• halcyoncmdr@lemmy.world
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    2 months ago

    You know guys, I’m starting to think what we heard about Altman when he was removed a while ago might actually have been real.

    /s

  • N0body@lemmy.dbzer0.com
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    2 months ago

    There’s an alternate timeline where the non-profit side of the company won, Altman the Conman was booted and exposed, and OpenAI kept developing machine learning in a way that actually benefits actual use cases.

    Cancer screenings approved by a doctor could be accurate enough to save so many lives and so much suffering through early detection.

    Instead, Altman turned a promising technology into a meme stock with a product released too early to ever fix properly.

      • mustbe3to20signs@feddit.org
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        2 months ago

        AI models can outmatch most oncologists and radiologists in recognition of early tumor stages in MRI and CT scans.
        Further developing this strength could lead to earlier diagnosis with less-invasive methods saving not only countless live and prolonging the remaining quality life time for the individual but also save a shit ton of money.

        • msage@programming.dev
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          2 months ago

          Wasn’t it proven that AI was having amazing results, because it noticed the cancer screens had doctors signature at the bottom? Or did they make another run with signatures hidden?

          • mustbe3to20signs@feddit.org
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            2 months ago

            There were more than one system proven to “cheat” through biased training materials. One model used to tell duck and chicken apart because it was trained with pictures of ducks in the water and chicken on a sandy ground, if I remember correctly.
            Since multiple medical image recognition systems are in development, I can’t imagine they’re all this faulty trained with unsuitable materials.

            • msage@programming.dev
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              2 months ago

              They are not ‘faulty’, they have been fed wrong training data.

              This is the most important aspect of any AI - it’s only as good as the training dataset is. If you don’t know the dataset, you know nothing about the AI.

              That’s why every claim of ‘super efficient AI’ need to be investigated deeper. But that goes against line-goes-up principle. So don’t expect that to happen a lot.