Process a word in the context of the rest of a long sentence.
Explain a Transformer concept.
Choose two correct statements.
Attention weights relationships among tokens, and Transformer architectures use it to build contextual representations; limits and factuality still require evaluation.
Detailed explanation
They fit large-scale pretraining.
Input and compute constraints remain.
Contextual combinations can be learned.
Representation and factual accuracy differ.
Check official documentation
Compare the following points with the official documentation.
AWS公式AIF-C01 Domain 2.1の基盤モデル、Transformer、Attentionを確認する。
Official references
What to confirm
Attentionの役割と、能力・知識・上限を混同しない説明ができる。
Key points
- Attention
- Transformer
- Context
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
Attention
A mechanism that assigns weights to relationships among input elements when building a representation.
Transformer
A neural-network architecture that uses attention to process sequences efficiently.