What if an AI could become smarter without being taught anything? In this episode, we dive into Absolute Zero, a groundbreaking framework where an AI model trains itself to reason—without any curated data, labeled examples, or human guidance. Developed by researchers from Tsinghua, BIGAI, and Penn State, this radical approach replaces traditional training with a bold form of self-play, where the model invents its own tasks and learns by solving them.

The result? Absolute Zero Reasoner (AZR) surpasses existing models that depend on tens of thousands of human-labeled examples, achieving state-of-the-art performance in math and code reasoning tasks. This paper doesn’t just raise the bar—it tears it down and rebuilds it.

Get ready to explore a future where models don’t just answer questions—they ask them too.

Original research by Andrew Zhao, Yiran Wu, Yang Yue, and colleagues. Content powered by Google’s NotebookLM.

Read the full paper: https://arxiv.org/abs/2505.03335

What if AI agents could collaborate as seamlessly as devices do over the Internet? In this episode, we dive into "A Survey of AI Agent Protocols" by Yingxuan Yang and colleagues from Shanghai Jiao Tong University, a landmark paper that tackles the missing piece in today’s intelligent agent landscape: standardized communication protocols. As large language model (LLM) agents spread across industries—from customer service to healthcare—they still operate in silos, struggling to integrate with tools or with one another. This paper proposes a two-dimensional classification of agent protocols and explores a future where agents form coalitions, speak common languages, and evolve into a decentralized, intelligent network. Expect insights on leading protocols like MCP, A2A, and ANP, a vision for “Agent Internets,” and a compelling case for why protocol design may shape the next era of AI collaboration.

This podcast was generated using insights from the original paper and synthesized via Google’s NotebookLM.

🔗 Read the full paper: https://arxiv.org/abs/2504.16736

What happens when generative AI collides with human creativity? In this episode, we dive into the extraordinary transformation sweeping across visual arts, music, film, and writing—powered by tools like DALL·E, Midjourney, Suno, and ChatGPT. From text-to-image magic and AI-composed music to VFX breakthroughs and story co-writing, we explore how these innovations are democratizing access, supercharging workflows, and sparking heated debates over ethics, copyright, and what it means to be an artist. Drawing on a wide range of sources—made accessible with help from Google’s NotebookLM—we unpack how individuals and industries are adapting, and what the future of artistic expression might look like.