[lubujackson]

Bit by bit, we need to figure out how to rebuild human contextual understanding in a way that LLMs can understand. One thing that gets overlooked is the problem if incorrect data. You can provide all of the context in the world but LLMs tend to choke on contradictions or, at the minimum, work a whole lot harder to determine how to ignore or work around incorrect facts.

"Forgetting" and "ignoring" are hugely valuable skills when building context.

[zahlman]

> the problem if incorrect data.

Was the typo intentional? :)

[bonesss]

I can’t help but feel the logical conclusion to such context conundrums is that”what if we spoke Haskell to the LLM, and also the LLM could compile Haskell?”

And, yeah. Imagine if our concept-words were comprehensible, transmittable, exhaustively checked, and fully defined. Imagine if that type inference extended to computational execution and contradictions had to be formally expunged. Imagine if research showed it was more efficient way to have dialog with the LLM (it does, btw, so like learning Japanese to JRPG adherents should learn Haskell to LLM optimally). Imagine if multiple potential outcomes from operations (test fail, test succeeds), could be combined for proper handling in some kind of… I dunno, monad?

Imagine if we had magic wiki-copy chat-bots that could teach us better ways of formalizing and transmitting our taxonomies and ontologies… I bet, if everything worked out, we’d be able to write software one time, one place, that could be executed over and over forever without a subscription. Maybe.