The recommendation pipeline has four steps:
The recommendation pipeline runs 5 billion times per day and completes in under 1.5 seconds on average.
Gets the best 1,500 recent tweets:
Ranking is achieved with a 48M parameter neural network that is continuously trained on tweet interactions to optimize for positive engagement (e.g. Likes, Retweets, and Replies). This ranking mechanism takes into account thousands of features and outputs ten labels to give each tweet a score, where each label represents the probability of an engagement.
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