FB's bait is user engagement. So, applying machine learning to the goal of engaging users makes sense.
But, to monetize that user-engagement they, of course, use ads. Applying machine learning directly there makes sense too.
Beyond that, it's just semantics. Yes, one could accurately say that everything FB does is about ads because, ultimately, they are a for-profit company which derives its revenue from advertising. In that way, the ultimate goal of all of its activity is aimed at generating ad revenue.
But, that doesn't mean that every single activity or bit of technology that supports that activity is directly tied to driving ad revenue. That is to say, that if FB featured no advertising but, instead, charged users, they would still likely deploy machine-learning to user-engagement and, thus, customer-retention.
FB's bait is user engagement. So, applying machine learning to the goal of engaging users makes sense.
But, to monetize that user-engagement they, of course, use ads. Applying machine learning directly there makes sense too.
Beyond that, it's just semantics. Yes, one could accurately say that everything FB does is about ads because, ultimately, they are a for-profit company which derives its revenue from advertising. In that way, the ultimate goal of all of its activity is aimed at generating ad revenue.
But, that doesn't mean that every single activity or bit of technology that supports that activity is directly tied to driving ad revenue. That is to say, that if FB featured no advertising but, instead, charged users, they would still likely deploy machine-learning to user-engagement and, thus, customer-retention.