Interview Q&A / AI & Generative AI
AI & Generative AI interview questions
LLMs, tokens, embeddings, RAG and prompt engineering, the questions every AI role now asks.
Prefer rapid revision? Practise AI & Generative AI short interview answers →
- What are embeddings, and how is vector similarity used to compare text?
An embedding is a list of numbers that represents the meaning of a piece of text, so texts with similar meaning get vectors that point in similar directions. Similarity measures such as cosine similarity compare these vectors to find related text.
IntermediateIn-depth3 min read - What is the difference between cosine similarity, dot product and Euclidean distance for vectors?
Cosine similarity compares only direction, dot product mixes direction and length, and Euclidean distance measures straight-line gap. For normalised vectors, cosine and dot product give the same ranking, and Euclidean distance ranks the same way too.
IntermediateQuick answer1 min read