when i say the output of my ml, i mean, i give the prediction and confidence score. for instance, if there's a process that has a high probability of being late based on the inputs, I'll say it'll be late, with the confidence. that's completely different from feeding the figures into a gpt and saying whatever the llm will say.

and when i say "ml" i mean a model I trained on specific data to do a very specific thing. there's no prompting, and no chatlike output. it's not a language model