Explain the difference between a foundation model and an application model.
Separate general learning from task adaptation.
Choose two correct statements.
Pretraining learns general patterns from broad data, after which prompting, retrieval, or fine-tuning can adapt the model to a use case.
Detailed explanation
Knowledge is limited by training and retrieval sources.
Bias can remain in data and design.
It forms capabilities beyond one narrow business task.
Different adaptation methods address different requirements.
Check official documentation
Compare the following points with the official documentation.
AWS公式AIF-C01ガイドDomain 2.1の基盤モデルと事前学習を確認する。
Official references
What to confirm
事前学習と用途適応、知識の限界を区別できる。
Key points
- Pretraining
- Adaptation
- Limitations
Notes
- Environment: AWS公式AIF-C01試験ガイドとAWS公式ドキュメントの確認
- Compare the definition with the AIF-C01 objective and the service documentation before applying it.
- Keep the concept separate from a particular answer choice or implementation step.
Foundation review
Pretraining
Learning broad representations or patterns from a large and diverse dataset before task adaptation.
Foundation model
A broadly trained model that can be adapted to multiple downstream tasks.