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
“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:
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
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%
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.
1 INTRODUCTION
1.1 STUDY OBJECTIVES
1.2 DEFINITION
1.3 STUDY SCOPE
1.3.1 MARKETS COVERED
1.3.2 YEARS CONSIDERED FOR THIS STUDY
1.4 CURRENCY
1.5 STAKEHOLDERS
2 RESEARCH METHODOLOGY
2.1 RESEARCH DATA
2.1.1 SECONDARY AND PRIMARY RESEARCH
2.1.1.1 Key industry insights
2.1.2 SECONDARY DATA
2.1.2.1 Major secondary sources
2.1.2.2 Secondary sources
2.1.3 PRIMARY DATA
2.1.3.1 Primary interviews with experts
2.1.3.2 Breakdown of primaries
2.1.3.3 Primary sources
2.2 MARKET SIZE ESTIMATION
2.2.1 BOTTOM-UP APPROACH
2.2.1.1 Approach for capturing market share by bottom-up analysis (demand side)
2.2.2 TOP-DOWN APPROACH
2.2.2.1 Approach for capturing market share by top-down analysis (supply side)
2.3 MARKET BREAKDOWN AND DATA TRIANGULATION
2.4 RESEARCH ASSUMPTIONS
3 EXECUTIVE SUMMARY
4 PREMIUM INSIGHTS
4.1 ATTRACTIVE OPPORTUNITIES IN DEEP LEARNING MARKET
4.2 DEEP LEARNING MARKET, BY OFFERING
4.3 DEEP LEARNING MARKET, BY HARDWARE
4.4 DEEP LEARNING MARKET IN APAC, BY END-USER INDUSTRY AND COUNTRY
4.5 DEEP LEARNING MARKET, BY COUNTRY
5 MARKET OVERVIEW
5.1 INTRODUCTION
5.2 MARKET DYNAMICS
5.2.1 DRIVERS
5.2.1.1 Improving computing power and declining hardware cost
5.2.1.2 Increasing adoption of cloud-based technology
5.2.1.3 Deep learning usage in big data analytics
5.2.1.4 Growing AI adoption in customer-centric services
5.2.2 RESTRAINTS
5.2.2.1 Increasing complexity in hardware due to complex algorithm used in deep learning technology
5.2.2.2 Lack of technical expertise and absence of standards and protocols
5.2.3 OPPORTUNITIES
5.2.3.1 Presence of limited structured data to increase demand for deep learning solutions
5.2.3.2 Cumulative spending in healthcare, travel, tourism, and hospitality industries
5.2.4 CHALLENGES
5.2.4.1 Lack of flexibility and multitasking
5.2.4.2 Deployment of DL for applications such as NLP in regional dialects
5.3 VALUE CHAIN ANALYSIS
5.4 SOME OF THE PROMINENT ML LIBRARIES (SOFTWARE FRAMEWORKS)
6 DEEP LEARNING MARKET, BY OFFERING
6.1 INTRODUCTION
6.2 HARDWARE
6.2.1 PROCESSOR
6.2.2 MEMORY
6.2.3 NETWORK
6.3 SOFTWARE
6.3.1 SOLUTION (SOFTWARE FRAMEWORK/SDK)
6.3.2 PLATFORM/API
6.4 SERVICES
6.4.1 INSTALLATION
6.4.2 TRAINING
6.4.3 SUPPORT & MAINTENANCE
7 DEEP LEARNING MARKET, BY APPLICATION
7.1 INTRODUCTION
7.2 IMAGE RECOGNITION
7.3 SIGNAL RECOGNITION
7.4 DATA MINING
7.5 OTHERS (RECOMMENDER SYSTEM AND DRUG DISCOVERY)
8 DEEP LEARNING MARKET, BY END-USER INDUSTRY
8.1 INTRODUCTION
8.2 HEALTHCARE
8.2.1 PATIENT DATA & RISK ANALYSIS
8.2.2 LIFESTYLE MANAGEMENT & MONITORING
8.2.3 PRECISION MEDICINE
8.2.4 INPATIENT CARE & HOSPITAL MANAGEMENT
8.2.5 MEDICAL IMAGING & DIAGNOSTICS
8.2.6 DRUG DISCOVERY
8.2.7 VIRTUAL ASSISTANT
8.2.8 WEARABLES
8.2.9 RESEARCH
8.3 MANUFACTURING
8.3.1 MATERIAL MOVEMENT
8.3.2 PREDICTIVE MAINTENANCE AND MACHINERY INSPECTION
8.3.3 PRODUCTION PLANNING
8.3.4 FIELD SERVICES
8.3.5 RECLAMATION
8.3.6 QUALITY CONTROL
8.4 AUTOMOTIVE
8.4.1 AUTONOMOUS DRIVING
8.4.2 HUMAN–MACHINE INTERFACE
8.4.3 SEMIAUTONOMOUS DRIVING
8.5 AGRICULTURE
8.5.1 PRECISION FARMING
8.5.2 LIVESTOCK MONITORING
8.5.3 DRONE ANALYTICS
8.5.4 AGRICULTURAL ROBOTS
8.5.5 OTHERS
8.6 RETAIL
8.6.1 PRODUCT RECOMMENDATION AND PLANNING
8.6.2 CUSTOMER RELATIONSHIP MANAGEMENT
8.6.3 VISUAL SEARCH
8.6.4 VIRTUAL ASSISTANT
8.6.5 PRICE OPTIMIZATION
8.6.6 PAYMENT SERVICES MANAGEMENT
8.6.7 SUPPLY CHAIN MANAGEMENT AND DEMAND PLANNING
8.6.8 OTHERS
8.7 SECURITY
8.7.1 IDENTITY AND ACCESS MANAGEMENT (IAM)
8.7.2 RISK AND COMPLIANCE MANAGEMENT
8.7.3 ENCRYPTION
8.7.4 DATA LOSS PREVENTION
8.7.5 UNIFIED THREAT MANAGEMENT
8.7.6 ANTIVIRUS/ANTIMALWARE
8.7.7 INTRUSION DETECTION/PREVENTION SYSTEMS
8.7.8 OTHERS
8.8 HUMAN RESOURCES
8.8.1 VIRTUAL ASSISTANT
8.8.2 SENTIMENT ANALYSIS
8.8.3 SCHEDULING GROUP MEETINGS AND INTERVIEWS
8.8.4 PERSONALIZED LEARNING AND DEVELOPMENT
8.8.5 APPLICANT TRACKING & ASSESSMENT
8.8.6 EMPLOYEE ENGAGEMENT
8.8.7 RESUME ANALYSIS
8.9 MARKETING
8.9.1 SOCIAL MEDIA ADVERTISING
8.9.2 SEARCH ADVERTISING
8.9.3 DYNAMIC PRICING
8.9.4 VIRTUAL ASSISTANT
8.9.5 CONTENT CURATION
8.9.6 SALES & MARKETING AUTOMATION
8.9.7 ANALYTICS PLATFORM
8.9.8 OTHERS
8.10 LAW
8.10.1 EDISCOVERY
8.10.2 LEGAL RESEARCH
8.10.3 CONTRACT ANALYSIS
8.10.4 CASE PREDICTION
8.10.5 COMPLIANCE
8.10.6 OTHERS
8.11 FINTECH
8.11.1 VIRTUAL ASSISTANT
8.11.2 BUSINESS ANALYTICS AND REPORTING
8.11.3 CUSTOMER BEHAVIOR ANALYTICS
8.11.4 OTHERS
9 GEOGRAPHIC ANALYSIS
9.1 INTRODUCTION
9.2 NORTH AMERICA
9.2.1 US
9.2.2 CANADA
9.2.3 MEXICO
9.3 EUROPE
9.3.1 UK
9.3.2 GERMANY
9.3.3 FRANCE
9.3.4 ITALY
9.3.5 SPAIN
9.3.6 REST OF EUROPE
9.4 APAC
9.4.1 CHINA
9.4.2 JAPAN
9.4.3 SOUTH KOREA
9.4.4 INDIA
9.4.5 REST OF APAC
9.5 ROW
9.5.1 MIDDLE EAST AND AFRICA
9.5.2 SOUTH AMERICA
10 COMPETITIVE LANDSCAPE
10.1 OVERVIEW
10.2 RANKING ANALYSIS: DEEP LEARNING MARKET
10.3 COMPETITIVE SITUATION AND TREND
10.3.1 NEW PRODUCT DEVELOPMENTS AND LAUNCHES
10.3.2 COLLABORATIONS AND PARTNERSHIPS
10.3.3 ACQUISITIONS
10.3.4 OTHERS
11 COMPANY PROFILES
(Business Overview, Products Offered, Recent Developments, SWOT Analysis, and MnM View)*
11.1 KEY PLAYERS
11.1.1 AMAZON WEB SERVICES (AWS)
11.1.2 GOOGLE
11.1.3 IBM
11.1.4 INTEL
11.1.5 MICRON TECHNOLOGY
11.1.6 MICROSOFT
11.1.7 NVIDIA
11.1.8 QUALCOMM
11.1.9 SAMSUNG ELECTRONICS
11.1.10 SENSORY INC.
11.1.11 SKYMIND
11.1.12 XILINX
11.2 OTHER COMPANIES
11.2.1 AMD
11.2.2 GENERAL VISION
11.2.3 GRAPHCORE
11.2.4 MELLANOX TECHNOLOGIES
11.2.5 HUAWEI TECHNOLOGIES
11.2.6 FUJITSU
11.2.7 BAIDU
11.2.8 MYTHIC
11.2.9 ADAPTEVA, INC.
11.2.10 KONIKU
11.2.11 TENSTORRENT
*Details on Business Overview, Products Offered, Recent Developments, SWOT Analysis, and MnM View might not be captured in case of unlisted companies.
12 APPENDIX
12.1 INSIGHTS OF INDUSTRY EXPERTS
12.2 DISCUSSION GUIDE
12.3 KNOWLEDGE STORE: MARKETSANDMARKETS’ SUBSCRIPTION PORTAL
12.4 INTRODUCING RT: REAL-TIME MARKET INTELLIGENCE
12.5 AVAILABLE CUSTOMIZATIONS
12.6 RELATED REPORTS
12.7 AUTHOR DETAILS
1.1 STUDY OBJECTIVES
1.2 DEFINITION
1.3 STUDY SCOPE
1.3.1 MARKETS COVERED
1.3.2 YEARS CONSIDERED FOR THIS STUDY
1.4 CURRENCY
1.5 STAKEHOLDERS
2 RESEARCH METHODOLOGY
2.1 RESEARCH DATA
2.1.1 SECONDARY AND PRIMARY RESEARCH
2.1.1.1 Key industry insights
2.1.2 SECONDARY DATA
2.1.2.1 Major secondary sources
2.1.2.2 Secondary sources
2.1.3 PRIMARY DATA
2.1.3.1 Primary interviews with experts
2.1.3.2 Breakdown of primaries
2.1.3.3 Primary sources
2.2 MARKET SIZE ESTIMATION
2.2.1 BOTTOM-UP APPROACH
2.2.1.1 Approach for capturing market share by bottom-up analysis (demand side)
2.2.2 TOP-DOWN APPROACH
2.2.2.1 Approach for capturing market share by top-down analysis (supply side)
2.3 MARKET BREAKDOWN AND DATA TRIANGULATION
2.4 RESEARCH ASSUMPTIONS
3 EXECUTIVE SUMMARY
4 PREMIUM INSIGHTS
4.1 ATTRACTIVE OPPORTUNITIES IN DEEP LEARNING MARKET
4.2 DEEP LEARNING MARKET, BY OFFERING
4.3 DEEP LEARNING MARKET, BY HARDWARE
4.4 DEEP LEARNING MARKET IN APAC, BY END-USER INDUSTRY AND COUNTRY
4.5 DEEP LEARNING MARKET, BY COUNTRY
5 MARKET OVERVIEW
5.1 INTRODUCTION
5.2 MARKET DYNAMICS
5.2.1 DRIVERS
5.2.1.1 Improving computing power and declining hardware cost
5.2.1.2 Increasing adoption of cloud-based technology
5.2.1.3 Deep learning usage in big data analytics
5.2.1.4 Growing AI adoption in customer-centric services
5.2.2 RESTRAINTS
5.2.2.1 Increasing complexity in hardware due to complex algorithm used in deep learning technology
5.2.2.2 Lack of technical expertise and absence of standards and protocols
5.2.3 OPPORTUNITIES
5.2.3.1 Presence of limited structured data to increase demand for deep learning solutions
5.2.3.2 Cumulative spending in healthcare, travel, tourism, and hospitality industries
5.2.4 CHALLENGES
5.2.4.1 Lack of flexibility and multitasking
5.2.4.2 Deployment of DL for applications such as NLP in regional dialects
5.3 VALUE CHAIN ANALYSIS
5.4 SOME OF THE PROMINENT ML LIBRARIES (SOFTWARE FRAMEWORKS)
6 DEEP LEARNING MARKET, BY OFFERING
6.1 INTRODUCTION
6.2 HARDWARE
6.2.1 PROCESSOR
6.2.2 MEMORY
6.2.3 NETWORK
6.3 SOFTWARE
6.3.1 SOLUTION (SOFTWARE FRAMEWORK/SDK)
6.3.2 PLATFORM/API
6.4 SERVICES
6.4.1 INSTALLATION
6.4.2 TRAINING
6.4.3 SUPPORT & MAINTENANCE
7 DEEP LEARNING MARKET, BY APPLICATION
7.1 INTRODUCTION
7.2 IMAGE RECOGNITION
7.3 SIGNAL RECOGNITION
7.4 DATA MINING
7.5 OTHERS (RECOMMENDER SYSTEM AND DRUG DISCOVERY)
8 DEEP LEARNING MARKET, BY END-USER INDUSTRY
8.1 INTRODUCTION
8.2 HEALTHCARE
8.2.1 PATIENT DATA & RISK ANALYSIS
8.2.2 LIFESTYLE MANAGEMENT & MONITORING
8.2.3 PRECISION MEDICINE
8.2.4 INPATIENT CARE & HOSPITAL MANAGEMENT
8.2.5 MEDICAL IMAGING & DIAGNOSTICS
8.2.6 DRUG DISCOVERY
8.2.7 VIRTUAL ASSISTANT
8.2.8 WEARABLES
8.2.9 RESEARCH
8.3 MANUFACTURING
8.3.1 MATERIAL MOVEMENT
8.3.2 PREDICTIVE MAINTENANCE AND MACHINERY INSPECTION
8.3.3 PRODUCTION PLANNING
8.3.4 FIELD SERVICES
8.3.5 RECLAMATION
8.3.6 QUALITY CONTROL
8.4 AUTOMOTIVE
8.4.1 AUTONOMOUS DRIVING
8.4.2 HUMAN–MACHINE INTERFACE
8.4.3 SEMIAUTONOMOUS DRIVING
8.5 AGRICULTURE
8.5.1 PRECISION FARMING
8.5.2 LIVESTOCK MONITORING
8.5.3 DRONE ANALYTICS
8.5.4 AGRICULTURAL ROBOTS
8.5.5 OTHERS
8.6 RETAIL
8.6.1 PRODUCT RECOMMENDATION AND PLANNING
8.6.2 CUSTOMER RELATIONSHIP MANAGEMENT
8.6.3 VISUAL SEARCH
8.6.4 VIRTUAL ASSISTANT
8.6.5 PRICE OPTIMIZATION
8.6.6 PAYMENT SERVICES MANAGEMENT
8.6.7 SUPPLY CHAIN MANAGEMENT AND DEMAND PLANNING
8.6.8 OTHERS
8.7 SECURITY
8.7.1 IDENTITY AND ACCESS MANAGEMENT (IAM)
8.7.2 RISK AND COMPLIANCE MANAGEMENT
8.7.3 ENCRYPTION
8.7.4 DATA LOSS PREVENTION
8.7.5 UNIFIED THREAT MANAGEMENT
8.7.6 ANTIVIRUS/ANTIMALWARE
8.7.7 INTRUSION DETECTION/PREVENTION SYSTEMS
8.7.8 OTHERS
8.8 HUMAN RESOURCES
8.8.1 VIRTUAL ASSISTANT
8.8.2 SENTIMENT ANALYSIS
8.8.3 SCHEDULING GROUP MEETINGS AND INTERVIEWS
8.8.4 PERSONALIZED LEARNING AND DEVELOPMENT
8.8.5 APPLICANT TRACKING & ASSESSMENT
8.8.6 EMPLOYEE ENGAGEMENT
8.8.7 RESUME ANALYSIS
8.9 MARKETING
8.9.1 SOCIAL MEDIA ADVERTISING
8.9.2 SEARCH ADVERTISING
8.9.3 DYNAMIC PRICING
8.9.4 VIRTUAL ASSISTANT
8.9.5 CONTENT CURATION
8.9.6 SALES & MARKETING AUTOMATION
8.9.7 ANALYTICS PLATFORM
8.9.8 OTHERS
8.10 LAW
8.10.1 EDISCOVERY
8.10.2 LEGAL RESEARCH
8.10.3 CONTRACT ANALYSIS
8.10.4 CASE PREDICTION
8.10.5 COMPLIANCE
8.10.6 OTHERS
8.11 FINTECH
8.11.1 VIRTUAL ASSISTANT
8.11.2 BUSINESS ANALYTICS AND REPORTING
8.11.3 CUSTOMER BEHAVIOR ANALYTICS
8.11.4 OTHERS
9 GEOGRAPHIC ANALYSIS
9.1 INTRODUCTION
9.2 NORTH AMERICA
9.2.1 US
9.2.2 CANADA
9.2.3 MEXICO
9.3 EUROPE
9.3.1 UK
9.3.2 GERMANY
9.3.3 FRANCE
9.3.4 ITALY
9.3.5 SPAIN
9.3.6 REST OF EUROPE
9.4 APAC
9.4.1 CHINA
9.4.2 JAPAN
9.4.3 SOUTH KOREA
9.4.4 INDIA
9.4.5 REST OF APAC
9.5 ROW
9.5.1 MIDDLE EAST AND AFRICA
9.5.2 SOUTH AMERICA
10 COMPETITIVE LANDSCAPE
10.1 OVERVIEW
10.2 RANKING ANALYSIS: DEEP LEARNING MARKET
10.3 COMPETITIVE SITUATION AND TREND
10.3.1 NEW PRODUCT DEVELOPMENTS AND LAUNCHES
10.3.2 COLLABORATIONS AND PARTNERSHIPS
10.3.3 ACQUISITIONS
10.3.4 OTHERS
11 COMPANY PROFILES
(Business Overview, Products Offered, Recent Developments, SWOT Analysis, and MnM View)*
11.1 KEY PLAYERS
11.1.1 AMAZON WEB SERVICES (AWS)
11.1.2 GOOGLE
11.1.3 IBM
11.1.4 INTEL
11.1.5 MICRON TECHNOLOGY
11.1.6 MICROSOFT
11.1.7 NVIDIA
11.1.8 QUALCOMM
11.1.9 SAMSUNG ELECTRONICS
11.1.10 SENSORY INC.
11.1.11 SKYMIND
11.1.12 XILINX
11.2 OTHER COMPANIES
11.2.1 AMD
11.2.2 GENERAL VISION
11.2.3 GRAPHCORE
11.2.4 MELLANOX TECHNOLOGIES
11.2.5 HUAWEI TECHNOLOGIES
11.2.6 FUJITSU
11.2.7 BAIDU
11.2.8 MYTHIC
11.2.9 ADAPTEVA, INC.
11.2.10 KONIKU
11.2.11 TENSTORRENT
*Details on Business Overview, Products Offered, Recent Developments, SWOT Analysis, and MnM View might not be captured in case of unlisted companies.
12 APPENDIX
12.1 INSIGHTS OF INDUSTRY EXPERTS
12.2 DISCUSSION GUIDE
12.3 KNOWLEDGE STORE: MARKETSANDMARKETS’ SUBSCRIPTION PORTAL
12.4 INTRODUCING RT: REAL-TIME MARKET INTELLIGENCE
12.5 AVAILABLE CUSTOMIZATIONS
12.6 RELATED REPORTS
12.7 AUTHOR DETAILS
LIST OF TABLES
Table 1 PRICE COMPARISON: AI CHIPSETS (LEADING COMPANIES)
Table 2 COMPANIES OFFERING CLOUD SERVICES FOR DEEP/MACHINE LEARNING
Table 3 MACHINE LEARNING LIBRARIES BY VARIOUS MARKET PLAYERS (2015–2017)
Table 4 DEEP LEARNING MARKET, BY OFFERING, 2015–2023 (USD MILLION)
Table 5 INDUSTRY PLAYERS IN DEEP LEARNING MARKET, 2017
Table 6 DEEP LEARNING MARKET, BY HARDWARE, 2015–2023 (USD MILLION)
Table 7 DEEP LEARNING MARKET, BY PROCESSOR, 2015–2023 (USD MILLION)
Table 8 DEEP LEARNING MARKET, BY PROCESSOR, 2015–2023 (THOUSAND UNITS)
Table 9 DEEP LEARNING HARDWARE MARKET, BY APPLICATION, 2015–2023 (USD MILLION)
Table 10 DEEP LEARNING HARDWARE MARKET, BY END-USER INDUSTRY, 2015–2023 (USD MILLION)
Table 11 DEEP LEARNING MARKET, BY SOFTWARE, 2015–2023 (USD MILLION)
Table 12 DEEP LEARNING SOFTWARE MARKET, BY APPLICATION, 2015–2023 (USD MILLION)
Table 13 DEEP LEARNING SOFTWARE MARKET, BY END-USER INDUSTRY, 2015–2023 (USD MILLION)
Table 14 DEEP LEARNING MARKET, BY SERVICE, 2015–2023 (USD MILLION)
Table 15 DEEP LEARNING SERVICE MARKET, BY APPLICATION, 2015–2023 (USD MILLION)
Table 16 DEEP LEARNING SERVICE MARKET, BY END-USER INDUSTRY, 2015–2023 (USD MILLION)
Table 17 DEEP LEARNING MARKET, BY APPLICATION, 2015–2023 (USD MILLION)
Table 18 DEEP LEARNING MARKET FOR IMAGE RECOGNITION, BY OFFERING, 2015–2023 (USD MILLION)
Table 19 DEEP LEARNING MARKET FOR SIGNAL RECOGNITION, BY OFFERING, 2015–2023 (USD MILLION)
Table 20 DEEP LEARNING MARKET FOR DATA MINING, BY OFFERING, 2015–2023 (USD MILLION)
Table 21 DEEP LEARNING MARKET FOR OTHERS, BY OFFERING, 2015–2023 (USD MILLION)
Table 22 DEEP LEARNING MARKET, BY END-USER INDUSTRY, 2015–2023 (USD MILLION)
Table 23 DEEP LEARNING MARKET FOR HEALTHCARE, BY OFFERING, 2015–2023 (USD MILLION)
Table 24 DEEP LEARNING MARKET FOR HEALTHCARE, BY APPLICATION, 2015–2023 (USD MILLION)
Table 25 DEEP LEARNING MARKET FOR MANUFACTURING, BY OFFERING, 2015–2023 (USD MILLION)
Table 26 DEEP LEARNING MARKET FOR MANUFACTURING, BY APPLICATION, 2015–2023 (USD MILLION)
Table 27 DEEP LEARNING MARKET FOR AUTOMOTIVE, BY OFFERING, 2015–2023 (USD MILLION)
Table 28 DEEP LEARNING MARKET FOR AUTOMOTIVE, BY APPLICATION, 2015–2023 (USD MILLION)
Table 29 DEEP LEARNING MARKET FOR AGRICULTURE, BY OFFERING, 2015–2023 (USD MILLION)
Table 30 DEEP LEARNING MARKET FOR AGRICULTURE, BY APPLICATION, 2015–2023 (USD MILLION)
Table 31 DEEP LEARNING MARKET FOR RETAIL, BY OFFERING, 2015–2023 (USD MILLION)
Table 32 DEEP LEARNING MARKET FOR RETAIL, BY APPLICATION, 2015–2023 (USD MILLION)
Table 33 DEEP LEARNING MARKET FOR SECURITY, BY OFFERING, 2015–2023 (USD MILLION)
Table 34 DEEP LEARNING MARKET FOR SECURITY, BY APPLICATION, 2015–2023 (USD MILLION)
Table 35 DEEP LEARNING MARKET FOR HR, BY OFFERING, 2015–2023 (USD MILLION)
Table 36 DEEP LEARNING MARKET FOR HR, BY APPLICATION, 2015–2023 (USD MILLION)
Table 37 DEEP LEARNING MARKET FOR MARKETING, BY OFFERING, 2015–2023 (USD MILLION)
Table 38 DEEP LEARNING MARKET FOR MARKETING, BY APPLICATION, 2015–2023 (USD MILLION)
Table 39 DEEP LEARNING MARKET FOR LAW, BY OFFERING, 2015–2023 (USD MILLION)
Table 40 DEEP LEARNING MARKET FOR LAW, BY APPLICATION, 2015–2023 (USD MILLION)
Table 41 DEEP LEARNING MARKET FOR FINTECH, BY OFFERING, 2015–2023 (USD MILLION)
Table 42 DEEP LEARNING MARKET FOR FINTECH, BY APPLICATION, 2015–2023 (USD MILLION)
Table 43 DEEP LEARNING MARKET, BY REGION, 2015–2023 (USD MILLION)
Table 44 DEEP LEARNING MARKET IN NORTH AMERICA, BY COUNTRY, 2015–2023 (USD MILLION)
Table 45 DEEP LEARNING MARKET IN US, BY END-USER INDUSTRY, 2015–2023 (USD MILLION)
Table 46 DEEP LEARNING MARKET IN CANADA, BY END-USER INDUSTRY, 2015–2023 (USD MILLION)
Table 47 DEEP LEARNING MARKET IN MEXICO, BY END-USER INDUSTRY, 2015–2023 (USD MILLION)
Table 48 DEEP LEARNING MARKET IN EUROPE, BY COUNTRY, 2015–2023 (USD MILLION)
Table 49 DEEP LEARNING MARKET IN UK, BY END-USER INDUSTRY, 2015–2023 (USD MILLION)
Table 50 DEEP LEARNING MARKET IN GERMANY, BY END-USER INDUSTRY, 2015–2023 (USD MILLION)
Table 51 DEEP LEARNING MARKET IN FRANCE, BY END-USER INDUSTRY, 2015–2023 (USD MILLION)
Table 52 DEEP LEARNING MARKET IN ITALY, BY END-USER INDUSTRY, 2015–2023 (USD MILLION)
Table 53 DEEP LEARNING MARKET IN SPAIN, BY END-USER INDUSTRY, 2015–2023 (USD MILLION)
Table 54 DEEP LEARNING MARKET IN REST OF EUROPE, BY END-USER INDUSTRY, 2015–2023 (USD MILLION)
Table 55 DEEP LEARNING MARKET IN APAC, BY COUNTRY, 2015–2023 (USD MILLION)
Table 56 DEEP LEARNING MARKET IN CHINA, BY END-USER INDUSTRY, 2015–2023 (USD MILLION)
Table 57 DEEP LEARNING MARKET IN JAPAN, BY END-USER INDUSTRY, 2015–2023 (USD MILLION)
Table 58 DEEP LEARNING MARKET IN SOUTH KOREA, BY END-USER INDUSTRY, 2015–2023 (USD MILLION)
Table 59 DEEP LEARNING MARKET IN INDIA, BY END-USER INDUSTRY, 2015–2023 (USD MILLION)
Table 60 DEEP LEARNING MARKET IN REST OF APAC, BY END-USER INDUSTRY, 2015–2023 (USD MILLION)
Table 61 DEEP LEARNING MARKET IN ROW, BY REGION, 2015–2023 (USD MILLION)
Table 62 DEEP LEARNING MARKET IN MIDDLE EAST AND AFRICA, BY END-USER INDUSTRY, 2015–2023 (USD MILLION)
Table 63 DEEP LEARNING MARKET IN SOUTH AMERICA, BY END-USER INDUSTRY, 2015–2023 (USD MILLION)
Table 64 RANKING OF KEY COMPANIES IN DEEP LEARNING MARKET (2017)
Table 65 NEW PRODUCT DEVELOPMENTS AND LAUNCHES (2015–2017)
Table 66 COLLABORATIONS AND PARTNERSHIPS (2015–2017)
Table 67 ACQUISITIONS (2015–2017)
Table 68 OTHERS (2015–2017)
Table 1 PRICE COMPARISON: AI CHIPSETS (LEADING COMPANIES)
Table 2 COMPANIES OFFERING CLOUD SERVICES FOR DEEP/MACHINE LEARNING
Table 3 MACHINE LEARNING LIBRARIES BY VARIOUS MARKET PLAYERS (2015–2017)
Table 4 DEEP LEARNING MARKET, BY OFFERING, 2015–2023 (USD MILLION)
Table 5 INDUSTRY PLAYERS IN DEEP LEARNING MARKET, 2017
Table 6 DEEP LEARNING MARKET, BY HARDWARE, 2015–2023 (USD MILLION)
Table 7 DEEP LEARNING MARKET, BY PROCESSOR, 2015–2023 (USD MILLION)
Table 8 DEEP LEARNING MARKET, BY PROCESSOR, 2015–2023 (THOUSAND UNITS)
Table 9 DEEP LEARNING HARDWARE MARKET, BY APPLICATION, 2015–2023 (USD MILLION)
Table 10 DEEP LEARNING HARDWARE MARKET, BY END-USER INDUSTRY, 2015–2023 (USD MILLION)
Table 11 DEEP LEARNING MARKET, BY SOFTWARE, 2015–2023 (USD MILLION)
Table 12 DEEP LEARNING SOFTWARE MARKET, BY APPLICATION, 2015–2023 (USD MILLION)
Table 13 DEEP LEARNING SOFTWARE MARKET, BY END-USER INDUSTRY, 2015–2023 (USD MILLION)
Table 14 DEEP LEARNING MARKET, BY SERVICE, 2015–2023 (USD MILLION)
Table 15 DEEP LEARNING SERVICE MARKET, BY APPLICATION, 2015–2023 (USD MILLION)
Table 16 DEEP LEARNING SERVICE MARKET, BY END-USER INDUSTRY, 2015–2023 (USD MILLION)
Table 17 DEEP LEARNING MARKET, BY APPLICATION, 2015–2023 (USD MILLION)
Table 18 DEEP LEARNING MARKET FOR IMAGE RECOGNITION, BY OFFERING, 2015–2023 (USD MILLION)
Table 19 DEEP LEARNING MARKET FOR SIGNAL RECOGNITION, BY OFFERING, 2015–2023 (USD MILLION)
Table 20 DEEP LEARNING MARKET FOR DATA MINING, BY OFFERING, 2015–2023 (USD MILLION)
Table 21 DEEP LEARNING MARKET FOR OTHERS, BY OFFERING, 2015–2023 (USD MILLION)
Table 22 DEEP LEARNING MARKET, BY END-USER INDUSTRY, 2015–2023 (USD MILLION)
Table 23 DEEP LEARNING MARKET FOR HEALTHCARE, BY OFFERING, 2015–2023 (USD MILLION)
Table 24 DEEP LEARNING MARKET FOR HEALTHCARE, BY APPLICATION, 2015–2023 (USD MILLION)
Table 25 DEEP LEARNING MARKET FOR MANUFACTURING, BY OFFERING, 2015–2023 (USD MILLION)
Table 26 DEEP LEARNING MARKET FOR MANUFACTURING, BY APPLICATION, 2015–2023 (USD MILLION)
Table 27 DEEP LEARNING MARKET FOR AUTOMOTIVE, BY OFFERING, 2015–2023 (USD MILLION)
Table 28 DEEP LEARNING MARKET FOR AUTOMOTIVE, BY APPLICATION, 2015–2023 (USD MILLION)
Table 29 DEEP LEARNING MARKET FOR AGRICULTURE, BY OFFERING, 2015–2023 (USD MILLION)
Table 30 DEEP LEARNING MARKET FOR AGRICULTURE, BY APPLICATION, 2015–2023 (USD MILLION)
Table 31 DEEP LEARNING MARKET FOR RETAIL, BY OFFERING, 2015–2023 (USD MILLION)
Table 32 DEEP LEARNING MARKET FOR RETAIL, BY APPLICATION, 2015–2023 (USD MILLION)
Table 33 DEEP LEARNING MARKET FOR SECURITY, BY OFFERING, 2015–2023 (USD MILLION)
Table 34 DEEP LEARNING MARKET FOR SECURITY, BY APPLICATION, 2015–2023 (USD MILLION)
Table 35 DEEP LEARNING MARKET FOR HR, BY OFFERING, 2015–2023 (USD MILLION)
Table 36 DEEP LEARNING MARKET FOR HR, BY APPLICATION, 2015–2023 (USD MILLION)
Table 37 DEEP LEARNING MARKET FOR MARKETING, BY OFFERING, 2015–2023 (USD MILLION)
Table 38 DEEP LEARNING MARKET FOR MARKETING, BY APPLICATION, 2015–2023 (USD MILLION)
Table 39 DEEP LEARNING MARKET FOR LAW, BY OFFERING, 2015–2023 (USD MILLION)
Table 40 DEEP LEARNING MARKET FOR LAW, BY APPLICATION, 2015–2023 (USD MILLION)
Table 41 DEEP LEARNING MARKET FOR FINTECH, BY OFFERING, 2015–2023 (USD MILLION)
Table 42 DEEP LEARNING MARKET FOR FINTECH, BY APPLICATION, 2015–2023 (USD MILLION)
Table 43 DEEP LEARNING MARKET, BY REGION, 2015–2023 (USD MILLION)
Table 44 DEEP LEARNING MARKET IN NORTH AMERICA, BY COUNTRY, 2015–2023 (USD MILLION)
Table 45 DEEP LEARNING MARKET IN US, BY END-USER INDUSTRY, 2015–2023 (USD MILLION)
Table 46 DEEP LEARNING MARKET IN CANADA, BY END-USER INDUSTRY, 2015–2023 (USD MILLION)
Table 47 DEEP LEARNING MARKET IN MEXICO, BY END-USER INDUSTRY, 2015–2023 (USD MILLION)
Table 48 DEEP LEARNING MARKET IN EUROPE, BY COUNTRY, 2015–2023 (USD MILLION)
Table 49 DEEP LEARNING MARKET IN UK, BY END-USER INDUSTRY, 2015–2023 (USD MILLION)
Table 50 DEEP LEARNING MARKET IN GERMANY, BY END-USER INDUSTRY, 2015–2023 (USD MILLION)
Table 51 DEEP LEARNING MARKET IN FRANCE, BY END-USER INDUSTRY, 2015–2023 (USD MILLION)
Table 52 DEEP LEARNING MARKET IN ITALY, BY END-USER INDUSTRY, 2015–2023 (USD MILLION)
Table 53 DEEP LEARNING MARKET IN SPAIN, BY END-USER INDUSTRY, 2015–2023 (USD MILLION)
Table 54 DEEP LEARNING MARKET IN REST OF EUROPE, BY END-USER INDUSTRY, 2015–2023 (USD MILLION)
Table 55 DEEP LEARNING MARKET IN APAC, BY COUNTRY, 2015–2023 (USD MILLION)
Table 56 DEEP LEARNING MARKET IN CHINA, BY END-USER INDUSTRY, 2015–2023 (USD MILLION)
Table 57 DEEP LEARNING MARKET IN JAPAN, BY END-USER INDUSTRY, 2015–2023 (USD MILLION)
Table 58 DEEP LEARNING MARKET IN SOUTH KOREA, BY END-USER INDUSTRY, 2015–2023 (USD MILLION)
Table 59 DEEP LEARNING MARKET IN INDIA, BY END-USER INDUSTRY, 2015–2023 (USD MILLION)
Table 60 DEEP LEARNING MARKET IN REST OF APAC, BY END-USER INDUSTRY, 2015–2023 (USD MILLION)
Table 61 DEEP LEARNING MARKET IN ROW, BY REGION, 2015–2023 (USD MILLION)
Table 62 DEEP LEARNING MARKET IN MIDDLE EAST AND AFRICA, BY END-USER INDUSTRY, 2015–2023 (USD MILLION)
Table 63 DEEP LEARNING MARKET IN SOUTH AMERICA, BY END-USER INDUSTRY, 2015–2023 (USD MILLION)
Table 64 RANKING OF KEY COMPANIES IN DEEP LEARNING MARKET (2017)
Table 65 NEW PRODUCT DEVELOPMENTS AND LAUNCHES (2015–2017)
Table 66 COLLABORATIONS AND PARTNERSHIPS (2015–2017)
Table 67 ACQUISITIONS (2015–2017)
Table 68 OTHERS (2015–2017)
According to the new market research report "Deep Learning Market by Application (Image Recognition, Signal Recognition, Data Mining), Offering (Hardware (Von Neumann and Neuromorphic Chip), and Software), End-User Industry, and Geography - Global Forecasts to 2022", the deep learning market is expected to be worth USD 1,722.9 Million by 2022, growing at a CAGR of 65.3% between 2016 and 2022. The deep learning market has a huge potential across various industries such as advertisement, finance, and automotive. The major factors driving the deep learning market globally are the robust R&D for the development of better processing hardware and increasing adoption of cloud-based technology for deep learning.
The major players included in the report are
- IBM Corporation (U.S.)
- Microsoft Corporation (U.S.)
- Google, Inc. (U.S.)
- Facebook, Inc. (U.S.)
- Qualcomm, Inc. (U.S.)
- NVIDIA Corporation (U.S.)
- Intel Corporation (U.S.)
- Skymind (U.S.)
- Baidu, Inc. (China)
- Hewlett Packard Enterprise (U.S.)
- Sensory Inc. (U.S.)
- General Vision Inc. (U.S.)
The market for the data mining application is expected to grow at the highest rate between 2016 and 2022
The deep learning market for data mining application is expected to grow at the highest CAGR between 2016 and 2022. The increasing usage of deep learning in data analytics, cyber security, fraud detection, and database systems is fueling the growth of data mining applications in the deep learning market. Medical industries generate huge amounts of data sets related to medication, patient details, and diagnosis. This data is converted into valuable patterns and is used to forecast future trends. Thus, data mining is expected to witness the highest growth rate in the medical industry.
Deep learning hardware market expected to grow at the highest rate between 2016 and 2022
The high growth rate of the hardware market for deep learning is attributed to the growing need for hardware platforms with a high computing power to run deep learning algorithms. There is increasing competition among established as well as startup players, leading to new product developments including both hardware development and software platforms to run deep learning algorithms and programs. For instance, Graphcore (a U.K.-based company) is developing the intelligent processing unit (IPU) for machine learning technology for use in applications from driverless cars to cloud computing. Some of the companies involved in the development of hardware for the deep learning technique are Google, Inc. (U.S.), Microsoft Corporation (U.S.), Intel Corporation (U.S.), Qualcomm, Inc. (U.S.), IBM Corporation (U.S.), and others.
North America leads the deep learning market in terms of market size
North America is currently leading the deep learning market and is projected to be in the leading position for the next few years owing to the wide adoption of deep learning technology. The growth of the deep learning market in North America is attributed to the high government funding, presence of leading players, and strong technical base.
