ASIMOV Platform - Conversational Knowledge Capture Using the KNOW Ontology

Join us for a comprehensive tutorial on capturing and modeling everyday knowledge using large language models (LLMs) and symbolic knowledge graphs (KGs), geared toward real-world AI applications. We'll begin by exploring the integration of LLMs with KGs—what we call the neurosymbolic synthesis—to create AI systems that are practical, trustworthy, explainable, and fully interoperable.

Next, we'll dive into the KNOW ontology, specially designed to enhance LLMs for applications such as personal AI assistants. We'll discuss its broad application across various domains of human life, from routine activities to significant life events, demonstrating its versatility in modeling real-world scenarios.

In our hands-on final section, participants will engage directly with ontology-guided knowledge capture using a popular open-source LLM. We'll explore the advantages and challenges of fine-tuning versus prompt engineering and showcase the practical differences between traditional retrieval-augmented generation (RAG) methods and those augmented with our advanced KG techniques, setting the stage for a discussion on the future of industry practices.