This is a special post for quick takes by spokeydoke. Only they can create top-level comments. Comments here also appear on the Quick Takes page and All Posts page.
I'm very new to alignment research: I'm a college professor with a philosophy background trying to write a realistic near-future case study for an undergraduate business ethics class about A(G)I, alignment and safety. I think I want to focus the case study around a (mid 2027?) decision in a particular company to implement or not implement chain-of-continuous-thought reasoning in developing a new, powerful LLM model.
My main questions for this community are:
(1) Am I correct in thinking chain-of-continuous-thought not yet been widely implemented in major LLMs? (i.e), Are the big players still using language tokens for chain-of-thought reasoning rather than vectors?
(2) Is it accurate that the choice to use chain-of-continuous-thought is quite likely to involve a sacrifice of interpretability in return for more (efficient) ability to "remember context" for the LLM?
Thank you on behalf of myself and my students!
2
1This is a good read: How AI Is Learning to Think in Secret
If you're short on time you can start reading from "The good news: Neuralese hasn't won yet."
(Searching "neuralese" seems to yield much more results than "continuous chain of thought")