New York, United States, Oct. 11, 2022 (GLOBE NEWSWIRE) -- The Global Self-Supervised Learning Market Size is projected to grow from USD 7.8 billion in 2021 to USD 100.8 billion by 2030 at a CAGR of 32.9% during the forecast period. as per the latest research report by Spherical Insights & Consulting.
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The Global Self-Supervised Learning Market Size is expected to grow from USD 7.8 billion in 2021 to USD 100.8 billion by 2030, at a CAGR of 32.9% during the forecast period 2022-2030. Self-supervised learning is a machine learning technique that is frequently used in applications for natural language processing (NLP), computer vision, and speech recognition. Speech recognition, colorization, and paraphrasing are used for self-supervised learning. The demand for self-supervised learning applications among sectors is being driven by factors including the expanding uses of technologies like voice recognition and facial detection and the growing desire to streamline workflow across industries. Additionally, the industry is projected to expand due to the growing digitalization of society. According to IBM's global AI adoption index 2022 research, 34% of respondents thought that a dearth of AI expertise prevented firms from adopting AI. Self-supervised learning is in a stage of growth that calls for skilled staff. Therefore, a dearth of competent labor will likely impede the expansion of the self-supervised learning sector. Companies like Apple Inc. and Microsoft, based in the United States, invest more money in R&D projects. Additionally, these businesses are investigating cutting-edge technologies like AI and ML. Self-supervised learning is being studied and experimented with by market participants like the American company Meta, creating major growth potential for the industry. The growing applications of technologies such as voice recognition and face detection are driving the growth of the market, coupled with increasing demand to streamline workflow across industries propelling the market’s growth. However, the lack of skilled workforce restraints the market’s growth over the forecast period. Increasing R&D activities in technology companies globally provide growth opportunities for the market’s growth over the forecast period.
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This research report categorizes the market for Self-supervised Learning based on various segments and regions and forecasts revenue growth and analysis trends in each of the submarkets. The report analyses the key growth drivers, opportunities, and challenges that influence the Self-supervised Learning market. Recent market developments and competitive strategies such as expansion, product launch and development, partnership, merger, and acquisition have been included in order to draw the competitive landscape in the market. The report strategically identifies and profiles the key market players and analyses their core competencies in each sub-segments of the Self-supervised Learning market.
Based on the technology, the global Self-supervised Learning market is categorized into Natural Language Processing(NLP), Computer Vision, and Speech Processing. In 2021, the Natural Language Processing(NLP) segment dominated the market with the largest market share of 41.6% and market revenue of 3.2 billion. The growth of this segment can be attributed to the increasing adoption of Natural Language Processing (NLP) applications such as chatbots and text prediction across several industries. Moreover, regional and global market players provide Natural Language Processing (NLP) solutions. For instance, AI-based SmartChat is being provided by Mexico-based BlueMessaging company, which helps companies build chatbots for personal use.
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Based on region, the Global Self-supervised Learning Market is segmented into North America, Europe, Asia Pacific, South America and Middle East & Africa. North America emerged as the largest market for the global Self-supervised Learning market, with a market share of around 31.7% and 2.47 billion of the market revenue in 2021. North America is expected to be the largest market for self-supervised learning. This is mostly due to the presence of prominent market players in the regions, such as U.S.-based Meta, Google, and Microsoft. Furthermore, the presence of specialists in self-supervised learning in the region also propels the growth of the market. Most of the countries in the North American region have developed technology infrastructure, which adds impetus to the growth of self-supervised learning in the region.
The Asia-Pacific market is expected to grow at the fastest CAGR between 2021 and 2030, owing to the increasing demand for increasing government initiatives in Artificial Intelligence solutions in several countries of the Asia Pacific region. Furthermore, there is rapid growth in the technological sector in several countries of the Asia Pacific, such as India, China, Japan, etc., which propel the market’s growth in the region. In addition, the increasing awareness about the benefits of self-supervised learning among consumers in the region is expected to propel the market’s growth during the forecast period.
Key Companies & Recent Developments
The report offers the appropriate analysis of the key organizations/companies involved within the global Self-supervised Learning market along with a comparative evaluation primarily based on their product offering, business overviews, geographic presence, enterprise strategies, segment market share, and SWOT analysis. Key Players are IBM, Alphabet Inc. (Google LLC), Microsoft, Amazon Web Services, Inc., SAS Institute Inc., Dataiku, The MathWorks, Inc., Meta, Databricks, DataRobot, Inc., Apple Inc., Tesla, Baidu, Inc and Others.
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