How do I avoid semantic drift in AI?
Semantic drift happens when the meaning of words, and the relationships between words, gradually diverge from what they were intended…
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Articles & Insights
What is semantic interoperability in AI?
Semantic interoperability (SI) refers to the ability of different AI systems to exchange data and interpret its meaning correctly. By…
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What is knowledge engineering?
Knowledge engineering is the process of acquiring, structuring, and then implementing expert knowledge in a machine-readable format so that AI…
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Does neuro-symbolic AI need ontologies?
Neuro-symbolic AI aims to reduce hallucinations in neural networks by applying the rules and logic of symbolic reasoning, often structured…
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What is an application ontology?
An application ontology fits knowledge into a machine-readable format for a specific purpose, such as running a specialised AI agent.…
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What is a vertical AI agent?
A vertical AI agent is an autonomous intelligent system that operates within a specific market or niche. By only using…
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What is the agentic web?
The agentic web envisions a structured global network designed for machine-to-machine interactions rather than human browsing. It builds on the…
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How does the semantic web use ontologies?
Ontologies bring rules and constraints to the machine-readable, interconnected knowledge of the semantic web. With an ontology to formally define…
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When does explainable AI (XAI) need an ontology?
Ontologies are helpful whenever non-technical humans need to understand the explanation of an AI’s outputs or decisions. By applying clear…
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What is ontological engineering?
Ontology engineering is the process of fitting domain knowledge into a structured, machine-readable format. It can make data easier to…
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