AXRP - the AI X-risk Research Podcast
Ein Podcast von Daniel Filan
59 Folgen
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35 - Peter Hase on LLM Beliefs and Easy-to-Hard Generalization
Vom: 24.8.2024 -
34 - AI Evaluations with Beth Barnes
Vom: 28.7.2024 -
33 - RLHF Problems with Scott Emmons
Vom: 12.6.2024 -
32 - Understanding Agency with Jan Kulveit
Vom: 30.5.2024 -
31 - Singular Learning Theory with Daniel Murfet
Vom: 7.5.2024 -
30 - AI Security with Jeffrey Ladish
Vom: 30.4.2024 -
29 - Science of Deep Learning with Vikrant Varma
Vom: 25.4.2024 -
28 - Suing Labs for AI Risk with Gabriel Weil
Vom: 17.4.2024 -
27 - AI Control with Buck Shlegeris and Ryan Greenblatt
Vom: 11.4.2024 -
26 - AI Governance with Elizabeth Seger
Vom: 26.11.2023 -
25 - Cooperative AI with Caspar Oesterheld
Vom: 3.10.2023 -
24 - Superalignment with Jan Leike
Vom: 27.7.2023 -
23 - Mechanistic Anomaly Detection with Mark Xu
Vom: 27.7.2023 -
Survey, store closing, Patreon
Vom: 28.6.2023 -
22 - Shard Theory with Quintin Pope
Vom: 15.6.2023 -
21 - Interpretability for Engineers with Stephen Casper
Vom: 2.5.2023 -
20 - 'Reform' AI Alignment with Scott Aaronson
Vom: 12.4.2023 -
Store, Patreon, Video
Vom: 7.2.2023 -
19 - Mechanistic Interpretability with Neel Nanda
Vom: 4.2.2023 -
New podcast - The Filan Cabinet
Vom: 13.10.2022
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.
