### Finally, a promising alternative approach ## Foundation Models _trained on broad data at scale and are adaptable to a wide range of downstream tasks_ * promise to store the knowledge about the world in text form * have a high capacity for learning * can be trained on all data available in text form * one day a general abstraction for everything? https://arxiv.org/abs/2108.07258
### What do you gain by adding priors to your model? * Fairness * by fighting unwanted bias * Explainability / Interpretability * by stating your priors (global interpretability) * without necessarily sacrificing accuracy * sometimes even improving on that * Trust * by making better predictions