Generative AI & Prompt Engineering interview questions and answers

An LLM is a neural network, usually based on the transformer architecture, trained on large amounts of text to understand and generate human-like language.

RAG retrieves relevant documents from a knowledge source, typically using a vector database, and passes them to the LLM as context so responses are grounded in specific data.

Prompt engineering is the practice of designing instructions, examples and context for an LLM to produce accurate, relevant and well-formatted outputs.

Embeddings are numerical vector representations of text or other data that capture meaning, so similar content has vectors that are close together. They power semantic search and RAG.

Hallucination is when a model generates confident but incorrect information. It can be reduced with RAG, clear prompts, lower temperature, output validation and human review.