I might be mistaken but I have the feeling you are not getting the point of this article. Your example is about identifying "facts" in a network. While very interesting is not what strikes me as the main point. The raw ability to state things about NNs is indeed an existing field, but...
The fact you can give an LLM a raw dump of neural weights and it will hand-wire a bunch of changes on the fly is quite something. It's not so much about the OMG! RSI! for me personally, it's more about the fact we are dealing with a system that reasons successfully over a raw bulk of extraordinarily opaque data without breaking a sweat. That ability is alien and we need time to adjust to that.
The fact you can give an LLM a raw dump of neural weights and it will hand-wire a bunch of changes on the fly is quite something. It's not so much about the OMG! RSI! for me personally, it's more about the fact we are dealing with a system that reasons successfully over a raw bulk of extraordinarily opaque data without breaking a sweat. That ability is alien and we need time to adjust to that.