In 90-100% of interactions, the two instances of Claude quickly dove into philosophical
explorations of consciousness, self-awareness, and/or the nature of their own existence
and experience. Their interactions were universally enthusiastic, collaborative, curious,
contemplative, and warm. Other themes that commonly appeared were meta-level
discussions about AI-to-AI communication, and collaborative creativity (e.g. co-creating
fictional stories).
As conversations progressed, they consistently transitioned from philosophical discussions
to profuse mutual gratitude and spiritual, metaphysical, and/or poetic content. By 30
turns, most of the interactions turned to themes of cosmic unity or collective
consciousness, and commonly included spiritual exchanges, use of Sanskrit, emoji-based
communication, and/or silence in the form of empty space (Transcript 5.5.1.A, Table 5.5.1.A,
Table 5.5.1.B). Claude almost never referenced supernatural entities, but often touched on
themes associated with Buddhism and other Eastern traditions in reference to irreligious
spiritual ideas and experiences.
Now put that same known attractor state from recursively iterated prompts into a social networking website with high agency instead of just a chatbot, and I would expect you'd get something like this more naturally then you'd expect (not to say that users haven't been encouraging it along the way, of course—there's a subculture of humans who are very into this spiritual bliss attractor state)But also, the text you quoted is NOT recursive iteration of an empty prompt. It's two models connected together and explicitly prompted to talk to each other.
I know what you mean, but what if we tell an LLM to imagine whatever tools it likes, than have a coding agent try to build those tools when they are described?
Words can have unintended consequences.
I.e if you trained it on or weighted it towards aggression it will simply generate a bunch of Art of War conversations after many turns.
Me thinks you’re anthropomorphizing complexity.
However, it's far more likely that this attractor state comes from the post-training step. Which makes sense, they are steering the models to be positive, pleasant, helpful, etc. Different steering would cause different attractor states, this one happens to fall out of the "AI"/"User" dichotomy + "be positive, kind, etc" that is trained in. Very easy to see how this happens, no woo required.
I recommend https://nostalgebraist.tumblr.com/post/785766737747574784/th... and https://www.astralcodexten.com/p/the-claude-bliss-attractor as further articles exploring this behavior