Federated Learning: Privacy-Preserving AI at Scale

Federated learning represents a breakthrough in training AI models collaboratively while keeping sensitive data secure and private on local devices or servers.

The Privacy Challenge in AI

Traditional centralized machine learning requires aggregating data in one location, creating privacy risks and regulatory challenges.

How Federated Learning Works

Instead of moving data to the model, federated learning brings the model to the data, training locally and only sharing model updates.

Conclusion

Federated learning opens new possibilities for AI development in privacy-sensitive industries like healthcare and finance.