What is Federated Learning?

Explained

Federated learning updates a shared model while keeping data on-premises or on-device, sharing only gradients or aggregates. It supports regulated industries and privacy-sensitive AI at scale.

Further reading

• Ethical AI: Building Responsible AI Experiences for Enhanced User Trust

Related terms

• Training Process of teaching the model with data (pre-training, fine-tuning).
• Big Data Large volumes of data requiring specialized tools; feedstock for training AI models.
• Context Engineering Designing what the model sees—retrieval, memory, summaries, and window budgeting.
• Corpus Collection of documents used to train or feed a system (e.g., RAG).
• Data Lake Repository that stores raw data; source for analytics and ML.
• Data Pipeline Automated flow of data from sources to models or applications.