Earlier quoted context omitted.
> I must stress that the idea of "Science predicting facts" is a consolidated formula in Philosophy of Science. Respectfully, I'd suggest that you are misinterpreting it or using the wrong terminology. Science is not a thing, it is a process: A hypothesis is a prediction about the world, which is validated or disproven via experiment. A validated hypothesis -- like Newton's physics -- is a model for how the world wor…
> Respectfully I have titles in the discipline. I know and I am supposed to know what you wrote there well. What I was telling you is that the use of 'predict' for the nature of Science is well established; of course it is a rhetoric simplification - but language in use is. Please see (I had to return to it a few weeks ago for another discussion) the article about Imre Lakatos in the Stanford Encyclopedia of Philosop…
You raise interesting points.
I'd propose a wager, but I'm not sure what the terms ought to be.
In general, I think that procedural thinking is a problem that is basically already cracked, and that all (or nearly all) hard problems that the 99.5th percentile human can solve, in any given domain, will be soluble by artificial intelligences in the near enough future. Five years, I think, would be a wild over-estimate. Maybe two?
I also think that, as a general rule, "prediction = intelligence" and that the breadth, accuracy, and extensibility of one's predictive capabilities is essentially correlated with just how intelligent one is. It doesn't matter how it happens; it can be a black box. Humans, to be sure, are black boxes. I think that scientists have been trying to simulate the nematode c.elegans brain for about two decades, and as far as I know they still haven't succeeded, despite it only having 900 neurons.