What is a defining paradigm shift when moving from Traditional AI (Discriminative/Task-specific) to Foundation Models?

Question

Accepted Answer

Foundation models are trained at scale on broad data and can be adapted to a wide range of downstream tasks via prompting or fine-tuning.

Answer

Traditional AI models utilize self-attention mechanisms, whereas foundation models do not.

Answer

Foundation models require manual feature engineering for every specific downstream task.

Answer

Traditional AI models are trained on massive, unlabelled datasets to generalize across domains.

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