• SoulWager@lemmy.ml
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    2 days ago

    It’s not necessary to improve the quality to make this happen, only to train it to work with that company’s products and issues, and integrate it into whatever other systems that may be needed. Just need enough call logs for training data, and that’s already something that’s collected.

    • Umbrias@beehaw.org
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      2 days ago

      except current robot systems and people are likely cheaper, especially when you consider companies are liable for what llm say. which leaves, essentially, scams and other slop, as the last remaining use cases. multi trillion dollar business without a use case.

      • SoulWager@lemmy.ml
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        2 days ago

        The money saved on wages would cover a LOT of liability. And most people that have a case don’t pursue it anyway.

        • Umbrias@beehaw.org
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          2 days ago

          what money saved on wages?? it’s competing with a dollar a day laborers. $10 per 1 million tokens, for the “bad” (they all suck) models (something that cant even do this job!). if you can pretend the hallucinations dont matter, you are getting a phone call for (4 letters per token, 6 minute avg support call, 135 wpm talking rate let’s say 120 to be nice -> 720 tokens per call) = $0.0072 per call. the average call center employee handles around 40 calls a day, so hey, the bad cant-actually-do-it chatgpt 4 is 70 cents per day cheaper than your typical call center indian!

          Except. that is the massively subsidized money hemorrhaging rate. We know that oai should be charging probably an oom or two more. and the newer models are vastly more expensive, o1 takes around 100x the compute, and still couldnt be a call center employee. so that price is actually at least $30 per day. Cheaper than a us employee, but still cant actually do the job anyway.