[HN Gopher] Why not faster computation via evolution and diffrac...
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Why not faster computation via evolution and diffracted light?
Author : tobr
Score : 50 points
Date : 2021-04-24 19:10 UTC (3 hours ago)
(HTM) web link (interconnected.org)
(TXT) w3m dump (interconnected.org)
| deckar01 wrote:
| I think the part they are missing is that a general purpose
| computer is required to train and simulate the physical model.
| The speed at which a trained model executes isn't really a
| problem in most domains as far as I'm aware. They can evaluate in
| real time already on standard hardware. It's also more efficient
| to push software updates when your model improves rather than
| retooling you manufacturing process and deprecating valuable
| resources into a landfill.
| SubiculumCode wrote:
| Speed and efficiency are often lost to gain flexibility, and this
| tradeoff is often ignored when you see articles extolling non-
| human intelligence of birds, insects, etc. Insects, through
| evolution have created highly efficient and FAST neural circuits
| that lead to fit behaviors, but the fitness of these circuits and
| behaviors often mask their inflexibility to a change of context.
| Change the context and the lightning fast reflexes of a fly can
| be made to make it unfit.
| ganafagol wrote:
| I have no idea what the author is trying to say.
|
| Given that they "just recently" learned about microcode, I'd not
| hold my breath expecting a profound insight about computer
| architecture or anything computer science though.
| tyingq wrote:
| Seems to be asking for some sort of optical FPGA thing with the
| hope that light will be immensely faster than electricity.
| Maybe not knowing that it's not?
|
| Also some hints at wanting this "optical FPGA" thing to be
| analog, rather than digital. And some notion that the various
| layers of abstraction (silicon->microcode->asm->code) must be
| wasting lots of cycles.
|
| I'm not really clear on where he thinks 40 years of instant
| fast-forward might come from.
| eecc wrote:
| > Seems to be asking for some sort of optical FPGA thing with
| the hope that light will be immensely faster than
| electricity. Maybe not knowing that it's not?
|
| But really it is. Except for interconnects or analog RF
| stages, ICs aren't built as if they were solid states
| waveguides. Indeed speed is determined by how powerful the
| charge pumps are in moving electrons, not quite the speed of
| EM propagation
| tyingq wrote:
| He's hoping for "a million times faster", and "that it
| might be possible, with today's technology".
| karmakaze wrote:
| On the one hand:
|
| > Could that task be performed by simply the right set of
| transistors, at the hardware level, no matter how insanely
| arranged?
|
| > What shortcuts could be taken?
|
| Seems to be suggesting ASICs as is done with Bitcoin mining. On
| the other about optical rather than electrical which could be
| more efficient, i.e. produce less heat.
|
| I was expecting a completely different post about evolution of
| brains that operate with photons, and another jump to entangled
| ones.
| e9 wrote:
| but that's basically already solved with FPGA, right? You can
| create any circuit on the fly with code.
| rini17 wrote:
| They propose to implement an algorithm such as a trained neural
| network by an single-purpose analog computer (whether
| electronic or optical).
|
| This is sound idea and subject to research but he himself lists
| some disadvantages and I can imagine there are many more.
| Generally, nonlinear analog systems are VERY fickle.
| [deleted]
| claudiojulio wrote:
| One day someone dreamed that he could fly like birds. Today we
| fly much higher and faster than them. Scientific achievement
| always begins with the imagination.
| cycomanic wrote:
| The whole space of analogue computing (circuits) did get a big
| boost in recent years (people had been doing it for years, but it
| never amounted to anything), largely because of the requirements
| of deep learning, which is essentially large matrix
| multiplications. I guess many of the recent ML accelerators fall
| under this category in some way.
|
| There's also been quite a bit of work on using optics (mainly
| integrated optics) for these tasks, but it's still very open if
| that will amount to anything.
|
| All that said, I really would be hesitant to call this computing
| in the traditional sense, it's more like an accelerator card if
| anything.
| pjc50 wrote:
| > Let's say you just wanted to perform just one task. Say,
| recognise a face. Or know whether a number is prime or not. And
| you didn't care about flexibility at all.
|
| > Could that task be performed by simply the right set of
| transistors, at the hardware level, no matter how insanely
| arranged?
|
| For quite a lot of things .. sort of yes. You can do functional
| reduction. Then you get a chip that does exactly one thing. Which
| works great until you want to change it. Since change flexibility
| is incredibly important, that's why we've gone the opposite
| direction and use microcontrollers for things that could be done
| with ASICs.
|
| He misinterprets Thompson though; the strange physical effects of
| the evolved circuits aren't "hidden", they're just _outside the
| model_. We rely on simplified models to make behavior
| predictable, and we design circuits to be as modellable as
| possible and _not use the properties that are hard to model_.
| daralthus wrote:
| I don't get the negativity. This is indeed an emerging field, so
| just going to throw in a few examples:
|
| - Google using RL for chip layout optimization [1]
|
| - Stanford profs optimizing lenses end to end with image
| processing [2]
|
| As for the "diffractive deep neural network" paper it is not
| really a deep network as they don't implement the non-linearities
| in the optical domain. That still is the hard bit, so maybe the
| monocle is not realistic, but fortunately there are ways it can
| still speed up computation.
|
| There is a general consensus that GPU-s enabled the current deep
| learning revolution and perhaps as argued by the Hardware Lottery
| paper [3] backprop is really just the current lucky ticket. So
| why not try to evolve hardware with ML for other algorithms too?
|
| As for the questions raised, I do want to know your answer to
| this:
|
| > a question for computer scientists, what single question would
| you ask if you have a dedicated computer that was [that
| multiplier] faster?
|
| [1] https://ai.googleblog.com/2020/04/chip-design-with-deep-
| rein...
|
| [2] https://www.youtube.com/watch?v=iJdsxXOfqvw
|
| [3] https://hardwarelottery.github.io
| tyingq wrote:
| >I don't get the negativity.
|
| I suppose my response looks negative. What drove that was that
| the writeup seemed to be "high confidence in something very
| unusual[1]" coupled with "very little detail on what he thinks
| would accomplish that[2]".
|
| [1] "Million times faster" "with today's technology" "40 years
| of performance gain"
|
| [2] I gathered only analog vs digital, light instead of
| electricity, and some sort of analog/optical FPGA.
|
| I felt negative only in the sense that the confidence seemed
| very high, but I couldn't see any detail that seemed to support
| it, or enough detail to search elsewhere. Especially with all
| the references that we could do it now.
|
| > a question for computer scientists, what single question
| would you ask if you have a dedicated computer that was [that
| multiplier] faster?
|
| Assuming climate change is the largest threat looming in the
| near future, I suppose better modeling and prediction on what
| to do, and when.
| benhoyt wrote:
| I think this is inspirational but it seems like puffy popular
| science ("pseudo-science" may or may not be too strong?). I'll
| quote what I wrote to a friend about this article:
|
| > It was intriguing and piqued my interest. However, it smells a
| lot like hyped-up crackpot science to me ... if it seems too good
| to be true, it probably is. There's a lot of vagueness here,
| "what ifs", etc. Like "What if we could evolve hardware to make
| use of hidden physics?" Yes, well, what if? What is "hidden
| physics"? And why doesn't the author try it? :-)
|
| > I looked briefly at his bio, and his background is "new media"
| and "addressing abstract social and technological ideas to mixed
| audiences" ... (computer) science, not so much.
|
| > That said, I do like the idea of reducing abstraction layers,
| getting closer to the hardware, and using seemingly-strange
| physics for what it's worth. I'm just very skeptical of his
| framing of it as something which could make everything 1000x
| faster overnight.
|
| > I remember reading a book years ago by "futurist" Michio Kaku
| called Visions. At the time I was really inspired by his
| "visions", which sounded very scientific. However, I think they
| were probably just vague, well, visions. This writing strikes me
| as similar.
| wizzwizz4 wrote:
| > _What is "hidden physics"?_
|
| Physics we don't know about. Our cells are doing that as we
| speak - though we'd probably call most of it "hidden
| biochemistry". I think it unlikely that we'd stumble upon such
| "hidden physics" unless we were evolving objects at close to
| the atomic scale, but it's _possible_ ; perhaps there's some
| way of getting phonons to interact with each other that behaves
| like Brownian motion, and then you can get metaphonons?
|
| The author doesn't try it probably because the author doesn't
| know how. I don't try it because I suspect it's not possible
| with the technology I have access to.
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