Elon Musk says X changed timeline recommendations with a new ranking model that predicts time spent and a retrieval model for posts people finish reading
Two important changes to timeline recommendations: - New AI/SI ranking model that predicts probable time spent much better - Retrieval model trained to surface posts people read all the way through User active seconds is growing exponentially and hitting all-time highs almost every day:
Context
How X's feed picks posts shapes what millions of people see, and Musk says the change is already lifting the time users spend on the app.
This is a self reported claim from the owner of X, and the chart shows X's own internal metric without a published definition. X publishes parts of its recommendation code on GitHub, but that code does not show the new models.
Deep dive
On October 19, Elon Musk posted two important changes to timeline recommendations on X: a new AI and SI ranking model that predicts probable time spent much better, and a retrieval model trained to surface posts people read all the way through. He added that user active seconds is growing exponentially and hitting all time highs almost every day.
The attached chart, titled Daily UAS, compares daily totals for 2023 through 2026. The 2026 line sits well above earlier years for most of the year and climbs past 500 billion in October, while 2023 to 2025 stay roughly between 300 billion and 400 billion. The chart does not explain how active seconds are counted, and its rise over the past few weeks is short compared with the whole series.
In a reply, Musk wrote that rewriting the X Android app was also a big deal, saying it was really bad for such a long time, which suggests the app rewrite may also have contributed to the growth.
In X's public algorithm repository, retrieval selects candidate posts and ranking orders them by a weighted mix of predicted actions that include dwell time. The new models' code and weights have not been published there, so outside researchers cannot yet check what changed.
What to expect next
Watch whether X publishes the new ranking and retrieval models in its open repository, and whether third party data such as app analytics firms show the same jump in usage. Optimizing for time spent and finished reading favors longer posts, so watch how creators and advertisers respond. Also watch whether the gains last once the new models are no longer novel.