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[ 英語タイトル ] 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


Product Code : MNMSE00109558
Survey : MarketsandMarkets
Publish On : February, 2021
Category : Semiconductor and Electronics
Study Area : Global
Report format : PDF
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[Report Description]

“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.

TABLE OF CONTENTS

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

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