The language model does not need interaction with the environment when the
language model is already complete which is possible for formal languages
but nearly impossible for natural language. That is the reason why formal
language need much less cost.

If the language must be learned then things are completely different and you
are right that the interaction with the environment is necessary to learn L.

But in any case there is a complete distinction between D and L. The brain
never sends entities of D to its output region but it sends entities of L.
Therefore there must be a strict separation between language model and D.

- Matthias

>>>
Vladimir Nesov wrote

I think that this model is overly simplistic, overemphasizing an
artificial divide between domains within AI's cognition (L and D), and
externalizing communication domain from the core of AI. Both world
model and language model support interaction with environment, there
is no clear cognitive distinction between them. As a given,
interaction happens at the narrow I/O interface, and anything else is
a design decision for a specific AI (even invariability of I/O is, a
simplifying assumption that complicates semantics of time and more
radical self-improvement). Sufficiently flexible cognitive algorithm
should be able to integrate facts about any "domain", becoming able to
generate appropriate behavior in corresponding contexts.




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agi
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