What are the key technologies that support federated learning?

What are the key technologies that support federated learning?

Federated learning relies on several key technologies, including secure multi-party computation, differential privacy, and edge computing.

How does secure multi-party computation work in this context?

Secure multi-party computation allows multiple parties to collaboratively compute a function over their inputs while keeping those inputs private.

Can you explain differential privacy in simple terms?

Differential privacy is a technique that adds noise to data to protect individual privacy while still allowing for useful insights.

What role does edge computing play in federated learning?

Edge computing processes data closer to where it is generated, reducing latency and bandwidth usage, which is crucial for federated learning.

Are there any specific frameworks for implementing federated learning?

Yes, frameworks like TensorFlow Federated and PySyft are designed to facilitate the implementation of federated learning.