What Is Self-Supervised Learning?

Supervised learning relies on labeled data, while self-supervised learning generates labels from the data itself.

No. Unsupervised learning finds patterns without targets, while self-supervised learning creates explicit prediction tasks.

It enables models to scale using massive unlabeled datasets and improves performance on downstream tasks.

LLMs are trained using next-token prediction, a self-supervised objective that teaches language structure and context.