Transfer Learning — AI Glossary

Transfer learning is a machine learning technique where a model trained on one task or dataset is reused as the starting point for a different but related task. Instead of training from scratch, you take a model that already understands a broad domain and adapt it to your specific use case with much less data and compute. Transfer learning is the foundation of modern LLMs — they are pre-trained on vast text corpora, then adapted for specific applications through fine-tuning.