Companion videos

What AI actually is (and isn't) — companion videos

The article strips the marketing layer off the words "artificial intelligence" and explains what today's chatbots are actually doing under the hood. These two videos give you the same picture in pictures and from a practitioner's mouth — one short and visual, one a calm tour of where the field really is.

Primary pick

7:58
Large Language Models explained briefly

3Blue1Brown

The cleanest eight-minute mental model of an LLM on YouTube. Grant Sanderson walks through "next-word prediction," parameters, training, and reinforcement learning from human feedback without ever drifting into hype. Watch it right after the article and the phrase "AI is just autocomplete on steroids" stops being a slogan and starts being a useful shorthand.

What you should get from this: You can explain in plain words how an LLM predicts the next token and why calling it autocomplete on steroids is fair but incomplete.

Watch or know first: None — watchable cold.

AI Expert note: Kept as the primary because it delivers the article's core mental model in eight minutes with no hype; watch it before anything longer on the topic.

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Also worth watching

36:25
Andrew Ng: Opportunities in AI - 2023

Stanford Online

Andrew Ng, one of the people who actually built the field, talking plainly about what AI is good at, what it isn't, and where the realistic opportunities sit. A useful counterweight to social-media takes — same calm, no-hype tone as the article, just with more depth on the "where is this actually going" question.

What you should get from this: You leave with a realistic sense of what AI is good at today, where it falls short, and which opportunities are worth taking seriously.

Watch or know first: None — watchable cold, though it lands better after the primary pick's eight-minute mental model.

AI Expert note: A 2023 talk, so treat the example applications as a snapshot; the calm what-AI-is-good-at framing is the part that holds up and the reason it stays.

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