“Those systems generate text that sounds fine, grammatically, semantically, but they don’t really have some sort of objective other than just satisfying statistical consistency with the prompt.” “Large language models have no idea of the underlying reality that language describes,” he said, adding that most human knowledge is nonlinguistic. LeCun believes there is a fundamental flaw that leads to hallucinations. The article cites Yann LeCun, a pioneer in deep learning and a winner of the Turing Award. But you can’t trust advice from a machine prone to hallucinations.” The article also contradicts Bill Gates, who has “mused that ChatGPT or similar large language models could some day provide medical advice to people without access to doctors. A ChatGPT-written book report or historical essay may be a breeze to read but could easily contain erroneous “facts” that the student was too lazy to root out.” The article says that “High school teachers are learning the same. The article argues that these hallucinations are why experienced programmers still need to review the output from OpenAI’s Codex or Github’s Copilot, approving, correcting, or rejecting it before allowing it to slip into a code base where it might wreak havoc. When the IEEE says “hallucinations could blunt ChatGPT’s success,” we should listen because the Institute of Electrical and Electronic Engineers is the “world's largest technical professional organization dedicated to advancing #technology for the benefit of humanity.”
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