I mean, I think it’s probably some kind of standard transformer architecture behind the scenes that predicts user behavior and giving it negative feedback is equivalent to a backropagation step, or maybe some kind of RL step. I don’t have that much deep uncertainty about how it works, besides of course that we have no idea what’s going on inside of deep neural nets.
They tout their transformer (“beeformer”) in marketing copy, but I expect mostly its driven by collaborative filtering, like most recommendation engines
My guess is most recommendation engines in use these days are ML/DL based. At least I can’t think of any major platform that hasn’t yet switched over, based on what I read.
I would definitely consider collaborative filtering ML, though I don’t think people normally make deep models for it. You can see on Recombee’s website that they use collaborative filtering, and use a bunch of weasel language that makes it unclear if they actually use anything else much at all
I mean, I think it’s probably some kind of standard transformer architecture behind the scenes that predicts user behavior and giving it negative feedback is equivalent to a backropagation step, or maybe some kind of RL step. I don’t have that much deep uncertainty about how it works, besides of course that we have no idea what’s going on inside of deep neural nets.
They tout their transformer (“beeformer”) in marketing copy, but I expect mostly its driven by collaborative filtering, like most recommendation engines
My guess is most recommendation engines in use these days are ML/DL based. At least I can’t think of any major platform that hasn’t yet switched over, based on what I read.
I would definitely consider collaborative filtering ML, though I don’t think people normally make deep models for it. You can see on Recombee’s website that they use collaborative filtering, and use a bunch of weasel language that makes it unclear if they actually use anything else much at all