"Netflix Knows What You'll Watch Next — Here's How" #netflixalgorithm

[00:00:00]You open Netflix, scroll for 10 seconds, and somehow find exactly what you were in the mood for.

[00:00:05]That's not luck. That's a machine that knows you better than your friends do.

[00:00:10]Over 80% of everything watched on Netflix comes directly from AI recommendations across the platform with hundreds of millions of subscribers. So, how does it work? Collaborative filtering. If two users share similar viewing habits, content enjoyed by one is recommended to the other. Netflix groups you with millions of taste alikes you'll never meet and uses their choices to predict yours. Content embeddings.

[00:00:37]Deep learning encodes users and content into a dense low-dimensional space [music] mapping your preferences alongside thousands of titles. It's not just [music] you liked thrillers, it captures why you liked them down to [music] pacing, tone, and cast chemistry. AB testing [music] thumbnails.

[00:00:56]The same show can look completely different to different users because a romance fan sees an emotional connection thumbnail, while an action fan sees an explosion from the same title.

[00:01:06]>> [music] >> Personalized thumbnails have increased click-through rates by up to 30%.

[00:01:11]Every scroll, every pause, every abandoned episode, it's all data training the machine to know you better.

[00:01:17]Netflix isn't just recommending [music] content, it's engineering your next obsession.