[HN Gopher] Why not faster computation via evolution and diffrac... ___________________________________________________________________ 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. ___________________________________________________________________ (page generated 2021-04-24 23:01 UTC)