Predictive Analytics
Using historical data to estimate what will happen next: which customers will lapse, which stock will run out. Useful precisely to the degree that the past resembles the future.
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Using historical data to estimate what will happen next: which customers will lapse, which stock will run out. Useful precisely to the degree that the past resembles the future.
A system of simple connected units, loosely inspired by the brain, that learns patterns from examples rather than following rules somebody wrote. Nearly all modern AI is built on one.
A longer, more specific search — “boutique hotel Siem Reap near Pub Street with a pool” rather than “hotel”. Individually rare, collectively most of all searches, and far easier to answer well.
Automatically judging whether text is positive, negative or neutral. Used to read reviews and messages at a scale nobody could read by hand.
Search that works on meaning rather than exact words, so a page can match a query it never literally contains. It is why writing naturally now beats repeating a keyword.
Training a model on unlabelled data and letting it find structure by itself — grouping similar customers, say, without being told what the groups are.
Organization markup with the details a local search needs — address, opening hours, service area, price range. What lets an assistant answer “is there one near me, and are they open now?”