One major problem with the current generation of "AI"seems to be it’s inability to use relevant information that it already has to assess the accuracy of the answers it provides.
Here’s a common scenario I’ve run into:
I’m trying to create a complex DAX Measure in Excel. I give ChatGPT the information about the tables I’m working with and the expected Pivot Table column value.
ChatGPT gives me a response in the form of a measure I can use. Except it uses one DAX function in a way that will not work. I point out the error and ChatGPT is like, "Oh, sorry. Yeah that won’t work because [insert correct reason here].
I’ll try adjusting my prompt a few more times before finally giving up and just writing the measure myself.
It does not have the ability to reason that an answer is incorrect even though it has all the information to know that the answer is incorrect and can even tell you why the answer is incorrect. It’s a glorified text generator and is definitely not “intelligent”.
It works fine for generating boiler plate code but that problem was already solved years ago with things like code templates.
I think a part of it is the scale of the data used to train it means there wasn’t likely much curation of that data. So it might complete the text using a wikipedia article, a knowledge forum post, a forum post that derailed the original topic, a forum post written by someone confidently wrong, a troll post, or two people arguing about the answer. In that last case, you might be able to get it to hash out the entire argument by asking if it’s sure about that after each response.
Which is also probably how it can correctly respond to “are you sure?” follow ups in the first place, because it was going off some forum post that someone questioned and then there was a follow-up.
It’s more complicated than that because it’s likely not just rehashing any one single conversation in any response, but all of those were a part of its training, and its training is all it knows.
One major problem with the current generation of "AI"seems to be it’s inability to use relevant information that it already has to assess the accuracy of the answers it provides.
Here’s a common scenario I’ve run into: I’m trying to create a complex DAX Measure in Excel. I give ChatGPT the information about the tables I’m working with and the expected Pivot Table column value.
ChatGPT gives me a response in the form of a measure I can use. Except it uses one DAX function in a way that will not work. I point out the error and ChatGPT is like, "Oh, sorry. Yeah that won’t work because [insert correct reason here].
I’ll try adjusting my prompt a few more times before finally giving up and just writing the measure myself. It does not have the ability to reason that an answer is incorrect even though it has all the information to know that the answer is incorrect and can even tell you why the answer is incorrect. It’s a glorified text generator and is definitely not “intelligent”.
It works fine for generating boiler plate code but that problem was already solved years ago with things like code templates.
I think a part of it is the scale of the data used to train it means there wasn’t likely much curation of that data. So it might complete the text using a wikipedia article, a knowledge forum post, a forum post that derailed the original topic, a forum post written by someone confidently wrong, a troll post, or two people arguing about the answer. In that last case, you might be able to get it to hash out the entire argument by asking if it’s sure about that after each response.
Which is also probably how it can correctly respond to “are you sure?” follow ups in the first place, because it was going off some forum post that someone questioned and then there was a follow-up.
It’s more complicated than that because it’s likely not just rehashing any one single conversation in any response, but all of those were a part of its training, and its training is all it knows.