Web search promised to resolve questions. Instead, it's brought on a soft apocalypse of a truth that's reduced to trivia.
But the more sophisticated NLP techniques that Google uses today involves wielding a concoction of interconnected machine learning algorithms that predict which results will be most useful to a searcher. The underlying goal is to understand a user's "intent" using any contextual clues at its disposal: current events, and the user's location, search history, language, device.
Of course, natural language is a bit of a misnomer. There is nothing "natural" about the way we talk to Google. We wouldn't walk over to a friend and bark "italian restaurant nearby" or "what watch netflix romcom."of the media scholar Father John Culkin, "we shape our tools and, thereafter, our tools shape us.
, which picks out specific excerpts from pages that might answer a user's question, whether or not it's the focus of the page. Passage Ranking can tell me, among other things, how Boygenius met , where the band's name came from , and pluck out of a 1400-wordThe vision of the world that these rich results represent is one in which everything worth knowing is unambiguous and perfectly atomizable; call it the baseball-card-ification of knowledge.
found that almost half of Google's mobile results page on the most popular queries was taken up by links to Google's own properties via sections like the “knowledge panel,” “people also ask,” and “featured snippets.”
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