Self-supervised Learning Market is projected to reach a valuation of US$ 222.31 Bn in 2033
During the forecast period, the global self-supervised learning market is anticipated to grow at a moderate rate of 33.4%. In 2023, the self-supervised learning market is expected to be worth US$12.46 billion. By 2033, the self-supervised learning market is projected to grow to a high of US$ 222.31 Bn.
Self-reinforcement learning has emerged as a viable machine learning technique to address the challenges brought on by an overreliance on labelled data. For a very long time, creating intelligent systems using machine learning techniques has required the availability of high-quality tagged data. Because of this, it will be difficult to overcome the high cost of high-quality annotations during the training process.
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The important trends in the self-supervised learning market are the increasing automation of banking procedures and the widespread adoption of the internet and linked devices. Moreover, the increasing need for predictive analytics is helping the self-reinforcement learning industry expand.
Self-reinforcement learning is a promising industry, but it is being held back by a shortage of qualified workers. Conversely, the self-supervised learning market prediction anticipates that the quick changes in business model technology are anticipated to present lucrative prospects for expansion.
- In 2021, China’s sales of self-supervised learning were worth the most in the Asia Pacific self-supervised learning market, and it is expected to maintain its dominance through 2028 when it would be worth an estimated $3,828.9 million.
- It is predicted that the Japanese demand for self-supervised learning would expand at a CAGR of 33.1% during the forecast period.
- The Indian demand for self-supervised learning is expected to register a CAGR of 34.7% during the projected period.
- In 2021, Natural Language Processing generated 38.6% of total revenue and was expected to post the fastest growth in terms of compound annual growth rate (CAGR) at 34.1%.
- Market researchers predict that the advertising and media industry is expected to grow at a rapid clip of 33.7% CAGR over the next several years.
- The BFSI market was worth $1.28 billion in 2021 and is expected to grow at a CAGR of 33.3% over the forecast period.
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Several different international and domestic companies compete for customers for the sales of self-supervised learning. Companies in the market are spending money on research and development (R&D) to create innovative solutions and give themselves an edge. Because of the rising demand for self-supervised learning and its propensity for innovation, upheaval, and fast evolution, businesses are also forming alliances and M&A deals.
The Australian government pledged USD 30.5 million, or approximately AU$490 million, to fund the establishment of four digital capacity and Artificial Intelligence (AI) centres in March 2022. With this funding, the government hopes to accelerate the commercialization of Australia’s AI research.
DataRobot, Inc. announced in July 2021 that it has acquired Algorithmia Inc., a provider of an MLOps (Machine Learning Operations) software platform based in the United States. The platform caters to IT operations experts, letting businesses deal with high-volume, sophisticated model manufacturing in a safe, effective manner. With this purchase, DataRobot, Inc. hopes to offer its customers a universal platform on which they may deploy any machine learning model.
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Key Segments in the Self-supervised Learning Market
- Automotive & Transportation
- Software Development (IT)
- Advertising & Media
- Natural Language Processing (NLP)
- Computer Vision
- Speech Processing
- North America
- Latin America
- Asia Pacific
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Table of Content
1. Executive Summary
1.1. Global Market Outlook
1.2. Demand-side Trends
1.3. Supply-side Trends
1.4. Technology Roadmap Analysis
1.5. Analysis and Recommendations
2. Market Overview
2.1. Market Coverage / Taxonomy
2.2. Market Definition / Scope / Limitations
3. Market Background
3.1. Market Dynamics
3.2. Scenario Forecast
4. Global Market Analysis 2017-2021 and Forecast, 2022-2032
4.1. Historical Market Size Value (US$ Mn) Analysis, 2017-2021
4.2. Current and Future Market Size Value (US$ Mn) Projections, 2022-2032
4.2.1. Y-o-Y Growth Trend Analysis
4.2.2. Absolute $ Opportunity Analysis