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Those are examples of problems that exist within the space of mathematics and number games we created for ourselves. Computers as we have them now are great for those.

However, when interfacing to the real, non-exactly specified, incomplete information world, "good enough most of the time" is not only fine, it is all you can hope for. For example, robots that need to navigate rough terrain, or in living orgamisms at the nano-scale, or communicate in human language.

There is a huge class of things that simply cannot be addressed with the current "correct" model of computation because they are not well-specified to the lowest level in the first place.

Computers, in other words, needs to be more like brains. Yes, this does give up certain advantages, and safety guarantees. But it does not give up everything. People have trusted their life to animals and other humans, for example, for all history, even though they are far from perfectly safe and/or compliant...

(and even now, it is "fallible" humans that control the technology, so you could make a point that nothing is lost, as it was never there in the first place)




> Computers, in other words, needs to be more like brains.

I wonder about this. One of the most common human methods of making decisions with incomplete information and/or short time frames is to fall back on heuristics rather than try to reason through the data. Heuristics have the advantage of being fast and available, but they're also notoriously bad at producing the quality of decision that might come from a more thorough analysis of the data.

Frankly, I think I'd feel more comfortable with computers that made decisions through brute force processing and bayesian analysis.


Yes, we'd all like to live in the best of all worlds. But in any real-life scenario, there is a trade-off.

Brute forcing all possible combinations and finding the best one (for your specific goal, or taking into account all externalities as well) would be great. But it is impossible for two reasons:

1) incomplete, or even purposefully incorrect information

2) time constraints/compexity. For a non-linear system with more than a few variables, it is just not feasible to enumerate everything.

You end up with heuristics. The challenge is that remains is finding good heuristics. If the decision is given more time, you can probably come up with better heuristics and even sort-of brute force through the "best" options (which is what humans do when they reason).




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