The Federated Learning Market size was valued at USD 113.2 Million in 2022. It is expected to hit USD 261.8 Million by 2030 and grow at a CAGR of 11.05% over the forecast period of 2023-2030.
Federated Learning represents a paradigm shift in machine learning where instead of centralizing data for training models, computations are distributed across multiple devices or servers. This approach ensures privacy and security by keeping sensitive data localized, making it particularly appealing in industries with strict data regulations such as healthcare and finance. As the demand for privacy-preserving AI grows, the Federated Learning market is expected to witness substantial expansion in the coming years.
One of the key drivers propelling the growth of the Federated Learning market is the increasing concern over data privacy and security. With regulations like GDPR and CCPA emphasizing user data protection, companies are seeking innovative solutions like Federated Learning to train AI models without compromising individual privacy. This demand is further fueled by the proliferation of IoT devices, generating vast amounts of sensitive data that require privacy-preserving machine learning techniques..
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Covid 19 impact analysis:
The latest report is the most recent study that offers 360° coverage of the Federated Learning industry that has been facing the brunt of the adverse economic impact of the COVID-19 outbreak since the beginning of this year. The global health crisis has affected nearly every aspect of the business vertical and led to massive disruptions to the global Federated Learning market demand and supply chains. Researchers draw predictions for the market scenario in the post-COVID era. The report, additionally, assesses the present market situation and estimates its future outcomes, keeping in mind the impact of the pandemic on the global economic landscape.
Major companies profiled in the market report include
Edge Delta Inc., Secure AI Labs, Intellegens Ltd., Decentralized Machine Learning, Microsoft Corporation, Nvidia Corporation, Owkin Inc., Enveil Inc., DataFleets Ltd, International Business Machines Corporation, FEDML, Cloudera Inc, Alphabet Inc., Apheris, Consilient, and others., and others.
Research objectives:
The latest research report has been formulated using industry-verified data. It provides a detailed understanding of the leading manufacturers and suppliers engaged in this market, their pricing analysis, product offerings, gross revenue, sales network & distribution channels, profit margins, and financial standing. The report’s insightful data is intended to enlighten the readers interested in this business sector about the lucrative growth opportunities in the Federated Learning market.
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It has segmented the global Federated Learning market
By Component
- Solutions
- Services
By Application
- Drug Discovery
- Data Privacy & Security Management
- Risk Management
- Shopping Experience Personalization
- Industrial Internet of Things
- Online Visual Object Detection
- Others
By Enterprise Size
- Large Enterprises
- Small & Medium Enterprises
By Industry Vertical
- BFSI
- Healthcare & Life Sciences
- Retail & E-commerce
- Manufacturing
- Energy & Utilities
- Others
Key Objectives of the Global Federated Learning Market Report:
- The report conducts a comparative assessment of the leading market players participating in the global Federated Learning market.
- The report marks the notable developments that have recently taken place in the Federated Learning industry
- It details on the strategic initiatives undertaken by the market competitors for business expansion.
- It closely examines the micro- and macro-economic growth indicators, as well as the essential elements of the Federated Learning market value chain.
- The repot further jots down the major growth prospects for the emerging market players in the leading regions of the market
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