Join Nikolaos Vasiloglou, VP of Research ML at RelationalAI, as he traces the evolution of AI from early neural networks through kernel methods, gradient boosted trees, and the deep learning revolution that transformed the field. He shares valuable insights on addressing hallucinations in AI systems through fact-checking, human annotation, and offline curation, while emphasizing the growing importance of Graph RAG (Retrieval-Augmented Generation) as a practical solution that bridges neural networks' generalization capabilities with symbolic AI's accuracy and speed. He explores agentic systems, both macro and micro approaches, and offers his perspective on recent developments like DeepSeek's R1 model, suggesting that while efficiency improvements are inevitable, they don't necessarily threaten established players in the field.
The Artificial Intelligence Podcast