3 ms·

> Ok, but my argument wasn’t with the OP mentioning capacity, but with their analogy. Am I not allowed to break down that analogy with evidence? If someone mak

> Ok, but my argument wasn’t with the OP mentioning capacity, but with their analogy. Am I not allowed to break down that analogy with evidence? If someone makes an analogy between aspects of A and B, then there is an implicit assumed shared understanding that A & B are DIFFERENT, and what is being pointed out is that they nonetheless may be considered as having something, typically fairly abstract, in common. Calling a horse's reins as analogous to a cars steering wheel doesn't mean that the person making the analogy can't tell a horse from a car - that would be a very dumb take. A reasonable criticism might be "it's an imperfect analogy since the reins also act as the brake". If you disagree with an analogy, then you need to address the analogy, not do the dumb take of "a horse is not a car" ("a brain is not a computer"). So, yes, you're "allowed" to "break down" (criticize) the analogy, but please don't just do the dumb take. So, hash key collisions are not analogous to associative recall and sparse embedding overlaps in what way?

randomImmigrant 2mo ago
> Calling a horse's reins as analogous to a cars steering wheel doesn't mean that the person making the analogy can't tell a horse from a car When a person says “I crashed the car because my steering wheel tore, like reigns tear”, they are overfitting their analogy, and it’s perfectly fine to point out the structural and physical differences that make the analogy useless for the question at hand. You have dismissed the biology that shows the problems with your analogy as immaterial. And continue to insist it’s the right one for the question at hand. This is a pretty pickle, because no facts can shake you from your certainty that you're right. You seem in love with your analogy no matter how incorrect it is. And I have no problem with that. But when you put half baked biological claims to support it, I’ll point it out. If that’s too much for you to bear, maybe come up with better analogies?
- HarHarVeryFunny 1mo ago
  > You seem in love with your analogy Where the hell did you get that from?! I mentioned the hash table / embedding space analogy precisely ONCE, in my initial post, and, just to try to avoid people like yourself being triggered by it, I even included "obviously the brain is not a computer". But you still got triggered by it, still did the dumb take of "a brain is not a computer" (no shit - I just said that), then spent your entire energy on fighting your own strawmen and not once even responding to my actual suggestion. Now, finally, you are asking "what is a sparse embedding"! Maybe next time don't bother responding to something if you don't even understand what is being talked about.
  - chermi 1mo ago
    He hadn't even considered whether capacity was well defined in a distributed system. He has a brand spanking new theory that allows him to jump straight past abstractions and simplifications and "ancient 1980s views"[1] and "fun curiosities" like the basics of dynamics, structure, organization, and composition described in an ancient book (2000s) he couldn't possibly learn anything from because he's a biologist and knows better. Nevermind that it smells an awful lot like [2]. But he doesn't need to know anything about it it or acknowledge it because dummy non-biologists couldn't possibly help someone as smart as him. [1] https://www.pnas.org/doi/pdf/10.1073/pnas.79.8.2554 https://www.pnas.org/doi/pdf/10.1073/pnas.79.8.2554 a paper he confidentally rejected as meaningless, unaware and not interested in the overwhelmingly likely possibility that his current brand new ideas trace back to it. [2] "I’m stitching across a lot of different research, and I want to be clear many aspects of this system are not yet fully worked out. But what we do know points to a system that works with different physical and algorithmic priors, and the dynamics are sharply distinct from current digital computers." Hmm, I wonder if "we" figured that stuff out from individual and especially collaborative efforts combining abstractions and more theoretical approaches with expertise in biology, not to mention EE, biophysics, physics, and whatever else other fields that don't know about his favorite molecule and thus can be ignored if not shit on?
chermi 2mo ago
Kind of done with the other guy, but reading this reminded me of a paper I saw a while ago but admit I haven't read yet. https://journals.aps.org/prx/pdf/10.1103/6shh-9h5m https://journals.aps.org/prx/pdf/10.1103/6shh-9h5m It's more about computational complexity it seems but maybe it cites stuff that might interest you. It's using computational neural networks that no one has ever believed represent the biology of the brain, but I think I must still disclose the following to save the precious time of the genius solving the problem all by himself: It doesn't fully account for every biological detail ever documented, so it's probably a meaningless "curiosity". Oh it probably also doesn't account for every detail discovered since publication so even if had value at time of publication it is not worth reading now.

randomImmigrant 2mo ago

> Calling a horse's reins as analogous to a cars steering wheel doesn't mean that the person making the analogy can't tell a horse from a car When a person says “I crashed the car because my steering wheel tore, like reigns tear”, they are overfitting their analogy, and it’s perfectly fine to point out the structural and physical differences that make the analogy useless for the question at hand. You have dismissed the biology that shows the problems with your analogy as immaterial. And continue to insist it’s the right one for the question at hand. This is a pretty pickle, because no facts can shake you from your certainty that you're right. You seem in love with your analogy no matter how incorrect it is. And I have no problem with that. But when you put half baked biological claims to support it, I’ll point it out. If that’s too much for you to bear, maybe come up with better analogies?

HarHarVeryFunny 1mo ago
> You seem in love with your analogy Where the hell did you get that from?! I mentioned the hash table / embedding space analogy precisely ONCE, in my initial post, and, just to try to avoid people like yourself being triggered by it, I even included "obviously the brain is not a computer". But you still got triggered by it, still did the dumb take of "a brain is not a computer" (no shit - I just said that), then spent your entire energy on fighting your own strawmen and not once even responding to my actual suggestion. Now, finally, you are asking "what is a sparse embedding"! Maybe next time don't bother responding to something if you don't even understand what is being talked about.
- chermi 1mo ago
  He hadn't even considered whether capacity was well defined in a distributed system. He has a brand spanking new theory that allows him to jump straight past abstractions and simplifications and "ancient 1980s views"[1] and "fun curiosities" like the basics of dynamics, structure, organization, and composition described in an ancient book (2000s) he couldn't possibly learn anything from because he's a biologist and knows better. Nevermind that it smells an awful lot like [2]. But he doesn't need to know anything about it it or acknowledge it because dummy non-biologists couldn't possibly help someone as smart as him. [1] https://www.pnas.org/doi/pdf/10.1073/pnas.79.8.2554 https://www.pnas.org/doi/pdf/10.1073/pnas.79.8.2554 a paper he confidentally rejected as meaningless, unaware and not interested in the overwhelmingly likely possibility that his current brand new ideas trace back to it. [2] "I’m stitching across a lot of different research, and I want to be clear many aspects of this system are not yet fully worked out. But what we do know points to a system that works with different physical and algorithmic priors, and the dynamics are sharply distinct from current digital computers." Hmm, I wonder if "we" figured that stuff out from individual and especially collaborative efforts combining abstractions and more theoretical approaches with expertise in biology, not to mention EE, biophysics, physics, and whatever else other fields that don't know about his favorite molecule and thus can be ignored if not shit on?

chermi 2mo ago

Kind of done with the other guy, but reading this reminded me of a paper I saw a while ago but admit I haven't read yet. https://journals.aps.org/prx/pdf/10.1103/6shh-9h5m https://journals.aps.org/prx/pdf/10.1103/6shh-9h5m It's more about computational complexity it seems but maybe it cites stuff that might interest you. It's using computational neural networks that no one has ever believed represent the biology of the brain, but I think I must still disclose the following to save the precious time of the genius solving the problem all by himself: It doesn't fully account for every biological detail ever documented, so it's probably a meaningless "curiosity". Oh it probably also doesn't account for every detail discovered since publication so even if had value at time of publication it is not worth reading now.