Show Notes
Explainer podcast for Richard Ngo's "Clarifying and predicting AGI" post on Lesswrong, which introduces the t-AGI framework to evaluate AI progress. A system is considered t-AGI if it can outperform most human experts, given time t, on most cognitive tasks.
This is a new format, quite different from the interviews and podcasts I have been recording in the past. If you enjoyed this, let me know in the YouTube comments, or on twitter, @MichaelTrazzi.
Youtube: https://youtu.be/JXYcLQItZsk
Clarifying and predicting AGI: https://www.alignmentforum.org/posts/BoA3agdkAzL6HQtQP/clarifying-and-predicting-agi
More from The Inside View
Owain Evans is an AI Alignment researcher, research associate at the Center of Human Compatible AI at UC Berkeley, and now leading a new AI safety research group.
This is a special crosspost episode where Adam Gleave is interviewed by Nathan Labenz from the Cognitive Revolution. At the end I also have a discussion with Nathan Labenz about his takes on AI.
Ethan Perez is a Research Scientist at Anthropic, where he leads a team working on developing model organisms of misalignment.
Emil is the co-founder of palette.fm (colorizing B&W pictures with generative AI) and was previously working in deep learning for Google Arts & Culture.
Evan Hubinger leads the Alignment stress-testing at Anthropic and recently published "Sleeper Agents: Training Deceptive LLMs That Persist Through Safety Training".