social-media

Two internets, same technology, different shapes. Learn the operating requirements that platforms in China work under, from licensing and real-name accounts to filing recommendation algorithms with the regulator, how compliance became a core product function rather than a legal afterthought, why micro-dramas became a format with no Western equivalent, and what all the differences add up to.

More than half of China's internet users buy things through live broadcasts, a habit the West has never come close to. Learn why livestream selling worked there and stalled elsewhere, the mechanics of a selling stream, why conversion runs far above normal e-commerce, the difference between renting reach and owning an audience, and the costs the model carries.

Douyin is not TikTok, Xiaohongshu is not Instagram, and Weibo is not quite Twitter. A guided map of the platforms 1.1 billion people actually use: what job each one does, which conglomerate stands behind it, why the ecosystems were walled off from each other, and which Western analogy helps you versus which one quietly misleads you.

Western phones hold a dozen apps for a dozen jobs. In China, one app is the messaging, the payments, the taxi, the bill, the government form, and the shop. Learn how the super-app model works, why mini-programs made bundling possible, why a market that skipped credit cards produced a different shape of internet, and what the design actually trades away.

How platforms decide what stays up, and why nobody can reliably tell you whether something was made by AI. Covers classification at scale and the precision-recall tradeoff, why AI detectors accuse innocent people at rates that make them unusable, and how provenance approaches like C2PA and SynthID try a different answer, plus where they break too.

A practical, honest account of using generative models to make social content. Covers the jobs they genuinely do well, the specific ways they fail, why a model that sounds confident can still be wrong, the disclosure rules that now apply in the EU, and why the tool that removes effort also removes the thing that made your work worth watching.

Before the tools, the map. AI does three separate jobs on a social platform: it decides what you see, it helps make the content, and it decides what stays up. Learn what each job actually is, why they are built and judged differently, and why the same word covering all three causes most of the confusion about AI and social media.

Why a brand new post can reach millions on one platform and nothing on another. Learn the cold-start problem and why collaborative filtering cannot solve it alone, how content embeddings let a system rank an item nobody has touched, the difference between a social graph and an interest graph, and what actually separates YouTube, TikTok, Instagram and Pinterest.

A feed does exactly what it was told to maximize, which is rarely what anyone wanted. Learn which signals rankers actually weight and why implicit ones beat likes, how proxy objectives produce clickbait and rage-bait as correct answers to badly posed questions, and the mechanisms platforms use to pull an optimizer back toward what people value.

Every feed has the same impossible job: pick ten items out of millions, in under a tenth of a second. The answer is a funnel. Learn why recommenders split into a cheap retrieval stage and an expensive ranking stage, how two-tower models make retrieval possible, and why nearest-neighbour search is the trick that makes the whole thing fit in a budget.