| > how Yes, it's what thinkers do :) Statements come from their own processing. > LMs I am afraid the term 'Language Model' does not fit the category; 'Statistical Language Model' is required to define (after interpretation) what they do. Not all Language Models need to be based on relational frequencies of term occurrence. (Hopefully, some will be even based on mechanisms of Intelligence - the opposite.) > «the theory and development [...]» If you wanted to quote John McCarthy (project proposal for the Dartmouth summer seminar, 1955), the actual words were «An attempt will be made to find how to make machines use language, form abstractions and concepts, solve kinds of problems now reserved for humans, and improve themselves». I reckon the letter of what you quoted seems to be a "merriamwebsterism" - inherently with limited authority, because dictionaries typically express use, not meaning. > qualify The output of text must be an intelligent composition to fit into the context of a «task» that «require[s] human intelligence», as per the definition you proposed - because you do not need «human intelligence» to delirate (as in, outputting text not filtered by intelligence). > minority If that ever were an indicator, it would suggest the possibility of a promising stance, given that in Paretian distributions (what you actually find outside of selected groups) the function of the majority is poor. |
You're proving that thinking and knowing are wholly uncorrelated.
> Not all Language Models need to be based on relational frequencies of term occurrence.
"A language model is a probability distribution over sequences of words"
If you don't even know what an LM is, I don't feel like reading the rest of this.