Tacking systems together with databases is not what I would call a human-brain analog or AGI.

Agreed, and either of those are more than a system with persistent memory.

I expect a plastic network with self modifying behavior in near real time along with the ability to expand at or arbitrarily alter any layer. It would also require a self test mechanism and bookmarking system to roll back any unstable or unexpected behavior using self generated tests.

I think it would be wise for such a system to have a rollback mechanism, but I don’t think it’s necessary for it to qualify as a human brain analog or AGI - I don’t have the ability to roll back my brain to the way it was yesterday, for example, and neither does anyone I’ve ever heard of.

self modifying behavior in near real time

I don’t think this is realistic or necessary, either. If I want to learn a new, non-trivial skill, I have to practice it, generally over a period of days or longer. I would expect the same from an AI.

Sleeping after practicing / studying often helps to learn a concept or skill. It seems to me that this is analogous to a re-training / fine-tuning process that isn’t necessarily part of the same system.

[An AGI] will not involve external code.

It’s unclear to me why you say this. External, traditional code is necessary to link multiple AI systems together, like a supervisor and a chatbot model, right? (Maybe I’m missing how this is different from invoking a language from within the LLM itself - I’m not familiar with Forth, after all.) And given that human neurology is basically comprised of multiple “systems” - left brain, right brain, frontal node, our five senses, etc. - why wouldn’t we expect the same to be true for more sophisticated AIs? I personally expect there to be breakthroughs if and when an AI that is trained on multi-modal data (sight + sound + touch + smell + taste + feedback from your body + anything else of relevance) is built (e.g., by wiring up people with sensors to pull down that data), and I believe that models capable of interacting with that kind of training data would comprise multiple systems.

At minimum you currently need an external system wrapped around the LLM to emulate “thinking,” which my understanding is something ChatGPT already does (or did) to an extent. I think this is currently just a “check your work” kind of loop but a more sophisticated supervisor / AI consciousness could be much more capable.

That said, I would expect an AGI to be able to leverage databases in the course of its work, much the same way that Bing can surf the web now or ChatGPT can integrate with Wolfram — separate from its own ability to remember, learn, and evolve.