4 minutesUsing AI Wisely for School Success
State one rule of thumb for telling AI homework help apart from AI cheating.
IBM Technology. Martin Keen sorts hallucinations into four named buckets — sentence contradictions, prompt contradictions, factual errors, nonsense — and walks through each on a lightboard. After the article gives you the why, this video gives you a vocabulary for spotting the type of mistake in the wild so you can decide how much to trust a given answer.
Chosen for the four-bucket vocabulary rather than depth; read the article first so the taxonomy has the why underneath it.
You can name the four kinds of hallucination and recognize which one you are looking at when a chatbot gets something wrong.
None — watchable cold.
Last reviewed: May 18, 2026
Continue through the same learning path with the next curated companion videos.
4 minutesState one rule of thumb for telling AI homework help apart from AI cheating.
5 minutesNote one example from the segment where an AI answer diverged from professional medical judgment - without treating the segment as medical advice.
11 minutesName gaps between AI conversation and licensed therapeutic care so you know when to seek a human professional.
Hand-picked external courses that go deeper on this topic.
Andrew Ng
Real time inside an LLM, learning to prompt deliberately and recognise where generative AI is genuinely useful versus where it's a trap. Calm, no-hype teaching — the perfect bridge from "I've tried ChatGPT once" to "I use it every day with confidence."
Antje Barth · Shelbee Eigenbrode · Mike Chambers · Chris Fregly
When practitioners ask "what should I take if I'm serious about building with LLMs?", this is the answer. Mathematically honest without being a research paper; AWS-flavoured deployment chapters stay useful even if you'll never touch SageMaker.
Google Cloud
Google's own answer to 'what is generative AI, actually' — the non-technical counterpart to Elements of AI, aimed explicitly at sales, HR, marketing, and operations roles rather than engineers. Forty-five minutes to a real mental model of how generative AI differs from classic machine learning, with no code and no jargon.