Some of them allow you to choose, I don't think many distros have the openbsd-netcat installed as default choice though.
I run Manjaro on my laptop and we have gnu-netcat as default with the choice of installing openbsd-netcat instead. On my Debian servers I have just "nc" which, if I'm not wrong, is the standard netcat (non-gnu/non-bsd).
Lots of network devices will not have nc, wget, curl, etc. Which makes exploiting cmd injection annoying, you often have to drop a bin in chunks using hex-formatted echo.
I think there's a strong argument to be made that the answer to this question depends on exactly what you mean by "reason" and "predict".
If you mean "predict" in the same sense as it's used in the phrase "predictive model", then the answer could be a resounding no - there's a hypothesis that the brain implements just one basic learning algorithm, and everything else is just emergent phenomena coming out of that.
I think there is a difference, but my view is that it is impossible to reason without sufficiently accurate prediction, and that the concepts we use for reasoning are largely formed based on how predictive they are. Consider playing a game where two players throw dice, and the one with the larger number wins. There is no predictability between turns, so there is no point in reasoning far into the future, unlike in chess, where the positions change slowly, one piece per turn and in predictable patterns. In chess you still don't know what the other player will do, but you can reason about it, because there is a level of predictability.
I would define reasoning as answering a question or optimization problem, e.g. What is my best move? What is a good move? This can be formalized as calculating some kind of score for a possible action, whereas prediction is just about assigning a probability value to an event.
Bad example. I can predict the dice game's problem space. E.g. for a single normal die (1-6), I can predict that I'll never observe a 7 [P(7) = 0%]. I can also predict the probability distribution. E.g. for two dice thrown together, the probability of throwing a sum of 7 is 1/6, whereas the probability of throwing snake eyes is only 1/36. Yes, the game's output is random. But what you're talking about is control, not prediction. If random meant "impossible to make predictions about", then statistics wouldn't exist.
Regarding winning, there's no way to improve one's chances (besides cheating?). But merely knowing that the game is predicated solely on chance can be useful for other applications. E.g. realizing that the lottery is a scam.
Personally, I'm in that camp that says reasoning is a instrumental value towards prediction.
I would define reasoning as answering a question or optimization problem, e.g. What is my best move? What is a good move? This can be formalized as calculating some kind of score for a possible action, whereas prediction is just about assigning a probability value to an event.
So would it be fair to summarize this as "reason is prediction with a goal"?
