The global federated learning market size is expected to reach USD 266.77 million by 2030, according to a new study by Polaris Market Research. The report “Federated Learning Market Share, Size, Trends, Industry Analysis Report, By Application (Industrial Internet of Things, Drug Discovery, Risk Management, Augmented and Virtual Reality, Data Privacy Management, Others); By Industry Vertical; By Region; Segment Forecast, 2022 - 2030” gives a detailed insight into current market dynamics and provides analysis on future market growth.
ML enables development of applications that learn and adapt from data with greater accuracy over time without explicit instructions. It includes algorithms that are capable to create systems by understanding input and output information that describes them. ML can be provided by several types of algorithms such as decision trees, neural networks, and inductive logic programming.
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Moreover, federated learning is the new era of secure artificial intelligence (AI), as this technique trains, tests, and provide data security. In addition, the data is difficult to be hacked due to the introduction of such method. Federated learning method has a huge potential, as it helps in securing sensitive and personal information of people and businesses. It also, aggregates outcome and recognizes familiar samples from various users, therefore, making the module robust.
Advent of cloud computing, deep federated learning, and parallel computing architectures; and rise in demand for AI capabilities such as image, speech, text, and recognition have fast-tracked the ongoing research associated with AI, fueling a new trend of rise in investment in developing premium AI hardware, which is capable of advancing application development. In addition, increase in interest of aerospace players to deploy AI across several applications is expected to boost demand for federated learning during the forecast period.
Moreover, the adoption of predictive and prescriptive analytics has been increasing. Predictive analytics is used to know the likelihood of certain events happening in the future, and prescriptive analytics provides solutions and actions to be taken in case of occurrence of such events. End-user industries have been recognizing the benefits of these analytical solutions and utilizing them to gain an edge over competitors. Widespread applications of predictive and prescriptive analytics would provide growth opportunities in the industry.
Federated Learning Market Report Highlights
Polaris Market Research has segmented the federated learning market report based on application, industry vertical, and region.:
Federated Learning, Application Outlook (Revenue - USD Million, 2018 - 2030)
Federated Learning, Industry Vertical Outlook (Revenue - USD Million, 2018 - 2030)
Federated Learning, Regional Outlook (Revenue - USD Million, 2018 - 2030)