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The basic thing here is that 1) we can guess from pretty basic physics that black holes have an entropy. 2) in order for a black hole to have an entropy it must
by nathan_compton 3y ago
The basic thing here is that 1) we can guess from pretty basic physics that black holes have an entropy. 2) in order for a black hole to have an entropy it must have microscopic degrees of freedom. 3) String theory is one of the few ways we've ever come close to actually calculating from microscopic degrees of freedom the entropy we "know" black holes should have. I think most physicists, even string theorists (perhaps them more than others) understand that there are physical and philosophical problems with string theory, but I think most folks also think its the closest thing we have to a working theory and that it is probably a useful language in which to cast certain calculations in lieu of a more complete or rigorous theory.
I'd also like to point out that the actual total funding for string theory is extremely tiny compared to scientific research funding in general since it is a theoretical discipline with very few practitioners. If you want to attach inefficiencies in scientific funding, the LHC is a much better target. I'm a physicist and have an interest in theory, and even I think that we spend too much money on particle accelerators given what we stand to learn from them and the other pressing problems the human race has. I'd be delighted to see all that money re-allocated to large scale public works building solar panels and infrastructure or just giving it to poor people.
- d0mine 3y agoIf we follow Pareto principle, then it doesn't make sense to optimize spendings that are close to zero if compared with something like military spendings. https://en.wikipedia.org/wiki/Pareto_principle https://en.wikipedia.org/wiki/Pareto_principle Even if string theory is just pure math with no base in reality, it still can be useful (any math domain for that matter).
- _0ffh 3y agoI don't think the spending is really a problem, but possibly the many work-hours of brilliant minds that might be more fruitfully employed working on different problems.
- dangerlibrary 3y agoLet's not pick on the LHC for that. How many gobsmackingly brilliant engineer-hours have gone into optimizing ad targeting or fine-tuning purchase attribution?
- ecnahc515 3y agoNot to mention, the LHC is responsible for a lot of innovation in it's own right, just in terms of hardware, software, etc.
- AmericanChopper 3y agoThe bigger picture is that only so many resources are going to be devoted to researching fundamental physics (both money and hours of work from human beings). If the majority of those resources are focused on a dead-end theory, then the opportunity cost is quite literally everything else.
- deleted 3y ago[deleted]
- nbardy 3y agoIt’s noble to want to help the poor but the economy isn’t zero sum in that way. Almost all the surplus we have could be traced back to our discoveries in physics leading to machines. People lived much much poorer lives without modern physics discoveries. The expects return on physics is so great we should find ways to afford more long shot experiments not less.
- nathan_compton 3y agoThis is some galaxy brain shit.
- edgyquant 3y agoThis is overblown. The vast majority of improvements to human lives can from textile and agricultural revolutions. Physics supplemented these, sure, but it wasn’t thanks to a few dudes hiding out in a lab doing theory.
- nathan_compton 3y agoSorry, but _even as a physicist_ I think the idea that the expected returns for society of discovering some other obscure standard model particle are trivial to nothing. Literally useless knowledge and only of interest to a tiny minority of people (of whom I am a part, I admit). Like seriously. Consider: how has anyone's life been improved by the discovery of the Higgs? By the absence of Supersymmetry?
- steve_mcdougall 3y ago[dead]
- senttoschool 3y agoWe don’t know yet. To be determined. But science has taken us pretty far.
- clarle 3y agoNeural network algorithm research was considered more of an academic endeavor rather than something that could have practical implications from the 1960s to even the early 2000s, compared to other machine learning algorithms. Look at where it took us today.