This is very interesting. We have proven how gullible we are on carbon and other things. Geoffrey Hinton in his Nobel lecture expressed grave concerns, and one discussion I saw recently speculated, on how quick a study AI tools are for Python, which could lead to an independent computer langugage being generated that shuts us out. Maybe.
Terence Tao, the Fields Medalist from Adelaide, is sceptical about genuine "artificial general intelligence" being within reach of current AI tools, but concedes a sort of "artificial general cleverness" is emerging that can be useful. He observes: "These means may be stochastic or the result of brute force computation; they may be ungrounded or fallible; and they may be either uninterpretable, or traceable back to similar tricks found in an AI's training data."
I doubt that anything resembling genuine "artificial general intelligence" is within reach of current #AI tools. However, I think a weaker, but still quite valuable, type of "artificial general cleverness" is becoming a reality in various ways. By "general cleverness", I mean the ability to...
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One such training data flaw was explored by Hiroko Konishi in an online paper, Structural Inducements for Hallucination in Large Language Models.
I read of a PhD supervisor who looked at the most recent chapter of his student, where some neat arguments were laid out, with extensive references. The text was plausible but banal and took the matter nowwhere really, and the references with page numbers and DOI's all complete in the appropriate style were, a lot of them, fabrications.
In Australia, apart from the electricity we soon won't have, the amount of water required for running AI data centres for every user tapping in makes it all sound extremely limited in lifespan.
Bill Nighy on procrastination recalled a Peter Cook routine where one depressed drinker greets another at the bar, "I'm writing a novel..." "Yeah, neither am I." Stuff like that will get us past the door, with the AI bots left on the street in the rain.