Cursor recently published a new blog outlining how they train models. Interestingly, the blog does not clarify how they handle opt-out user data and/or business user data -- exact phrasing: "[cursor's] model runs on every user action, handling over 400 million requests per day. As a result, we have a lot of data about which suggestions users accept and reject. This post describes how we use this data to improve Tab using online reinforcement learning."
As a matter of fact, the wording sounds like all cursor user data (opt-in and opt-out alike) are being used.
Anyone knows what's going on behind the scenes?