Jamesian Philosophy Refreshed

People are looking for "tells".  What is a quick way to tell when I am reading AI slop, rather than something some real human has composed?  One of the better tells is the frequent use of the adverb "quietly" in metaphorical contexts. LLMs have received a level of publicity out of proportion to their role within the AI world (see the above Venn diagram) in part because they impact and indeed may threaten the livelihood of people like me. So we, because loquacious folk, talk about it. LLMs, large language models, have quietly developed the tick of using the word "quietly" a lot. You may recently have read about how a certain individual has "quietly" become important in deliberations of Congress, or how Stephen King has "quietly" amassed some large number of acreage of Maine real estate, or some whatever. "Quietly" does a lot of work for these models. It sounds as if it is saying something about something conspiratorial or trick...

In recent discussions of artificial intelligence, the idea of "large language models" has become closely associated with that of AI itself.  A "large language model" is an algorithm that is fed, as a training set of data, a huge array of human-generated writing, generally internet available, that includes relevant problems (the questions that users might ask it) as well as their solutions.  Anyway, in a new paper computer scientists challenge how intelligent this sort of artificial intelligence is. The paper is called "The Wall confronting large language models" and it is the work of Peter Coveney and Sauro Succi.  The idea is that LLMs aren't some wave of the future, about to be scaled up in ways that will put people like me out of work. Rather, LLMs are hitting a wall at their current level of application. (Whew.)  LLMs, they say, are built o n stochastic, non-Gaussian architectures that make them prone to error accumulation.  The models can be rewor...