These are GenAI questions of the kind Cognizant actually asks — the patterns that keep coming back in Cognizant's GenAI and AI-project interview rounds, where the focus is on applying LLMs sensibly for clients rather than research depth. My advice: treat this page as a mock interview. Say every answer out loud before revealing it — GenAI rounds are conversations, not written tests. If an answer surprises you, the lesson behind it is linked at the bottom.
Cognizant GenAI concept questions
A model is described as '7B parameters with a 128K context window'. Explain both numbers to a junior teammate — and why neither means the model 'knows more facts'.
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Walk through, step by step, what happens between you pressing Enter in a chat app and the answer appearing word by word.
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You're configuring a code-generation assistant for internal developers. What temperature do you set and why? What's one more setting you'd configure deliberately?
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Cognizant GenAI applied & hands-on questions
Your summary bot shows two bugs: (1) different wording every run for the same input, breaking snapshot tests; (2) on long documents the summary ends abruptly mid-sentence. Name the parameter behind each, the fix, and how you'd confirm the second diagnosis from the API response.
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How to use this page: Cognizant rarely asks a question you've never seen — they ask standard GenAI concepts and then push one level deeper ("why?", "what would you do if..."). Master the concept in the GenAI course lessons, and the follow-up stops being scary.
Keep practising: How LLMs Work, Prompting Basics, RAG and Fine-tuning vs RAG cover what most Cognizant GenAI rounds test — and the Cognizant questions section covers the rest of their selection process.