@GaryMarcus
RT @ValerioCapraro: Here's the longer version of our Nature piece. Our argument is simple:Ā statistical approximation is not the same thingā¦
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"text": "Here's the longer version of our Nature piece.\n\nOur argument is simple:Ā statistical approximation is not the same thing as intelligence.\n\nStrong benchmark scores often say very little about how LLMs behave underĀ novelty, uncertainty, or shifting goals.\n\nEven more importantly,Ā similar behaviors can arise from fundamentally different processes. In another paper, we identifiedĀ seven epistemological fault linesĀ between humans and LLMs.\n\nFor example, LLMs have no internal representation of what is true. They often generateĀ confident contradictions, especially in longer interactions, because they do not track what is actually true.\n\nAnother example. Yes, LLMs have solved some open mathematical problems, but these cases typically involveĀ applying known methods to well-defined problems. LLMs cannot invent anything that is truly new and true at the same time, because they lack the epistemic machinery to determine what is true.\n\nNone of this means LLMs are useless. Quite the opposite: they are extraordinarily useful.\n\nBut we should be careful about what they are and what they are not.\n\nProducing plausible text is not the same as understanding.\nStatistical prediction is not the same as intelligence.\n\nSo despite the hype from the usual suspects,Ā AGI has not been achieved.\n\n*\npaper in the first reply\n\nJoint with @Walter4C and @GaryMarcus",
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