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To expand on that point, the brain is not good at simple products of large numbers, but is fantastic at doing things like triangulation. Or calculating how much
by vacri 9y ago
To expand on that point, the brain is not good at simple products of large numbers, but is fantastic at doing things like triangulation. Or calculating how much muscle to contract to keep your balance going into a turn whilst running. Or eyeballing quantities - we notice when we get it wrong, but the vast majority of the time, we're pretty good at getting estimates correct about the human-scale world around us.
- TheSpiceIsLife 9y agoHave you seen that fellow that calls himself a mathemagician, Arthur Benjamin? I believe he would argue it's a matter of training.
- vacri 9y agoWell, yes, but that's not a very useful distinction. You train computers as well by programming them. In meatspace, there was a famous experiment in the '60s where kittens had their heads locked into position so that they only saw vertical lines - their nascent neuroplastic brains then trained that way, and as they matured, they simply couldn't see horizontal lines (eg: would walk into horizontal bars). In the Nature vs Nurture debate, the purists on either side tend to use tortured, hair-splitting definitions to make their arguments, and it's usually those somewhere in the middle that sound the sanest.
- TheSpiceIsLife 9y agoIn which case, computers, as in microprocessors, are extraordinarily bad at math. Without the appropriate programming they can't do anything.
- fooker 9y agoWhat we do regularly (..say.. move your hand to reach something or catch a ball) does take a large amount of very precise products though (i.e. Inverse Kinematics). It is not very meaningful from an information theoretic pov to debate whether the results come from the multiplication algorithms computers follow or via some trained analog network; the result is the same.