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.
A conversation with Bob Ransijn from Siemens exploring the evolution and application of system simulation, from its historical roots to its modern-day integration with multi-physics modeling, digital twins, and AI-driven reduced-order models for predictive maintenance and real-time analysis.
A product manager from Cisco's incubation group, Outshift, details a solution that uses a multi-agent AI system combined with a dynamic network knowledge graph to solve critical issues in IT change management. The system integrates with ITSM tools like ServiceNow to automate impact assessment, test plan generation, and pre-production validation in a "digital twin" environment, significantly reducing production failures.
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.
Stephanie Kirmer, a staff machine learning engineer at DataGrail, adapts her experience as a former professor to address the challenge of evaluating LLMs in production. She proposes a robust methodology using LLM-based evaluators guided by rigorous, human-calibrated rubrics to bring objectivity and scalability to the subjective task of assessing text generation quality.