How does LLM grounding work?
Grounding a large language model (LLM) means anchoring its outputs in reality, as defined by the organisation that is using…
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Articles & Insights
Does my LLM need an ontology?
A large language model (LLM) benefits most from an ontology in domains where hallucinations and errors can have serious consequences,…
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Why does ontology engineering need consensus?
The hardest part of an ontology engineer’s job can be getting people to agree on the definitions of key concepts,…
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What is natural language processing (NLP) in AI?
Natural language processing (NLP) is the field of AI that enables computers to understand and generate human language. While NLP…
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What is polysemy in AI?
Polysemy describes one word that means more than one thing depending on its context, where all of the meanings are…
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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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What is semantic interoperability in AI?
Semantic interoperability (SI) refers to how well different AI systems exchange data and interpret its meaning correctly. Interoperability helps intelligent…
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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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