Mind Matters Natural and Artificial Intelligence News and Analysis

TagGPT-3 (Gary Smith's tests)

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Chat bot and future marketing concept , Chatbot icon , Hand holding mobile phone with automatic chatbot message screen with abstract background

Let’s Call AI What It Really Is: Faux Intelligence

Gary Smith at Salon: While GPT-3 can string words together in convincing ways, it has no idea what the words mean

Pomona College business and investments prof Gary Smith warns Salon readers not to be too gullible about what human-sounding chatbots really amount to. He notes that in the 1960s, a pioneer chatbot called ELIZA convinced many psychiatric patients that they were interacting with a real psychiatrist. The machine simply repeated back their statements as questions, a popular psychiatric technique at the time because it generated more and more discussion — from the patient. The patients’ belief that they were interacting with a human being came to be called the Eliza effect. Has much changed? If you play around with GPT-3 (and I encourage you to do so) your initial response is likely to be astonishment — a full-blown Eliza effect. Read More ›

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Chatbots: Still Dumb After All These Years

Intelligence is more than statistically appropriate responses

This story, by Pomona College business and investment prof Gary Smith was #6 in 2022 at Mind Matters News in terms of reader numbers. As we approach the New Year, we are rerunning the top ten Mind Matters News stories of 2022, based on reader interest. At any rate: “Chatbots: Still dumb after all these years.” (January 3, 2022) In 1970, Marvin Minsky, recipient of the Turing Award (“the Nobel Prize of Computing”), predicted that within “three to eight years we will have a machine with the general intelligence of an average human being.”  Fifty-two years later, we’re still waiting. The fundamental roadblock is that, although computer algorithms are really, really good at identifying statistical patterns, they have no way of Read More ›

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Concept creative idea and innovation. Hand picked wooden cube block with head human symbol and light bulb icon

Computer Prof: We Can’t Give Machines Understanding of the World

Not now, anyway. Melanie Mitchell of the Santa Fe Institute finds that ever larger computers are learning to sound more sophisticated but have no intrinsic knowledge

Last December, computer science prof Melanie Mitchell, author of Artificial Intelligence: A Guide for Thinking Humans (2019), let us in on a little-publicized fact: Despite the greatly increased capacity of the vast new neural networks. they are not closer to actually understanding what they read: The crux of the problem, in my view, is that understanding language requires understanding the world, and a machine exposed only to language cannot gain such an understanding. Consider what it means to understand “The sports car passed the mail truck because it was going slower.” You need to know what sports cars and mail trucks are, that cars can “pass” one another, and, at an even more basic level, that vehicles are objects that Read More ›