The promise of agentic AI is being realized in systems like the Service Copilot that Zeiss microscopes provides for its field service engineers.

The system integrates technical documentation, subject matter expertise, and user-generated insights which are orchestrated and shared with a suite of AI agents.

While it relies heavily on modern LLM technology, it's the system's solid knowledge graph and metadata foundation that make it a success.

https://knowledgegraphinsights.com/max-gaerber/

The complementary nature of knowledge graphs and LLMs has become clear, and long-time knowledge engineering professionals like Quentin Reul now routinely combine them in hybrid neuro-symbolic AI systems.

While it's tempting to get caught up in the details of rapidly advancing AI technology, Quentin emphasizes the importance of always staying focused on the business problems your systems are solving.

https://knowledgegraphinsights.com/quentin-reul/

As the World Wide Web emerged in the late 1990s, AI experts like Jim Hendler spotted an opportunity to imbue in the new medium, in a scale-able way, knowledge about the information on the web along with its simple representation as content.

With his colleagues Tim Berners-Lee, the inventor of the web, and Ora Lasilla, an early expert on AI agents, Jim set out their vision in the famous "Semantic Web" article for the May 2001 issue of Scientific American magazine.

Since then, semantic web implementations have blossomed, deployed in virtually every large enterprise on the planet and adding meaning to the web by appearing in the majority of pages on the internet.

https://knowledgegraphinsights.com/jim-hendler/