Post

We launched some updates to the Discover feed today. This likely won't affect existing users as much, but for new users it's a big improvement. Basically: the ML team managed to build an improved topic classifier, which means Discover is better at responding to selected interests.

The classifier uses BLIP2 embeddings with training on labels which we manually created (yep). The ML team has the exact numbers but anecdotally it seems to have jumped from 40%ish accuracy to more like 90%. I'm surprised at how much more consistent it is.

How many labels had to be manually created in this way?