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Comparing Human Brain with a CPU is misconception. In the past when we didn't have digital computers we used to compare Brain with other machines. And now with

by tegeek 6y ago

Comparing Human Brain with a CPU is misconception. In the past when we didn't have digital computers we used to compare Brain with other machines. And now with a CPU. A Brain from a primitive neuron to higher level is not comparable to any machine at all including the CPU.

est31 6y ago
That's what the article does though. And there are experiments trying to simulate parts of brains but we realize that it's extremely hard to do that and we are very far away from simulating even a mouse brain.
The_rationalist 6y ago
Comparing Human Brain with a CPU is misconception. no it is not. Yeah architecturally they are very different and CPU are arguably more programmable / general and less efficient. What does matter is whether CPUs are theoretically able to achieve all the things that a brain can do (and even more) And indeed CPUs as turing complete, programmable machine are a strict superset of what brains can do. The gap between what task and at which accuracy a brain achieve vs a CPU is decreasing each year as you can contemplate on the paperswithcode.com leaderboards. The difficulty is in software, hardware through clusterisation has arguably order of magnitude more compute than a brain has. There are four big missing pieces to match human brain performance: 1) Matching its pattern recognition abilities I believe that current statistical learning techniques of SOTA neural networks actually outperform humans on learning continuous data. But humans outperforms by far current software at zero/few shot learning on sparse/discrete data (where gradient descent is not applicable) I believe humans have this performance edge because of 2), 3) and 4): 2) humans can encode and decode meaning with great accuracy in a high level, descriptive complete declarative language called natural languages. They are in many ways far superior to current GQL/datalog/SQL DB languages at encoding and retrieving meaning (that is an isomorphic description of a denoted thing). The field of semantic parsing (+ question answering from the parsed knowledge) is the key to general language understanding and crucially lack funding. Once machines will be able to understand language and retrieve all the knowledge of say Wikipedia, they will be able to transcend human performance on many intelligence/erudition tasks. 3) humans seems to be able to do meaningful runtime code generation. That is you can develop on demand new solutions to new problems: such as https://www.kaggle.com/c/abstraction-and-reasoning-challenge https://www.kaggle.com/c/abstraction-and-reasoning-challenge The field of specification and implementation generation is too underfunded. 4) is the observation that 3) is probably a necessary key for unlocking 2) and that both 2) and 3) are needed to achieve this communication/feedback loop between high level semantic reasoning and statistical operations. As we can see, humanity overfocus funding on 1) despite being the most solved of all others necessary foundation's to achieve AGI and hence, as a side effect, empirically prove that CPUs superset brains
- JBiserkov 6y ago
  I agree. For some reason 2) and 3) reminded me of the book "The mating mind" https://en.wikipedia.org/wiki/Geoffrey_Miller_(psychologist)#Books https://en.wikipedia.org/wiki/Geoffrey_Miller_(psychologist)...
- otabdeveloper4 6y ago
  The human brain isn't Turing-complete. Turing completeness implies infinite recursion, which the brain obviously can't do.
  - rabryan 6y ago
    Why is that obvious? My brain’s been infinitely recursing for years as far as I know
  - lagadu 6y ago
    Technically Turing completeness requires infinite memory for that (or an infinite tape if we're talking about the original turing machine concept), which no Turing-complete machine has. In other words, the brain is as Turing-complete as any machine that we also consider to be so. We'll always be bounded by limited memory and limited time.
    - SomeoneFromCA 6y ago
      We do not know if human brain is indeed Turing-complete, or even if it is a Turing machine at all. Human Mind certainly is, but if brain is or not we do not know.
  - mannykannot 6y ago
    While I agree that comparing a human brain or mind to a Turing machine is not helpful, the objection you make here is less significant than it first appears. There is a subtle difference between unbounded recursion, which a Turing machine is taken to be capable of, and the actual ability to achieve infinite recursion. In no application of a Turing machine, either as an actual physical device or as a hypothetical one in a logical argument, is it ever required to perform infinite recursion, which would just be one way of not halting. For all practical and theoretical purposes, what matters is that the machine being considered does not exhaust its ability to recurse while performing the computations being considered. Consequently, the standard practice, of saying that computers and certain other devices are Turing-equivalent, with the usually-implicit caveat of being so up to the limit of their recursive ability, is both reasonable and useful.
ResidentSleeper 6y ago
Whether or not it's comparable depends on the level of distinction you're trying to make. Obviously, CPUs don't think or experience the world (but on the other hand that kind of "feature" seems increasingly likely to be implementable in software, even if our current CPU architectures are rather unsuitable for that goal). However, if we're gonna talk about energy efficiency and computation performance, now that it has become evident that the brain is merely a kind of a computer, we can definitely look for parallels.
- kalcode 6y ago
  > now that it has become evident that the brain is merely a kind of a computer I am ignorant in this area. But I keep reading how brains are nothing like computers the more we learn. Your statement seems to suggest otherwise and id love to read about it. Can you drop something where I can start exploring about how the brain has become more evident that it's merely a kind of computer? Thanks!
  - whatshisface 6y ago
    The brain is thought to be merely a computer in the original sense of a long strip of paper along with a scribe and a rulebook. The logic is, a Turing machine can simulate quantum electrodynamics to an arbitrary degree of accuracy. Then, two beliefs about physics and the structure of the brain are included: 1. There is nothing going on in the brain that would require simulation to infinite accuracy. Not even a chaotic system would have this property, because they take a finite time to "blow up" an initial uncertainty, and the smaller the initial uncertainty the longer they take to blow up. For this proposition to be violated there would have to be an undiscovered fininite-time nondeterministic blowup, which is unlikely, but I've heard rumblings that we haven't proven that it can't happen in Navier-Stokes. So maybe it can happen in the brain. 2. There is nothing going on in the brain that depends on nuclear physics or anything more "powerful" than quantum electrodynamics. I have not seen any evidence that 1 or 2 aren't true for the brain, so that puts something behind saying it's "merely a computer."
  - checkyoursudo 6y ago
    If you are looking for a book for an introduction, I would suggest Mindware by Andy Clark is pretty reasonable. Pub 2014; ISBN: 9780199828159
sa1 6y ago
Computers are mathematical concepts, Turing machines being one such concept. Whether computers are implemented using silicon, or oil, or using neurons, it doesn't really matter as we have a mathematical framework for describing abstract machines, and we can determine what is a machine, and what is not. We did not have this mathematical framework before the age of Turing, Church, Russel, et al. This doesn't mean that brains are very similar to CPUs, they are not, just like they were not similar to mechanical machines before. Yet we do now have a way of studying the similarities they have.
derefr 6y ago
The difference is that CPUs, unlike those other machines, can be used to model/simulate things that are similar to brains. There is impedance in the translation, of course, but that impedance can be measured as a sort of “distance” between the architectures; just like one might measure the “distance” between two Instruction Set Architectures.
kyuudou 6y ago
"...the question of whether Machines Can Think, a question of which we now know that it is about as relevant as the question of whether Submarines Can Swim." Edsger Dijkstra, EWD898, 1984

by tegeek 6y ago

est31 6y ago

That's what the article does though. And there are experiments trying to simulate parts of brains but we realize that it's extremely hard to do that and we are very far away from simulating even a mouse brain.

The_rationalist 6y ago

Comparing Human Brain with a CPU is misconception. no it is not. Yeah architecturally they are very different and CPU are arguably more programmable / general and less efficient. What does matter is whether CPUs are theoretically able to achieve all the things that a brain can do (and even more) And indeed CPUs as turing complete, programmable machine are a strict superset of what brains can do. The gap between what task and at which accuracy a brain achieve vs a CPU is decreasing each year as you can contemplate on the paperswithcode.com leaderboards. The difficulty is in software, hardware through clusterisation has arguably order of magnitude more compute than a brain has. There are four big missing pieces to match human brain performance: 1) Matching its pattern recognition abilities I believe that current statistical learning techniques of SOTA neural networks actually outperform humans on learning continuous data. But humans outperforms by far current software at zero/few shot learning on sparse/discrete data (where gradient descent is not applicable) I believe humans have this performance edge because of 2), 3) and 4): 2) humans can encode and decode meaning with great accuracy in a high level, descriptive complete declarative language called natural languages. They are in many ways far superior to current GQL/datalog/SQL DB languages at encoding and retrieving meaning (that is an isomorphic description of a denoted thing). The field of semantic parsing (+ question answering from the parsed knowledge) is the key to general language understanding and crucially lack funding. Once machines will be able to understand language and retrieve all the knowledge of say Wikipedia, they will be able to transcend human performance on many intelligence/erudition tasks. 3) humans seems to be able to do meaningful runtime code generation. That is you can develop on demand new solutions to new problems: such as https://www.kaggle.com/c/abstraction-and-reasoning-challenge https://www.kaggle.com/c/abstraction-and-reasoning-challenge The field of specification and implementation generation is too underfunded. 4) is the observation that 3) is probably a necessary key for unlocking 2) and that both 2) and 3) are needed to achieve this communication/feedback loop between high level semantic reasoning and statistical operations. As we can see, humanity overfocus funding on 1) despite being the most solved of all others necessary foundation's to achieve AGI and hence, as a side effect, empirically prove that CPUs superset brains

JBiserkov 6y ago
I agree. For some reason 2) and 3) reminded me of the book "The mating mind" https://en.wikipedia.org/wiki/Geoffrey_Miller_(psychologist)#Books https://en.wikipedia.org/wiki/Geoffrey_Miller_(psychologist)...
otabdeveloper4 6y ago
The human brain isn't Turing-complete. Turing completeness implies infinite recursion, which the brain obviously can't do.
- rabryan 6y ago
  Why is that obvious? My brain’s been infinitely recursing for years as far as I know
- lagadu 6y ago
  Technically Turing completeness requires infinite memory for that (or an infinite tape if we're talking about the original turing machine concept), which no Turing-complete machine has. In other words, the brain is as Turing-complete as any machine that we also consider to be so. We'll always be bounded by limited memory and limited time.
  - SomeoneFromCA 6y ago
    We do not know if human brain is indeed Turing-complete, or even if it is a Turing machine at all. Human Mind certainly is, but if brain is or not we do not know.
- mannykannot 6y ago
  While I agree that comparing a human brain or mind to a Turing machine is not helpful, the objection you make here is less significant than it first appears. There is a subtle difference between unbounded recursion, which a Turing machine is taken to be capable of, and the actual ability to achieve infinite recursion. In no application of a Turing machine, either as an actual physical device or as a hypothetical one in a logical argument, is it ever required to perform infinite recursion, which would just be one way of not halting. For all practical and theoretical purposes, what matters is that the machine being considered does not exhaust its ability to recurse while performing the computations being considered. Consequently, the standard practice, of saying that computers and certain other devices are Turing-equivalent, with the usually-implicit caveat of being so up to the limit of their recursive ability, is both reasonable and useful.

ResidentSleeper 6y ago

Whether or not it's comparable depends on the level of distinction you're trying to make. Obviously, CPUs don't think or experience the world (but on the other hand that kind of "feature" seems increasingly likely to be implementable in software, even if our current CPU architectures are rather unsuitable for that goal). However, if we're gonna talk about energy efficiency and computation performance, now that it has become evident that the brain is merely a kind of a computer, we can definitely look for parallels.

kalcode 6y ago
> now that it has become evident that the brain is merely a kind of a computer I am ignorant in this area. But I keep reading how brains are nothing like computers the more we learn. Your statement seems to suggest otherwise and id love to read about it. Can you drop something where I can start exploring about how the brain has become more evident that it's merely a kind of computer? Thanks!
- whatshisface 6y ago
  The brain is thought to be merely a computer in the original sense of a long strip of paper along with a scribe and a rulebook. The logic is, a Turing machine can simulate quantum electrodynamics to an arbitrary degree of accuracy. Then, two beliefs about physics and the structure of the brain are included: 1. There is nothing going on in the brain that would require simulation to infinite accuracy. Not even a chaotic system would have this property, because they take a finite time to "blow up" an initial uncertainty, and the smaller the initial uncertainty the longer they take to blow up. For this proposition to be violated there would have to be an undiscovered fininite-time nondeterministic blowup, which is unlikely, but I've heard rumblings that we haven't proven that it can't happen in Navier-Stokes. So maybe it can happen in the brain. 2. There is nothing going on in the brain that depends on nuclear physics or anything more "powerful" than quantum electrodynamics. I have not seen any evidence that 1 or 2 aren't true for the brain, so that puts something behind saying it's "merely a computer."
- checkyoursudo 6y ago
  If you are looking for a book for an introduction, I would suggest Mindware by Andy Clark is pretty reasonable. Pub 2014; ISBN: 9780199828159

sa1 6y ago

Computers are mathematical concepts, Turing machines being one such concept. Whether computers are implemented using silicon, or oil, or using neurons, it doesn't really matter as we have a mathematical framework for describing abstract machines, and we can determine what is a machine, and what is not. We did not have this mathematical framework before the age of Turing, Church, Russel, et al. This doesn't mean that brains are very similar to CPUs, they are not, just like they were not similar to mechanical machines before. Yet we do now have a way of studying the similarities they have.

derefr 6y ago

The difference is that CPUs, unlike those other machines, can be used to model/simulate things that are similar to brains. There is impedance in the translation, of course, but that impedance can be measured as a sort of “distance” between the architectures; just like one might measure the “distance” between two Instruction Set Architectures.

kyuudou 6y ago

"...the question of whether Machines Can Think, a question of which we now know that it is about as relevant as the question of whether Submarines Can Swim." Edsger Dijkstra, EWD898, 1984