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by drweevil
454 days ago
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So far the AI use cases that have succeeded are those where that accuracy requirement is not stringent. Image generation and coding assistants, e.g. Cursor, Copilot, and similar, are the only ones that come readily to mind. In the case of images, you are generating them and evaluating the results. There is not usually a factual requirement. For code assistance, the programmer fortunately has a fact-checker at hand: the compilers, interpreters, language-servers. So any mistake is usually fact checked early, before real damage is done. (Security is another can of worms though.) The other side of that coin are the use cases where inaccuracies are not easily tolerated. Legal documents, transcripts, translations, summaries, reporting the news, medical diagnosis, and such. In fact some of the most memorable flops have happened in those domains. The specific example of translation is a fuzzy one, since indeed it is nice to get the gist of a news story written in, say, German. But if you are translating a legal document or a critical piece of intelligence, LLMs are simply not good enough. I don't believe that most people have any real need for something that isn't 100% accurate. I can just ask a buddy if I merely wish for an opinion ;) |
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Or where accuracy does matter and ML-based tools are the most accurate of the available options. Material/product defect detection, weather forecasting/early warning systems, OCR, spam filtering, protein folding, medical segmentation, interaction prediction, etc.
> The other side of that coin are the use cases where inaccuracies are not easily tolerated. Legal documents, transcripts, translations, summaries, reporting the news, medical diagnosis, and such. In fact some of the most memorable flops have happened in those domains.
Translation (like Google Translate) and transcription (like Whisper) are huge and successful uses of transformers. Albeit, not necessarily because they're more accurate than a human (though they sometimes are) but because there's generally some point, varying by scenario, at which their increased speed/cost/accessibility outweighs disparity in accuracy.
> I don't believe that most people have any real need for something that isn't 100% accurate. I can just ask a buddy if I merely wish for an opinion ;)
Is a 99% accurate weather forecast, one which is better than available alternates, useless? Is anything 100% accurate?