"On two occasions I have been asked, 'Pray, Mr. Babbage, if you put into the machine wrong figures, will the right answers come out?' I am not able rightly to apprehend the kind of confusion of ideas that could provoke such a question."
So the result might not necessarily be bad, it's just that the machine _can_ detect that you entered the wrong figures! By the way, the answer is 7.
> Can you please give an example of a “completely illogical statement” produced by o1 model? I suspect it would be easier to get an average human to produce an illogical statement.
Following the trail as you did originally: you do not hire "ordinary humans", you hire "good ones for the job"; going for a "cost competitive" bargain can be suicidal in private enterprise and criminal in public ones.
Sticking instead to the core matter: the architecture is faulty, unsatisfactory by design, and must be fixed. We are playing with the partials of research and getting some results, even some useful tools, but the idea that this is not the real thing must be clear - also since this two years plus old boom brought another horribly ugly cultural degradation ("spitting out prejudice as normal").
> For simple tasks where we would alternatively hire only ordinary humans AIs have similar error rates.
Yes if a task requires deep expertise or great care the AI is a bad choice. But lots of tasks don't. And in those kinds of tasks even ordinary humans are already too expensive to be economically viable
Do you have good examples of tasks in which dubious verbal prompt could be an acceptable outcome?
By the way, I noticed:
> AI
Do not confuse LLMs with general AI. Notably, general AI was also implemented in system where critical failures would be intolerable - i.e., made to be reliable, or part of a finally reliable process.
So the result might not necessarily be bad, it's just that the machine _can_ detect that you entered the wrong figures! By the way, the answer is 7.