Artificial Intelligence

This category explains how AI language models, AI search assistants and AI search engines such as Google AI Overviews work – from basic terms such as LLM and RAG to practical topics such as local AI, AI bias and the new EU AI Act.

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AI Agent (Agentic AI) An AI agent is a system built on a language model that plans multi-step tasks on its own, uses external tools such as …
AI Bias AI bias is a systematic distortion in the answers of an AI system that arises from one-sided, incomplete or skewed …
AI Hallucination An AI hallucination is a statement produced by a language model that is factually wrong or entirely invented, yet …
AI Labelling Requirement The AI labelling requirement means that content produced wholly or largely by AI, such as images, videos or certain …

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EU AI Act (AI Regulation) The EU AI Act (Regulation (EU) 2024/1689) is the first comprehensive AI regulation in the world; it classifies AI …

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Google AI Overviews Google AI Overviews are AI-generated summaries that Google places above the classic organic search results; they answer …

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NLP (Natural Language Processing) Natural language processing (NLP) is a subfield of AI concerned with how computers process, analyse and understand …

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Prompt Engineering Prompt engineering is the deliberate crafting of inputs (prompts) to an AI system in order to obtain a response that is …

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RAG (Retrieval-Augmented Generation) Retrieval-Augmented Generation (RAG) is a method in which an AI language model retrieves current external sources …

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Semantic Search Semantic search is search technology that captures the meaning and context of a query instead of only matching exact …

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Vector Embeddings Vector embeddings are numerical representations of words, sentences or entire passages of text in which similar …