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Today's Large Language Models are Essentially BS Machines (quandyfactory.com)
submitted 3 years ago by to c/technology@beehaw.org
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[–] 1 point 3 years ago (1 child)

Yes, it's been my career for the last two decades and before that was the focus of my education. The idea that "correctness is a coincidence" is absurd and either fails to understand how training works or rejects the entire premise of large data revealing functional relationships in the underlying processes.

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  • [–] [S] 1 point 3 years ago

    Or you've simply misunderstood what I've said despite your two decades of experience and education.

    If you train a model on a bad dataset, will it give you correct data?

    If you ask a question a model it doesn't have enough data to be confident about an answer, will it still confidently give you a correct answer?

    And, more importantly, is it trained to offer CORRECT data, or is it trained to return words regardless of whether or not that data is correct?

    I mean, it's like you haven't even thought about this.

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