A.I.’s un-learning problem: Researchers say it’s virtually impossible to make an A.I. model ‘forget’ the things it learns from private user data

That’s how LLMs work.

This is not how LLMs work. LLMs do not have complex thought webs correlating concepts birds, flightlessness, extinction, food, and so on. That is how humans work.

An LLM assembles a mathematical model of what word should follow any other word by analyzing terabytes of data. If in its training corpus the nearest word to "dodo" is "attractive," the LLM will almost always tell you that dodos are attractive. This is not because those concepts are actually related to the LLM, because the LLM is attracted to dodos, or because LLMs have any thoughts at all. It is simply the output of bunch of math based on word proximity.

Humans have cognition and mental models. LLMs have frequency and word weights. While you have correctly identified that both of these things can be portrayed as n-dimensional matrixes, you can also use those tools to describe electrical currents or the movement of stars. But those things contain no more thought and have no more mental phenomenon occurring in them than LLMs.