As machine learning pioneer @tdietterich says in his 'What's wrong with LLMs and what we should be building', there is a need to separate linguistics skill from world knowledge. Like the difference between dictionaries versus encyclopedias.

Emulating the brain, as was the original goal of AI from 1956, we want machines to quickly learn our language as their 'interface' that enables continual on-the-fly learning like humans have.

@jbthinking 's Patom Theory is a a theory of how the brain works. It's effectively teaching machines our language so we can control them. This same structure of language when used to store information like PubMed or enterprise data is then accessible infinitely with conversation in a trustworthy language interface.