Mentioned in 11 AI use cases across 3 industries
This is like hiring millions of super-fast digital editors who watch everything posted on a social network in real time—hiding abusive or illegal content, flagging rule‑breaking posts, and deciding what to show in people’s feeds based on their interests.
This describes how modern social platforms use AI as an always‑on assistant that decides what each person sees, when they see it, and how brands can talk to them—so every user’s feed and every ad feel custom‑made.
This is like having a smart digital marketing assistant inside Facebook and Instagram that automatically builds and optimizes your ads so more of the right people see them, for less money, with less manual tweaking.
This is like giving your marketing team a super-smart assistant that constantly studies which people click and buy, then automatically adjusts who sees your ads so you’re not wasting money showing ads to the wrong audience.
Think of this as a super-smart ad trader that watches billions of people’s clicks in real time and automatically decides which ad to show, to whom, at what price, and on which platform to get the best return—far faster and more accurately than any human team could.
This is Meta’s “autopilot” for ads: instead of you manually picking every audience detail, Meta’s AI watches how people behave on Facebook and Instagram, learns who reacts to which ads, and then automatically shows your ads to the people most likely to care, in real time.
This is about using YouTube’s AI and machine learning to automatically find the right viewers for your ads, set smarter bidding, and continuously improve performance—like giving your media buying team a super-intelligent autopilot that learns who is most likely to watch, click, or buy.
Think of GEM as a super-smart matchmaker that reads every ad, every user’s behavior, and a ton of context, then “imagines” which specific ad version and placement a person is most likely to respond to—millions of times per second across Meta’s apps.
Think of this as a smart ad-placing assistant that studies who actually clicks and buys from your ads on social platforms, then automatically shows future ads to more people who look and behave like those best customers.
This is like having a super-curious librarian who learns what movies, songs, or shows you like and then quietly rearranges the shelves so that whenever you walk in, the things you’re most likely to enjoy are right in front of you.
This is like a super-smart “TikTok/Netflix-style” recommender that looks at everything about a piece of content—its text, images, video, and user behavior—and learns end‑to‑end what people are most likely to enjoy, instead of relying on many hand‑tuned sub‑systems.