Lesson 4 · Natural Language Processing
Attention & Transformers for Language
9 min
You'll be able to
- Understand how attention resolves ambiguity
- Explain why transformers handle long context well
- Connect transformers to chatbot quality
Transformers changed NLP by replacing fixed left-to-right processing with attention, which lets every token attend to every other token and weigh relevance. A model reading 'The bank approved the loan' attends strongly to 'loan' when encoding 'bank', picking the financial sense.
This architecture underpins modern chatbots and translation systems, and it scales with more data and compute to produce remarkably coherent language.
Challenge
Resolve the ambiguity
For the sentence 'She saw the bat fly at dusk', identify which words disambiguate 'bat' and explain what attention should weigh.
Knowledge Check
Transformers for language
Attention helps a model:
Transformers process tokens in a way that captures long-range context effectively.
Answer all questions to submit.