​AI is already a huge part of how we work and study, but most people learn through extensive trial and error. Join this lunch & learn session to get a head start at understanding what AI is actually good at, where it fails, and how to use it without compromising academic integrity. ​This session is a practical, no-jargon introduction to AI for life sciences students. No prior AI experience needed. ​We'll cover: ​• What a large language model actually is, and how it "thinks" ​• Core terminology, explained simply: prompts, models, hallucination, context windows, agents/workflows ​• Real examples of how AI can get it wrong • ​How to go from a basic prompt to a well-structured one, using a real biology task ​• A live look at how AI-assisted research workflows work in practice, including why traceability (seeing and editing every step) matters for academic integrity ​• Free lunch included! ​This is a hands-on session, not a lecture. Bring your questions and be ready to engage with questions. ​Ideal for undergraduate and masters students studying life science and looking for some practical help with how to use AI in their coursework and research. ​Hosted by ​This session is sponsored by Amytis, a visual AI workspace built for life sciences researchers. You'll hear from the Amytis team, who between them have 4 science degrees, 2 PhDs and no shortage of anecdotes about the good, bad and ugly of using AI in your work.

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