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Enterprise Wide Search 25: Frédéric Verhelst - From Data Chaos to Meaning: The Rise of Ontologies in AI cover
Enterprise Wide Search 25: Frédéric Verhelst - From Data Chaos to Meaning: The Rise of Ontologies in AI cover
Enterprise Wide Search

Enterprise Wide Search 25: Frédéric Verhelst - From Data Chaos to Meaning: The Rise of Ontologies in AI

Enterprise Wide Search 25: Frédéric Verhelst - From Data Chaos to Meaning: The Rise of Ontologies in AI

22min |23/01/2026
Play
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Enterprise Wide Search 25: Frédéric Verhelst - From Data Chaos to Meaning: The Rise of Ontologies in AI cover
Enterprise Wide Search 25: Frédéric Verhelst - From Data Chaos to Meaning: The Rise of Ontologies in AI cover
Enterprise Wide Search

Enterprise Wide Search 25: Frédéric Verhelst - From Data Chaos to Meaning: The Rise of Ontologies in AI

Enterprise Wide Search 25: Frédéric Verhelst - From Data Chaos to Meaning: The Rise of Ontologies in AI

22min |23/01/2026
Play

Description

In this episode, co-hosts Emma McGrattan and Ole Olesen-Bagneux sit down with Frédéric Verhelst — a leading voice in semantic technologies and agentic AI, and longtime semantic web advocate — for a practical dive into ontologies, knowledge graphs, and why they matter more than ever in an AI-first world.


From his early work with TotalEnergies to today’s experiments in integrating AI into digital service platforms, Frédéric brings clarity and historical depth to a topic many still find intimidating.


Together, they explore:

  • What an ontology actually is, and why it’s not as scary as it sounds.

  • The difference between a knowledge graph and a graph database, and why that difference matters.

  • Why LLMs need structured knowledge, and why hallucinations were a necessary wake-up call.

  • What Google, Netflix, and AstraZeneca all get right about semantics.

  • Why there’s a global shortage of knowledge graph talent, and how philosophy grads might help.


🎧 Tune in for a conversation that moves from data modeling to AI safety, and shows why the most innovative organizations are investing in semantics — not just models.


Hosted on Ausha. See ausha.co/privacy-policy for more information.

Description

In this episode, co-hosts Emma McGrattan and Ole Olesen-Bagneux sit down with Frédéric Verhelst — a leading voice in semantic technologies and agentic AI, and longtime semantic web advocate — for a practical dive into ontologies, knowledge graphs, and why they matter more than ever in an AI-first world.


From his early work with TotalEnergies to today’s experiments in integrating AI into digital service platforms, Frédéric brings clarity and historical depth to a topic many still find intimidating.


Together, they explore:

  • What an ontology actually is, and why it’s not as scary as it sounds.

  • The difference between a knowledge graph and a graph database, and why that difference matters.

  • Why LLMs need structured knowledge, and why hallucinations were a necessary wake-up call.

  • What Google, Netflix, and AstraZeneca all get right about semantics.

  • Why there’s a global shortage of knowledge graph talent, and how philosophy grads might help.


🎧 Tune in for a conversation that moves from data modeling to AI safety, and shows why the most innovative organizations are investing in semantics — not just models.


Hosted on Ausha. See ausha.co/privacy-policy for more information.

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Description

In this episode, co-hosts Emma McGrattan and Ole Olesen-Bagneux sit down with Frédéric Verhelst — a leading voice in semantic technologies and agentic AI, and longtime semantic web advocate — for a practical dive into ontologies, knowledge graphs, and why they matter more than ever in an AI-first world.


From his early work with TotalEnergies to today’s experiments in integrating AI into digital service platforms, Frédéric brings clarity and historical depth to a topic many still find intimidating.


Together, they explore:

  • What an ontology actually is, and why it’s not as scary as it sounds.

  • The difference between a knowledge graph and a graph database, and why that difference matters.

  • Why LLMs need structured knowledge, and why hallucinations were a necessary wake-up call.

  • What Google, Netflix, and AstraZeneca all get right about semantics.

  • Why there’s a global shortage of knowledge graph talent, and how philosophy grads might help.


🎧 Tune in for a conversation that moves from data modeling to AI safety, and shows why the most innovative organizations are investing in semantics — not just models.


Hosted on Ausha. See ausha.co/privacy-policy for more information.

Description

In this episode, co-hosts Emma McGrattan and Ole Olesen-Bagneux sit down with Frédéric Verhelst — a leading voice in semantic technologies and agentic AI, and longtime semantic web advocate — for a practical dive into ontologies, knowledge graphs, and why they matter more than ever in an AI-first world.


From his early work with TotalEnergies to today’s experiments in integrating AI into digital service platforms, Frédéric brings clarity and historical depth to a topic many still find intimidating.


Together, they explore:

  • What an ontology actually is, and why it’s not as scary as it sounds.

  • The difference between a knowledge graph and a graph database, and why that difference matters.

  • Why LLMs need structured knowledge, and why hallucinations were a necessary wake-up call.

  • What Google, Netflix, and AstraZeneca all get right about semantics.

  • Why there’s a global shortage of knowledge graph talent, and how philosophy grads might help.


🎧 Tune in for a conversation that moves from data modeling to AI safety, and shows why the most innovative organizations are investing in semantics — not just models.


Hosted on Ausha. See ausha.co/privacy-policy for more information.

Share

Embed

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