59 Episodo

  1. 35 - Peter Hase on LLM Beliefs and Easy-to-Hard Generalization

    Publicado: 24/8/2024

  2. 34 - AI Evaluations with Beth Barnes

    Publicado: 28/7/2024

  3. 33 - RLHF Problems with Scott Emmons

    Publicado: 12/6/2024

  4. 32 - Understanding Agency with Jan Kulveit

    Publicado: 30/5/2024

  5. 31 - Singular Learning Theory with Daniel Murfet

    Publicado: 7/5/2024

  6. 30 - AI Security with Jeffrey Ladish

    Publicado: 30/4/2024

  7. 29 - Science of Deep Learning with Vikrant Varma

    Publicado: 25/4/2024

  8. 28 - Suing Labs for AI Risk with Gabriel Weil

    Publicado: 17/4/2024

  9. 27 - AI Control with Buck Shlegeris and Ryan Greenblatt

    Publicado: 11/4/2024

  10. 26 - AI Governance with Elizabeth Seger

    Publicado: 26/11/2023

  11. 25 - Cooperative AI with Caspar Oesterheld

    Publicado: 3/10/2023

  12. 24 - Superalignment with Jan Leike

    Publicado: 27/7/2023

  13. 23 - Mechanistic Anomaly Detection with Mark Xu

    Publicado: 27/7/2023

  14. Survey, store closing, Patreon

    Publicado: 28/6/2023

  15. 22 - Shard Theory with Quintin Pope

    Publicado: 15/6/2023

  16. 21 - Interpretability for Engineers with Stephen Casper

    Publicado: 2/5/2023

  17. 20 - 'Reform' AI Alignment with Scott Aaronson

    Publicado: 12/4/2023

  18. Store, Patreon, Video

    Publicado: 7/2/2023

  19. 19 - Mechanistic Interpretability with Neel Nanda

    Publicado: 4/2/2023

  20. New podcast - The Filan Cabinet

    Publicado: 13/10/2022

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AXRP (pronounced axe-urp) is the AI X-risk Research Podcast where I, Daniel Filan, have conversations with researchers about their papers. We discuss the paper, and hopefully get a sense of why it's been written and how it might reduce the risk of AI causing an existential catastrophe: that is, permanently and drastically curtailing humanity's future potential. You can visit the website and read transcripts at axrp.net.

Visit the podcast's native language site