Deep Learning
Machine learning using neural networks with many layers. The depth is what lets a system learn complicated things — recognising a face, translating a sentence — without anyone specifying how.
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Machine learning using neural networks with many layers. The depth is what lets a system learn complicated things — recognising a face, translating a sentence — without anyone specifying how.
Google’s shorthand for Experience, Expertise, Authoritativeness and Trust — the qualities its raters look for. Not a score you can see, but a decent description of what makes content worth surfacing.
Tools that claim to identify AI-written text. Unreliable in both directions, and worth knowing about mainly because somebody may point one at your content and draw a confident wrong conclusion.
Text, images or video produced by AI. Not penalised for being synthetic, but it is judged by the same standard as anything else — and thin AI-written pages fail that standard easily.
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.
A working model of something real — a building, a supply chain — kept in step with it using live data, so changes can be tested before they are made for real.
Perplexity’s crawler. Perplexity cites its sources prominently, so being readable by it is one of the more direct routes to a visible citation.