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Any correspondence between formal properties of the algorithm, namely, the logical model of the system and its physical properties requires (1) the algorith

Any correspondence between formal properties of the algorithm, namely, the logical model of the system and its physical properties *requires* (1) the algorithm; and (2) the implementation model. Speaking about "computational processes" and "reversibility" at all, absent these, is meaningless. What exactly, of the brain is the "computational process" ? What exactly is "irreversable" ? This is really just pseduo-science, though it may not seem it. We have no idea whatsoever what a logical model of anything to do with animal intelligence is, and hence, absolutely no idea what properties of animals (local to the brain or otherwise) are relevant to them implementing this logical model. To say any process of the brain is "computational" is either to say something useless (namely in the sense in which every process is "presumably, somehow computational, given a logical model") -- or, to say something pseudoscientific. I would agree that animals, in modifying their environments by conceptualising them and developing skillful techniques to regulate themselves in response to them (ie., largely: intelligence), are highly thermodynamically irreversible systems. This isnt a useful observation, given in pseudo-csci terminology, absent a correspondence between this physical facts and the presumed logical model of the computation going on. If the whole of reality is an algorithm, it's one (via energy conservation) which requires zero energy to run. Ie., "logical bit" and "thermal bit" are radically different notions. They are connected contingently when one has an algorithm to-hand, and knows how it will be implemented. There's nothing to be said about the logical bits of animal intelligence, ie., nothing to be said computationally, because we have no idea what they are.

sudosysgen 4y ago
No, there is no pseudo-science there, except when one takes the statements to mean more than they actually mean. >Any correspondence between formal properties of the algorithm, namely, the logical model of the system and its physical properties requires (1) the algorithm; and (2) the implementation model. >Speaking about "computational processes" and "reversibility" at all, absent these, is meaningless. This is simply not true. We start from the assumption (as does all theoretical CS) that computational models are equivalent in capability. We observe that the brain has inputs and outputs. We observe that the outputs are at least partially determined by the inputs. From this, we can conclude rigorously that the brain does computation, and there is thus a computational process going on in the brain. >What exactly, of the brain is the "computational process" ? The correlation between inputs and outputs that follows a process in which information is transformed. This is readily observable. >What exactly is "irreversable" ? It is impossible to reconstruct the input from the output, therefore the computation is said to be irreversible, and is thus subject to various thermodynamic limits. Therefore, we can rigorously conclude that the brain performs irreversible computation. >We have no idea whatsoever what a logical model of anything to do with animal intelligence is, and hence, absolutely no idea what properties of animals (local to the brain or otherwise) are relevant to them implementing this logical model. To say any process of the brain is "computational" is either to say something useless (namely in the sense in which every process is "presumably, somehow computational, given a logical model") -- or, to say something pseudoscientific. Now you're just taking what I said far above and beyond its actual meaning, and taking that interpretation to be pseudo-scientific. I said nothing about intelligence, all I'm saying is that there are computational processes going on inside the brain, and that those are irreversible. We don't need to know what algorithm is going on, nor do we need to know the precise model of computation, to be able to draw conclusions. One of the conclusions we can draw is that the brain executes irreversible computation, and that the general algorithms implementing those computations must not be zero-work. That is done without needing to know the details you seem to argue are necessary to draw such a conclusion. We can also conclude more from this. We can, for example, place lower and upper bounds on the information being processed by various elements. Now, someone could take this methodology and abuse it, or, as the article does, use it in conjunction with supplementary assumptions and go beyond absolute rigour. >If the whole of reality is an algorithm, it's one (via energy conservation) which requires zero energy to run. Ie., "logical bit" and "thermal bit" are radically different notions. They are connected contingently when one has an algorithm to-hand, and knows how it will be implemented. Now you're going way beyond what we can rigorously ascertain. If you consider the whole of reality to be a computer, then what are the inputs, and what are the outputs? Perhaps you consider the process of time to be an algorithm with the past as an input, in which case it is an algorithm that does require energy to run because it's performing irreversible computation, unless there is hidden state somewhere.
- mjburgess 4y ago
  "computation" is only equivalent when it's calculative, ie., when the algorithm in question is merely computing some number. The reason the LCD screen displays some output isn't because the electrical switches have some numerical state, its because they have some electrical state. The sense in which "computer" describes any system is trivial, for there to be any empirical content to computational language, we need an empirical model of the relevant algorithms the computer is performing. My kettle is also a computer: water is its state, boiling is the "computational process", and its change of state is the "number being computed". But it is only a kettle because that "calculation" which computes a number is a magnitude which is implemented by the kinetic state of the water. The sense in which "computers are equivalent" is *empirically empty*. There is no scientific content to this; it is merely a statement of pure mathematics. To use this language, of pure discrete mathematics, as-if it is informative about empirical systems *is pseudo-science*. One may as well say the brain is a geometrical system which is extended in Euclidean space, and we know topologically, that all such systems are geometrically equivalent. The world science studies (unlike that of pure mathematics), is extended in space and time, and has properties (eg., charge, mass, etc.). The number "34029348309384398" is only a frame of a video game when it names (charge, mass, extention, duration...) in a highly particular manner. Unless you have an algorithm in mind, and a model which says how its numerical content corresponds to physical properties, you arent saying anything empirical at all.
  - sudosysgen 4y ago
    >"computation" is only equivalent when it's calculative, ie., when the algorithm in question is merely computing some number. Whoever said that computation has to be with numbers? Here we are seeing the brain as calculative, because the output of the brain is some function of it's input, is it not? Surely we can agree that this is an important, crucial, and interesting function of the brain, that is worthwhile to study? I'm not saying that this is necessarily all that the brain does, but it's an interesting and unresolved dimension of what the brain does, perhaps even the most interesting. >The reason the LCD screen displays some output isn't because the electrical switches have some numerical state, its because they have some electrical state. Sure, I don't see how that's an issue. Why does computation have to be on numerical states? It can be on any kind of state at all, even continuous states. Be it water pressure, base pairs in DNA, luminosity, anything at all that can represent data. In fact, some of the earliest algorithms were operating on lines and circles, which are neither numerical nor even discrete. >My kettle is also a computer: water is its state, boiling is the "computational process", and its change of state is the "number being computed". Sure, you could see it that way. But computation isn't the only thing your kettle is doing - and it's not the interesting part about it either. > The sense in which "computers are equivalent" is empirically empty. There is no scientific content to this; it is merely a statement of pure mathematics. To use this language, of pure discrete mathematics, as-if it is informative about empirical systems is pseudo-science. It's far from purely mathematical, nor pseudo-scientific. Sure, you could define almost anything to do some computation, but that doesn't mean the computation it is doing is worthwhile, or an interesting dimension of its operation. Certainly, however, the computational dimension of the human brain - that is, how it manipulates data - is the most interesting part of it. It's clearly informative - in this case we can conclude that the brain does irreversible computation, and thus establish various bounds on how it operates. > One may as well say the brain is a geometrical system which is extended in Euclidean space, and we know topologically, that all such systems are geometrically equivalent. Sure, we can say that. How is this helpful in this context? Understanding the brain as doing computation is certainly helpful, and perhaps understanding it as topologically equivalent to other objects is too, but I can't really see how. >Unless you have an algorithm in mind, and a model which says how its numerical content corresponds to physical properties, you arent saying anything empirical at all. Again, why does an algorithm even require a numerical content? All an algorithm needs is data, and we clearly have data going in and out, which constrains the physical system that is processing that data.

Any correspondence between formal properties of the algorithm, namely, the logical model of the system and its physical properties *requires* (1) the algorith

sudosysgen 4y ago

No, there is no pseudo-science there, except when one takes the statements to mean more than they actually mean. >Any correspondence between formal properties of the algorithm, namely, the logical model of the system and its physical properties requires (1) the algorithm; and (2) the implementation model. >Speaking about "computational processes" and "reversibility" at all, absent these, is meaningless. This is simply not true. We start from the assumption (as does all theoretical CS) that computational models are equivalent in capability. We observe that the brain has inputs and outputs. We observe that the outputs are at least partially determined by the inputs. From this, we can conclude rigorously that the brain does computation, and there is thus a computational process going on in the brain. >What exactly, of the brain is the "computational process" ? The correlation between inputs and outputs that follows a process in which information is transformed. This is readily observable. >What exactly is "irreversable" ? It is impossible to reconstruct the input from the output, therefore the computation is said to be irreversible, and is thus subject to various thermodynamic limits. Therefore, we can rigorously conclude that the brain performs irreversible computation. >We have no idea whatsoever what a logical model of anything to do with animal intelligence is, and hence, absolutely no idea what properties of animals (local to the brain or otherwise) are relevant to them implementing this logical model. To say any process of the brain is "computational" is either to say something useless (namely in the sense in which every process is "presumably, somehow computational, given a logical model") -- or, to say something pseudoscientific. Now you're just taking what I said far above and beyond its actual meaning, and taking that interpretation to be pseudo-scientific. I said nothing about intelligence, all I'm saying is that there are computational processes going on inside the brain, and that those are irreversible. We don't need to know what algorithm is going on, nor do we need to know the precise model of computation, to be able to draw conclusions. One of the conclusions we can draw is that the brain executes irreversible computation, and that the general algorithms implementing those computations must not be zero-work. That is done without needing to know the details you seem to argue are necessary to draw such a conclusion. We can also conclude more from this. We can, for example, place lower and upper bounds on the information being processed by various elements. Now, someone could take this methodology and abuse it, or, as the article does, use it in conjunction with supplementary assumptions and go beyond absolute rigour. >If the whole of reality is an algorithm, it's one (via energy conservation) which requires zero energy to run. Ie., "logical bit" and "thermal bit" are radically different notions. They are connected contingently when one has an algorithm to-hand, and knows how it will be implemented. Now you're going way beyond what we can rigorously ascertain. If you consider the whole of reality to be a computer, then what are the inputs, and what are the outputs? Perhaps you consider the process of time to be an algorithm with the past as an input, in which case it is an algorithm that does require energy to run because it's performing irreversible computation, unless there is hidden state somewhere.

mjburgess 4y ago
"computation" is only equivalent when it's calculative, ie., when the algorithm in question is merely computing some number. The reason the LCD screen displays some output isn't because the electrical switches have some numerical state, its because they have some electrical state. The sense in which "computer" describes any system is trivial, for there to be any empirical content to computational language, we need an empirical model of the relevant algorithms the computer is performing. My kettle is also a computer: water is its state, boiling is the "computational process", and its change of state is the "number being computed". But it is only a kettle because that "calculation" which computes a number is a magnitude which is implemented by the kinetic state of the water. The sense in which "computers are equivalent" is *empirically empty*. There is no scientific content to this; it is merely a statement of pure mathematics. To use this language, of pure discrete mathematics, as-if it is informative about empirical systems *is pseudo-science*. One may as well say the brain is a geometrical system which is extended in Euclidean space, and we know topologically, that all such systems are geometrically equivalent. The world science studies (unlike that of pure mathematics), is extended in space and time, and has properties (eg., charge, mass, etc.). The number "34029348309384398" is only a frame of a video game when it names (charge, mass, extention, duration...) in a highly particular manner. Unless you have an algorithm in mind, and a model which says how its numerical content corresponds to physical properties, you arent saying anything empirical at all.
- sudosysgen 4y ago
  >"computation" is only equivalent when it's calculative, ie., when the algorithm in question is merely computing some number. Whoever said that computation has to be with numbers? Here we are seeing the brain as calculative, because the output of the brain is some function of it's input, is it not? Surely we can agree that this is an important, crucial, and interesting function of the brain, that is worthwhile to study? I'm not saying that this is necessarily all that the brain does, but it's an interesting and unresolved dimension of what the brain does, perhaps even the most interesting. >The reason the LCD screen displays some output isn't because the electrical switches have some numerical state, its because they have some electrical state. Sure, I don't see how that's an issue. Why does computation have to be on numerical states? It can be on any kind of state at all, even continuous states. Be it water pressure, base pairs in DNA, luminosity, anything at all that can represent data. In fact, some of the earliest algorithms were operating on lines and circles, which are neither numerical nor even discrete. >My kettle is also a computer: water is its state, boiling is the "computational process", and its change of state is the "number being computed". Sure, you could see it that way. But computation isn't the only thing your kettle is doing - and it's not the interesting part about it either. > The sense in which "computers are equivalent" is empirically empty. There is no scientific content to this; it is merely a statement of pure mathematics. To use this language, of pure discrete mathematics, as-if it is informative about empirical systems is pseudo-science. It's far from purely mathematical, nor pseudo-scientific. Sure, you could define almost anything to do some computation, but that doesn't mean the computation it is doing is worthwhile, or an interesting dimension of its operation. Certainly, however, the computational dimension of the human brain - that is, how it manipulates data - is the most interesting part of it. It's clearly informative - in this case we can conclude that the brain does irreversible computation, and thus establish various bounds on how it operates. > One may as well say the brain is a geometrical system which is extended in Euclidean space, and we know topologically, that all such systems are geometrically equivalent. Sure, we can say that. How is this helpful in this context? Understanding the brain as doing computation is certainly helpful, and perhaps understanding it as topologically equivalent to other objects is too, but I can't really see how. >Unless you have an algorithm in mind, and a model which says how its numerical content corresponds to physical properties, you arent saying anything empirical at all. Again, why does an algorithm even require a numerical content? All an algorithm needs is data, and we clearly have data going in and out, which constrains the physical system that is processing that data.