Senior interview questionAsked at Apple · interview write-up
Design a voice assistant whose answers stay grounded. How would you reduce hallucinations?
Model answer
Voice adds two problems: errors start at speech recognition, and the user can't see sources. So use the recogniser's confidence, and confirm an uncertain name or number before acting on it.
Then answer from tools and retrieval, like calendar, contacts and search, not model memory, telling the model to answer only from those results. Check the draft against them before speaking, and confirm before any action. Keep replies short, name the source aloud, and say when it doesn't know. Evaluate on recorded, noisy, accented queries, scoring faithfulness and task success.
Practise the rest
11 Hallucination questions, 492 in all, each with a model answer. Free.
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More Hallucination interview questions
- What is a hallucination, and why can a next-token predictor produce one so fluently?
- GPT-2 small completes 'The capital of Australia is the city of' with Sydney. Walk me through why a model does that.
- Why do long generated answers leave more room for hallucination than one-word answers?
- You want to automatically flag answers that are probably wrong, using the model's token probabilities. How would you design and validate that?
- You're shipping a support bot that answers from your company's policy documents. What do you put in place to reduce hallucination, and how do you evaluate it?
- Design how a chatbot falls back when it doesn't know the answer, covering uncertainty, retrieval and tools.