Zohar Bronfman discusses why current LLMs are not on a path to AGI, contrasting their combinatorial creativity with the transformational, domain-general intelligence of humans. He argues that predictive models, not generative ones, deliver the most business value and explains how his platform, Pecan AI, automates the critical data preparation bottleneck to democratize predictive analytics for all businesses.
The OpenAI team details the creation of a new, powerful AI agent in ChatGPT, achieved by unifying the Deep Research and Operator models. They cover its unified architecture with shared state across tools, the reinforcement learning techniques used for training, and the critical safety measures required for an agent that can take real-world actions.
A discussion on the state of technical infrastructure, focusing on how AI and Large Language Models represent a new, fourth foundational pillar alongside compute, network, and storage. The talk covers how AI is disrupting software itself, the investment landscape, and the future of the developer profession.
This research explores the distillation and pruning of large, self-supervised speech quality assessment models into compact and efficient versions. Starting with the high-performing but large XLSR-SQA model, the work details a process of knowledge distillation using a teacher-student framework with a diverse, on-the-fly generated dataset. The resulting compact models successfully close over half the performance gap to the teacher, making them suitable for on-device and production applications where model size is a critical constraint.
Ben Mann, co-founder of Anthropic, discusses the accelerating progress in AI, forecasting superintelligence by 2028. He details Anthropic's safety-first mission, the "Economic Turing Test" for AGI, the mechanisms of Constitutional AI, and why focusing on alignment created Claude's unique personality.
Sagar Batchu, CEO of Speakeasy, discusses the pivotal shift in API development as AI agents become primary consumers. The conversation covers the rise of the Model Context Protocol (MCP), the challenges in building agent-ready APIs, and how Speakeasy provides a toolchain for creating, managing, and securing MCP servers.