5 ms·

I appreciate the OP (of the reddit post) wants to keep his/her identity secret but I remain completely unsatisfied with the response to someone asking exactly w

I appreciate the OP (of the reddit post) wants to keep his/her identity secret but I remain completely unsatisfied with the response to someone asking exactly what they need this analogue computer for > My job is to make and maintain models of economic trends in my company’s industry. I find analogue computing to be the best way for me to easily and effectively model dynamic real world systems. I don't have much of an understanding of analgoue computers so I can't grasp why this computer is better at solving this sort of problem over a digital one.

pgeorgi 8y ago
> so I can't grasp why this computer is better at solving this sort of problem over a digital one As the original author mentioned in the discussion, it's better for _them_ and that's enough in that situation to keep doing it that way. The assessment may be entirely different for you, or maybe even everybody but that author.
- lodi 8y ago
  It hasn't been established that it's better, only that he or she thinks it's better--and we're all trying to understand why that is. Because we're (or at least I am) 99.99% sure that it's much, much worse. To start with, the whole thing could easily be simulated in software...
  - dfox 8y ago
    I suspect that the main reason why it is better is UX of representing whatever you want to calculate by physical structure and tunable parameters by physical knobs.
leggomylibro 8y ago
I don't have a good answer, but there does appear to be a history of using analog computing for financial modeling. One famous example is the MONIAC, which used fluids to simulate the flow of money: https://en.wikipedia.org/wiki/MONIAC https://en.wikipedia.org/wiki/MONIAC I wonder if 'fuzzy' or uncertain models like economic ones can tolerate or benefit from slightly less deterministic algorithms.
- floatingatoll 8y ago
  My favorite “impossibly difficult” computing problem that’s unsolved (brute force required) by digital but solved by analog is in finding the shortest path from A to B, wherein you just apply electricity to the start and endpoint and let the neon glow demonstrate the optimal solution. For example: https://www.nature.com/news/2002/020520/full/news020520-12.html https://www.nature.com/news/2002/020520/full/news020520-12.h...
  - taktoa 8y ago
    I'm pretty sure the actually difficult (i.e.: not handled by the heuristics TSP solvers use in practice) examples for TSP are impractical to convert to a physical object, and I'm not sure that physics would actually do a good job with them. Remember, it's the principal of _stationary_ action, not _least_ action, so it's basically a greedy search.
  - yorwba 8y ago
    Finding the shortest path from A to B is very much a solved problem, e.g. Dijkstra's algorithm can do it in quadratic time on arbitrary graphs. The article tries hard to pretend that the analog method presented could solve traveling salesman problems, but the actual paper only talks about ordinary shortest path problems. I don't see how it could be extended to TSP either, since it's hard to make electrons actually visit all destinations you want to cover when there's a shorter route available.
  - krastanov 8y ago
    While this is certainly a great trick (my favorite version of it is the use of soap bubbles to solve the traveling salesman problem) this solution is certainly no better than what you would achieve with an optimization that runs on a digital computer (and very often it is much worse, given the advances in numerical optimization). There is one very general problem with these "analog" solutions to optimization problems: nature (i.e. the analog computer) quickly finds a local minimum and it does not bother to find a global one (or as the sibling mentioned, it finds a stationary solution, not the true minimal solution). There are tricks you can use to try to search for a better minimum, but all of these tricks are applicable to the digital computer as well. Which is really exciting: you get to talk about annealing and how it works the same in metallurgy and in numerical optimization. Even more fascinating, you get to talk about how a whole host of diseases are inherently due to this "failure of convergence" of analog computers: prion diseases would not exist if analog computers (our cells) folded their proteins to the true minima.
twic 8y ago
Maybe the OP works in infosec, and this is the one computer they can guarantee won't be hacked.
- J5892 8y ago
  I would assume this computer generates a huge amount of EM interference(?) that could be mined with an antenna up to a mile away.
  - dfox 8y ago
    The frequencies involved are generally low enough that EMI is not an issue (which is generally required because of big nests of random banana plug patch cords of unknown RF performance)

pgeorgi 8y ago

> so I can't grasp why this computer is better at solving this sort of problem over a digital one As the original author mentioned in the discussion, it's better for _them_ and that's enough in that situation to keep doing it that way. The assessment may be entirely different for you, or maybe even everybody but that author.

lodi 8y ago
It hasn't been established that it's better, only that he or she thinks it's better--and we're all trying to understand why that is. Because we're (or at least I am) 99.99% sure that it's much, much worse. To start with, the whole thing could easily be simulated in software...
- dfox 8y ago
  I suspect that the main reason why it is better is UX of representing whatever you want to calculate by physical structure and tunable parameters by physical knobs.

leggomylibro 8y ago

I don't have a good answer, but there does appear to be a history of using analog computing for financial modeling. One famous example is the MONIAC, which used fluids to simulate the flow of money: https://en.wikipedia.org/wiki/MONIAC https://en.wikipedia.org/wiki/MONIAC I wonder if 'fuzzy' or uncertain models like economic ones can tolerate or benefit from slightly less deterministic algorithms.

floatingatoll 8y ago
My favorite “impossibly difficult” computing problem that’s unsolved (brute force required) by digital but solved by analog is in finding the shortest path from A to B, wherein you just apply electricity to the start and endpoint and let the neon glow demonstrate the optimal solution. For example: https://www.nature.com/news/2002/020520/full/news020520-12.html https://www.nature.com/news/2002/020520/full/news020520-12.h...
- taktoa 8y ago
  I'm pretty sure the actually difficult (i.e.: not handled by the heuristics TSP solvers use in practice) examples for TSP are impractical to convert to a physical object, and I'm not sure that physics would actually do a good job with them. Remember, it's the principal of _stationary_ action, not _least_ action, so it's basically a greedy search.
- yorwba 8y ago
  Finding the shortest path from A to B is very much a solved problem, e.g. Dijkstra's algorithm can do it in quadratic time on arbitrary graphs. The article tries hard to pretend that the analog method presented could solve traveling salesman problems, but the actual paper only talks about ordinary shortest path problems. I don't see how it could be extended to TSP either, since it's hard to make electrons actually visit all destinations you want to cover when there's a shorter route available.
- krastanov 8y ago
  While this is certainly a great trick (my favorite version of it is the use of soap bubbles to solve the traveling salesman problem) this solution is certainly no better than what you would achieve with an optimization that runs on a digital computer (and very often it is much worse, given the advances in numerical optimization). There is one very general problem with these "analog" solutions to optimization problems: nature (i.e. the analog computer) quickly finds a local minimum and it does not bother to find a global one (or as the sibling mentioned, it finds a stationary solution, not the true minimal solution). There are tricks you can use to try to search for a better minimum, but all of these tricks are applicable to the digital computer as well. Which is really exciting: you get to talk about annealing and how it works the same in metallurgy and in numerical optimization. Even more fascinating, you get to talk about how a whole host of diseases are inherently due to this "failure of convergence" of analog computers: prion diseases would not exist if analog computers (our cells) folded their proteins to the true minima.

twic 8y ago

Maybe the OP works in infosec, and this is the one computer they can guarantee won't be hacked.

J5892 8y ago
I would assume this computer generates a huge amount of EM interference(?) that could be mined with an antenna up to a mile away.
- dfox 8y ago
  The frequencies involved are generally low enough that EMI is not an issue (which is generally required because of big nests of random banana plug patch cords of unknown RF performance)