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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