I've worked on very large scale recommendation systems at a FAANG. If Twitter's system resembles anything like ours, the concept of publishing or open sourcing "the algorithm" doesn't make sense. Even if we were to open source all associated code and publish all related documents it would be very difficult to make sense of the entire system. That is precisely why companies such as Twitter A/B test the hell out of eve…
There are ways to translating trained ML models and associated systems into understandable hierarchical rules.
Twitter's timeline is NOT AGI.