Ontologies and Large Language Models
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Ken Baclawski
Oct 2, 2023, 10:44:24 PM10/2/23
to ontolog...@googlegroups.com, ontolog-forum
Ontologies and Large Language Models: Related but Different
This is a reminder that the Fall Series of the Ontology Summit 2024 will begin in just 2 days on Wednesday 4 October 2023.
The first session will be the kickoff and overview of the series hosted by the two co-chairs, Andrea Westerinen and Mike Bennett.
Sessions will be on Wednesdays at Noon US/Canada Eastern Time on Zoom https://bit.ly/48lM0Ik
Ontology Summit 2024 webpage: https://bit.ly/3RDw4LD
Session webpage: https://bit.ly/466Uth6
Description:
Ontologies are representations of a knowledge domain. They define the concepts, relationships, properties, axioms and rules within that domain, providing a framework that enables a deep understanding of that subject area. Ontologies are used to enable machine reasoning and semantic understanding, allowing a system to draw inferences and to derive new information and relationships between entities.
On the other hand, LLMs are machine learning models that aim to generate human-like responses (including text and images) based on an input (“prompt”). They are trained on a large corpora of (mostly online) text, learning the patterns and connections between words and images. Hence, although their “knowledge base” is broad, it is also sometimes incorrect and/or biased. LLMs generate new content based on their training data, but don't explicitly understand the semantics or relationships in that content. This mini-summit explores the similarities and distinctions between ontologies and LLMs, as well as how they can be used together. In addition, the success of LLMs has generated much interest in AI and machine learning. This can be leveraged to promote the benefits of, and increase awareness of, the value of ontologies.
Ken Baclawski
Chair, Ontolog Board of Trustees
This is a reminder that the Fall Series of the Ontology Summit 2024 will begin in just 2 days on Wednesday 4 October 2023.
The first session will be the kickoff and overview of the series hosted by the two co-chairs, Andrea Westerinen and Mike Bennett.
Sessions will be on Wednesdays at Noon US/Canada Eastern Time on Zoom https://bit.ly/48lM0Ik
Ontology Summit 2024 webpage: https://bit.ly/3RDw4LD
Session webpage: https://bit.ly/466Uth6
Description:
Ontologies are representations of a knowledge domain. They define the concepts, relationships, properties, axioms and rules within that domain, providing a framework that enables a deep understanding of that subject area. Ontologies are used to enable machine reasoning and semantic understanding, allowing a system to draw inferences and to derive new information and relationships between entities.
On the other hand, LLMs are machine learning models that aim to generate human-like responses (including text and images) based on an input (“prompt”). They are trained on a large corpora of (mostly online) text, learning the patterns and connections between words and images. Hence, although their “knowledge base” is broad, it is also sometimes incorrect and/or biased. LLMs generate new content based on their training data, but don't explicitly understand the semantics or relationships in that content. This mini-summit explores the similarities and distinctions between ontologies and LLMs, as well as how they can be used together. In addition, the success of LLMs has generated much interest in AI and machine learning. This can be leveraged to promote the benefits of, and increase awareness of, the value of ontologies.
Ken Baclawski
Chair, Ontolog Board of Trustees
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