Siddharth Bidasaria from Anthropic shares the origin story of Claude Code, from a simple internal terminal app to a powerful coding agent. He discusses the team's core philosophy of 'letting the model cook,' the evolution of agentic capabilities, the critical role of verification and testing, and the future of complex, multi-agent systems.
The Mixture of Experts panel discusses Anthropic's major investment in Google's TPUs for inference, debates the feasibility of insuring superintelligence, critiques OpenAI's approach to handling sensitive user conversations, and explores the futuristic concept of data centers in outer space.
Anthropic's team discusses Claude for Financial Services, an agentic AI solution designed to transform financial workflows. They explore how Claude's core strengths in coding and reasoning are applied to tasks like real-time data analysis and generating investor-ready reports, highlighting practical customer examples and future developments.
Anthropic's Jonah Cool and Eric Kauderer-Abrams outline their vision for making Claude an indispensable AI research assistant for scientists. They discuss a multi-faceted strategy that includes enhancing model capabilities for long-horizon tasks, building a rich ecosystem through partnerships with companies like Benchling and 10x Genomics, and applying Claude across the entire R&D lifecycle—from bioinformatics analysis to navigating regulatory submissions.
Sarah Nam, VP of AI Strategy and Partnerships at AbbVie, and Anthropic’s Ivy Weng discuss how AbbVie is transforming pharmaceutical research and development with AI, from reimagining drug discovery and clinical trials to driving enterprise-wide adoption and evaluating strategic partnerships.
Anthropic's Head of Pre-training, Nick Joseph, details the immense engineering and infrastructure challenges behind training frontier models like Claude. He covers the evolution from early-stage custom frameworks to debugging hardware at massive scale, balancing pre-training with RL, and the strategic importance of data quality and team composition.