Here we go, the start of LLMs plugged into everything.
Do Netflix recommendations really need to use LLMs?
This post paints a very altruistic picture of how recommendations can be fed from user history, preferences, device and environment context etc. However they make no mention of needing to advertise content from paid clients, promote new releases, and increase views on certain underperforming content. I'm assuming that once their fancy LLM spits out some user recommendations, they are then run through another process to 'commercialise' the results before displaying them to the user.
Also, if "The Odyssey" is coming out and and you know I love Nolan, and Netflix is getting paid to promote it, would you rather them NOT recommend that to me?
These types of things are natrually constrained. If you send me too many ads, or bad content, I leave. So you are incentived to do a good job.
You could make the argument that you just need to be incrementally better than the other streaming service, but then you are giving away potential advantage and profit.
If that's true, people will leave for bigger libraries and netflix will have to rotate into quantity. That hasn't been the case so far (net flix is killing everyone in terms of subscribers/growth YoY), but doesnt mean it can't be, especially with the paramount merger potentially going through.
I think it's been a little bit proven that it's more about specific shows (friends, seinfeld, how to lose a guy in 10 days, etc) that just mass amount of quantity, but we'll see
This post paints a very altruistic picture of how recommendations can be fed from user history, preferences, device and environment context etc. However they make no mention of needing to advertise content from paid clients, promote new releases, and increase views on certain underperforming content. I'm assuming that once their fancy LLM spits out some user recommendations, they are then run through another process to 'commercialise' the results before displaying them to the user.