"However, we should be careful with the metaphors and paradigms commonly introduced when dealing with the nervous system. It seems to be a
constant in the history of science that the brain has always been compared
to the most complicated contemporary artifact produced by human industry
[297]. In ancient times the brain was compared to a pneumatic machine, in
the Renaissance to a clockwork, and at the end of the last century to the telephone network. There are some today who consider computers the paradigm
par excellence of a nervous system. It is rather paradoxical that when John
von Neumann wrote his classical description of future universal computers, he
tried to choose terms that would describe computers in terms of brains, not
brains in terms of computers."
I have no idea what the submitted MIT article is trying to say. Does the MIT article try to make the point that neural networks can be used for computation given ridiculous amounts of memory? They can, but that still does not explain real intelligence. Otherwise, the article makes the same mistakes as pointed out in the above quote.
I don't see the point of asking this question. Like, sure, all physical systems follow certain rules, so any such process will develop in a way that it look like a computation of an algorithm. Also, evolution itself is constantly optimizing organisms to best adapt to their environment, just like a computation.
So asking if life is a computation seems mostly like a semantic musing. Define "life" and define "computation", then see if they're the same.
This feels like the kind of popsci that's written for people who already agree with the author - there's nothing resembling an argument, or even a definition of "computation." There are nods to Church-Turing, but the leap from "every effectively calculable function is computable" to "life is a computation" is larger than anything you could fit in a book.
Is the author advancing a new argument? Has anyone read the book? A quick review suggests that the author posits that symbiogenesis is central to evolution, and artificial intelligence. This is interesting because I recall no mention of this mechanism in the current AI literature. The promise of a symbiotic relationship with artificial life sounds like a balm to people anxious about the future. It is a possibility, not a certainty. https://en.wikipedia.org/wiki/Symbiogenesis
there are criticisms of life as classical computation or in a more restricted context, cognition as computation [1] - one of which amounts to this: for any computation, there is a frame of reference in which that computation can be modeled, and if so, that frame of reference itself cannot be modeled by said computation.
The basic parameters of affective neuroscience make it difficult to conflate actions with computations. Because there isn't a content to thought, thoughts aren't about things, brains/CNS/bodies lack any units that could be computed, there's only an arbitrary sleight of hand linking life and computation.
I like the idea instead that some biological components have deterministic optimizations because they’re closer to a molecular form, like DNA, RNA, some protein machinery, etc. because essentially these are driven by some kind of chemistry and physics. Whereas higher level, emergent biological forms are more stochastic in their function, like organelles, an organism, or populations, etc. In that sense, there’s no computation to life, more that life is constrained by the physics of the world in which it develops.
It’s likely if different life forms on another planet, it will have a different “computation” model because its defined by different physics that it experiences during evolution. Though I suppose there will some similarities depending on some fundamental rules of the universe. Will propagation molecules like RNA or DNA always look like helixes, or will the radiation or physics of another planet create another form of propagation molecule we haven’t yet observed. Might make for an interesting experiment to simulate.
this question reminded me of the poetry of terrence mckenna. "Technology is the real skin of our species. Humanity, correctly seen in the context of the last five hundred years, is an extruder of technological material. We take in matter that has a low degree of organization; we put it through mental filters, and we extrude jewelry, gospels, space shuttles. This is what we do. We are like coral animals embedded in a technological reef of extruded psychic objects. All our tool making implies our belief in an ultimate tool. That tool is the flying saucer, or the soul, exteriorized in three-dimensional space."
No, and this is a very philosophically confused post because it weirdly does not really give any definition of computation.
Computation really is a fancy word for calculation. What matters about computation is that its teleological. Computers are physical systems designed towards a particular end. A computer is, physically, no different than any other system. What differentiates it is that it's designed and we're interpreting its behaviour in a particular way.
Unless you're trying to make a grand theological argument in which "life" is taken to be some Hitchhikers Guide-like machination towards some end, it's not a computation. Life doesn't compute anything, the same way a falling pen doesn't compute gravity unless in a metaphorical sense.
The article is a pretty good example honestly of the problems of taking metaphors literally, common in the AI space where the author hails from. A similar case "artificial neurons" which are really metaphorical neurons. You have to be particularly careful when making comparisons between intentionally designed technological artifacts and biological and physical processes.
Articles like this indicate we should lock down the definition of "computation" that meaningfully distinguishes computing machines from other physical phenomena - a computation is a process that maps symbols (or strings of symbols) to other symbols, obeying certain simple rules[1]. A computer is a machine that does computations.
In that sense life is obviously not a computation: it makes some sense to view DNA as symbolic but it is misleading to do the same for the proteins they encode. These proteins are solving physical problems, not expressing symbolic solutions to symbolic problems - a wrench is not a symbolic solution to the problem of a symbolic lug nut. From this POV the analogy of DNA to computer program is just wrong: they are both analogous to blueprints, but not particularly analogous to each other. We should insist that DNA is no more "computational" than the rules that dictate how elements are formed from subatomic particles.
I love thinking about life as computation. Cells are computers, enzymes are functions, ribosomes are compilers, nucleic acids are source code...
Enzymes in particular are a lot like unix pipelines. An enzyme catalyzes its substrate's conversion into its product which is the substrate of another enzyme. When cells ingest glucose, it flows through the glycolysis metabolic pathway until it becomes pyruvate, and may be reduced even further depending on available resources. It's a huge pipeline of enzymes. They just kinda float around within the cell and randomly perform their tasks when their substrates chemically interact with them. No explicit program exists, it emerges from the system within the cell.
Cell - Computer
Enzyme - Function / Process / Filter
Substrate - Data
Product - Data
Metabolic pathway - Program / Script
I've been playing in my mind with an idea for an esoteric programming language modeled around enzymes. The program defines a set of enzymes which are functions that match on the structure of data, automatically apply themselves to them and produce a modified version of the input which may in turn match against other enzymes. The resulting program metabolizes input by looping over the set of enzymes and continuously matching and applying them until the data is reduced to its final form. If no enzymes match, the output is the unmodified input.
I'm not too impressed with this article since it doesn't really give a definition for computing, just picks a few similarities between what we see as computing (in the practical sense) and what cells do.
It's a shame because there *has* been a lot of deep work done on what kind of computer life is.
People often use the Chomsky Hierarchy (https://en.wikipedia.org/wiki/Chomsky_hierarchy) to define the different types of computer vs automata. Importantly, a classical Turing machine is Type-0 on the Chomsky Hierarchy. Depending on what parts you include from a biological system, you could argue it's anywhere from Type-0 to Type-4.
Interestingly, the PhD thesis of well-known geneticist Aviv Regev was to show that certain combinations of enzymes with chemical concentration states are enough to emulate pi-calculus, and therefore are Turing machines!
https://psb.stanford.edu/psb-online/proceedings/psb01/regev....
The Aviv Regev paper you link was recently recommended to me as a useful reference for something. It was a nice surprise to see that Regev's thesis advisor was Ehud Shapiro, known to the Prolog community from his co-authorship of one of the good Prolog books (The Art of Prolog, with Leon Sterling - https://mitpress.mit.edu/9780262691635/the-art-of-prolog/). Indeed, Regev's thesis (and the paper above) propose a system based on a Flat Concurrent Prolog.
Shapiro was also the author of one of the two PhD theses that were a major influence to Inductive Logic Programming, a field at the intersection of logic programming and machine learning.
A lot of the kind of "deep work" you mention used to be done in the logic programming and ILP community in times past, before everyone seemingly switched to neural nets and statistical machine learning.
No, obviously not. This is just clickbait and self-congratulation for the tech industry. Computation is not the end-all of every process or entropy flow. Please get better philosophy.
49 comments
[ 5.2 ms ] story [ 59.6 ms ] threadCould you pull out the specific list of ATCG and make a brain
https://www.inf.fu-berlin.de/inst/ag-ki/rojas_home/documents...
"However, we should be careful with the metaphors and paradigms commonly introduced when dealing with the nervous system. It seems to be a constant in the history of science that the brain has always been compared to the most complicated contemporary artifact produced by human industry [297]. In ancient times the brain was compared to a pneumatic machine, in the Renaissance to a clockwork, and at the end of the last century to the telephone network. There are some today who consider computers the paradigm par excellence of a nervous system. It is rather paradoxical that when John von Neumann wrote his classical description of future universal computers, he tried to choose terms that would describe computers in terms of brains, not brains in terms of computers."
I have no idea what the submitted MIT article is trying to say. Does the MIT article try to make the point that neural networks can be used for computation given ridiculous amounts of memory? They can, but that still does not explain real intelligence. Otherwise, the article makes the same mistakes as pointed out in the above quote.
So asking if life is a computation seems mostly like a semantic musing. Define "life" and define "computation", then see if they're the same.
https://publicservicesalliance.org/2025/05/24/what-is-intell...
[1] https://plato.stanford.edu/entries/computational-mind/#GodIn...
[1] https://www.youtube.com/watch?v=0FUFewGHLLg
It’s likely if different life forms on another planet, it will have a different “computation” model because its defined by different physics that it experiences during evolution. Though I suppose there will some similarities depending on some fundamental rules of the universe. Will propagation molecules like RNA or DNA always look like helixes, or will the radiation or physics of another planet create another form of propagation molecule we haven’t yet observed. Might make for an interesting experiment to simulate.
Computation really is a fancy word for calculation. What matters about computation is that its teleological. Computers are physical systems designed towards a particular end. A computer is, physically, no different than any other system. What differentiates it is that it's designed and we're interpreting its behaviour in a particular way.
Unless you're trying to make a grand theological argument in which "life" is taken to be some Hitchhikers Guide-like machination towards some end, it's not a computation. Life doesn't compute anything, the same way a falling pen doesn't compute gravity unless in a metaphorical sense.
The article is a pretty good example honestly of the problems of taking metaphors literally, common in the AI space where the author hails from. A similar case "artificial neurons" which are really metaphorical neurons. You have to be particularly careful when making comparisons between intentionally designed technological artifacts and biological and physical processes.
In that sense life is obviously not a computation: it makes some sense to view DNA as symbolic but it is misleading to do the same for the proteins they encode. These proteins are solving physical problems, not expressing symbolic solutions to symbolic problems - a wrench is not a symbolic solution to the problem of a symbolic lug nut. From this POV the analogy of DNA to computer program is just wrong: they are both analogous to blueprints, but not particularly analogous to each other. We should insist that DNA is no more "computational" than the rules that dictate how elements are formed from subatomic particles.
[1] Turing computability, lambda definability, primitive recursion, whatever.
Enzymes in particular are a lot like unix pipelines. An enzyme catalyzes its substrate's conversion into its product which is the substrate of another enzyme. When cells ingest glucose, it flows through the glycolysis metabolic pathway until it becomes pyruvate, and may be reduced even further depending on available resources. It's a huge pipeline of enzymes. They just kinda float around within the cell and randomly perform their tasks when their substrates chemically interact with them. No explicit program exists, it emerges from the system within the cell.
I've been playing in my mind with an idea for an esoteric programming language modeled around enzymes. The program defines a set of enzymes which are functions that match on the structure of data, automatically apply themselves to them and produce a modified version of the input which may in turn match against other enzymes. The resulting program metabolizes input by looping over the set of enzymes and continuously matching and applying them until the data is reduced to its final form. If no enzymes match, the output is the unmodified input.It's a shame because there *has* been a lot of deep work done on what kind of computer life is. People often use the Chomsky Hierarchy (https://en.wikipedia.org/wiki/Chomsky_hierarchy) to define the different types of computer vs automata. Importantly, a classical Turing machine is Type-0 on the Chomsky Hierarchy. Depending on what parts you include from a biological system, you could argue it's anywhere from Type-0 to Type-4.
Interestingly, the PhD thesis of well-known geneticist Aviv Regev was to show that certain combinations of enzymes with chemical concentration states are enough to emulate pi-calculus, and therefore are Turing machines! https://psb.stanford.edu/psb-online/proceedings/psb01/regev....
Shapiro was also the author of one of the two PhD theses that were a major influence to Inductive Logic Programming, a field at the intersection of logic programming and machine learning.
A lot of the kind of "deep work" you mention used to be done in the logic programming and ILP community in times past, before everyone seemingly switched to neural nets and statistical machine learning.