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The Information Bottleneck

von Ravid Shwartz-Ziv & Allen Roush

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  1. EP16: AI News and Papers

    In this episode, we discuss various topics in AI, including the challenges of the conference review process, the capabilities of Kimi K2 thinking, the advancements in TPU technology, the significance of real-world data in robotics, and rece

  2. EP15: The Information Bottleneck and Scaling Laws with Alex Alemi

    In this episode, we sit down with Alex Alemi, an AI researcher at Anthropic (previously at Google Brain and Disney), to explore the powerful framework of the information bottleneck and its profound implications for modern machine learning.

  3. EP14: AI News and Papers

    In this episode, we talked about AI news and recent papers. We explored the complexities of using AI models in healthcare (the Nature Medicine paper on GPT-5's fragile intelligence in medical contexts). We discussed the delicate balance bet

  4. EP13: Recurrent-Depth Models and Latent Reasoning with Jonas Geiping

    In this episode, we host Jonas Geiping from ELLIS Institute & Max-Planck Institute for Intelligent Systems, Tübingen AI Center, Germany. We talked about his broad research on Recurrent-Depth Models and latent reasoning in large language mod

  5. EP12: Adversarial attacks and compression with Jack Morris

    In this episode of the Information Bottleneck Podcast, we host Jack Morris, a PhD student at Cornell, to discuss adversarial examples (Jack created TextAttack (https://arxiv.org/abs/2005.05909), the first software package for LLM jailbreaki

  6. EP11: JEPA with Randall Balestriero

    In this episode we talk with Randall Balestriero, an assistant professor at Brown University. We discuss the potential and challenges of Joint Embedding Predictive Architectures (JEPA). We explore the concept of JEPA, which aims to learn go

  7. EP10: Geometric Deep Learning with Michael Bronstein

    In this episode, we talked with Michael Bronstein, a professor of AI at the University of Oxford and a scientific director at AITHYRA, about the fascinating world of geometric deep learning. We explored how understanding the geometric struc

  8. EP9: AI in Natural Sciences with Tal Kachman

    In this episode we host Tal Kachman, an assistant professor at Radboud University, to explore the fascinating intersection of artificial intelligence and natural sciences. Prof. Kachman's research focuses on multiagent interaction, complex

  9. EP8: RL with Ahmad Beirami

    In this episode, we talked with Ahmad Beirami, an ex-researcher at Google, to discuss various topics. We explored the complexities of reinforcement learning, its applications in LLMs, and the evaluation challenges in AI research. We also di

  10. EP7: AI and Neuroscience with Aran Nayebi

    In this episode of the "Information Bottleneck" podcast, we hosted Aran Nayeb, an assistant professor at Carnegie Mellon University, to discuss the intersection of computational neuroscience and machine learning. We talked about the challen

  11. EP6: Urban Design Meets AI: With Ariel Noyman

    We talked with Ariel Noyman, an urban scientist, working in the intersection of cities and technology. Ariel is a research scientist at the MIT Media Lab, exploring novel methods of urban modeling and simulation using AI. We discussed the p

  12. EP5: Speculative Decoding with Nadav Timor

    We discussed the inference optimization technique known as Speculative Decoding with a world class researcher, expert, and ex-coworker of the podcast hosts: Nadav Timor. Papers and links: • Accelerating LLM Inference with Lossless Speculati

  13. EP4: AI Coding

    In this episode, Ravid and Allen discuss the evolving landscape of AI coding. They explore the rise of AI-assisted development tools, the challenges faced in software engineering, and the potential future of AI in creative fields. The conve

  14. EP3: GPU Cloud

    Allen and Ravid discuss the dynamics associated with the extreme need for GPUs that AI researchers utilize. They also discuss the latest advancements in AI, including Google's Nano Banana and DeepSeek V3.1, exploring the implications of syn

  15. EP2: PeFT

    Allen and Ravid sit down and talk about Parameter Efficient Fine Tuning (PeFT) along with the latest updated in AI/ML news.

  16. EP1: Sampling

    Allen and Ravid discuss a topic near and dear to their hearts, LLM Sampling! In this episode of the Information Bottleneck Podcast, Ravid Shwartz-Ziv and Alan Rausch discuss the latest developments in AI, focusing on the controversial relea

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