The Dawn of the Ultra-Tailored Ad Era.

Part One Recap

This is the second article of a two-part series.

If you haven't read part one of this series and aren’t 100% certain about how LLM works. This is probably the world’s most straightforward LLM explanation that you can find:

The Valuable LLM Apps Excel At Being Wrong

Yes, there was a little bit of a mechanism. More importantly, you would then understand the true value of LLM.

It's also essential groundwork to grasp what's coming in this article.

In it, I stripped away the mystique around LLMs – not by drowning you in technical jargon, but by laying bare the mechanics that separate revolutionary AI applications from expensive distractions.

You learned why the most successful LLM apps aren't fighting hallucinations – they're strategically leveraging them. The breakthrough insight? Being "broadly right and precisely wrong" isn't a bug; it's a feature when applied to the right problems.

The bullshit detector you gained in part one will prove invaluable as we now examine Meta's uniquely powerful position in the AI landscape.

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TL;DR:

• Explain how Meta could generate 1,000 personalized ads for less than $1 (that's $0.0000164 per ad)

• Explain why their unmatched social graph gives them a data advantage no competitor can replicate

• Who would be impacted? This shatters advertising's oldest constraint: the tradeoff between personalization and scale

• 20,000 ft view. The economics and the strategic implications for platforms, advertisers, and your privacy are far more complex than most realize

Subscribing to access the complete economic analysis, the interactive explainer understanding of Meta’s empire (screenshot below), and the implications for the future of advertising.