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Why Agentic Systems Need Ontologies — Frank Coyle, UC Berkeley

AI Engineer · · Durée 21:18

Frank Coyle explains ontologies as shared conceptualizations for agents, proposes neurosymbolic guardrails for probabilistic LLMs, and discusses validating tool outputs and catching business logic errors with ontologies. Lisez 4 points de vue avec leurs éléments à l’appui et les liens vers les sources.

Frank Coyle
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En un coup d’œil

  • Ontologies as formal shared conceptualizations

    Frank Coyle defines an ontology as a formal specification of a shared conceptualization and says agents should be given that conceptualization of their domain.

    Lire le moment probant · 3:45

  • Neurosymbolic AI as LLM guardrails

    Frank Coyle argues that neurosymbolic AI can help keep probabilistic LLMs on guardrails.

    Lire le moment probant · 4:46

  • Ontology-driven validation in agent loops

    Frank Coyle proposes using ontologies after a tool runs, formatting the returned information for a validator that operates with domain ontologies.

    Lire le moment probant · 16:45

  • Ontologies for catching domain-specific errors

    Frank Coyle says ontologies could catch errors such as a second refund on one order or a payout sent to support instead of the buyer. He describes catching such errors in English as tricky.

    Lire le moment probant · 19:12

Moments clés4

Extraits courts et attribués, avec le contexte permettant de les vérifier. La conversation complète reste chez son éditeur.

3:45 (s’ouvre dans un nouvel onglet)
ontology design for AI agents

Ontologies as formal shared conceptualizations

Extrait original

It is a, a formal specification of a shared conceptualization, and that's what we wanna give to our agents. We wanna give them our concept-- our conceptualization of the universe, our universe, our domains.
Frank Coyle·
Contexte

knowledge and, uh, graph technology really represents.

16:45 (s’ouvre dans un nouvel onglet)
agent validation workflow

Ontology-driven validation in agent loops

Extrait original

if you look down there, a-after the, the tool is called, it said, "Tool runs," this is where ontologies could come in. The tool's gonna give us information. We put the information in a form that our, our, our, our validator can use.
Frank Coyle·
19:12 (s’ouvre dans un nouvel onglet)
ontology-based business logic enforcement

Ontologies for catching domain-specific errors

Extrait original

A second refund on the same order is a, is, is a problem. [laughs] Ontologies could catch it, whereas it's ver- it's very tricky to do that in, in English. A payout sent to the support desk instead of the buyer, okay?
Frank Coyle·

Source et méthodologie

Ces points de vue renvoient à leurs sources originales. Les reformulations sont signalées et ne sont pas des citations mot à mot.

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