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Mechanistic Interpretability for AI Alignment | Callum McDougall, Joseph Bloom | EAGxBerlin 2023

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Manage episode 383174121 series 3503936
Content provided by Aaron Bergman. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Aaron Bergman or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

This talk covers the fundamentals of mechanistic interpretability: what it is, why it might be impactful for alignment, and how you can get involved. It is most useful for people who are either new to AI safety, or limited knowledge about mechanistic interpretability. The speakers hope you gain insights into what interpretability research can look like, and whether it is a good fit for you. They also discuss some of the other work being done in technical alignment research.

  continue reading

159 episodes

Artwork
iconShare
 
Manage episode 383174121 series 3503936
Content provided by Aaron Bergman. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Aaron Bergman or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

This talk covers the fundamentals of mechanistic interpretability: what it is, why it might be impactful for alignment, and how you can get involved. It is most useful for people who are either new to AI safety, or limited knowledge about mechanistic interpretability. The speakers hope you gain insights into what interpretability research can look like, and whether it is a good fit for you. They also discuss some of the other work being done in technical alignment research.

  continue reading

159 episodes

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