Martin,
I agree that accuracy is low. However, the ability to reason with AI is good. 
It can be persuaded it is wrong and go and re-examine the question and its 
sources. It can state what its sources are, and can produce other suggestions. 
It's a bit like have a colleague to discuss the subject with; except this 
colleague has all the references to hand immediately.

Lennie

-----Original Message-----
From: IBM Mainframe Discussion List <IBM-MAIN@LISTSERV.UA.EDU> On Behalf Of 
Martin Packer
Sent: 26 May 2025 09:49
To: IBM-MAIN@LISTSERV.UA.EDU
Subject: Re: RTFM

Periodically I test Generative AI with stuff I darned well know about. I'm 
still unimpressed.

Oh well, accuracy seems to be deprecated  in favour of expedience.

Cheers, Martin

From: IBM Mainframe Discussion List <IBM-MAIN@LISTSERV.UA.EDU> on behalf of 
Andrew Rowley <0000070d6809bfe9-dmarc-requ...@listserv.ua.edu>
Date: Sunday, 25 May 2025 at 23:56
To: IBM-MAIN@LISTSERV.UA.EDU <IBM-MAIN@LISTSERV.UA.EDU>
Subject: [EXTERNAL] Re: RTFM
On 26/05/2025 3:31 am, Lennie Bradshaw wrote:
> I have found AI to be really useful in negotiating the wealth of IBM 
> documentation. I can ask AI a question that is pretty detailed and get a 
> meaningful response. It is not always right, but I can then discuss it and 
> refine it with the AI and find the correct answer.

My attempts to use AI for mainframe related stuff have yielded 100% wrong 
answers. Some have been quite convincing and taken some research to find it's 
wrong, but still 100% wrong.

Non-mainframe stuff I would say the rate is about 50%.

If there's a lot of examples of something out there it maybe generates a good 
result. But there's no actual intelligence in AI. What worries me most is what 
happens when knowledge changes, e.g. if a new feature is developed that makes 
old information obsolete. How does that get incorporated in the AI model? Where 
does the training data come from, and how does the model verify the reliability?

--
Andrew Rowley
Black Hill Software

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