Self-supervised Learning Market Size, Share & Trends Analysis Report By End Use (Healthcare, BFSI), By Technology (NLP, Computer Vision, Speech Processing), By Region (North America, Europe, Asia Pacific), And Segment Forecasts, 2022 - 2030

Self-supervised Learning Market Growth & Trends

The global self-supervised learning market size is anticipated to reach USD 89.68 billion by 2030, according to a new report by Grand View Research, Inc. The market is expected to expand at a CAGR of 33.4% from 2022 to 2030. Self-supervised learning is a machine learning technique used prominently in Natural Language Processing (NLP), followed by computer vision and speech processing applications. Applications of self-supervised learning include paraphrasing, colorization, and speech recognition.

The COVID-19 pandemic had a positive impact on the market. More businesses adopted AI and Machine Learning as a response to the COVID-19 pandemic. Many prominent market players such as U.S.-based Amazon Web Services, Inc., Google, and Microsoft witnessed a rise in revenue during the pandemic. Moreover, accelerated digitalization also contributed to the adoption of self-supervised learning applications. For instance, in April 2020, Google Cloud, a business segment of Google, launched an Artificial Intelligence (AI) chatbot that provides critical information to fight the COVID-19 pandemic.

Many market players offer solutions for various applications such as text-to-speech and language translation & prediction. Moreover, these players are researching in self-supervised learning. For instance, U.S.-based Meta has been advancing in self-supervised learning research and has developed various algorithms and models. In February 2022, Meta announced new advances in the company’s self-supervised computer vision model SEER. The model is more powerful and is expected to enable the company in building computer vision products.

Self-supervised LearningMarket Report Highlights

  • In terms of end-use, the BFSI segment accounted for the largest revenue share of 18.3% in 2021 and is expected to retain its position over the forecast period. This can be attributed to the increasing adoption of technologies such as AI and ML in the segment. The advertising & media segment is likely to expand at the highest CAGR of 33.7 % during the forecast period.
  • Based on technology, the Natural Language Processing (NLP) segment dominated the market with a share of 38.6% in 2021 and is also expected to grow at the highest CAGR of 34.1% during the forecast period. This can be attributed to the variety and penetration of NLP applications.
  • North America held the largest share of 31.7% in 2021 and is expected to retain its position over the forecast period. This can be attributed to the presence of a large number of market players in the region. Moreover, the presence of specialists and developed technology infrastructure are aiding the growth of the market.
  • In March 2022, the Australian government announced an investment of USD 30.5 million for establishing four digital capability and Artificial Intelligence (AI) centers. The government aims to drive the commercialization of Australia's AI research with this investment.
  • In July 2021, DataRobot, Inc. announced the acquisition of Algorithmia Inc., a U.S.-based Machine Learning Operations (MLOps) software platform. The platform is made for IT operations specialists’ needs, enabling organizations to address high-volume and complex model production securely and efficiently. DataRobot, Inc. aims to provide customers with a platform for running any machine learning model with this acquisition.
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Chapter 1 Methodology and Scope
1.1 Information Procurement
1.1.1 Purchased database
1.1.2 GVR’s internal database
1.1.3 Secondary sources & third-party perspective
1.1.4 Primary research
1.2 Information Analysis
1.2.1 Data analysis models
1.3 Market Formulation and Data Visualization
1.4 Data Validation and Publishing
Chapter 2 Executive Summary
2.1 Market Outlook
2.2 Segment Outlook
Chapter 3 Market Variables, Trends & Scope
3.1 Market Lineage Outlook
3.1.1 Parent market outlook
3.2 Penetration & Growth Prospect Mapping
3.3 Industry Value Chain Analysis
3.4 Regulatory Scenario
3.5 Market Dynamics
3.5.1 Market driver analysis
3.5.1.1 Growing applications of technologies such as voice recognition and face detection
3.5.1.2 Increasing demand to streamline workflow across industries
3.5.2 Market restraint/challenges analysis
3.5.2.1 Lack of skilled workforce
3.5.3 Market opportunity analysis
3.5.3.1 Increasing R&D activities in technology companies
3.6 PEST Analysis
3.7 Porter’s Five Forces Analysis
3.8 COVID-19 Impact on Self-supervised Learning Market
Chapter 4 Self-supervised Learning Market: End-use Estimates & Trend Analysis
4.1 Market Size Estimates & Forecasts and Trend Analysis, 2017 - 2030 (USD Million)
4.2 End-use Movement Analysis & Market Share, 2021 & 2030
4.3 Healthcare
4.3.1 Market size estimates and forecasts, 2017 - 2030 (USD Million)
4.4 BFSI
4.4.1 Market size estimates and forecasts, 2017 - 2030 (USD Million)
4.5 Automotive & Transportation
4.5.1 Market size estimates and forecasts, 2017 - 2030 (USD Million)
4.6 Software Development (IT)
4.6.1 Market size estimates and forecasts, 2017 - 2030 (USD Million)
4.7 Advertising & Media
4.7.1 Market size estimates and forecasts, 2017 - 2030 (USD Million)
4.8 Others
4.8.1 Market size estimates and forecasts, 2017 - 2030 (USD Million)
Chapter 5 Self-supervised Learning Market: Technology Estimates & Trend Analysis
5.1 Market Size Estimates & Forecasts and Trend Analysis, 2017 - 2030 (USD Million)
5.2 Technology Movement Analysis & Market Share, 2021 & 2030
5.3 Natural Language Processing (NLP)
5.3.1 Market size estimates and forecasts, 2017 - 2030 (USD Million)
5.4 Computer Vision
5.4.1 Market size estimates and forecasts, 2017 - 2030 (USD Million)
5.5 Speech Processing
5.5.1 Market size estimates and forecasts, 2017 - 2030 (USD Million)
Chapter 6 Self-supervised Learning Market: Regional Estimates & Trend Analysis
6.1 Self-supervised Learning Market by Region, 2021 & 2030
6.2 Regional Movement Analysis & Market Share, 2021 & 2030
6.3 North America
6.3.1 North America self-supervised learning market, 2017 to 2030 (USD Million)
6.3.2 North America self-supervised learning market, by end-use, 2017 to 2030 (USD Million)
6.3.3 North America self-supervised learning market, by technology, 2017 to 2030 (USD Million)
6.3.4 U.S.
6.3.4.1 U.S. self-supervised learning market, by end-use, 2017 to 2030 (USD Million)
6.3.4.2 U.S. self-supervised learning market, by technology, 2017 to 2030 (USD Million)
6.3.5 Canada
6.3.5.1 Canada self-supervised learning market, by end-use, 2017 to 2030 (USD Million)
6.3.5.2 Canada self-supervised learning market, by technology, 2017 to 2030 (USD Million)
6.4 Europe
6.4.1 Europe self-supervised learning market, 2017 to 2030 (USD Million)
6.4.2 Europe self-supervised learning market, by end-use, 2017 to 2030 (USD Million)
6.4.3 Europe self-supervised learning market, by technology, 2017 to 2030 (USD Million)
6.4.4 U.K.
6.4.4.1 U.K. self-supervised learning market, by end-use, 2017 to 2030 (USD Million)
6.4.4.2 U.K. self-supervised learning market, by technology, 2017 to 2030 (USD Million)
6.4.5 Germany
6.4.5.1 Germany self-supervised learning market, by end-use, 2017 to 2030 (USD Million)
6.4.5.2 Germany self-supervised learning market, by technology, 2017 to 2030 (USD Million)
6.4.6 France
6.4.6.1 France self-supervised learning market, by end-use, 2017 to 2030 (USD Million)
6.4.6.2 France self-supervised learning market, by technology, 2017 to 2030 (USD Million)
6.4.7 Italy
6.4.7.1 Italy self-supervised learning market, by end-use, 2017 to 2030 (USD Million)
6.4.7.2 Italy self-supervised learning market, by technology, 2017 to 2030 (USD Million)
6.4.8 Rest of Europe
6.4.8.1 Rest of Europe self-supervised learning market, by end-use, 2017 to 2030 (USD Million)
6.4.8.2 Rest of Europe self-supervised learning market, by technology, 2017 to 2030 (USD Million)
6.5 Asia Pacific
6.5.1 Asia Pacific self-supervised learning market, 2017 to 2030 (USD Million)
6.5.2 Asia Pacific self-supervised learning market, by end-use, 2017 to 2030 (USD Million)
6.5.3 Asia Pacific self-supervised learning market, by technology, 2017 to 2030 (USD Million)
6.5.4 China
6.5.4.1 China self-supervised learning market, by end-use, 2017 to 2030 (USD Million)
6.5.4.2 China self-supervised learning market, by technology, 2017 to 2030 (USD Million)
6.5.5 India
6.5.5.1 India self-supervised learning market, by end-use, 2017 to 2030 (USD Million)
6.5.5.2 India self-supervised learning market, by technology, 2017 to 2030 (USD Million)
6.5.6 Japan
6.5.6.1 Japan self-supervised learning market, by end-use, 2017 to 2030 (USD Million)
6.5.6.2 Japan self-supervised learning market, by technology, 2017 to 2030 (USD Million)
6.5.7 Australia
6.5.7.1 Australia self-supervised learning market, by end-use, 2017 to 2030 (USD Million)
6.5.7.2 Australia self-supervised learning market, by technology, 2017 to 2030 (USD Million)
6.5.8 Rest of Asia Pacific
6.5.8.1 Rest of Asia Pacific self-supervised learning market, by end-use, 2017 to 2030 (USD Million)
6.5.8.2 Rest of Asia Pacific self-supervised learning market, by technology, 2017 to 2030 (USD Million)
6.6 Latin America
6.6.1 Latin America self-supervised learning market, 2017 to 2030 (USD Million)
6.6.2 Latin America self-supervised learning market, by end-use, 2017 TO 2030 (USD Million)
6.6.3 Latin America self-supervised learning market, by technology, 2017 to 2030 (USD Million)
6.6.4 Brazil
6.6.4.1 Brazil self-supervised learning market, by end-use, 2017 to 2030 (USD Million)
6.6.4.2 Brazil self-supervised learning market, by technology, 2017 to 2030 (USD Million)
6.6.5 Mexico
6.6.5.1 Mexico self-supervised learning market, by end-use, 2017 to 2030 (USD Million)
6.6.5.2 Mexico self-supervised learning market, by technology, 2017 to 2030 (USD Million)
6.6.6 Rest of Latin America
6.6.6.1 Rest of Latin America self-supervised learning market, by end-use, 2017 to 2030 (USD Million)
6.6.6.2 Rest of Latin America self-supervised learning market, by technology, 2017 to 2030 (USD Million)
6.7 Middle East & Africa (MEA)
6.7.1 Middle East & Africa (MEA) self-supervised learning market, 2017 to 2030 (USD Million)
6.7.2 Middle East & Africa (MEA) self-supervised learning market, by end-use, 2017 to 2030 (USD Million)
6.7.3 Middle East & Africa (MEA) self-supervised learning market, by technology, 2017 to 2030 (USD Million)
Chapter 7 Competitive Analysis
7.1 Key Competitor Overview, 2021
7.2 Recent Developments & Impact Analysis, by Key Market Participants
7.3 Heat Map Analysis
7.4 List of Market Players
7.5 Vendor Landscape
Chapter 8 Competitive Landscape
8.1 IBM
8.1.1 Company overview
8.1.2 Financial performance
8.1.3 Product benchmarking
8.1.4 Recent developments
8.2 Alphabet Inc. (Google LLC)
8.2.1 Company overview
8.2.2 Financial performance
8.2.3 Product benchmarking
8.2.4 Recent developments
8.3 Microsoft
8.3.1 Company overview
8.3.2 Financial performance
8.3.3 Product benchmarking
8.3.4 Recent developments
8.4 Amazon Web Services, Inc.
8.4.1 Company overview
8.4.2 Financial performance
8.4.3 Product benchmarking
8.4.4 Recent developments
8.5 SAS Institute Inc.
8.5.1 Company overview
8.5.2 Financial performance
8.5.3 Product benchmarking
8.5.4 Recent developments
8.6 Dataiku
8.6.1 Company overview
8.6.2 Financial performance
8.6.3 Product benchmarking
8.7 The MathWorks, Inc.
8.7.1 Company overview
8.7.2 Financial performance
8.7.3 Product benchmarking
8.7.4 Recent developments
8.8 Meta
8.8.1 Company overview
8.8.2 Financial performance
8.8.3 Product benchmarking
8.8.4 Recent developments
8.9 Databricks
8.9.1 Company overview
8.9.2 Financial performance
8.9.3 Product benchmarking
8.9.4 Recent developments
8.10 DataRobot, Inc.
8.10.1 Company overview
8.10.2 Financial performance
8.10.3 Product benchmarking
8.10.4 Recent developments
8.11 Apple Inc.
8.11.1 Company overview
8.11.2 Financial performance
8.11.3 Product benchmarking
8.11.4 Recent developments
8.12 Tesla
8.12.1 Company overview
8.12.2 Financial performance
8.12.3 Product benchmarking
8.13 Baidu, Inc.
8.13.1 Company overview
8.13.2 Financial performance
8.13.3 Product benchmarking
8.13.4 Recent developments
Chapter 9 KOL Commentary
9.1 KoL Commentary Analysis, 2021

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