Dr. Sarah Gebauer presents a clinical framework for deploying AI agents in healthcare, drawing a powerful analogy between AI agents and medical residents. She outlines the critical risks, validation strategies, and post-deployment monitoring required to make agents useful, safe, and credible in high-stakes clinical environments.
Ben Lorica and David Talby of 'The Data Exchange' podcast analyze the 2025 AI Governance Survey, revealing a significant gap between AI adoption and mature risk management. While 30% of organizations have models in production, many lack robust governance frameworks, incident response plans, and comprehensive monitoring, often prioritizing speed-to-market over safety and compliance.
Anthropic's Threat Intelligence team discusses their new report on how AI models are being used in sophisticated cybercrime operations. They cover the concept of "vibe hacking," a large-scale employment scam run by North Korea, and Anthropic’s multi-layered strategy to detect and counteract these threats.
A deep dive into why most enterprise GenAI pilots are failing, the debate around hidden system prompts in models like GPT-5, new research questioning the reliability of "chain of thought" reasoning, and the controversy over Anthropic's "AI welfare" justification for shutting down conversations.
Tom Brown, co-founder of Anthropic, shares his journey from a YC founder to a key figure behind AI's scaling breakthroughs. He discusses the discovery of scaling laws that underpinned GPT-3, the mission-driven founding of Anthropic, the surprising success of Claude for coding, and his perspective on what he calls "humanity's largest infrastructure buildout ever."
Members of Anthropic's interpretability team discuss their research into the inner workings of large language models. They explore the analogy of studying AI as a biological system, the surprising discovery of internal "features" or concepts, and why this research is critical for understanding model behavior like hallucinations, sycophancy, and long-term planning, ultimately aiming to ensure AI safety.