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Deep Learning Market

Deep Learning Market Forecasts to 2028 – Global Analysis By Solution (Hardware, Software, Services), Architecture Industry (Recurrent Neural Network (RNN), Convolutional Neural Networks (CNN)) and By Geography

4.8 (76 reviews)
Published: June 2022 ID: SMRC21557
4.8 (76 reviews)
Published: June 2022 ID: SMRC21557

This report covers the impact of COVID-19 on this global market
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According to Stratistics MRC, the Global Deep Learning Market is accounted for $9.45 billion in 2021 and is expected to reach $119.61 billion by 2028 growing at a CAGR of 43.7% during the forecast period. Deep learning is a type of machine learning and artificial intelligence (AI) that imitates the way humans gain certain types of knowledge. Deep learning is an important element of data science, which includes statistics and predictive modeling.

Market Dynamics:

Driver:

Rise in digitization & cyber attack


An increase in digitalization along with the development of the information technology (IT) industry across the globe is one of the major factors driving the growth of the market. Deep learning algorithms are proficient in inevitably intercepting available data points that improve the accuracy and efficiency of the decision-making process. The increase in the number of cyber-attacks encouraging industries to employ database management, fraud detection systems, and cyber security accelerate the market. This technology is used for processing medical images for drug discovery, and disease diagnosis delivering virtual patient assistance in the healthcare sector.

Restraint:

Shortage of expertise


In contrast to traditional data analysis, deep learning demands a totally diverse set of technical skills and expertise. There are an inadequate number of specialists to provide the required expertise in business problems and organizations that have budget constraints have to shy away from hiring the right talent to fulfil the needs. Besides, it is time-consuming for organizations to find well-trained professionals with appropriate skill sets. Thus, due to the shortage of expertise is limiting the implementation of deep learning models restricting the market growth.

Opportunity:

Rise in entry of startups


With an upsurge in funding through numerous global investors, the global market has witnessed an intrusion of start-ups in recent years. The major start-up sector that offers global deep learning is healthcare, which is focused on drug research and development. Other areas of application in deep learning are visual recognition, fraud detection, insurance, and agriculture. This gives opportunities to vendors to increase their market shares and attract customers from a wide range of industries. Thus, the rise in start-ups and deep learning applications in several industries creates ample opportunity.

Threat:

Quality of Data


The quality of data remains to be one of the biggest factors as models like deep learning need a lot of quality data. With small enough datasets, an algorithm may be taught without being inclusive. This is very much required for processes like image recognition; without accurate and adequate data, it becomes a fairly uphill task for the deep learning model to reach the next stage and ensure a greater grasp in the market. Such errors can lie undiscovered for a long time and correcting them can take much longer. Rigid business models also limit the revenue growth of the market. However, not all corporations are flexible in their business process and do not allow experimentation which limits the revenue growth of the market.

Hardware segment is expected to be the largest during the forecast period

The hardware segment dominated the market, owing to the increasing requirement for hardware platforms with high computing power to implement deep learning algorithms. The hardware segment comprises processors such as GPU, FPGA, and CPU among others, memory, and network. The rapidly evolving R&D activities for the expansion of better processing hardware for deep learning are also accelerating the market value.

The recurrent neural networks (RNN) segment is expected to have the highest CAGR during the forecast period

The recurrent neural networks (RNN) segment held the highest market share. As recurrent Neural Networks (RNN) is a powerful and vigorous type of neural network and belong to the most capable algorithms at the moment, as they are the only ones with internal memory. Due to their internal memory, RNNs can remember significant things about the input they received, which allows them to be very accurate in predicting what’s coming next.

Region with highest share:

The North America is projected to hold the highest market share, owing to growing funding in artificial intelligence and neural networks and the province's widespread use of image and monitoring purposes is estimated to generate new growth prospects over the forecast period. Moreover, upsurge in investments in deep learning start-ups and a surge in popularity of deep learning technology among end-users. Additionally, the province is one of the pioneers of modern technologies, allowing firms to accelerate the adoption of deep learning ability.

Region with highest CAGR:

Asia Pacific is projected to have the highest CAGR, due to the rapid economic development of key nations such as China and India is important to encourage the growth of the Asia Pacific deep learning market. The growing penetration and development of deep learning technology are the driving forces behind the market's growth. Additionally, the spurring rise of digitization and image and voice recognition platforms is giving a boost to the growth of the market. Moreover, foreign investments in model applications of deep learning favor the growth of the regional market. 

Key players in the market:

Some of the key players profiled in the Deep Learning Market include Advanced Micro Devices, Inc., Amazon Web Services (AWS), ARM Ltd., Clarifai, Inc., Entilic, Google, IBM, Hewlett Packard Enterprise, HyperVerge, IBM Corporation, Intel Corporation, Micron Technology, Microsoft Corporation, NVIDIA Corporation, Qualcomm Technologies, Inc   , Samsung Electronics, Johnson Controls, Larsen & Toubro Infotech.

Key developments:

In January 2020: Johnson Controls announced that its retail solutions portfolio, Sensormatic Solutions and Intel Corporation, collaborated to deliver scalable, AI-powered solutions for retailers. Moving forward, the Sensormatic Solutions AI portfolio at the edge will be based on Intel platforms. Sensormatic Solutions will also leverage Intel Distribution of OpenVINO toolkit and Intel models for delivering its solutions.

In December 2019: Intel Corp. acquired Habana Labs Ltd., an Israel-based startup working on deep learning algorithms for data center applications strengthening the AI capability of Intel Corporation.

In November 2018: Amazon Web Services announced Amazon Elastic Inference, allowing users to add elastic GPU support, reducing deep learning costs by up to 75%.

In June 2021: Larsen & Toubro Infotech entered into a strategic collaboration agreement with Amazon Web Services. The company recently launched a dedicated cloud unit for AWS, which will focus on migration and modernization, SAP application workloads, data analytics, and the Internet of things. It will also provide advisory, professional services, and delivery capabilities.

Solutions Covered: 
• Hardware
• Software
• Services 

Architecture Industry’s Covered:
• Recurrent Neural Network (RNN)
• Convolutional Neural Networks (CNN)
• Deep belief network (DBN)
• Deep Stacking Network (DSN)
• Gated Recurrent Unit (GRU). 

Hardware Components Covered:
• Application-Specific Integration Circuit (ASIC)
• Central Processing Unit (CPU) 
• Field Programmable Gate Array (FPGA)
• Graphics Processing Unit (GPU)
 
Applications Covered:
• Data Mining  
• Image Recognition    
• Signal Recognition   
•  Video Surveillance & Diagnostics

End Users Covered:
• Aerospace & Defense  
• Agriculture  
• Automotive  
• Education  
• Finance   
• Industrial   
• IT & Telecom   
• Media & Advertising  
• Medical   
• Oil, Gas, & Energy  
• Retail   

Regions Covered:
• North America
o US
o Canada
o Mexico
• Europe
o Germany
o UK
o Italy
o France
o Spain
o Rest of Europe
• Asia Pacific
o Japan       
o China       
o India       
o Australia 
o New Zealand
o South Korea
o Rest of Asia Pacific   
• South America
o Argentina
o Brazil
o Chile
o Rest of South America
• Middle East & Africa
o Saudi Arabia
o UAE
o Qatar
o South Africa
o Rest of Middle East & Africa

What our report offers:
- Market share assessments for the regional and country-level segments
- Strategic recommendations for the new entrants
- Covers Market data for the years 2020, 2021, 2022, 2025 and 2028
- Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
- Strategic recommendations in key business segments based on the market estimations
- Competitive landscaping mapping the key common trends
- Company profiling with detailed strategies, financials, and recent developments
- Supply chain trends mapping the latest technological advancements

Free Customization Offerings:
All the customers of this report will be entitled to receive one of the following free customization options:
• Company Profiling
o Comprehensive profiling of additional market players (up to 3)
o SWOT Analysis of key players (up to 3)
• Regional Segmentation
o Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
• Competitive Benchmarking
o Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances

1 Executive Summary  
   
2 Preface  

 2.1 Abstract 
 2.2 Stake Holders 
 2.3 Research Scope 
 2.4 Research Methodology 
  2.4.1 Data Mining
  2.4.2 Data Analysis
  2.4.3 Data Validation
  2.4.4 Research Approach
 2.5 Research Sources 
  2.5.1 Primary Research Sources
  2.5.2 Secondary Research Sources
  2.5.3 Assumptions
   
3 Market Trend Analysis  
 3.1 Introduction 
 3.2 Drivers 
 3.3 Restraints 
 3.4 Opportunities 
 3.5 Threats 
 3.6 Application Analysis 
 3.7 End User Analysis 
 3.8 Emerging Markets 
 3.9 Impact of Covid-19 
   
4 Porters Five Force Analysis  
 4.1 Bargaining power of suppliers 
 4.2 Bargaining power of buyers 
 4.3 Threat of substitutes 
 4.4 Threat of new entrants 
 4.5 Competitive rivalry 
   
5 Global Deep Learning Market, By Solution  
 5.1 Introduction 
 5.2 Hardware 
  5.2.1 Von Neumann Architecture-Based Chips
  5.2.2 Neuromorphic Architecture-Based Chips
 5.3 Software 
 5.4 Services     
  5.4.1 Installation Services 
  5.4.2 Integration Services  
  5.4.3 Maintenance & Support Services
   
6 Global Deep Learning Market, By Architecture Industry  
 6.1 Introduction 
 6.2 Recurrent Neural Network (RNN) 
 6.3 Convolutional Neural Networks (CNN) 
 6.4 Deep belief network (DBN) 
 6.5 Deep Stacking Network (DSN)  
 6.6 Gated Recurrent Unit (GRU). 
   
7 Global Deep Learning Market, By Hardware Component  
 7.1 Introduction 
 7.2 Application-Specific Integration Circuit (ASIC) 
 7.3 Central Processing Unit (CPU)   
 7.4 Field Programmable Gate Array (FPGA)  
 7.5 Graphics Processing Unit (GPU)  
   
8 Global Deep Learning Market, By Application  
 8.1 Introduction 
 8.2 Data Mining    
  8.2.1 Bioinformatics  
  8.2.2 Fingerprint Identification 
  8.2.3 Sentiment Analysis  
  8.2.4 Cyber Security  
  8.2.5 Machine Translation 
 8.3 Image Recognition    
  8.3.1 Robotics   
  8.3.2 Security/Video Surveillance 
  8.3.3 Machine Vision  
  8.3.4 Smart Motion  
  8.3.5 Medical & Satellite Imaging 
 8.4 Signal Recognition     
  8.4.1 Voice Identification  
  8.4.2 Speech Recognition  
  8.4.3 Vibration Monitoring 
  8.4.4 Electrocardiogram (ECG or EKG), Electroencephalography (EEG) 
  8.4.5 Radar/Sonar  
 8.5 Video Surveillance & Diagnostics  
   
9 Global Deep Learning Market, By End User  
 9.1 Introduction 
 9.2 Aerospace & Defense    
 9.3 Agriculture    
 9.4 Automotive    
 9.5 Education    
 9.6 Finance     
 9.7 Industrial     
 9.8 IT & Telecom     
 9.9 Media & Advertising    
 9.10 Medical     
 9.11 Oil, Gas, & Energy    
 9.12 Retail     
   
10 Global Deep Learning Market, By Geography  
 10.1 Introduction 
 10.2 North America 
  10.2.1 US
  10.2.2 Canada
  10.2.3 Mexico
 10.3 Europe 
  10.3.1 Germany
  10.3.2 UK
  10.3.3 Italy
  10.3.4 France
  10.3.5 Spain
  10.3.6 Rest of Europe
 10.4 Asia Pacific 
  10.4.1 Japan
  10.4.2 China
  10.4.3 India
  10.4.4 Australia
  10.4.5 New Zealand
  10.4.6 South Korea
  10.4.7 Rest of Asia Pacific
 10.5 South America 
  10.5.1 Argentina
  10.5.2 Brazil
  10.5.3 Chile
  10.5.4 Rest of South America
 10.6 Middle East & Africa 
  10.6.1 Saudi Arabia
  10.6.2 UAE
  10.6.3 Qatar
  10.6.4 South Africa
  10.6.5 Rest of Middle East & Africa
   
11 Key Developments  
 11.1 Agreements, Partnerships, Collaborations and Joint Ventures 
 11.2 Acquisitions & Mergers 
 11.3 New Product Launch 
 11.4 Expansions 
 11.5 Other Key Strategies 
   
12 Company Profiling  
 12.1 Advanced Micro Devices, Inc. 
 12.2 Amazon Web Services (AWS) 
 12.3 ARM Ltd. 
 12.4 Clarifai, Inc. 
 12.5 Entilic 
 12.6 Google, IBM 
 12.7 Hewlett Packard Enterprise    
 12.8 HyperVerge 
 12.9 IBM Corporation 
 12.10 Intel Corporation 
 12.11 Micron Technology 
 12.12 Microsoft Corporation 
 12.13 NVIDIA Corporation 
 12.14 Qualcomm Technologies, Inc    
 12.15 Samsung Electronics 
 12.16 Johnson Controls 
 12.17 Larsen & Toubro Infotech 


List of Tables   
1 Global Deep Learning Market Outlook, By Region (2020-2028) (US $MN)   
2 Global Deep Learning Market Outlook, By Solution (2020-2028) (US $MN)   
3 Global Deep Learning Market Outlook, By Hardware (2020-2028) (US $MN)   
4 Global Deep Learning Market Outlook, By Von Neumann Architecture-Based Chips (2020-2028) (US $MN)   
5 Global Deep Learning Market Outlook, By Neuromorphic Architecture-Based Chips (2020-2028) (US $MN)   
6 Global Deep Learning Market Outlook, By Software (2020-2028) (US $MN)   
7 Global Deep Learning Market Outlook, By Services     (2020-2028) (US $MN)   
8 Global Deep Learning Market Outlook, By Installation Services  (2020-2028) (US $MN)   
9 Global Deep Learning Market Outlook, By Integration Services   (2020-2028) (US $MN)   
10 Global Deep Learning Market Outlook, By Maintenance & Support Services (2020-2028) (US $MN)   
11 Global Deep Learning Market Outlook, By Hardware Component (2020-2028) (US $MN)   
12 Global Deep Learning Market Outlook, By Application-Specific Integration Circuit (ASIC) (2020-2028) (US $MN)   
13 Global Deep Learning Market Outlook, By Central Processing Unit (CPU)   (2020-2028) (US $MN)   
14 Global Deep Learning Market Outlook, By Field Programmable Gate Array (FPGA)  (2020-2028) (US $MN)   
15 Global Deep Learning Market Outlook, By Graphics Processing Unit (GPU)  (2020-2028) (US $MN)   
16 Global Deep Learning Market Outlook, By Architecture Industry (2020-2028) (US $MN)  
17 Global Deep Learning Market Outlook, By Recurrent Neural Network (RNN) (2020-2028) (US $MN)  
18 Global Deep Learning Market Outlook, By Convolutional Neural Networks (CNN) (2020-2028) (US $MN)  
19 Global Deep Learning Market Outlook, By Deep belief network (DBN) (2020-2028) (US $MN)  
20 Global Deep Learning Market Outlook, By Deep Stacking Network (DSN)  (2020-2028) (US $MN)  
21 Global Deep Learning Market Outlook, By Gated Recurrent Unit (GRU). (2020-2028) (US $MN)  
22 Global Deep Learning Market Outlook, By Application (2020-2028) (US $MN)   
23 Global Deep Learning Market Outlook, By Data Mining    (2020-2028) (US $MN)   
24 Global Deep Learning Market Outlook, By Bioinformatics   (2020-2028) (US $MN)   
25 Global Deep Learning Market Outlook, By Fingerprint Identification  (2020-2028) (US $MN)   
26 Global Deep Learning Market Outlook, By Sentiment Analysis   (2020-2028) (US $MN)   
27 Global Deep Learning Market Outlook, By Cyber Security   (2020-2028) (US $MN)   
28 Global Deep Learning Market Outlook, By Machine Translation  (2020-2028) (US $MN)   
29 Global Deep Learning Market Outlook, By Image Recognition    (2020-2028) (US $MN)   
30 Global Deep Learning Market Outlook, By Robotics    (2020-2028) (US $MN)   
31 Global Deep Learning Market Outlook, By Security/Video Surveillance  (2020-2028) (US $MN)   
32 Global Deep Learning Market Outlook, By Machine Vision   (2020-2028) (US $MN)   
33 Global Deep Learning Market Outlook, By Smart Motion   (2020-2028) (US $MN)   
34 Global Deep Learning Market Outlook, By Medical & Satellite Imaging  (2020-2028) (US $MN)   
35 Global Deep Learning Market Outlook, By Signal Recognition     (2020-2028) (US $MN)   
36 Global Deep Learning Market Outlook, By Voice Identification   (2020-2028) (US $MN)   
37 Global Deep Learning Market Outlook, By Speech Recognition   (2020-2028) (US $MN)   
38 Global Deep Learning Market Outlook, By Vibration Monitoring  (2020-2028) (US $MN)   
39 Global Deep Learning Market Outlook, By Electrocardiogram (ECG or EKG), Electroencephalography (EEG)  (2020-2028) (US $MN)   
40 Global Deep Learning Market Outlook, By Radar/Sonar   (2020-2028) (US $MN)   
41 Global Deep Learning Market Outlook, By Video Surveillance & Diagnostics  (2020-2028) (US $MN)   
42 Global Deep Learning Market Outlook, By End User (2020-2028) (US $MN)   
43 Global Deep Learning Market Outlook, By Aerospace & Defense (2020-2028) (US $MN)   
44 Global Deep Learning Market Outlook, By Agriculture (2020-2028) (US $MN)   
45 Global Deep Learning Market Outlook, By Automotive (2020-2028) (US $MN)   
46 Global Deep Learning Market Outlook, By Education (2020-2028) (US $MN)   
47 Global Deep Learning Market Outlook, By Finance (2020-2028) (US $MN)   
48 Global Deep Learning Market Outlook, By Industrial (2020-2028) (US $MN)   
49 Global Deep Learning Market Outlook, By IT & Telecom (2020-2028) (US $MN)   
50 Global Deep Learning Market Outlook, By Media & Advertising (2020-2028) (US $MN)   
51 Global Deep Learning Market Outlook, By Medical (2020-2028) (US $MN)   
52 Global Deep Learning Market Outlook, By Oil, Gas, & Energy (2020-2028) (US $MN)   
53 Global Deep Learning Market Outlook, By Retail (2020-2028) (US $MN)   
   
Note- Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.   

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