November 2024
tl;dr: Nice def and summary of FM.
- A foundation model is any model that is trained on broad data (generally using self-supervision at scale) that can be adapted (e.g., fine-tuned) to a wide range of downstream tasks
- The significance of foundation models can be summarized by two words: emergence and homogenization.
- Emergence means that the behavior of a system is implicitly induced rather than explicitly constructed;
- Homogenization indicates the consolidation of methodologies for building machine learning systems across a wide range of applications