The example I saw them use was turning one line text reviews into a simple positive or negative so you can count them.
So it could be useful for things like that, even if we ignore the “then why not just ask for the star rating” that probably went along with that review…
MS is now an AI company that sells to excited bosses who would love to fire somebody somewhere to save a few bucks.
In the short term, people who rushed into AI are finding out that a 1 in 100 error rate is absurdly high when literally every action is done through an LLM.
Ah, sorry, I though you were disagreeing with me by posting a link that companies are unsuccessful with it, so I was confused - because my point was that error rate is gigantic. My bad!
I used to work for Comcast as a mobile app developer. We used to get uncountable numbers of reviews along the lines of “I gave this app one star because you can’t give an app zero stars”. Honestly depressing even though I wasn’t personally responsible for the apps or the company.
To be fair, MS says you shouldn’t use it for caculations.
“Why is it there then?” No clue.
The example I saw them use was turning one line text reviews into a simple positive or negative so you can count them.
So it could be useful for things like that, even if we ignore the “then why not just ask for the star rating” that probably went along with that review…
MS is now an AI company that sells to excited bosses who would love to fire somebody somewhere to save a few bucks.
“… to save a few bucks.”
In the short term, people who rushed into AI are finding out that a 1 in 100 error rate is absurdly high when literally every action is done through an LLM.
No third-party research ever arrived at such absurdly low number as 1% error rate.
Internal OpenAi research from May 2025 said 50% error rate and growing.
This is a headline from a few weeks ago
I’m not sure what you’re trying to say here?
Just giving evidence that companies are bailing from AI, fuel for the fire so to speak
Ah, sorry, I though you were disagreeing with me by posting a link that companies are unsuccessful with it, so I was confused - because my point was that error rate is gigantic. My bad!
At the same time, that sounds like something you’d just use old-fashioned sentiment analysis for.
It’s less accurate, but also far less demanding, and doesn’t risk hallucinating.
I might be mistaken, but don’t these two lines mean the exact opposite in this context?
Is AI more often right, or more often wrong?
Both, because the way it’s right and wrong are different.
Sentiment analysis might misclassify some of the data, but it doesn’t risk making things up wholescale like an LLM would.
I used to work for Comcast as a mobile app developer. We used to get uncountable numbers of reviews along the lines of “I gave this app one star because you can’t give an app zero stars”. Honestly depressing even though I wasn’t personally responsible for the apps or the company.
Do you think someone dumb enough to cause problems with this is smart enough to read the warning?
There’s different kinds of smartness and dumbness and they are not always toggled on.
Sounds like it’s made to replace C-suits
you should use it write a beautiful poem! That’s what calculators are for!
That is only there to cover their asses not to actually be informative