4 ms·
Your very valid points are - in my reading - addressed in this paper, albeit in a milder and more forgiving form, in the Results section under A Baseline for Ma
by dav_Oz 4y ago
Your very valid points are - in my reading - addressed in this paper, albeit in a milder and more forgiving form, in the Results section under A Baseline for Maximally Efficient Computation.
A simplistic model relates physics to neuroscience.
Especially:
That is, physics looks at each computational element only as a solitary individual, performing but a single operation. There is no consideration that each neuron participates in a large network or even that a logical gate must communicate its inference in a digital computer in a timely manner. Unlike idealized physics, Nature cannot afford to ignore the energy requirements arising from communication and time constraints that are fundamental network considerations (43) and fundamental to survival itself (especially time) (18, 19).
I wouldn't call it outright pseudo-science as the authors are trying to impose some limited working framework with very technical meanings of "communication" and "computation" in this context. I too, find this "physics"/"cs" excursion very basic and questionable which kind of points to the purpose of that paper: demonstrating an exercise. And as a general symptom the difficulty to overcome the shallow waters of interdisciplinary fields/approaches.
[From my own experience in talking with biologists only after awhile I begin to appreciate the deep complexities of biological/biochemical systems, only to - after some time has passed - forget those subtleties again.
I'm so used to simplify from my physics background that it is actually quite hard to recognize important distinctions in different (more complex) fields which can lead to vastly different mathematical models.]
- mjburgess 4y agoIf this were one paper in isolation, I'd call it an honest attempt at good science gone-wrong by a lack of consultation with theoretical computer scientists and specialists in thermodynamics. However, I think this is just *the entire field* -- which is then different. I think a whole field is pseudoscience when it systematically engages in the same games. I think likewise of much fMRI work,... all the way to basically the whole of nutritional science, etc. If the premises of your project can be pretty quickly falsified by relevant domain experts, and you build a whole field out of it, you slip into my category of "pseudoscience". This paper explicitly tries to prescribe to engineers (!!!) where their "focus" should be, having absolutely no warrant to do so. A trivial application of the same analysis to CPUs would provide the relevant baseline comparison the paper should have made. With this analysis, the key results of the paper would be exposed as useless. I have little sympathy for all this now: it's a research hype cycle craze to apply random bits of computer science to random bits of science in the most hairbrained manner.
- 867-5309 4y ago>it's a research hype cycle craze perhaps you should address this in a counter paper rather than an HN comment. researchers have to justify grant money and regularly twist the facts to accomplish this, that's just how the system operates. let the dregs drag and the Einsteins elevate. a large percentage of "research" quite rightly never sees the light of day. groundbreaking and globally impacting discoveries and inventions are only a few in a century
- deleted 4y ago[deleted]