The global self-supervised learning market is projected to have a moderate-paced CAGR of 33.4% during the forecast period. The current valuation of the self-supervised learning market is US$ 12.46 Bn in 2023. The value of the self-supervised learning market is anticipated to reach a high of US$ 222.31 Bn by the year 2033.
To combat the difficulties caused by excessive reliance on labelled data, self-reinforcement learning has emerged as a promising machine learning method. Having high-quality labelled data has long been a prerequisite for developing intelligent systems employing machine learning techniques.
This makes the high price of good annotations a significant obstacle to overcome during the training process. IBM’s global AI adoption index 2022 found that 34 per cent of respondents agreed that a shortage of AI capabilities is a barrier to AI’s widespread adoption in business. There is an increasing need for qualified workers in the self-supervised learning market. Therefore, it is anticipated that the growth of the self-supervised learning market is expected to be stifled by a lack of competent labour.
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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.
Key Takeaways
· 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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Competitive Landscape
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.
Recent Developments
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.
Key Segments in the Self-supervised Learning Market
End-use:
- Healthcare
- BFSI
- Automotive & Transportation
- Software Development (IT)
- Advertising & Media
- Others
Technology:
- Natural Language Processing (NLP)
- Computer Vision
- Speech Processing
By Region:
- North America
- Latin America
- Asia Pacific
- Middle East and Africa (MEA)
- Europe
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