Course

The AI Landscape

New labs, models, and benchmarks land every week — enough to make anyone feel behind. This is the orientation. The handful of labs racing to build AI. The difference between renting a closed model and owning an open one. How to read a leaderboard without being fooled by it. Why everything now runs on a scramble for chips. And the direction the whole field is moving. Six short scenes, no version decimals to memorise — just the shape of the field, so the next headline makes sense.

6 lessonsBeginner32 min

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Course lessons

Who's who

A dozen names, one race. Meet the handful of labs actually building today's AI — and what each is known for.

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Open vs closed weights

Two ways to get a model: rent a closed one through an app, or download an open one and own it. Each buys something different.

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Reading leaderboards

Benchmarks and arenas rank the models. They're useful — and easy to misread. Here's what a rank does and doesn't tell you.

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Compute & chips

Bigger models eat staggering amounts of computing power. That hunger — and the chips that feed it — is the real bottleneck.

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Where it's heading

No crystal ball — but the field has a clear direction: more doing, more senses, lower cost, closer to your device.

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Reading the field

You've met the labs, the open/closed split, leaderboards, compute, and the trends. Here's how to put it together the next time AI is in the news.

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