Hopefully IG doesnt take this down 😩 #reverseengineering #swe #cs #tech #ai
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TL;DR
This video explores the AI models behind Instagram's algorithm, detailing how they predict user behavior and optimize engagement.
Chapters
- 0:00Introduction to Instagram's Algorithm01
- 0:10AI Models Overview02
- 0:20Predicting App Usage03
- 0:30Reel Interaction Predictions04
- 0:40Carousel Slide Selection05
- 0:50Niche Use Cases of AI06
- 1:00Conclusion and Next Steps07
Transcript
I reverse engineered Instagram to see what makes its algorithm so addicting. It starts with the 87 different AI models I found in its code base. For instance, this model takes 44 possible inputs, including your battery level, your last 7 days of activity, and the day of the week, and predicts when you'll open the app next. Another model, named L-I-G-E-G-R, takes your reel history and uses that to predict
how likely you'll complete the reel you're watching, how likely you'll continue watching reels, and how likely you will comment, like, or share that reel. They also have another model that decides which carousel slide to show you first, your likelihood that you will interact or tap on a story, and even a budgeting system that uses what they call common currency
to see which ads are eligible for viewing. They also have models that serve really niche use cases, just like this one that tracks activity over the past 200 times you open the reels tab just to predict if you'll open it up again and if it should preload that tab for you.
So yeah, apparently this is what 16 years of retention optimization on an app looks like. There's a lot more to cover, so follow and I will post a part 2.
There's a lot more to cover, so follow and I will post a part 2.
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