Quentin Reul

Quentin Reul, an AI strategy executive and long-time semantic tech practitioner, blends generative AI, knowledge graphs, and agentic workflows. He discusses combining symbolic structure with LLM pattern-finding. Topics include entity resolution limits, using graphs to prevent hallucinations, LLM-driven graph population, pragmatic mixes of rules and ML, and starting designs from concrete business problems.

Quentin Reul, Founder and Chief AI Officer, discusses pivotal challenges in Generative AI. He reveals how businesses can leverage their data to stand out amidst the evolving AI landscape. Topics include the differences between Generative AI and traditional models, the complexities of selecting the right tools, and the importance of fine-tuning large language models. Quentin emphasizes focusing on customer needs and navigating the regulatory environment to enhance AI effectiveness, ensuring that data remains a strong competitive advantage.