What is Self-Supervised Learning?

Learning patterns from unlabeled data without explicit target outputs.

A record of where data came from, how it was transformed, and where it is used.

A training setup where a model improves by generating data through interactions or competitions with copies of itself.

Training approaches that let a model keep learning from new data without forgetting prior knowledge.

The process of assigning tags or target outputs to raw data for supervised learning.

Predicting the user's purpose from a text query to route it correctly.