Karan Goel, CEO of Cartesia, discusses the fundamental limitations of Transformer architectures, arguing they behave more like retrieval systems than learning systems. He explains how State Space Models (SSMs) enable compression and abstraction, and why Cartesia is tackling multimodal intelligence by first solving for voice AI, aiming to develop a transferable 'recipe' for end-to-end representation learning.
Nathan Labenz joins Erik Torenberg to challenge the narrative that AI progress is slowing down. He argues that despite perceptions around GPT-5, capabilities in reasoning and frontier science are advancing exponentially. They discuss the future of AI agents, the prospect of recursive self-improvement, the impact on jobs, and progress beyond language models into robotics and biology. The conversation culminates in a call for a more imaginative, positive vision to guide AI's trajectory.