[I keep bringing these up on Bluesky, so I think it’s time to gather them up and make a post out of them.] This is a collection of articles on the problems of “AI.” “AI”—really, various sorts of generative machine learning models—including generative large language models (gLLMs) and generative stable diffusion models (gSDMs) so far do not live up to the promises of their marketers. A computer you can talk to is one of the great dreams of computing, and the initial releases of transformer-model based chatbots seemed to live up to this. There have been long-standing qualms about this idea, most notably Dijkstra’s argument that the imprecision of natural language was an impediment to correct thinking about computation and to accurate computing. 1 Unfortunately, so far it appears that Dijkstra was correct; gLLMs and gSDMs are notorious for errors and they are not currently designed to indicate uncertainty to their users so that people confidently rely on their erroneous output. There ar...
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