: TOP-DOWN APPROACH 28
FIGURE 5 DATA TRIANGULATION 29
FIGURE 6 DEEP LEARNING MARKET, BY OFFERING, 2018 VS. 2023 (USD BILLION) 32
FIGURE 7 DEEP LEARNING MARKET, BY PROCESSOR, 2015–2023 (USD BILLION) 33
FIGURE 8 DEEP LEARNING MARKET, BY APPLICATION, 2018 VS. 2023 (USD BILLION) 34
FIGURE 9 DEEP LEARNING MARKET, BY END-USER INDUSTRY, 2018 VS. 2023 35
FIGURE 10 DEEP LEARNING MARKET, BY REGION, 2018 36
FIGURE 11 IMPROVING COMPUTING POWER AND DECLINING HARDWARE COST DRIVING
DEEP LEARNING MARKET 37
FIGURE 12 SOFTWARE TO HOLD LARGEST SIZE OF DEEP LEARNING MARKET BY 2023 38
FIGURE 13 PROCESSOR TO HOLD LARGEST SHARE OF DEEP LEARNING MARKET BY 2023 38
FIGURE 14 CHINA EXPECTED TO HOLD LARGEST SHARE OF DEEP LEARNING MARKET IN
APAC IN 2018 39
FIGURE 15 DEEP LEARNING MARKET IN CHINA TO GROW AT HIGHEST CAGR DURING FORECAST PERIOD 40
FIGURE 16 INCREASING ADOPTION OF CLOUD-BASED TECHNOLOGY AND DEEP LEARNING USAGE IN BIG DATA ANALYTICS DRIVING DEEP LEARNING MARKET 41
FIGURE 17 VALUE CHAIN ANALYSIS: MAJOR VALUE ADDED DURING MANUFACTURING AND TESTING PHASES 46
FIGURE 18 DEEP LEARNING MARKET, BY OFFERING 50
FIGURE 19 DEEP LEARNING PROCESSOR MARKET FOR OTHERS TO GROW AT HIGHEST CAGR DURING FORECAST PERIOD 53
FIGURE 20 DEEP LEARNING SOFTWARE MARKET FOR DATA MINING TO GROW AT HIGHEST CAGR DURING FORECAST PERIOD 58
FIGURE 21 IMAGE RECOGNITION TO HOLD MAJOR SHARE OF DEEP LEARNING MARKET BETWEEN 2018 AND 2023 63
FIGURE 22 DEEP LEARNING MARKET (OTHERS) FOR SERVICES TO GROW AT HIGHEST CAGR DURING FORECAST PERIOD 68
FIGURE 23 DEEP LEARNING MARKET FOR MANUFACTURING TO GROW AT HIGHEST CAGR DURING FORECAST PERIOD 71
FIGURE 24 PREDICTIVE MAINTENANCE AND MACHINERY INSPECTION TO HOLD LARGEST SIZE OF DEEP LEARNING MARKET FOR MANUFACTURING DURING FORECAST PERIOD 78
FIGURE 25 SOFTWARE TO HOLD LARGEST SHARE OF DEEP LEARNING MARKET FOR AUTOMOTIVE DURING FORECAST PERIOD 82
FIGURE 26 PRECISION FARMING TO HOLD LARGEST SIZE OF DEEP LEARNING MARKET FOR AGRICULTURE DURING FORECAST PERIOD 86
FIGURE 27 ANTIVIRUS/ANTIMALWARE TO HOLD LARGEST SIZE OF DEEP LEARNING MARKET FOR SECURITY BY 2023 93
FIGURE 28 DEEP LEARNING MARKET (HR) FOR APPLICANT TRACKING & ASSESSMENT TO GROW AT HIGHEST CAGR DURING FORECAST PERIOD 97
FIGURE 29 SEARCH ADVERTISING TO HOLD LARGEST SHARE OF DEEP LEARNING MARKET FOR MARKETING DURING FORECAST PERIOD 101
FIGURE 30 DEEP LEARNING MARKET (FINTECH) FOR VIRTUAL ASSISTANT TO GROW AT HIGHEST CAGR BETWEEN 2018 AND 2023 106
FIGURE 31 DEEP LEARNING MARKET GEOGRAPHIC SNAPSHOT (2018–2023) 110
FIGURE 32 DEEP LEARNING MARKET IN APAC TO GROW AT HIGHEST CAGR FROM
2018 TO 2023 111
FIGURE 33 DEEP LEARNING MARKET SNAPSHOT: NORTH AMERICA 113
FIGURE 34 HEALTHCARE TO HOLD LARGEST SIZE OF DEEP LEARNING MARKET IN MEXICO
BY 2023 117
FIGURE 35 DEEP LEARNING MARKET SNAPSHOT: EUROPE 119
FIGURE 36 HEALTHCARE TO HOLD LARGEST SIZE OF FRENCH DEEP LEARNING MARKET
BY 2023 123
FIGURE 37 DEEP LEARNING MARKET SNAPSHOT: APAC 127
FIGURE 38 MARKETING TO HOLD LARGEST SIZE OF DEEP LEARNING MARKET IN CHINA
BY 2023 129
FIGURE 39 DEEP LEARNING MARKET SNAPSHOT: ROW 134
FIGURE 40 SECURITY TO HOLD LARGEST SHARE OF DEEP LEARNING MARKET IN MIDDLE EAST & AFRICA BY 2023 135
FIGURE 41 COMPANIES ADOPTED COLLABORATION AS KEY GROWTH STRATEGY BETWEEN 2015 AND 2017 138
FIGURE 42 NEW PRODUCT DEVELOPMENTS–KEY STRATEGY ADOPTED BY PLAYERS BETWEEN 2015 AND 2017 141
FIGURE 43 AWS: COMPANY SNAPSHOT 154
FIGURE 44 GOOGLE: COMPANY SNAPSHOT 158
FIGURE 45 IBM: COMPANY SNAPSHOT 161
FIGURE 46 INTEL: COMPANY SNAPSHOT 165
FIGURE 47 MICRON TECHNOLOGY: COMPANY SNAPSHOT 169
FIGURE 48 MICROSOFT: COMPANY SNAPSHOT 172
FIGURE 49 NVIDIA: COMPANY SNAPSHOT 176
FIGURE 50 QUALCOMM TECHNOLOGIES: COMPANY SNAPSHOT 181
FIGURE 51 SAMSUNG ELECTRONICS: COMPANY SNAPSHOT 184
FIGURE 52 XILINX: COMPANY SNAPSHOT 192
 

 

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プレスリリース

[プレスリリース原文]

Deep Learning Market worth 18.16 Billion USD by 2023


March 26, 2018

According to the latest market research report "Deep Learning Market by Offering (Hardware, Software, and Services), Application (Image Recognition, Signal Recognition, Data Mining), End-User Industry (Security, Marketing, Healthcare, Fintech, Automotive, Law), and Geography - Global Forecast to 2023", the deep learning market, the overall deep learning market is estimated to be valued at USD 3.18 Billion in 2018 and is expected to be worth USD 18.16 Billion by 2023, at a CAGR of 41.7% from 2018 to 2023. Improving computing power, declining hardware cost, and the increasing adoption of cloud-based technology are fueling the growth of the deep learning market. Usage in big data analytics and growing AI adoption in customer-centric services are the other key factors driving this market.

Software to hold largest market share from 2018 to 2023

Software currently holds the largest market share, while the market for services is expected to grow at the highest CAGR between 2018 and 2023. The software segment consists of software frameworks and platforms/APIs developed using algorithms and codes that enable hardware to carry out deep learning programs. Manufacturers and software providers offer different solutions (frameworks/software development kits (SDKs)) and APIs/platforms that are open to developers working on deep learning programs. For example, Qualcomm offers Zeroth SDK, which helps users and developers use Snapdragon 820 capabilities for deep learning applications such as image and sound processing, including speech recognition. The hardware segment consists of processor chips used for running deep learning algorithms based on neuromorphic architecture and/or von Neumann architecture.

Deep learning market for data mining to grow at highest CAGR from 2018 to 2023

Data mining abstracts related data from files, such as image, video, and audio. With the advent of new technologies, natural language processing and visual data mining have been developed using deep learning techniques. Data mining is used in the following applications: sentiment analysis, machine translation, fingerprint identification, cybersecurity, and bioinformatics. Deep learning offers faster and better memory utilization than traditional computing systems. As data mining is a complex operation, it requires complex hardware architecture and algorithms to perform computational functions, along with service and maintenance of systems. Thus, the demand for services in data mining is expected to grow significantly between 2018 and 2023.

Security to account for largest market size among other end-user industries between 2018 and 2023

Deep learning- and AI-based systems are being significantly used in antivirus and antimalware solutions owing to the rise in cybersecurity attacks across the world. The increasing use of mobile devices for a wide range of applications, such as social networking, emails, remote monitoring, phone banking, and data storage, opens doors for hackers to attack, thereby making networks more vulnerable to risks. The rapid adoption of cloud-based services, along with the user-friendly approach of antivirus/antimalware solutions, is contributing to the growth of this application in the deep learning market for security. The adoption of DL technologies for encryption is likely to witness growth in the coming years.

North America to lead deep learning market in terms of market size

North America accounts for a substantial share of the deep learning market, with the US being the major contributor. The increasing adoption of deep learning technology in various end-user industries, such as security, marketing, healthcare, fintech, automotive, law, retail, agriculture, and manufacturing, and the strong presence of industry giants and emerging deep learning companies/start-ups in the region are the key factors supporting the growth of the deep learning market in North America.

Companies that are profiled in this report are NVIDIA (US), Intel (US), Xilinx (US), Samsung Electronics (South Korea), Micron Technology (US), Qualcomm (US), IBM (US), Google (US), Microsoft (US), and AWS (US). Some of the key start-ups included in this report are Graphcore (UK), Mythic (US), Adapteva (US), and Koniku (US).

 

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