Your brain does not process information, retrieve knowledge or store memories. In short: your brain is not a computer

the-podcast guy recently linked this essay, its old, but i don't think its significantly wrong (despite gpt evangelists) also read weizenbaum, libs, for the other side of the coin

  • Frank [he/him, he/him]4•1 month ago

    Almost all of this is people assuming other people are taking the metaphor to far.

    The mind is best understood, not as software, but rather as an emergent property of the physical brain.

    No one who is worth talking to about this disagrees with this. Everyone is running on systems theory now, including the computer programmers trying to build artificial intelligence. All the plagiarism machines run on systems theory and emergence. The people they're yelling at about reductive computer metaphors are doing the thing the author is saying they don't do, and the plagiarism machines were only possible because people were using systems theory and emergent behaviors arising from software to build the worthless things!

    . The brain is much more complicated than that, and is very likely simply not amenable to that kind of mathematical reductionism, any more than economic systems are.

    This author just said that economics isn't maths, that it's spooky and mysterious and can't be undersyood.

    This is so frustrating. "You see, the brain isn't like this extremely reductive model of computation, it's actually" and then the author just lists every advance, invention, and field of inquiry in computation for the last several decades.

    But looking at the workings of the brain in more detail reveal some more fundamental flaws with computational theory. For one thing, the brain itself isn't structured like a Turing machine. It's a parallel processing network of neural nodes - but not just any network. It's a plastic neural network that can in some ways be actively changed through influences by will or environment. For example, so long as some crucial portions of the brain aren't injured, it's possible for the brain to compensate for injury by actively rewriting its own network. Or, as you might notice in your own life, its possible to improve your own cognition just by getting enough sleep and exercise.

    "The brain isn't a computer, it's actually a different kind of computer! The brain compensates for injury the same way the internet that was in some ways designed after the brain compensates for injury! If you provide the discrete nodes of a distributed network with the inputs they need to function efficiently the performance of the entire network improves!"

    This is just boggling, what argument do they think they're making? Software does all these things specifically because scientists are investigating the functions of the brain and applying what they find to the construction of new computer systems. Our increasing understanding of the brain feeds back to novel computational models which generate new tools, data, and insight for understanding the brain!

    • Tomorrow_Farewell [any, they/them]2•1 month ago

      "The brain isn't a computer, it's actually a different kind of computer! The brain compensates for injury the same way the internet that was in some ways designed after the brain compensates for injury! If you provide the discrete nodes of a distributed network with the inputs they need to function efficiently the performance of the entire network improves!"

      Not even that. They literally did not provide any argument that brains are not structured like Turing machines. Hell, the author seems to not be aware of backup tools in hardware and software, including RAID.

    • @TraumaDumpling1•1 month ago

      https://medium.com/the-spike/yes-the-brain-is-a-computer-11f630cad736

      people are absolutely arguing that the human brain is a turing machine. please actually read the articles before commenting, you clearly didn't read any of them in any detail or understand what they are talking about. a turing machine isn't a specific type of computer, it is a model of how all computing in all digital computers work, regardless of the specific software or hardware.

      https://en.wikipedia.org/wiki/Turing_machine

      A Turing machine is a mathematical model of computation describing an abstract machine[1] that manipulates symbols on a strip of tape according to a table of rules.[2] Despite the model's simplicity, it is capable of implementing any computer algorithm.[3]

      A Turing machine is an idealised model of a central processing unit (CPU) that controls all data manipulation done by a computer, with the canonical machine using sequential memory to store data. Typically, the sequential memory is represented as a tape of infinite length on which the machine can perform read and write operations.

      In the context of formal language theory, a Turing machine (automaton) is capable of enumerating some arbitrary subset of valid strings of an alphabet. A set of strings which can be enumerated in this manner is called a recursively enumerable language. The Turing machine can equivalently be defined as a model that recognises valid input strings, rather than enumerating output strings.

      Given a Turing machine M and an arbitrary string s, it is generally not possible to decide whether M will eventually produce s. This is due to the fact that the halting problem is unsolvable, which has major implications for the theoretical limits of computing.

      The Turing machine is capable of processing an unrestricted grammar, which further implies that it is capable of robustly evaluating first-order logic in an infinite number of ways. This is famously demonstrated through lambda calculus.

      A Turing machine that is able to simulate any other Turing machine is called a universal Turing machine (UTM, or simply a universal machine). Another mathematical formalism, lambda calculus, with a similar "universal" nature was introduced by Alonzo Church. Church's work intertwined with Turing's to form the basis for the Church–Turing thesis. This thesis states that Turing machines, lambda calculus, and other similar formalisms of computation do indeed capture the informal notion of effective methods in logic and mathematics and thus provide a model through which one can reason about an algorithm or "mechanical procedure" in a mathematically precise way without being tied to any particular formalism. Studying the abstract properties of Turing machines has yielded many insights into computer science, computability theory, and complexity theory.