Earlier quoted context omitted.
> Turns out that all those execs who've decided to incorporate AI into their product strategy have already tried it out and ensured that it will actually work. The 2-4-6 game comes to mind. They may well have verified the AI will work, but it's hard to learn the skill of thinking about how to falsify a belief.
You mean this one here? - https://mathforlove.com/lesson/2-4-6-puzzle/ Looking at the example patterns given: MATCH 2, 4, 6 8, 10, 12 12, 14, 16 20, 40, 60 NOT MATCH 10, 8, 6 If the answer is "numbers in ascending order", then this is a perfect illustration of synthetic vs. realistic examples. The numbers indeed fit that rule, so in theory , everything is fine. In practice , you'd be an ass to give such examples on a…
I'd say that every black swan is an example of a real process that is misleading.
But more than that, I mentioned verified/falsified, as in the difference between the two in science. We got a long way with just the first (Karl Popper only died in 1994), but it does seem to make a difference?