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.
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- What are hallucinations in LLMs, and how can you reduce them?
A hallucination is when an LLM produces fluent, confident output that is false or not supported by its input, such as an invented fact or citation. You reduce them by grounding the model in real sources, allowing it to say "I don't know", lowering randomness and checking outputs.
BeginnerIn-depth3 min read - What are tokens and the context window in an LLM?
Tokens are the small pieces of text (whole words, parts of words or symbols) that an LLM reads and writes. The context window is the maximum number of tokens the model can consider at once, including both your input and its output.
BeginnerIn-depth3 min read - What is a large language model (LLM), and how does it generate text?
An LLM is a neural network trained on a huge amount of text to predict the next token. It generates text by predicting one token at a time, adding it to the input, and repeating until it stops.
BeginnerIn-depth3 min read - What is prompt engineering, and what makes a good prompt?
Prompt engineering is writing and testing the input to an LLM so it reliably produces the output you need. Good prompts give clear instructions and context, show a few examples when the format matters, and ask for a specific output structure.
BeginnerIn-depth3 min read