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Discover how platforms find people like you and recommend what they enjoyed
Educational content slides
2006: Netflix offers $1 million prize to improve recommendations by 10%
The winning insight: Don't analyze movies. Analyze PEOPLE.
"People who liked what you liked also enjoyed..."
This single idea revolutionized recommendations. Instead of understanding why you like Attack on Titan (complex plot, dark themes, action), the algorithm finds people with similar taste patterns and recommends what they watched.
No content analysis needed. Just behavior patterns.
This is collaborative filtering—and it changed everything.
You just created a Netflix account. Why does it show 'Trending Now' instead of personalized recommendations?
Complete this exercise and get AI-powered feedback.
Collaborative filtering finds patterns in collective behavior. Where could this help in your life?
Think about: Any situation where 'people like you' is a useful signal—classes, food, events, content, purchases.
Key insight: You don't need to understand why similar people like something, just that they do.