8 ms·

The Future of Computing Is Analog

54 points by zerogvt 8y ago

joe_the_user 8y ago
The article seems a bit abstract. I think the question that comes to mind is whether it's possible to take GPU-styles architecture and give it 100x more power or more by replacing bits with approximate voltage levels that are "fuzzy" but statistical guarantees to their performance, along with gates that allow the values to be filtered back to zeros and ones. The thing is the "neural architectures" seem to have been more or less failure through requiring the user to accept one particular neural net structure while the standard GPU seems to have succeeded through being generic-enough to use for a variety of tasks. So some sort of analogy-GPU should also have a similar generic model - but of course it seems likely that the creator of this stuff will want to impose their special model. Edit: More or less like the D-wave "quantum computer" except not milking quantum hype and being reconciled to being understood as "massively analogue"
- krastanov 8y ago
  The "fuzzy but statistical guarantees" is basically "error correction". Which is (handwavily) the difference between digital and analog computing. What you are describing is the engineer's definition of a digital computer. Admittedly, there might be interesting performance gains if we use less stringent statistical guarantees... which happens to be what is happening each time we make the transistors smaller and more susceptible to noise. C.f. the paper that introduced the distinction between analog and "statistically guaranteed" digital in the case of classical computers (before it people were arguing that you can not build a scallable classical digital computer because of noise): by von Neumann http://www.sns.ias.edu/pitp2/2012files/Probabilistic_Logics.pdf http://www.sns.ias.edu/pitp2/2012files/Probabilistic_Logics.... The paper that did the same for quantum computers 50 years later: by Shor http://www-math.mit.edu/~shor/papers/good-codes.pdf http://www-math.mit.edu/~shor/papers/good-codes.pdf P.S. FYI DWave is not a scallable quantum computer. They have another "quantumy" word for what they do, so that they can keep the hype without angering people that are trying to build an actual quantum computer.
  - kangnkodos 8y ago
    Yes. Concentrating on error correction reveals the difference between digital and analog computing. Digital computers have error correction. Analog computers don't. Some small number of problems might be solved efficiently using analog computers, but they will never take over the role of general purpose computers because of error correction issues.
ineedasername 8y ago
I guess I see the point being made, but it was all a bit long on rhetoric and analogy, and short on concrete examples.
- Animats 8y ago
  Yes. This is the same argument that audio nuts make for analog recording. It's known to be bogus. (Yes, 16-bit CD audio has resolution problems for soft passages, and early filters for the sampling rate were not too good. We're past that.) One of the few concrete examples of a complex analog computer system still used in recent decades was the F-16 flight control system. It's a four channel fly by wire stabilization and control system, all analog. It was, at the time, the most advanced flight control system, and it's still well thought of. That's from the 1970s, and modernized F-16s use a digital replacement. For several decades, full authority digital flight control systems were disfavored in aerospace because there were no analysis techniques to be sure they were bug free. There are ways to analyze an analog computer system to be sure that the test case set is sufficient, and that behavior will be smooth continuous between the test case points. Eventually that problem was solved for digital flight control systems, and now everybody goes digital.
  - Junk_Collector 8y ago
    Analog computers still crop up in all sorts of places these days but have become very niche and are typically a small part of an otherwise larger system. It's rare to see a general purpose analog computer outside of a very small number of research labs and FPAAs exist but are expensive novelties. As digital processors continue to get better and we develop better ways to work with them, there just isn't the need for the cost and effort required to make analog computers. Some common places where you might see one is in audio driver amplifiers where it is common to implement a bit of trans-linear logic at the output stage to reduce distortion. Same in some high quality power supplies. Sometimes very high performance sensor systems will have an analog pre-processor to perform some calculation on the incoming signal before handing it off to the digitizers and DSP. Think multi-microphone arrays.
coupdejarnac 8y ago
Too bad the author didn't substantiate his claims that analog computing will make a comeback. I found this article [0] with a real world application, but no performance comparison to a digital computer. I also take issue with the claim that a transistor has infinite possible states, and that we're ignoring most of them. This doesn't take into account real world limitations of components' precision and noise. [0] https://news.mit.edu/2016/analog-computing-organs-organisms-0620 https://news.mit.edu/2016/analog-computing-organs-organisms-...
- adamnemecek 8y ago
  > I found this article [0] with a real world application, but no performance comparison to a digital computer. This is impossible right now, no one is really making analog computers to make this comparison.
_bxg1 8y ago
A couple of interesting examples in this (loose) subject area: https://arstechnica.com/science/2018/07/neural-network-implemented-with-light-instead-of-electrons/ https://arstechnica.com/science/2018/07/neural-network-imple... https://pruned.blogspot.com/2012/01/gardens-as-crypto-water-computers.html https://pruned.blogspot.com/2012/01/gardens-as-crypto-water-...
tabtab 8y ago
I agree that analog computing is probably more efficient, or can be more efficient if predictability is sacrificed. However, there are societal implications to this. We prefer the processing steps be traceable and dissactable for accountability and managing the distribution of tasks/parts in terms of accountability. We may not accept a higher degree of "rogue machines" to gain average efficiency. However, I suppose a given country or group could accept the tradeoff to gain a military advantage, which could spell chaos. They may accept a higher degree of rogue battle bots in order to win via average efficiency, or at least be willing to take the gamble that the theory is true. The chance of a high-stakes or borderline suicidal leader/dictator eventually coming on the scene is historically high, leading inadvertently to run-away human-flattening bots. Maybe that's the answer to the Fermi Paradox.
- tabtab 8y ago
  Okay, people, why the "-2". Fess up.
Junk_Collector 8y ago
Perhaps I missed it, but the point of the article seems to be that eventually a complex "neuro" computer will be to complicated to understand and produce unaccountable results. The Author makes a few poor assumptions about analog vs digital computing and seems to ramble a lot, but ultimately, his main point doesn't have much to do with either.
vgoh1 8y ago
Digital computation has been able to rise to this level of complexity because we can precisely predict/repeat outcomes because of exact numbers and boolean logic. I could not fathom anything like what we have using analog. I was reading the article, waiting for some type of plan for how to tackle analog computing, but it never came. A thought provoking article, but I'm not holding my breath for analog.
agumonkey 8y ago
Everytime I see large digital systems, the deterministic nature fades and it starts looking probabilistic, noisy .. continuous
etaioinshrdlu 8y ago
I suspect that the 'excess' precision of digital computers could be able to be retargeted towards some other use, negating any benefit that a analog computer had.
ychen306 8y ago
> It is entirely possible to build something without understanding it. [...] Our relationship with true A.I. will always be a matter of faith, not proof WTF. I have no problem with building something without understanding how or why it works, but I do have problem of using something without at least some sort of guarantee on its behavior.
- jethro_tell 8y ago
  You may, but the vast majority of the population is already way past that with an iPhone and search bubbles, apps . . .. And honestly, even if you're in tech, this feild is so broad and so many people are doing so many cool things that there's almost no way to keep up with it unless you're a ludite. If the case we are talking about involves building a single giant computer that no one knows how to use, you won't have much say in that.
adamnemecek 8y ago
I've been saying this for a while. https://hn.algolia.com/?query=adamnemecek%20analog%20quantum&type=comment&sort=byPopularity&prefix&page=0&dateRange=all https://hn.algolia.com/?query=adamnemecek%20analog%20quantum... The main problem with old school analog computers is that they were based on electricity which ended up causing rift (imprecision that gets worse over time). A photonic, analog, quantum computer (also called continuous variable quantum computer) https://en.wikipedia.org/wiki/Continuous-variable_quantum_information https://en.wikipedia.org/wiki/Continuous-variable_quantum_in... is possible and would run circles around discrete quantum computers (those with qubits).
- krastanov 8y ago
  The claim about relative performance of continuous variable models versus circuit models is completely unsubstantiated. Especially given that most uses of the continuous variable systems is to encode discrete qubits on top of them with GKP/cat/binomial codes. Is there any Complexity Theory work published about continuous variable models? And photonic systems do not magically fix the noise issue. Noise grows in a fast non-linear fashion with the size of the system, so the "constant factor" noise suppression you gain from switching to photonic systems is quickly washed away.
  - adamnemecek 8y ago
    > Especially given that most uses of the continuous variable systems is to encode discrete qubits Current uses, maybe. > Is there any Complexity Theory work published about continuous variable models? "Complexity and Real Computation". > And photonic systems do not magically fix the noise issue. Noise grows in a fast non-linear fashion with the size of the system, so the "constant factor" noise suppression you gain from switching to photonic systems is quickly washed away. Is there anything published on the fact that this cannot be overcome?
    - krastanov 8y ago
      Just looking at the wiki pages for Real Computation is enough to see it is not a physically realizable model. For more detailed discussion of the problem you can see the essay "NP-complete Problems and Physical Reality". To quote from it "The problem, of course, is that unlimited-precision real numbers would violate the holographic entropy bound". At every level of physics there is a bound on precision, from boring things like classical macroscopic thermodynamics and noise, to quantum noise, to bounds that emerge in speculative theoretical physics. Basically, anything capable of encoding an infinitely precise real number in a finite amount of space will collapse and form a black hole. In case this is not convincing enough, to your question about how this noise can not be overcome: if there was a method that can overcome the noise asymptotically in photonic systems, then that method would work in electric systems too. And there is actually such a method: turning the computer into a digital computer thanks to error correction codes. The claim that Real Computation can be realized in our universe is comparable to the claim one can construct a perpetual motion machine or some other generator of free energy. They are both preposterous given our understanding of physics. And yes, I would celebrate if either of one turns out to actually be possible, but incredible claims require incredible evidence.
twtw 8y ago
With respect, I think most comments here are missing Dyson's point (perhaps because it was somewhat poorly made). I don't think his point is about whether the integrator and analog electronics will be resurgent in the next century, and analog hardware will be common. I think Dyson is talking about the complex network of the modern world, where humans interact with computing machine, and with each other - humans influence computers, and computers come back around and influence humans. I think his "future of computing" is a future where human society and culture is decided based on the interplay between humans and our machines, and this decision is an "analog computation" made by a massive scale hybrid computer that no one has intentionally designed or understands. You can see examples of this already, with youtube recommendation engines influencing the belief systems of millions (billions?) of people across all kinds of subjects, and with our thoughts frequently dominated by whatever happens to show up on our phones.
- usgroup 8y ago
  Maybe I’m just simple but couldn’t you say it was always case that the human hive mind is a bit like a giant analog computer ? Not sure why the digital stuff is important for the analogy.
- patrickyeon 8y ago
  Oh absolutely you're correct here. > In analog computing, complexity resides in network topology, not in code. Information is processed as continuous functions of values, such as voltage and relative pulse frequency, rather than by logical operations on discrete strings of bits. ... > Individually deterministic finite-state processors, running finite codes, are forming large-scale, nondeterministic, non-finite-state metazoan organisms running wild in the real world. The resulting hybrid analog/digital systems treat streams of bits collectively, the way the flow of electrons is treated in a vacuum tube, rather than individually, as bits are treated by the discrete-state devices generating the flow. Bits are the new electrons. Analog is back, and its nature is to assume control. > Say, for example, you build a system to map highway traffic in real time simply by giving cars access to the map in exchange for reporting their own speed and location at the time. The result is a fully decentralized control system. Nowhere is there any controlling model of the system except the system itself. ... > Even in the age of all things digital, this cannot be defined in any strictly logical sense, because meaning, among humans, isn’t fundamentally logical. The best you can do, once you have collected all possible answers, is to invite well-defined questions and compile a pulse-frequency weighted map of how everything connects. Before you know it, your system will not only be observing and mapping the meaning of things, it will start constructing meaning as well. In time, it will control meaning, in the same way the traffic map starts to control the flow of traffic even though no one seems to be in control. In these passages, "The Computer" that's running is the network, a meta-computer, made up of the individual "computing elements" if you will that are the physical pieces of hardware that most anyone would point to and call "a computer". And as you've recognized, that's Dyson's point: No matter what those little elements are made of, the overall picture is analog. If we want to understand how "Algorithms" are influencing the world, we can't think of them as "discrete computing algorithms". And finally, the emergent behaviour out of this can lead to large-scale control effected on our society without being designed in, and even if nobody is thinking to effect control.
medius 8y ago
Just a few thoughts I've been mulling for a while about this topic: Machine learning is something that I believe can take advantage of analog computing. A machine learning algorithm does not need highly precise or accurate representations. Most current implementations of such processing units use fewer bits (usually 8). However, even if we use fewer bits, the engineering effort (design, layout, lithography, etc.) that goes into making the processing unit still assumes that those few bits are error free. The manufacturing process treats it like any other digital circuit. It assumes data processing part should be fault free (e.g. treat MSB and LSB the same). Digital circuits also demand higher power compared to analog versions. If an analog circuit can be designed for such algorithms, not only could it be much faster, it will probably consume far less power. With a super high bandwidth consuming little power, an analog processing chip may give us a much better playground to try advanced algorithms. The materials can then be optimized and we might end up with something like a brain. Brains (all animals) process far more information for the power they consume. Digital circuits give us low level reliability and so they are really good for simple control. Analog/biology don't give us that. But they can give us a high level reliability while delegating the low level reliability to digital counterparts.
- usgroup 8y ago
  I think you’re wrong about the ML precision. You need highly precise for most recursive machine learning tasks because you’re compounding errors otherwise. Typically you can’t even use floating point representation: not accurate enough.
  - SomaticPirate 8y ago
    Disagree. https://arxiv.org/abs/1805.08691 https://arxiv.org/abs/1805.08691 demonstrates 8-bit architecture for a pre-trained CNN provides more than acceptable results with lower latency and higher throughput than a higher precision version.
    - usgroup 8y ago
      Sure but we were talking about precision rather than throughput ; tbh the result is hardly surprising .
reading-at-work 8y ago
> even though vacuum tubes are commercially extinct Sounds like someone's never shopped for guitar amps before.
- tabtab 8y ago
  In art, sometimes you want "happy accidents", even if they are not always reproducible.
nat8265639392 8y ago
Can anyone recommend any good books or resources to learn more about analog computing?
- boomlinde 8y ago
  The Heathkit EC-1 operations manual seems like a good start for electronic analog computers and has some examples of problem circuits: http://www.ccapitalia.net/descarga/docs/1959-ec-1-heathkit.pdf http://www.ccapitalia.net/descarga/docs/1959-ec-1-heathkit.p... I also like to share an instruction video on mechanical computers on every suitable occasion: https://www.youtube.com/watch?v=s1i-dnAH9Y4 https://www.youtube.com/watch?v=s1i-dnAH9Y4
ubu7737 8y ago
Perhaps I'm missing the more grandiose point, but I think his message is simple: digital computing is a handy abstraction for humans who like to count, but computing is essentially analog. This layman likes to refer to something about genetic algorithms and magnetic flux for reference on this. I mean this: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.50.9691&rep=rep1&type=pdf http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.50....
adamnemecek 8y ago
Does anyone know how to contact the author?
peter_d_sherman 8y ago
Quantum, Analog, and Fuzzy Logic - are different terms that I believe some bright person in the future will prove as describing exactly the same underlying phenomenon. (Also, if this could be accomplished, the next step in human evolution might be proving that the entire universe is a giant Analog computer, but that's Sci-Fi at this point in time...)
jakeogh 8y ago
not really related, there is a interesting use of analog effects in fpga's: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.50.9691&rep=rep1&type=pdf http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.50.... old paper. 1996. Fragile.
unnouinceput 8y ago
There is no such thing as "analog". Everything in this Universe is digitized, down to elemental particles inside atoms. What you experience as "analog" is just digitization with a very fine grain, or if you like it, with better sampling. So no, the future of computing is not analog at all, it will still be digital, just with better sampling, aka quantum computing.

54 points by zerogvt 8y ago

The article seems a bit abstract. I think the question that comes to mind is whether it's possible to take GPU-styles architecture and give it 100x more power or more by replacing bits with approximate voltage levels that are "fuzzy" but statistical guarantees to their performance, along with gates that allow the values to be filtered back to zeros and ones. The thing is the "neural architectures" seem to have been more or less failure through requiring the user to accept one particular neural net structure while the standard GPU seems to have succeeded through being generic-enough to use for a variety of tasks. So some sort of analogy-GPU should also have a similar generic model - but of course it seems likely that the creator of this stuff will want to impose their special model. Edit: More or less like the D-wave "quantum computer" except not milking quantum hype and being reconciled to being understood as "massively analogue"

krastanov 8y ago
The "fuzzy but statistical guarantees" is basically "error correction". Which is (handwavily) the difference between digital and analog computing. What you are describing is the engineer's definition of a digital computer. Admittedly, there might be interesting performance gains if we use less stringent statistical guarantees... which happens to be what is happening each time we make the transistors smaller and more susceptible to noise. C.f. the paper that introduced the distinction between analog and "statistically guaranteed" digital in the case of classical computers (before it people were arguing that you can not build a scallable classical digital computer because of noise): by von Neumann http://www.sns.ias.edu/pitp2/2012files/Probabilistic_Logics.pdf http://www.sns.ias.edu/pitp2/2012files/Probabilistic_Logics.... The paper that did the same for quantum computers 50 years later: by Shor http://www-math.mit.edu/~shor/papers/good-codes.pdf http://www-math.mit.edu/~shor/papers/good-codes.pdf P.S. FYI DWave is not a scallable quantum computer. They have another "quantumy" word for what they do, so that they can keep the hype without angering people that are trying to build an actual quantum computer.
- kangnkodos 8y ago
  Yes. Concentrating on error correction reveals the difference between digital and analog computing. Digital computers have error correction. Analog computers don't. Some small number of problems might be solved efficiently using analog computers, but they will never take over the role of general purpose computers because of error correction issues.

ineedasername 8y ago

I guess I see the point being made, but it was all a bit long on rhetoric and analogy, and short on concrete examples.

Animats 8y ago
Yes. This is the same argument that audio nuts make for analog recording. It's known to be bogus. (Yes, 16-bit CD audio has resolution problems for soft passages, and early filters for the sampling rate were not too good. We're past that.) One of the few concrete examples of a complex analog computer system still used in recent decades was the F-16 flight control system. It's a four channel fly by wire stabilization and control system, all analog. It was, at the time, the most advanced flight control system, and it's still well thought of. That's from the 1970s, and modernized F-16s use a digital replacement. For several decades, full authority digital flight control systems were disfavored in aerospace because there were no analysis techniques to be sure they were bug free. There are ways to analyze an analog computer system to be sure that the test case set is sufficient, and that behavior will be smooth continuous between the test case points. Eventually that problem was solved for digital flight control systems, and now everybody goes digital.
- Junk_Collector 8y ago
  Analog computers still crop up in all sorts of places these days but have become very niche and are typically a small part of an otherwise larger system. It's rare to see a general purpose analog computer outside of a very small number of research labs and FPAAs exist but are expensive novelties. As digital processors continue to get better and we develop better ways to work with them, there just isn't the need for the cost and effort required to make analog computers. Some common places where you might see one is in audio driver amplifiers where it is common to implement a bit of trans-linear logic at the output stage to reduce distortion. Same in some high quality power supplies. Sometimes very high performance sensor systems will have an analog pre-processor to perform some calculation on the incoming signal before handing it off to the digitizers and DSP. Think multi-microphone arrays.

coupdejarnac 8y ago

Too bad the author didn't substantiate his claims that analog computing will make a comeback. I found this article [0] with a real world application, but no performance comparison to a digital computer. I also take issue with the claim that a transistor has infinite possible states, and that we're ignoring most of them. This doesn't take into account real world limitations of components' precision and noise. [0] https://news.mit.edu/2016/analog-computing-organs-organisms-0620 https://news.mit.edu/2016/analog-computing-organs-organisms-...

adamnemecek 8y ago
> I found this article [0] with a real world application, but no performance comparison to a digital computer. This is impossible right now, no one is really making analog computers to make this comparison.

_bxg1 8y ago

A couple of interesting examples in this (loose) subject area: https://arstechnica.com/science/2018/07/neural-network-implemented-with-light-instead-of-electrons/ https://arstechnica.com/science/2018/07/neural-network-imple... https://pruned.blogspot.com/2012/01/gardens-as-crypto-water-computers.html https://pruned.blogspot.com/2012/01/gardens-as-crypto-water-...

tabtab 8y ago

I agree that analog computing is probably more efficient, or can be more efficient if predictability is sacrificed. However, there are societal implications to this. We prefer the processing steps be traceable and dissactable for accountability and managing the distribution of tasks/parts in terms of accountability. We may not accept a higher degree of "rogue machines" to gain average efficiency. However, I suppose a given country or group could accept the tradeoff to gain a military advantage, which could spell chaos. They may accept a higher degree of rogue battle bots in order to win via average efficiency, or at least be willing to take the gamble that the theory is true. The chance of a high-stakes or borderline suicidal leader/dictator eventually coming on the scene is historically high, leading inadvertently to run-away human-flattening bots. Maybe that's the answer to the Fermi Paradox.

tabtab 8y ago
Okay, people, why the "-2". Fess up.

Junk_Collector 8y ago

Perhaps I missed it, but the point of the article seems to be that eventually a complex "neuro" computer will be to complicated to understand and produce unaccountable results. The Author makes a few poor assumptions about analog vs digital computing and seems to ramble a lot, but ultimately, his main point doesn't have much to do with either.

vgoh1 8y ago

Digital computation has been able to rise to this level of complexity because we can precisely predict/repeat outcomes because of exact numbers and boolean logic. I could not fathom anything like what we have using analog. I was reading the article, waiting for some type of plan for how to tackle analog computing, but it never came. A thought provoking article, but I'm not holding my breath for analog.

agumonkey 8y ago

Everytime I see large digital systems, the deterministic nature fades and it starts looking probabilistic, noisy .. continuous

etaioinshrdlu 8y ago

I suspect that the 'excess' precision of digital computers could be able to be retargeted towards some other use, negating any benefit that a analog computer had.

ychen306 8y ago

> It is entirely possible to build something without understanding it. [...] Our relationship with true A.I. will always be a matter of faith, not proof WTF. I have no problem with building something without understanding how or why it works, but I do have problem of using something without at least some sort of guarantee on its behavior.

jethro_tell 8y ago
You may, but the vast majority of the population is already way past that with an iPhone and search bubbles, apps . . .. And honestly, even if you're in tech, this feild is so broad and so many people are doing so many cool things that there's almost no way to keep up with it unless you're a ludite. If the case we are talking about involves building a single giant computer that no one knows how to use, you won't have much say in that.

adamnemecek 8y ago

I've been saying this for a while. https://hn.algolia.com/?query=adamnemecek%20analog%20quantum&type=comment&sort=byPopularity&prefix&page=0&dateRange=all https://hn.algolia.com/?query=adamnemecek%20analog%20quantum... The main problem with old school analog computers is that they were based on electricity which ended up causing rift (imprecision that gets worse over time). A photonic, analog, quantum computer (also called continuous variable quantum computer) https://en.wikipedia.org/wiki/Continuous-variable_quantum_information https://en.wikipedia.org/wiki/Continuous-variable_quantum_in... is possible and would run circles around discrete quantum computers (those with qubits).

krastanov 8y ago
The claim about relative performance of continuous variable models versus circuit models is completely unsubstantiated. Especially given that most uses of the continuous variable systems is to encode discrete qubits on top of them with GKP/cat/binomial codes. Is there any Complexity Theory work published about continuous variable models? And photonic systems do not magically fix the noise issue. Noise grows in a fast non-linear fashion with the size of the system, so the "constant factor" noise suppression you gain from switching to photonic systems is quickly washed away.
- adamnemecek 8y ago
  > Especially given that most uses of the continuous variable systems is to encode discrete qubits Current uses, maybe. > Is there any Complexity Theory work published about continuous variable models? "Complexity and Real Computation". > And photonic systems do not magically fix the noise issue. Noise grows in a fast non-linear fashion with the size of the system, so the "constant factor" noise suppression you gain from switching to photonic systems is quickly washed away. Is there anything published on the fact that this cannot be overcome?
  - krastanov 8y ago
    Just looking at the wiki pages for Real Computation is enough to see it is not a physically realizable model. For more detailed discussion of the problem you can see the essay "NP-complete Problems and Physical Reality". To quote from it "The problem, of course, is that unlimited-precision real numbers would violate the holographic entropy bound". At every level of physics there is a bound on precision, from boring things like classical macroscopic thermodynamics and noise, to quantum noise, to bounds that emerge in speculative theoretical physics. Basically, anything capable of encoding an infinitely precise real number in a finite amount of space will collapse and form a black hole. In case this is not convincing enough, to your question about how this noise can not be overcome: if there was a method that can overcome the noise asymptotically in photonic systems, then that method would work in electric systems too. And there is actually such a method: turning the computer into a digital computer thanks to error correction codes. The claim that Real Computation can be realized in our universe is comparable to the claim one can construct a perpetual motion machine or some other generator of free energy. They are both preposterous given our understanding of physics. And yes, I would celebrate if either of one turns out to actually be possible, but incredible claims require incredible evidence.

twtw 8y ago

With respect, I think most comments here are missing Dyson's point (perhaps because it was somewhat poorly made). I don't think his point is about whether the integrator and analog electronics will be resurgent in the next century, and analog hardware will be common. I think Dyson is talking about the complex network of the modern world, where humans interact with computing machine, and with each other - humans influence computers, and computers come back around and influence humans. I think his "future of computing" is a future where human society and culture is decided based on the interplay between humans and our machines, and this decision is an "analog computation" made by a massive scale hybrid computer that no one has intentionally designed or understands. You can see examples of this already, with youtube recommendation engines influencing the belief systems of millions (billions?) of people across all kinds of subjects, and with our thoughts frequently dominated by whatever happens to show up on our phones.

usgroup 8y ago
Maybe I’m just simple but couldn’t you say it was always case that the human hive mind is a bit like a giant analog computer ? Not sure why the digital stuff is important for the analogy.
patrickyeon 8y ago
Oh absolutely you're correct here. > In analog computing, complexity resides in network topology, not in code. Information is processed as continuous functions of values, such as voltage and relative pulse frequency, rather than by logical operations on discrete strings of bits. ... > Individually deterministic finite-state processors, running finite codes, are forming large-scale, nondeterministic, non-finite-state metazoan organisms running wild in the real world. The resulting hybrid analog/digital systems treat streams of bits collectively, the way the flow of electrons is treated in a vacuum tube, rather than individually, as bits are treated by the discrete-state devices generating the flow. Bits are the new electrons. Analog is back, and its nature is to assume control. > Say, for example, you build a system to map highway traffic in real time simply by giving cars access to the map in exchange for reporting their own speed and location at the time. The result is a fully decentralized control system. Nowhere is there any controlling model of the system except the system itself. ... > Even in the age of all things digital, this cannot be defined in any strictly logical sense, because meaning, among humans, isn’t fundamentally logical. The best you can do, once you have collected all possible answers, is to invite well-defined questions and compile a pulse-frequency weighted map of how everything connects. Before you know it, your system will not only be observing and mapping the meaning of things, it will start constructing meaning as well. In time, it will control meaning, in the same way the traffic map starts to control the flow of traffic even though no one seems to be in control. In these passages, "The Computer" that's running is the network, a meta-computer, made up of the individual "computing elements" if you will that are the physical pieces of hardware that most anyone would point to and call "a computer". And as you've recognized, that's Dyson's point: No matter what those little elements are made of, the overall picture is analog. If we want to understand how "Algorithms" are influencing the world, we can't think of them as "discrete computing algorithms". And finally, the emergent behaviour out of this can lead to large-scale control effected on our society without being designed in, and even if nobody is thinking to effect control.

medius 8y ago

Just a few thoughts I've been mulling for a while about this topic: Machine learning is something that I believe can take advantage of analog computing. A machine learning algorithm does not need highly precise or accurate representations. Most current implementations of such processing units use fewer bits (usually 8). However, even if we use fewer bits, the engineering effort (design, layout, lithography, etc.) that goes into making the processing unit still assumes that those few bits are error free. The manufacturing process treats it like any other digital circuit. It assumes data processing part should be fault free (e.g. treat MSB and LSB the same). Digital circuits also demand higher power compared to analog versions. If an analog circuit can be designed for such algorithms, not only could it be much faster, it will probably consume far less power. With a super high bandwidth consuming little power, an analog processing chip may give us a much better playground to try advanced algorithms. The materials can then be optimized and we might end up with something like a brain. Brains (all animals) process far more information for the power they consume. Digital circuits give us low level reliability and so they are really good for simple control. Analog/biology don't give us that. But they can give us a high level reliability while delegating the low level reliability to digital counterparts.

usgroup 8y ago
I think you’re wrong about the ML precision. You need highly precise for most recursive machine learning tasks because you’re compounding errors otherwise. Typically you can’t even use floating point representation: not accurate enough.
- SomaticPirate 8y ago
  Disagree. https://arxiv.org/abs/1805.08691 https://arxiv.org/abs/1805.08691 demonstrates 8-bit architecture for a pre-trained CNN provides more than acceptable results with lower latency and higher throughput than a higher precision version.
  - usgroup 8y ago
    Sure but we were talking about precision rather than throughput ; tbh the result is hardly surprising .

reading-at-work 8y ago

> even though vacuum tubes are commercially extinct Sounds like someone's never shopped for guitar amps before.

tabtab 8y ago
In art, sometimes you want "happy accidents", even if they are not always reproducible.

nat8265639392 8y ago

Can anyone recommend any good books or resources to learn more about analog computing?

boomlinde 8y ago
The Heathkit EC-1 operations manual seems like a good start for electronic analog computers and has some examples of problem circuits: http://www.ccapitalia.net/descarga/docs/1959-ec-1-heathkit.pdf http://www.ccapitalia.net/descarga/docs/1959-ec-1-heathkit.p... I also like to share an instruction video on mechanical computers on every suitable occasion: https://www.youtube.com/watch?v=s1i-dnAH9Y4 https://www.youtube.com/watch?v=s1i-dnAH9Y4

ubu7737 8y ago

Perhaps I'm missing the more grandiose point, but I think his message is simple: digital computing is a handy abstraction for humans who like to count, but computing is essentially analog. This layman likes to refer to something about genetic algorithms and magnetic flux for reference on this. I mean this: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.50.9691&rep=rep1&type=pdf http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.50....

adamnemecek 8y ago

Does anyone know how to contact the author?

peter_d_sherman 8y ago

Quantum, Analog, and Fuzzy Logic - are different terms that I believe some bright person in the future will prove as describing exactly the same underlying phenomenon. (Also, if this could be accomplished, the next step in human evolution might be proving that the entire universe is a giant Analog computer, but that's Sci-Fi at this point in time...)

jakeogh 8y ago

not really related, there is a interesting use of analog effects in fpga's: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.50.9691&rep=rep1&type=pdf http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.50.... old paper. 1996. Fragile.

unnouinceput 8y ago

There is no such thing as "analog". Everything in this Universe is digitized, down to elemental particles inside atoms. What you experience as "analog" is just digitization with a very fine grain, or if you like it, with better sampling. So no, the future of computing is not analog at all, it will still be digital, just with better sampling, aka quantum computing.