A deep dive into building expert AI systems using a Wisdom-Driven Knowledge Graph. This approach enhances Knowledge-Augmented Generation (KAG) to surpass traditional Retrieval-Augmented Generation (RAG) by enabling systems to understand, reason, and provide expert-level quantitative analysis and advice.
Google DeepMind’s Chief Scientist Jeff Dean discusses the origins of his work on scaling neural networks, the founding of the Google Brain team, the technical breakthroughs that enabled training massive models, the development of TensorFlow and TPUs, and his perspective on the evolution and future of artificial intelligence.
Professor Hannah Fry speaks with Jack Parker-Holder and Shlomi Fruchter about Genie 3, a general-purpose world model that generates diverse, interactive environments from prompts. The discussion covers its auto-regressive nature, which enables the creation of consistent, explorable worlds, its key differences from video models like Veo, and its foundational role in training AI agents and advancing toward AGI.
Eoghan McCabe, founder and CEO of Intercom, shares the unfiltered story of transforming a multi-billion dollar, stagnating SaaS business into a rapidly growing, AI-first company. He details the necessity of 'founder mode,' a radical cultural overhaul, and why having nothing to lose is the ultimate advantage in the AI era.
Andrew Ng discusses the rise of agentic AI, moving beyond scale as the sole driver of progress. He explores how AI-assisted coding is creating a new startup paradigm, shifting the bottleneck from engineering to product management and favoring technical founders. Ng argues for smaller, highly-skilled teams and predicts AI will profoundly empower individuals across all job functions.
Yuki Watanabe from Databricks introduces Evaluation-Driven Development (EDD) as a critical methodology for building production-ready AI agents. This talk explores the five pillars of EDD and demonstrates how MLflow 3.0's new features—including one-line tracing, automated evaluation, human-in-the-loop feedback, and monitoring—provide a comprehensive toolkit to ensure agent quality and reliability.