4 ms·

Yeah humans can be terrible. I am not sure what is the argument here. Does that make it ok to use software that can be just as terrible?

SpicyLemonZest 1y ago
Depends on the context. I've seen a lot of value from deploying LLMs in things like first-line customer support, where a suggestion that works 60% of the time is plenty valuable, especially if the bot can crank it out in 10 seconds when a human would take 5-10 minutes to get on the phone.
- namaria 1y ago
  I too have seen economic value be collected by terrible things that absolutely not exist in my opinion. Your example fits the bill. Profitability is not the absolute measure of what should exist.
  - SpicyLemonZest 1y ago
    I'm not sure what you're referring to, since profitability wasn't a metric I used. I agree not all profitable things should exist, but increasing the availability of customer support seems to me like a clearly good thing. Perhaps you're thinking that profit-chasing is the only reason companies don't offer good customer support today? That's not accurate. Providing enough smart, well-resourced human beings to answer every question your customers can come up with is a huge operational challenge, unless your product is absolutely dead simple or you're small enough to make random employees help in their spare time.
    - namaria 1y ago
      > I've seen a lot of value from deploying LLMs in things like first-line customer support, where a suggestion that works 60% of the time is plenty valuable Valuable to whom? How so? At that rate I would end my business with such a company. If you claim such a terrible level of costumer support is valuable, I question your judgement of value.
      - SpicyLemonZest 1y ago
        Valuable to customers, because it allows them to get instant advice that will often solve their problem. I strongly suspect that some companies you do business with have already integrated LLMs into their customer support workflow - it's very common these days.
        namaria 1y ago
        Hard disagree on instant suggestions with 40% miss rate being valuable. I want support not half backed guesses.

SpicyLemonZest 1y ago

Depends on the context. I've seen a lot of value from deploying LLMs in things like first-line customer support, where a suggestion that works 60% of the time is plenty valuable, especially if the bot can crank it out in 10 seconds when a human would take 5-10 minutes to get on the phone.

namaria 1y ago
I too have seen economic value be collected by terrible things that absolutely not exist in my opinion. Your example fits the bill. Profitability is not the absolute measure of what should exist.
- SpicyLemonZest 1y ago
  I'm not sure what you're referring to, since profitability wasn't a metric I used. I agree not all profitable things should exist, but increasing the availability of customer support seems to me like a clearly good thing. Perhaps you're thinking that profit-chasing is the only reason companies don't offer good customer support today? That's not accurate. Providing enough smart, well-resourced human beings to answer every question your customers can come up with is a huge operational challenge, unless your product is absolutely dead simple or you're small enough to make random employees help in their spare time.
  - namaria 1y ago
    > I've seen a lot of value from deploying LLMs in things like first-line customer support, where a suggestion that works 60% of the time is plenty valuable Valuable to whom? How so? At that rate I would end my business with such a company. If you claim such a terrible level of costumer support is valuable, I question your judgement of value.
    - SpicyLemonZest 1y ago
      Valuable to customers, because it allows them to get instant advice that will often solve their problem. I strongly suspect that some companies you do business with have already integrated LLMs into their customer support workflow - it's very common these days.
      - namaria 1y ago
        Hard disagree on instant suggestions with 40% miss rate being valuable. I want support not half backed guesses.