Transfer learning boosts Generative AI by leveraging pre-trained models and fine-tuning them on domain-specific data, making them more effective in tasks like legal document generation or medical diagnosis, thus reducing the need for extensive training from scratch. You can refer to the following code snippet:

In the above code, we are using the following key points:
- Pre-trained Models: Use models trained on large datasets and adapt them to specific domains (e.g., law, medicine).
- Fine-tuning: Modify a pre-trained model with domain-specific data to improve performance on specialized tasks.
- Reduced Training Time: Transfer learning minimizes the need for training from scratch, saving time and resources.
- Improved Accuracy: Fine-tuning ensures the model understands industry-specific terminology and nuances.
Hence, by referring to the above, you can transfer learning to enhance Generative AI for specific industries like law or medicine.