32 - Understanding Agency with Jan Kulveit

What's the difference between a large language model and the human brain? And what's wrong with our theories of agency? In this episode, I chat about these questions with Jan Kulveit, who leads the Alignment of Complex Systems research group.
Patreon: / axrpodcast
Ko-fi: ko-fi.com/axrp...
The transcript: axrp.net/episode/2024/05/30/episode-32-understanding-agency-jan-kulveit.html
Topics we discuss, and timestamps:
0:00:47 - What is active inference?
0:15:14 - Preferences in active inference
0:31:33 - Action vs perception in active inference
0:46:07 - Feedback loops
1:01:32 - Active inference vs LLMs
1:12:04 - Hierarchical agency
1:58:28 - The Alignment of Complex Systems group
Website of the Alignment of Complex Systems group (ACS): acsresearch.org
ACS on X/Twitter: x.com/acsresearchorg
Jan on LessWrong: lesswrong.com/users/jan-kulveit
Predictive Minds: Large Language Models as Atypical Active Inference Agents: arxiv.org/abs/2311.10215
Other works we discuss:
Active Inference: The Free Energy Principle in Mind, Brain, and Behavior: / 58275959
Book Review: Surfing Uncertainty: slatestarcodex...
The self-unalignment problem: www.lesswrong....
Mitigating generative agent social dilemmas (aka language models writing contracts for Minecraft): social-dilemma...

[@dizietz]

Any other interesting work to recommend on the idea that our senses/control mechanisms are both generative processes and predictive processes?
I also had some more to add on the topic why there isn't convergent behavior that might seem obvious. Like Jan mentioned, there might be local environment state differences, prediction optimization on a longer timescale has potential errors, etc. But there are also potential 'hardware' and 'software' differences as well -- humans don't run on completely homogenized brains, and it's possible to imagine that the initialization of various weights in our brains are randomly distributed that yields different outcomes.

[@axrpodcast]

Nothing I can think of beyond what's in the episode notes, I'm afraid.

[@AnalyzeR84]

Sometimes Guinness record in likes is needed to explain what's theory like.