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JimmyRuska | 1 year ago

Pretty amusing the old AI revolution was pure logic/reasoning/inference based. People knew to be a believable AI the system needed some level of believable reasoning and logic capabilities, but nobody wanted to decompose a business problem into disjunctive logic statements, and any additional logic can have implications across the whole universe of other logic making it hard to predict and maintain.

LLMs brought this new revolution where it's not immediately obvious you're chatting with a machine, but, just like most humans, they still severely lack the ability to decompose unstructured data into logic statements and prove anything out. It would be amazing if they could write some datalog or prolog to approximate more complex neural-network-based understanding of some problem, as logic based systems are more explainable

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LunaSea|1 year ago

One of the reasons for why word vectors, sentence embeddings and LLMs won (for now) is that text found on the web especially, does not necessarily follow strict grammar and lexical rules.

Sentences that are incorrect but still understandable.

If you then include leet speak, acronyms, short form writing (SMS / Tweets), it quickly becomes unmanageable.

puzzledobserver|1 year ago

I am not a linguist, but I don't think that many linguists would agree with your assessment that dialects, leet speak, short form writing, slang, creoles, or vernaculars are necessarily ungrammatical.

From what I understand, the modern understanding is that these point to the failure of grammar as a prescriptive exercise ("This is how thou shalt speak"). Human speech is too complex for simple grammar rules to fully capture its variety. Strict grammar and lexical rules were always fantasies of the grammar teacher anyway.

See, for example, the following article on double negatives and African American Vernacular English: https://daily.jstor.org/black-english-matters/.

agumonkey|1 year ago

I wonder if people approach NLP as a sea of semes rather than a semi-rigid grammatical structures to then be affected with meaning. (probably but I'm not monitoring these field)