Federated Learning Market Poised for Explosive Growth, as Companies Seek Secure & Efficient Data Sharing Forecast 2032
federated learning Market Size – USD 112.7 Million in 2022, Market Growth – at a CAGR of 10.5%, Market Trends – Growing adoption of federated learning
VANCOUVER, BRITISH COLUMBIA, CANADA, April 24, 2023 /EINPresswire.com/ — The global federated learning market size reached USD 112.7 Million in 2021 and is expected to register a revenue CAGR of 10.5% during the forecast period, according to the latest analysis by Emergen Research. Rising need to increase learning between organizations and devices is the key factor driving market revenue growth.
Despite these obstacles, the federated learning industry is anticipated to expand significantly over the next several years, thanks to a number of driving forces. The growing use of 5G networks is one of the major growth drivers. The deployment of 5G networks is anticipated to greatly boost mobile network speed and capacity, allowing for quicker and more effective federated learning.
The growing use of edge computing is another growth element. Edge computing provides a mechanism to process data locally, minimising the requirement for data transfer and enhancing the effectiveness of federated learning as a result of the growing volume of data produced by IoT devices. Additionally, the need for federated learning solutions that can be used on edge devices is anticipated to rise in response to the increasing popularity of edge computing.
Scope of Research:
The market Size Value in 2022: USD 112.7 Million
CAGR (2023-2032): 10.5%
Report Coverage: Revenue Forecast, Company Ranking. Competitive landscape, growth factors, and trends
Customization Scope: 10hrs of free customization and expert consultation
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The major companies Covered in the report are:
IBM Corporation, Cloudera, Inc., NVIDIA Corporation, Acuratio Inc., Apheris AI GmbH, Intel Corporation, Google, Consilient, Edge Delta, Inc., and Sherpa.ai
The report, additionally, offers a comprehensive SWOT analysis and Porter’s Five Forces analysis to offer a better understanding of the competitive landscape of the industry. It also covers strategies adopted by prominent players such as mergers and acquisitions, collaborations, joint ventures, product launches, and brand promotions, among others. The report aims to offer the readers a holistic understanding of the relevant features of the industry.
Some Key Highlights from the Report
The visual object detection segment is expected to register a steady revenue growth rate over the forecast period. Federated learning has the potential to be particularly useful for visual object detection, as it allows multiple parties to collaborate on training a model without requiring them to share their data. This can be especially useful in cases where the data is sensitive or proprietary, or where the parties are concerned about data privacy.
The retail and e-commerce segment is expected to account for a significant revenue share over the forecast period due to the increasing adoption of federated learning in this sector. Retail and eCommerce companies are under constant pressure to improve their customer experiences and stay ahead of the competition. Federated learning can allow them to leverage data from multiple sources to train more accurate and effective models, which can give them a competitive edge. In addition, it can be used to train models that can personalize and optimize the shopping experience for customers, leading to improved satisfaction and loyalty.
The market in Asia Pacific is expected to register a significantly fast revenue growth rate during the forecast period due to the increasing use of mobile devices and the Internet of Things (IoT) in the region. In the first half of 2022, China Telecom reported a 21% increase in the number of IoT-connected devices, and according to the Chinese Ministry of Industry and Information Technology (MIIT), the national cellular IoT market grew by nearly 17% between the beginning of the year and the end of June 2022. This increase in the use of IoT devices, particularly in countries such as China, Japan, and India, is expected to rise demand for federated learning solutions that can enable companies to train accurate models on large volumes of distributed data.
Browse the Complete Research Report – Industry Analysis, Size, Share, Growth, Trends @ https://www.emergenresearch.com/industry-report/federated-learning-market
Analysis of the segments and their growth projection is carried out by extensive historical and current analysis of the market scenario. Further, the report offers details about the factors and features of the Federated Learning market expected to boost the growth of the industry in the coming years.
Federated Learning Market Segmentation:
Deployment Outlook (Revenue, USD Million; 2019-2032)
Cloud
On-Premises
Application Outlook (Revenue, USD Million; 2019-2032)
Industrial Internet of Things
Visual Object Detection
Drug Discovery
Risk Management
Augmented and Virtual Reality
Data Privacy Management
Others
End-Use Outlook (Revenue, USD Million; 2019-2032)
Retail and Ecommerce
Automotive
IT & Telecommunication
Healthcare
BFSI
Manufacturing
Others
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Key Questions Answered in the Report:
How does federated learning differ from other machine learning techniques, and what does it entail?
What are the primary market factors for federated learning, and how do you anticipate they will change over the next few years?
What are the biggest obstacles the federated learning market is facing, and how are industry players overcoming them?
What are some of the main market opportunities for growth for federated learning, and how can businesses seize them?
What consequences might this have for market participants when the regulatory environment for federated learning changes?
What sectors are most likely to gain from federated learning, and why?
What are some of the top businesses involved in the federated learning market, and what are some of their main advantages and disadvantages?
What are some of the most significant recent changes in the federated learning market, and what effects do you anticipate they will have on the sector?
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