Market Overview:
The global deep learning market is expected to grow from USD 2.17 Billion in 2018 to USD 35.06 Billion by 2030, at a CAGR of 31.5% during the forecast period. The growth of the global deep learning market can be attributed to the increasing demand for artificial intelligence (AI) and machine learning (ML) across industries, growing number of AI and ML startups, and rising investments in AI and ML technologies by tech giants. However, data privacy concerns may restrain the growth of the global deep learning market to some extent during the forecast period. The hardware segment is expected to hold a larger share of the global deep learning market during the forecast period. The increasing adoption of GPUs for training neural networks is drivingthe growthof this segment. Moreover, rising demand for parallel computing capabilitiesin data centers is also contributingto thistrend .
Product Definition:
Deep learning is a subset of machine learning that is used to create artificial neural networks. These networks are composed of many layers of interconnected processing nodes, and can be trained to recognize patterns in data. Deep learning has proven to be very effective at tasks such as image recognition, natural language processing, and predictive modeling.
Hardware:
Hardware is the part of technology that supports the software and enables it to execute. It includes computer hardware such as chipsets, microprocessors, application-specific integrated circuits (ASIC), field-programmable gate array (FPGA) and other supporting components. The growth factor for hardware in deep learning market is high compared to other segments due to its usage in training data sets which are used by neural networks during the development process of Deep Learning Algorithms.
Software:
Software is the collection of tools and techniques that help in carrying out a specific task. In deep learning, software is used for various purposes such as data processing, analysis, programming and Artificial Intelligence (AI) among others. The different types of software include libraries & toolboxes, application codes &scripts along with Deep Learning frameworks like TensorFlow or Caffeine among others.
Application Insights:
The marketing segment dominated the global market in 2017. The growth can be attributed to the increasing adoption of deep learning based services and applications for customer profiling, product design, and advertising. Moreover, companies are focusing on developing customized solutions for their customers by using AI technology. For instance, in January 2018 Microsoft launched a chatbot platform powered by neural networks that can understand user input and deliver a more personalized experience. Such initiatives are expected to drive the marketing segment over the forecast period.
The healthcare application is anticipated to register significant growth over the forecast period owing to its ability to automate processes such as data entry into patient records.
Regional Analysis:
The market in North America is expected to grow at a significant rate over the forecast period owing to increasing investments by companies in the region. The U.S. dominated the market in 2017 and is expected to continue its dominance over the forecast period due to increased spending on research & development activities, growing adoption of deep learning technologies, and high demand for advanced AI-based services from businesses across all industry verticals including healthcare, manufacturing, retail among others.
However, Asia Pacific is anticipated to be a lucrative destination for deep learning technology providers as well as service providers operating across industries such as insurance (BFSI), e-commerce (retail), logistics & warehousing among others due to increasing investments by companies such as Google LLC; Baidu Inc.; Alibaba Group Holding Ltd.; Tencent Holdings Limited; Amazon Web Services Inc.
Growth Factors:
- Increasing demand for Deep Learning in various industries such as automotive, retail, healthcare, and finance for improving the efficiency of operations.
- Growing number of start-ups and venture capitalists investing in Deep Learning technology to develop new applications.
- Rapid increase in data generation due to the proliferation of smart devices and the Internet of Things (IoT).
- Development of open source platforms and libraries that make it easier for organizations to adopt Deep Learning technology.
- Advancements in hardware such as GPUs and TPUs that improve the performance of Deep Learning algorithms
Scope Of The Report
Report Attributes
Report Details
Report Title
Deep Learning Market Research Report
By Type
Hardware, Software, Services
By Application
Healthcare, Manufacturing, Automotive, Agriculture, Retail, Security, Human Resources, Marketing
By Companies
Amazon Web Services (AWS), Google, IBM, Intel, Micron Technology, Microsoft, Nvidia, Qualcomm, Samsung, Sensory Inc., Skymind, Xilinx, AMD, General Vision, Graphcore, Mellanox Technologies, Huawei Technologies, Fujitsu, Baidu, Mythic, Adapteva, Koniku
Regions Covered
North America, Europe, APAC, Latin America, MEA
Base Year
2021
Historical Year
2019 to 2020 (Data from 2010 can be provided as per availability)
Forecast Year
2030
Number of Pages
168
Number of Tables & Figures
118
Customization Available
Yes, the report can be customized as per your need.
Global Deep Learning Market Report Segments:
The global Deep Learning market is segmented on the basis of:
Types
Hardware, Software, Services
The product segment provides information about the market share of each product and the respective CAGR during the forecast period. It lays out information about the product pricing parameters, trends, and profits that provides in-depth insights of the market. Furthermore, it discusses latest product developments & innovation in the market.
Applications
Healthcare, Manufacturing, Automotive, Agriculture, Retail, Security, Human Resources, Marketing
The application segment fragments various applications of the product and provides information on the market share and growth rate of each application segment. It discusses the potential future applications of the products and driving and restraining factors of each application segment.
Some of the companies that are profiled in this report are:
- Amazon Web Services (AWS)
- Google
- IBM
- Intel
- Micron Technology
- Microsoft
- Nvidia
- Qualcomm
- Samsung
- Sensory Inc.
- Skymind
- Xilinx
- AMD
- General Vision
- Graphcore
- Mellanox Technologies
- Huawei Technologies
- Fujitsu
- Baidu
- Mythic
- Adapteva
- Koniku
Highlights of The Deep Learning Market Report:
- The market structure and projections for the coming years.
- Drivers, restraints, opportunities, and current trends of market.
- Historical data and forecast.
- Estimations for the forecast period 2030.
- Developments and trends in the market.
- By Type:
- Hardware
- Software
- Services
- By Application:
- Healthcare
- Manufacturing
- Automotive
- Agriculture
- Retail
- Security
- Human Resources
- Marketing
- Market scenario by region, sub-region, and country.
- Market share of the market players, company profiles, product specifications, SWOT analysis, and competitive landscape.
- Analysis regarding upstream raw materials, downstream demand, and current market dynamics.
- Government Policies, Macro & Micro economic factors are also included in the report.
We have studied the Deep Learning Market in 360 degrees via. both primary & secondary research methodologies. This helped us in building an understanding of the current market dynamics, supply-demand gap, pricing trends, product preferences, consumer patterns & so on. The findings were further validated through primary research with industry experts & opinion leaders across countries. The data is further compiled & validated through various market estimation & data validation methodologies. Further, we also have our in-house data forecasting model to predict market growth up to 2030.
Regional Analysis
- North America
- Europe
- Asia Pacific
- Middle East & Africa
- Latin America
Note: A country of choice can be added in the report at no extra cost. If more than one country needs to be added, the research quote will vary accordingly.
The geographical analysis part of the report provides information about the product sales in terms of volume and revenue in regions. It lays out potential opportunities for the new entrants, emerging players, and major players in the region. The regional analysis is done after considering the socio-economic factors and government regulations of the countries in the regions.
How you may use our products:
- Correctly Positioning New Products
- Market Entry Strategies
- Business Expansion Strategies
- Consumer Insights
- Understanding Competition Scenario
- Product & Brand Management
- Channel & Customer Management
- Identifying Appropriate Advertising Appeals
8 Reasons to Buy This Report
- Includes a Chapter on the Impact of COVID-19 Pandemic On the Market
- Report Prepared After Conducting Interviews with Industry Experts & Top Designates of the Companies in the Market
- Implemented Robust Methodology to Prepare the Report
- Includes Graphs, Statistics, Flowcharts, and Infographics to Save Time
- Industry Growth Insights Provides 24/5 Assistance Regarding the Doubts in the Report
- Provides Information About the Top-winning Strategies Implemented by Industry Players.
- In-depth Insights On the Market Drivers, Restraints, Opportunities, and Threats
- Customization of the Report Available
Frequently Asked Questions?
Deep learning is a subset of machine learning that uses deep neural networks. Deep neural networks are composed of many layers, or neurons, and can learn complex patterns with the help of artificial intelligence.
Some of the key players operating in the deep learning market are Amazon Web Services (AWS), Google, IBM, Intel, Micron Technology, Microsoft, Nvidia, Qualcomm, Samsung, Sensory Inc., Skymind, Xilinx, AMD, General Vision, Graphcore, Mellanox Technologies, Huawei Technologies, Fujitsu, Baidu, Mythic, Adapteva, Koniku.
The deep learning market is expected to register a CAGR of 31.5%.
Chapter 1 Executive Summary
Chapter 2 Assumptions and Acronyms Used
Chapter 3 Research Methodology
Chapter 4 Deep Learning Market Overview
4.1 Introduction
4.1.1 Market Taxonomy
4.1.2 Market Definition
4.1.3 Macro-Economic Factors Impacting the Market Growth
4.2 Deep Learning Market Dynamics
4.2.1 Market Drivers
4.2.2 Market Restraints
4.2.3 Market Opportunity
4.3 Deep Learning Market - Supply Chain Analysis
4.3.1 List of Key Suppliers
4.3.2 List of Key Distributors
4.3.3 List of Key Consumers
4.4 Key Forces Shaping the Deep Learning Market
4.4.1 Bargaining Power of Suppliers
4.4.2 Bargaining Power of Buyers
4.4.3 Threat of Substitution
4.4.4 Threat of New Entrants
4.4.5 Competitive Rivalry
4.5 Global Deep Learning Market Size & Forecast, 2020-2028
4.5.1 Deep Learning Market Size and Y-o-Y Growth
4.5.2 Deep Learning Market Absolute $ Opportunity
Chapter 5 Global Market Analysis and Forecast by Type
5.1 Introduction
5.1.1 Key Market Trends & Growth Opportunities by Type
5.1.2 Basis Point Share (BPS) Analysis by Type
5.1.3 Absolute $ Opportunity Assessment by Type
5.2 Market Size Forecast by Type
5.2.1 Hardware
5.2.2 Software
5.2.3 Services
5.3 Market Attractiveness Analysis by Type
Chapter 6 Global Market Analysis and Forecast by Applications
6.1 Introduction
6.1.1 Key Market Trends & Growth Opportunities by Applications
6.1.2 Basis Point Share (BPS) Analysis by Applications
6.1.3 Absolute $ Opportunity Assessment by Applications
6.2 Market Size Forecast by Applications
6.2.1 Healthcare
6.2.2 Manufacturing
6.2.3 Automotive
6.2.4 Agriculture
6.2.5 Retail
6.2.6 Security
6.2.7 Human Resources
6.2.8 Marketing
6.3 Market Attractiveness Analysis by Applications
Chapter 7 Global Deep Learning Market Analysis and Forecast by Region
7.1 Introduction
7.1.1 Key Market Trends & Growth Opportunities by Region
7.1.2 Basis Point Share (BPS) Analysis by Region
7.1.3 Absolute $ Opportunity Assessment by Region
7.2 Deep Learning Market Size Forecast by Region
7.2.1 North America
7.2.2 Europe
7.2.3 Asia Pacific
7.2.4 Latin America
7.2.5 Middle East & Africa (MEA)
7.3 Market Attractiveness Analysis by Region
Chapter 8 Coronavirus Disease (COVID-19) Impact
8.1 Introduction
8.2 Current & Future Impact Analysis
8.3 Economic Impact Analysis
8.4 Government Policies
8.5 Investment Scenario
Chapter 9 North America Analysis and Forecast
9.1 Introduction
9.2 North America Market Size Forecast by Country
9.2.1 U.S.
9.2.2 Canada
9.3 Basis Point Share (BPS) Analysis by Country
9.4 Absolute $ Opportunity Assessment by Country
9.5 Market Attractiveness Analysis by Country
9.6 North America Market Size Forecast by Type
9.6.1 Hardware
9.6.2 Software
9.6.3 Services
9.7 Basis Point Share (BPS) Analysis by Type
9.8 Absolute $ Opportunity Assessment by Type
9.9 Market Attractiveness Analysis by Type
9.10 North America Market Size Forecast by Applications
9.10.1 Healthcare
9.10.2 Manufacturing
9.10.3 Automotive
9.10.4 Agriculture
9.10.5 Retail
9.10.6 Security
9.10.7 Human Resources
9.10.8 Marketing
9.11 Basis Point Share (BPS) Analysis by Applications
9.12 Absolute $ Opportunity Assessment by Applications
9.13 Market Attractiveness Analysis by Applications
Chapter 10 Europe Analysis and Forecast
10.1 Introduction
10.2 Europe Market Size Forecast by Country
10.2.1 Germany
10.2.2 France
10.2.3 Italy
10.2.4 U.K.
10.2.5 Spain
10.2.6 Russia
10.2.7 Rest of Europe
10.3 Basis Point Share (BPS) Analysis by Country
10.4 Absolute $ Opportunity Assessment by Country
10.5 Market Attractiveness Analysis by Country
10.6 Europe Market Size Forecast by Type
10.6.1 Hardware
10.6.2 Software
10.6.3 Services
10.7 Basis Point Share (BPS) Analysis by Type
10.8 Absolute $ Opportunity Assessment by Type
10.9 Market Attractiveness Analysis by Type
10.10 Europe Market Size Forecast by Applications
10.10.1 Healthcare
10.10.2 Manufacturing
10.10.3 Automotive
10.10.4 Agriculture
10.10.5 Retail
10.10.6 Security
10.10.7 Human Resources
10.10.8 Marketing
10.11 Basis Point Share (BPS) Analysis by Applications
10.12 Absolute $ Opportunity Assessment by Applications
10.13 Market Attractiveness Analysis by Applications
Chapter 11 Asia Pacific Analysis and Forecast
11.1 Introduction
11.2 Asia Pacific Market Size Forecast by Country
11.2.1 China
11.2.2 Japan
11.2.3 South Korea
11.2.4 India
11.2.5 Australia
11.2.6 South East Asia (SEA)
11.2.7 Rest of Asia Pacific (APAC)
11.3 Basis Point Share (BPS) Analysis by Country
11.4 Absolute $ Opportunity Assessment by Country
11.5 Market Attractiveness Analysis by Country
11.6 Asia Pacific Market Size Forecast by Type
11.6.1 Hardware
11.6.2 Software
11.6.3 Services
11.7 Basis Point Share (BPS) Analysis by Type
11.8 Absolute $ Opportunity Assessment by Type
11.9 Market Attractiveness Analysis by Type
11.10 Asia Pacific Market Size Forecast by Applications
11.10.1 Healthcare
11.10.2 Manufacturing
11.10.3 Automotive
11.10.4 Agriculture
11.10.5 Retail
11.10.6 Security
11.10.7 Human Resources
11.10.8 Marketing
11.11 Basis Point Share (BPS) Analysis by Applications
11.12 Absolute $ Opportunity Assessment by Applications
11.13 Market Attractiveness Analysis by Applications
Chapter 12 Latin America Analysis and Forecast
12.1 Introduction
12.2 Latin America Market Size Forecast by Country
12.2.1 Brazil
12.2.2 Mexico
12.2.3 Rest of Latin America (LATAM)
12.3 Basis Point Share (BPS) Analysis by Country
12.4 Absolute $ Opportunity Assessment by Country
12.5 Market Attractiveness Analysis by Country
12.6 Latin America Market Size Forecast by Type
12.6.1 Hardware
12.6.2 Software
12.6.3 Services
12.7 Basis Point Share (BPS) Analysis by Type
12.8 Absolute $ Opportunity Assessment by Type
12.9 Market Attractiveness Analysis by Type
12.10 Latin America Market Size Forecast by Applications
12.10.1 Healthcare
12.10.2 Manufacturing
12.10.3 Automotive
12.10.4 Agriculture
12.10.5 Retail
12.10.6 Security
12.10.7 Human Resources
12.10.8 Marketing
12.11 Basis Point Share (BPS) Analysis by Applications
12.12 Absolute $ Opportunity Assessment by Applications
12.13 Market Attractiveness Analysis by Applications
Chapter 13 Middle East & Africa (MEA) Analysis and Forecast
13.1 Introduction
13.2 Middle East & Africa (MEA) Market Size Forecast by Country
13.2.1 Saudi Arabia
13.2.2 South Africa
13.2.3 UAE
13.2.4 Rest of Middle East & Africa (MEA)
13.3 Basis Point Share (BPS) Analysis by Country
13.4 Absolute $ Opportunity Assessment by Country
13.5 Market Attractiveness Analysis by Country
13.6 Middle East & Africa (MEA) Market Size Forecast by Type
13.6.1 Hardware
13.6.2 Software
13.6.3 Services
13.7 Basis Point Share (BPS) Analysis by Type
13.8 Absolute $ Opportunity Assessment by Type
13.9 Market Attractiveness Analysis by Type
13.10 Middle East & Africa (MEA) Market Size Forecast by Applications
13.10.1 Healthcare
13.10.2 Manufacturing
13.10.3 Automotive
13.10.4 Agriculture
13.10.5 Retail
13.10.6 Security
13.10.7 Human Resources
13.10.8 Marketing
13.11 Basis Point Share (BPS) Analysis by Applications
13.12 Absolute $ Opportunity Assessment by Applications
13.13 Market Attractiveness Analysis by Applications
Chapter 14 Competition Landscape
14.1 Deep Learning Market: Competitive Dashboard
14.2 Global Deep Learning Market: Market Share Analysis, 2019
14.3 Company Profiles (Details – Overview, Financials, Developments, Strategy)
14.3.1 Amazon Web Services (AWS)
14.3.2 Google
14.3.3 IBM
14.3.4 Intel
14.3.5 Micron Technology
14.3.6 Microsoft
14.3.7 Nvidia
14.3.8 Qualcomm
14.3.9 Samsung
14.3.10 Sensory Inc.
14.3.11 Skymind
14.3.12 Xilinx
14.3.13 AMD
14.3.14 General Vision
14.3.15 Graphcore
14.3.16 Mellanox Technologies
14.3.17 Huawei Technologies
14.3.18 Fujitsu
14.3.19 Baidu
14.3.20 Mythic
14.3.21 Adapteva
14.3.22 Koniku
