22 - Shard Theory with Quintin Pope
AXRP - the AI X-risk Research Podcast
The Limits of Shard Theory in Deep Learning
Shard theory is meant to evoke the idea of like people is almost kind of reflexive. i think that for most systems you could construct out of deep learning components it's still going to be in the shard theory domain okay so i think part of this perception is that during the shard Theory sequence we very much did focus on simple examples of externally clear behaviors with a simple reward function such as juice consumption. You can have shards which activate when you're like thinking in a rude way and push your thoughts towards not being rude without like this necessarily corresponding to any externally visible sort of reward okay. These meta level cognitive processes are built on the workhorse of self-supervised slash reinforcement learn
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