Future Directions
The field of LLMs is rapidly evolving, with several future directions that are expected to shape the development of language models in the coming years. These include:
- Multitask learning: The development of multitask learning algorithms that enable language models to learn multiple tasks simultaneously.
- Transfer learning: The development of transfer learning algorithms that enable language models to fine-tune pre-trained models for specific tasks.
- Explainability: The development of explainability techniques that enable language models to provide insights into their decision-making processes.