A similar type of machine learning (neural networks, transformer model type thing), but I assume one is built and trained explicitly on medical records instead of scraping the internet for whatever. Correct me if I am wrong!
@YourMomsTrashman A purpose-designed system might have the same underlying POTENTIAL for garbage output, IF you train it inappropriately. But it would be trained on a discretely selected range of content both relevant to its purpose, and carefully vetted to ensure it’s accurate (or at least believed to be).
A cancer-recognizing system, for example, would be trained on known examples of cancer, and ONLY that.
@YourMomsTrashman I’m no expert, but my sense is that you’re probably correct. This seems to me a version of the long-understood GIGO principle in computing (Garbage In, Garbage Out), also a principle in nearly all forensics of any kind. Your output can only be as good as your input.
Most of our general-use ‘AI’ (scorn quotes intentional) has been trained on an essentially random corpus of any and all content available, including a lot of garbage.
A similar type of machine learning (neural networks, transformer model type thing), but I assume one is built and trained explicitly on medical records instead of scraping the internet for whatever. Correct me if I am wrong!
@YourMomsTrashman A purpose-designed system might have the same underlying POTENTIAL for garbage output, IF you train it inappropriately. But it would be trained on a discretely selected range of content both relevant to its purpose, and carefully vetted to ensure it’s accurate (or at least believed to be).
A cancer-recognizing system, for example, would be trained on known examples of cancer, and ONLY that.
@YourMomsTrashman I’m no expert, but my sense is that you’re probably correct. This seems to me a version of the long-understood GIGO principle in computing (Garbage In, Garbage Out), also a principle in nearly all forensics of any kind. Your output can only be as good as your input.
Most of our general-use ‘AI’ (scorn quotes intentional) has been trained on an essentially random corpus of any and all content available, including a lot of garbage.
A purpose-designed system would not be.