I really hope people are starting to catch on, large language models aren’t “intelligent”, they’re multidimensional maps of human language use and querying them is just tracing a vector “forward” through language-space from the starting point of a prompt.

It’s the reification fallacy writ so large it’s eclipsing entire national economies. Human intelligence isn’t in language, language is a product of human intelligence. The map is not the territory.

And yeah, it is pretty cool that we have the processing power to map out language-space well enough to draw some vectors that remain coherent over thousands of tokens, but using a billion-parameter model to do what could be accomplished with probably-already-existing management software and a few seconds of CPU time per week is as wasteful as it is misguided.

Totally unnecessary. A simple price/demand curve can easily be written in a few lines of code.

My new baseless theory: We know that AI is trained on tons of novels and fictional stories. Is it possible that because all novels have significant conflicts and drama, and stories where some person just boringly does his boring job forever aren’t exactly bestsellers, the AI is maybe trying to inject drama even when it makes no sense, since it’s been conditioned that way through the training data? So it’s seeing these inconsequential issues and since every novel it’s ever “read” turns them into massive conflicts, it’s trying to follow suit?