How Instagram Picks Your Next Reel
Summary
Instagram's recommender narrows a pool of billions of posts to one winner every time you swipe, and it only ever scores about a hundred of them. Stage one is retrieval: a Two Tower model turns you and every reel into embeddings, and approximate nearest neighbor search grabs a few thousand candidates in hundredths of a second. Stage two is a lightweight ranker distilled from the heavy one, cutting thousands to hundreds. Stage three sends roughly the 100 best through the heavy model, which predicts completion, likes, shares, and audio taps. Integrity filters and diversity rules rerank the top, and the winner lands on your screen. The same architecture (embeddings, retrieval, rankers) is what Mixpeek runs over your own video and image catalog. Meta's engineering write-up: engineering.fb.com/2023/08/09/ml-applications/scaling-instagram-explore-recommendations-system
About this video
Instagram's recommender narrows a pool of billions of posts to one winner every time you swipe, and it only ever scores about a hundred of them. Stage one is retrieval: a Two Tower model turns you and every reel into embeddings, and approximate nearest neighbor search grabs a few thousand candidates in hundredths of a second. Stage two is a lightweight ranker distilled from the heavy one, cutting thousands to hundreds. Stage three sends roughly the 100 best through the heavy model, which predicts completion, likes, shares, and audio taps. Integrity filters and diversity rules rerank the top, and the winner lands on your screen. The same architecture (embeddings, retrieval, rankers) is what Mixpeek runs over your own video and image catalog. Meta's engineering write-up: engineering.fb.com/2023/08/09/ml-applications/scaling-instagram-explore-recommendations-system