Tom Smoker, co-founder of WhyHow.ai, shares insights on transforming unstructured data into structured knowledge. He discusses how knowledge graphs enhance AI retrieval, citing successful applications at LinkedIn and Pinterest. The conversation delves into the complexities of building these graphs and the balance between automation and intentional design. They also tackle the hallucination problem in AI, emphasizing the role of data clarity. Smoker argues for leveraging operational data to improve AI systems, showcasing the potential of graph-based methodologies.

Tom Smoker, Cofounder of WhyHow.ai, discusses using knowledge graphs in multi-agent systems. Topics include mitigating hallucination issues, optimizing search with knowledge graphs, agile problem-solving, and integrating vector databases. The conversation explores agents in multi-agent systems, stepping back for growth, and using AI models for automated content creation and revenue generation.