GenAI Basics · Question 8 · Medium
What does Retrieval-Augmented Generation (RAG) do?
- Permanently retrains the model on every user question
- Generates images from retrieved text
- Compresses the model so that it runs faster
- Retrieves relevant passages from an external knowledge source at query time and adds them to the prompt, so the answer is grounded in those passages
Answer and explanation
Answer: D. Retrieves relevant passages from an external knowledge source at query time and adds them to the prompt, so the answer is grounded in those passages
Explanation: RAG combines a retriever, often a vector search over embeddings, with the generator. Fresh or private knowledge is supplied in the context without changing the model's weights.
Previous: What is the cosine similarity between the vectors (3, 4) and (6, 8)? · Next: Setting the sampling temperature of an LLM close to 0 typically makes its…
Practise genai basics
Try a fresh set of genai basics questions with an explanation after every answer, free and without signing up: GenAI Basics practice. Or sit a full placement mock test.
More genai basics questions
- What is few-shot prompting?
- What is a text embedding?
- What is the cosine similarity between the vectors (3, 4) and (6, 8)?
- Setting the sampling temperature of an LLM close to 0 typically makes its…
- What is an LLM's context window?
- A company's product price list changes every day, and its chatbot must answer…
- In a transformer model, what does the self-attention mechanism do?
- Which order of steps is correct for answering a user question with a typical…
- A model has a context window of 8,000 tokens, shared by the input and the…
- What is the main pre-training objective of decoder-only (GPT-style) large…
More technical & programming practice
Pseudo-code · C Programming · Java · Python · Data Structures · Algorithms · Object-Oriented Programming · DBMS
LogicWiz Exams home · All practice topics · Placement mock tests · Daily 10 challenge