Federated Learning: Privacy-Preserving AI at Scale

# 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.