Flower Labs Raises $20M to Advance Privacy-First Federated Learning for AI Models
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Flower Labs, a startup offering open-source software for federated learning, raised $20M at a $100M valuation to make it easier to train AI models without centralizing data.
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Federated learning allows multiple organizations to jointly train an AI model without sharing raw data, helping with privacy, security, and regulations.
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The funding will help Flower Labs grow its community of developers using the open-source Flower framework for federated learning projects.
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Federated learning unlocks more private, distributed data to train models, often outperforming centralized learning with less data.
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Distributed learning on devices could allow models to tap into significantly more computing power than available in centralized data centers.