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Could the Facebook app do the same, listening only for specific keywords that trigger ads?
Not exactly. The Facebook targeting system had something like a million targetable keywords when I left, and it's likely held steady or increased slightly. But unlike the Amazon Echo, which listens for just one of four trigger words, millions or perhaps billions of words and phrases could land you in a Facebook targeting segment.
For example, saying 'golf,' 'Tiger Woods,' 'The Masters,' or 'Augusta National Golf Course' all should land you in the 'Golf' targeting segment, and your phone would need to detect each and every one. Because it has no specific trigger word for Facebook, your phone would need to listen for every targetable keyword. That means the speech-to-text translation code could only run on your phone itself, a taxing demand even for the beefy cloud servers that usually handle those tasks.
You could maybe hack around the problem by limiting the keyword list, or tightening the mapping from spoken word to targeting keyword to reduce the search space (only the literal word 'golf' instead of 'Tiger Woods'), but it's still daunting to do on every smartphone in existence, from slow, older phones to fast flagships like the iPhone X. Targeting a specific type of phone would ease that burden somewhat, but any significant scale presents an extraordinary challenge.
Furthermore, as in our naive approach above, this would be eminently noticeable as a performance degradation on your phone, since the background inference process would soon eat all your phone's CPU and battery, something you could easily check via the device's monitoring tools. That could change as smartphones get more powerful, and mobile developers more clever at running real computation in situ, but Facebook's targeting engine won't be running on your phone anytime soon.