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 think the issue with this way of thinking is that humans think in abstractions.
Abstractions don't really exist, they're a product of the human mind, but then we apply them to nature. Calling DNA code, comparing NNs and the brain, etc. But those abstractions fall apart when you look a little too deeply at what actually happens in nature.
Is DNA code? Or is it more like a machine? Is it neither, or is it something embedded in such a complex space that our simple abstractions can't capture the full nature of its being?
When you look at the nature of DNA, it does more than simply act as code. It can edit and self-modify, self-assemble, self-replicate, it can turn genes on and off, it can perform what can be argued as computations itself. If you limit yourself to thinking of it as code, you might miss crucial ways it exists/performs in real life.
> When you look at the nature of DNA, it does more than simply act as code.
> It can edit and self-modify, self-assemble, self-replicate, it can turn genes on and off
Unless my knowledge of biology is very outdated or incomplete, all of those things you cited are done to DNA. They don't happen spontaneously.
DNA doesn't self-replicate, a whole bunch of enzymes come and actively copy it. Genes don't spontaneously turn on and off, some enzyme comes and attaches or removes a methyl group. DNA doesn't self-assemble, it is actively coiled around histones to form nucleosomes. Bacteria have a huge variety of enzymes for manipulating native and foreign DNA, they have their own CRISPR mechanisms.
I'm thinking more of early RNA and DNA life, where ideas like the RNA-world might have happened and applied. RNA can assemble, replicate, and catalyze to form deoxynucleosides in a proto-DNA, without "outside" work needing to happen from enzymes/proteins/etc.
Similarly, RNA and DNA "machines" could have existed before cellular life, in which genetic material self-assembled, transferred genes horizontally/vertically, etc, blurring the lines between genes as "code" and something else.
I think RNA (in particular, ribozymes) does those things.
But DNA is effectively separation of concerns: RNA systems evolved to RNA mediated systems with DNA as more inert and reliable storage and enzymes as more effective catalysts. Or so the RNA world hypothesis goes.
> I think the issue with this way of thinking is that humans think in abstractions.
Isn't that the entire point of making abstractions? Understanding things "as they are" is impossible, so we need simplifications. Of course it should be appreciated that the abstractions are always "wrong".
"A map is not the territory it represents, but, if correct, it has a similar structure to the territory, which accounts for its usefulness."
I think the point is more that if you’re saying one abstraction is similar to another abstraction, you run the risk of over-analyzing the abstraction level and not the thing-in-itself.
Well the funny thing about abstractions is they are physically real in our imaginations even if only ephemerally.
Human imagination allows us to explore as a simulation anything we want with a form of physicalized internal coherence.
Does internal coherence align with repeatable external coherence? That's what we call empirical.
Humans are the known meaning generators of the universe, we are interesting and special and our unique/random walks are important in an uncomputable and unbound sense. Who knows what casual chains will lead us, where they'll take us or how they might save us (from asteroids let's say) or might reshape the topology of spacetime.
You're one of those cats that provides a subtle reminder that Dr. Alan Kay (invented the tablet/Xerox ALTO interface) was first a biologist. Thank you for the enlightened smalltalk! (;3)
You might be interested in Tinkercell, though at this point it may be somewhat outdated and old. There are lots of other more granular systems biology/chemical reaction network software tools, the most ambitious is probably OpenWorm which is still active.
Just keep in mind though that you have to think of cells as very slow, but massively parallel computers.
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.
Reminds me of Wolfram's "Principle of Computational Equivalence"[1].
1. Things in nature have a maximum complexity which is like computation
2. Most things get this complicated
3. Therefore most things are "computationally equivalent"
4. "For example, the workings of the human brain or the evolution of weather systems can, in principle, compute the same things as a computer. "
The leap between things being in an equivalence class according to some relation and being "in principle, the same" might present difficulty if you've done any basic set theory, but that's just because you lack vision.
Yes, the article appears to be a short excerpt from a book and probably loses a lot of context because of that. I am interested in the questions raised by the author but will wait for the book to come out. The good news is that it appears the book will be open access - MIT Press seems to be encouraging this lately (at least by allowing this as an option for authors).
I would say the answer is 'yes'. Mainly because organisms are reproducing and developing. However, if we just consider the adult form of an organism apart from reproduction, it is mainly focused on maintaining its state, which is pretty much the opposite of computation.
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....
This is the kind of evolved computer science that was going on when I was a teenager. Have an upvote eig!
My addition: it's funny for how much speculation we get in the, "hard cognitive science" (RIP) that in lieu of the big insights we get from Godel, Turing, Russell that many/most undergraduates and even post-graduates still haven't internalized Wittgenstein's work especially the Tractatus. I feel like it gets us to, "the questions you're asking about how life works and the questions about what is at the core of logic and mathematics (language) are definitely related but not in any of the fundamental ways you hope they are..."
For the uninitiated-- try reading the thing in one sitting. It takes about an hour:
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.
The title should definitely be "Is it possible to simulate living organism?" given the last sentence is "Simulations like these show how computation can produce lifelike behavior across scales".
Nothing about life is discussed here, it's not even defined once.
> Also, evolution itself is constantly optimizing organisms to best adapt to their environment, just like a computation.
There is no optimization, if organisms can reproduce, they'll continue to exist. That does not mean they are the "best adapted" or on a trajectory toward better adaptation.
It's entirely possible for a germ line to become less fit over time, even to the point of extinction, and that's still evolution. Time has shown that is the case for most germ lines.
> Time has shown that is the case for most germ lines.
This is true, but that sure seems unfair. ;) You have multiple competing systems, in the case of a germ. The system that human related germs are competing with is around 30 trillion times the size, with the advantage of some fairly incredible emergent properties that come from that. The germ is evolving, but in a system that completely overwhelms it, with evolved tricks to specifically force the germ along the "unhappy path" of evolution.
Evolution is not optimizing anything. What's happening in the biosphere is a process of mutation & selection, it's not optimization towards any particular goal or objective. Furthermore & slightly more abstractly, b/c of conservation of mass & energy, what's actually happening is re-organization of existing biomass into different life forms enabled by solar radiation.
That's a rather strong statement, but incorrect in both result and formulation.
How is mutation and selection entail it's not optimization? Your motivating the lack of a goal for a process by describing it's composition. It seems like a logical (Non sequitur fallacy) and categorical erorr.
For reference
> optimization = the selection of a best element, with regard to some criteria, from some set of available alternatives
What's the selection selecting from, what's evolution evolving towards?
Moreover, you motivate with conservation. Conservation is an optimization criterion.
I suppose I fail to see why evolution through natural selection is not optimizing. That was Darwin's big idea, right? That given heredity, selection, and variation you end up with life forms we'd consider optimized for their environments?
Or do you mean that optimization by definition must include intent, and evolution as a mindless process has no intentionality?
Evolution has no goals, not even survival. Evolution is something that happens. Some species survive for a while, others don't.
Think of it like saying water has the goal of flowing down the mountain along the path of least resistance. Of course it doesn't, it's just something that happens. There's no goal.
I think the article is a bit out of focus, but its premise reminded me about the discussions that we students had at the university many years ago. It was a popular view that the universe is a big all-encompassing computer, and everyhting happening in it is part of its computation. Not just life, but really everything. The big question was, is this computer a Turing machine? Not necessarily in the sense of a state machine and an infinite tape, but in the sense of its computational power. These days the question would be whether it is a quantum Turing machine, I guess.
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 don't think it's necessary to completely discard the idea. However, I do think it's important, at the end of it all, to ask: Okay, so what's the utility of this framework? What am I getting out of setting up my point of view this way?
I'm reminded of an old YouTube video [0] that I rewatched recently. That video is "Every Zelda is the Darkest Zelda." Topically, it's completely different. But in it Jacob Geller talks about how there are many videos with fan theories about Zelda games where they're talking about how messed up the game is. Except, that's their only point. If you frame the game in some way, it's really messed up. It doesn't extract any additional meaning, and textually it's not what's present. So you're going through all this decoding and framing, and at the end your conclusion is... nothing. The Mario characters represent the seven deadly sins? Well, that's messed up. That's maybe fun, but it's an empty analysis. It has no insight. No bite.
So, what's the result here other than: Well, that's neat. It's an interesting frame. But other than the thought to construct it, does it inform us of anything? Honestly, I'm not even sure it's really saying life is a form of programming. It seems equally likely it's saying programming is a form of biochemistry (which, honestly, makes more sense given the origins of programming). But even if that were so, what does that give us that we didn't already know? I'm going to bake a pie, so I guess I should learn Go? No, the idea feels descriptive rather than a synthesis. Like an analogy without the conclusion. The pie has no bite.
> I don't think it's necessary to completely discard the idea. However, I do think it's important, at the end of it all, to ask: Okay, so what's the utility of this framework? What am I getting out of setting up my point of view this way?
That's the important question indeed. In particular, classing life as a computation means that it's amenable to general theories of computation. Can we make a given computation--an individual--non-halting? Can we configure a desirable attractor, i.e. remaining "healthy" or "young"? Those are monumentally complex problems, and nobody is going to even try to tackle them while we still believe that life is a mixture of molecules dunked in unknowable divine aether.
Beyond that, the current crop of AI gets closer to anything we have had before to general intelligence, and when you look below the hood, it's literally a symbols-in symbols-out machine. To me, that's evidence that symbol-in symbol-out machines are a pretty general conceptual framework for computation, even if concrete computation is actually implemented in CPUs, GPUs, or membrane-delimited blobs of metabolites.
> 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.
Proteins can also be seen as sequence of symbols: one symbol for each aminoacid. But that's beyond the point. Computational theory uses Turing Machines as a conceptual model. The theories employ some human-imposed conceptual translation to encode what happens in a digital processor or a Lego computer, even if those are not made with a tape and a head. Anybody who actually understands these theories could try to make a rigorous argument of why biological systems are Turning Machines, and I give them very high chances of succeeding.
> These proteins are solving physical problems, not expressing symbolic solutions to symbolic problems
This sentence is self-contradictory. If a protein solves a physical problem and it can only do so because of its particular structure, then its particular structure is an encoding of the solution to the physical problem. How can that encoding be "symbolic" is more of a problem for the beholder (us, humans), but as stated before, using the aminoacid sequence gives one such symbolic encoding. Another symbolic encoding could be the local coordinates of each atom of the protein, up to the precision limits allowed by quantum physics.
The article correctly states that biological computation is full of randomness, but it also explains that computational theories are well furnished with revolving doors between randomness and determinism (Pseudo-random numbers and Hopfield networks are good examples of conduits in either direction).
> ... whatever.
Please don't use this word to finish an argument where there are actual scientists who care about the subject.
> a computation is a process that maps symbols (or strings of symbols) to other symbols, obeying certain simple rules[1]
There are quite a number of people who believe this is the universe. Namely, that the universe is the manifestation of all rule sets on all inputs at all points in time. How you extract quantum mechanics out of that... not so sure
our relationship to computation got weird when we moved to digital computers. Like, I don’t think anyone was saying “life is like millions of slide-rules solving logarithms
in parallel”. but now that computers are de-materialized, they can be a metaphor for pretty much anything
Good point - maybe the analogy to computation arises simply because digital computation and the synthesis of DNA, RNA and proteins are all performed by discrete-state machines?
I don't think they are. The things analog computers work on are still symbolic - we don't care about the length of the rod or what have you, we care about the thing the length of the rod represents.
analog computers don't generally compute by operating on symbols. For example see the classic video on fire control computers https://youtu.be/s1i-dnAH9Y4?t=496
OP's specific phrasing is that they "map symbols to symbols". Analog computers don't do that. Some can, but that's not their definition.
Turing machines et al. are a model of computation in mathematics. Humans do math by operating on symbols, so that's why that model operates on symbols. It's not an inherent part of the definition.
> analog computers don't generally compute by operating on symbols. For example see the classic video on fire control computers https://youtu.be/s1i-dnAH9Y4?t=496
> OP's specific phrasing is that they "map symbols to symbols". Analog computers don't do that. Some can, but that's not their definition.
How is that not symbolic? Fundamentally that kind of computer maps the positions of some rods or gears or what have you to the positions of some other rods or gears or what have you, and the first rods or gears are symbolising motion or elevation or what have you and the final one is symbolising barrel angle or what have you. (And sure, you might physically connect the final gear directly to the actual gun barrel, but that's not the part that's computation; the computation is the part happening with the little gears and rods in the middle, and they have symbolic meanings).
No, analog computers truly are symbolic. The simplest analog computer - the abacus - is obviously symbolic, and thus is also true for WW2 gun fire control computers, ball-and-shaft integrators, etc. They do not use inscriptions which is maybe where you're getting confused. But the turning of a differential gear to perform an addition is a symbolic operation: we are no more interested in the mechanics of the gear than we are the calligraphy of a written computation or the construction of an abacus bead, we are interested in the physical quantity that gear is symbolically representing.
Your comment is only true if you take an excessively reductive view of "symbol."
I'm not confused, and an abacus is a digital computer.
You keep referring to what we are interested in, but that's not a relevant quantity here.
A symbol is a discrete sign that has some sort of symbol table (explicit or not) describing the mapping of the sign to the intended interpretation. An analog computer often directly solves the physical problem (e.g. an ODE) by building a device whose behavior is governed by that ODE. That is, it solves the ODE by just applying the laws of physics directly to the world.
If your claim is that analog computers are symbolic but the same physical process is not merely because we are "interested in" the result then I don't agree. And you'd also be committed to saying proteins are symbolic if we build an analog computer that runs on DNA and proteins. In which case it seems like they become always symbolic if we're always interested in life as computation.
This is where you are confused - in fact just plain wrong:
A symbol is a discrete sign that has some sort of symbol table (explicit or not) describing the mapping of the sign to the intended interpretation
Symbols do not have to be discrete signs. You are thinking of inscriptions, not symbols. Symbols are impossible for humans to define. For an analog computer, the physical system of gears / etc symbolically represent the physical problem you are trying to solve. X turns of the gear symbolizes Y physical kilometers.
Surely an abacus is a simple form of digital computer? The position/state of the beads is not continuous, ignoring the necessary changes of position/state.
In what sense? I agree the tech industry fucking sucks right now, but I don't see how this has anything to do with that.
A physical computer is still a computer, no matter what it's computing. The only use a computer has to us is to compute things relative to physical reality, so a physical computer seems even closer to a "real computer" or "real computation" to me than our sad little hot rocks, which can barely simulate anything real to any degree of accuracy, when compared to reality.
I suspect what the parent is alluding to is that we tend to reduce everything to computer-world analogies, which we believe we're uniquely qualified to analyze.
It's sort of like a car mechanic telling you "SQL query, eh? It must be similar to what happens in an intake manifold." For all I know, there might be Turing-equivalency between databases and the inner workings of internal combustion engines, but you wouldn't consider that to be a useful take.
I understand that this post is actually about biology and DNA, but the headline asks a broader and more interesting question than what the article itself cares to address --
At the root of this question is whether life is entirely deterministic. Either position - yes it is, or no it isn't - is unfalsifiable.
And in either case, one must live as if life is not deterministic, or else one's sense of agency and meaning dissolve.
Just because something is computational doesn't mean it's deterministic. There are quantum effects and ghosts in the machine.
Also, maybe the goal of the computation isn't to generate a deterministic output. Maybe it's just to compress a lot of very random input, in a way that smooths out the noise. In this way life could be essentially random on purpose, because all the varieties of randomness are better at modeling the data (the observable universe) than a classical deterministic function would be.
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.
Above all, we mustn't torment the sacrosanct biological neuron center too much (they already have a hard time accepting that they're monkeys, so give them a little dignity, damn it).
“A man doesn't think. It's just probabilistic generation.”
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.
Surprised the article didn't mention the most fitting sense in which life is computation, which is at the biosphere level. Life can be characterized as a (recursive) search function executing continuously over billions of years. It seeks out new environments, reacts to changes in the environment at all scales between molecules and mountains. Life is a vast, distributed visitor pattern whose payload is itself.
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.
Allegedly it can find the Answer, unfortunately it'll take so long to do it we'll forget what the Question was before life is done computing the Answer!
"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.
To me, the article just ask "Is it possible to simulate living organism features?" and say a small yes by saying "Simulations like these show how computation can produce lifelike behavior across scales".
I'm not expert to judge the result of "drawing a missing hand by using neural network on each pixels"(if it's what it's done? Again not an expert).
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.
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."
Whenever I see such claims, it becomes obvious how philosophically and intellectually incompetent we are.
There are several notions that aren’t examined, which stands in the way of having a sensible conversation about the question.
1. The definition of computation.
2. The definition of life.
3. The difference between the real order and the logical and epistemic orders.
Searle famously pointed out that computation is observer-relative. Sure, we can establish some kind of abstracted correspondence between a computing formalism and a natural process, and this correspondence can be fun or even a useful metaphor, but it is senseless to ask whether life is computation. Objectively, without an observer, there is no computation going on. In fact, even your computer is not objectively speaking computing.
You can effectively draw this correspondence with anything (Seth Lloyd did this with quantum mechanics), and if everything is computation, then nothing is. It becomes a synonym for all of reality.
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.
It often seems that people think that the answers to the important questions must align with the subject they know best. Statisticians think life is all about probabilities. Economists think it's game theory. Computer scientists think it's computational.
"Everything can be understood through mathematics" is usually said by a mathematician.
I've noticed this – I'm a former software engineer, now a full-time priest. It's been fascinating to reflect on how the base of my analogies has shifted from software/tech to theology/the Christian tradition. Not entirely though, there are many times when I've found resonances in between.
One extension I'd make from your comment is how rich interdisciplinary work can be, because all the resonances between different fields can come to life and some really wonderful creativity happens.
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.
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 think the issue with this way of thinking is that humans think in abstractions.
Abstractions don't really exist, they're a product of the human mind, but then we apply them to nature. Calling DNA code, comparing NNs and the brain, etc. But those abstractions fall apart when you look a little too deeply at what actually happens in nature.
Is DNA code? Or is it more like a machine? Is it neither, or is it something embedded in such a complex space that our simple abstractions can't capture the full nature of its being?
When you look at the nature of DNA, it does more than simply act as code. It can edit and self-modify, self-assemble, self-replicate, it can turn genes on and off, it can perform what can be argued as computations itself. If you limit yourself to thinking of it as code, you might miss crucial ways it exists/performs in real life.
> When you look at the nature of DNA, it does more than simply act as code.
> It can edit and self-modify, self-assemble, self-replicate, it can turn genes on and off
Unless my knowledge of biology is very outdated or incomplete, all of those things you cited are done to DNA. They don't happen spontaneously.
DNA doesn't self-replicate, a whole bunch of enzymes come and actively copy it. Genes don't spontaneously turn on and off, some enzyme comes and attaches or removes a methyl group. DNA doesn't self-assemble, it is actively coiled around histones to form nucleosomes. Bacteria have a huge variety of enzymes for manipulating native and foreign DNA, they have their own CRISPR mechanisms.
I'm thinking more of early RNA and DNA life, where ideas like the RNA-world might have happened and applied. RNA can assemble, replicate, and catalyze to form deoxynucleosides in a proto-DNA, without "outside" work needing to happen from enzymes/proteins/etc.
Similarly, RNA and DNA "machines" could have existed before cellular life, in which genetic material self-assembled, transferred genes horizontally/vertically, etc, blurring the lines between genes as "code" and something else.
I think RNA (in particular, ribozymes) does those things.
But DNA is effectively separation of concerns: RNA systems evolved to RNA mediated systems with DNA as more inert and reliable storage and enzymes as more effective catalysts. Or so the RNA world hypothesis goes.
> ribozymes
I learned something new today! Thank you.
It's impressive that RNA of all things can be folded in such a way that it also acts like an enzyme.
> I think the issue with this way of thinking is that humans think in abstractions.
Isn't that the entire point of making abstractions? Understanding things "as they are" is impossible, so we need simplifications. Of course it should be appreciated that the abstractions are always "wrong".
"A map is not the territory it represents, but, if correct, it has a similar structure to the territory, which accounts for its usefulness."
https://en.wikipedia.org/wiki/Map%E2%80%93territory_relation
I think the point is more that if you’re saying one abstraction is similar to another abstraction, you run the risk of over-analyzing the abstraction level and not the thing-in-itself.
Well the funny thing about abstractions is they are physically real in our imaginations even if only ephemerally.
Human imagination allows us to explore as a simulation anything we want with a form of physicalized internal coherence.
Does internal coherence align with repeatable external coherence? That's what we call empirical.
Humans are the known meaning generators of the universe, we are interesting and special and our unique/random walks are important in an uncomputable and unbound sense. Who knows what casual chains will lead us, where they'll take us or how they might save us (from asteroids let's say) or might reshape the topology of spacetime.
It's early days yet.
> It can edit and self-modify, self-assemble, self-replicate, it can turn genes on and off, it can perform what can be argued as computations itself.
Malbolge
Have a look at the join calculus and the "chemical abstract machine" as implemented in JoCaml, e.g., https://sites.google.com/site/winitzki/tutorial-on-join-calc...
You're one of those cats that provides a subtle reminder that Dr. Alan Kay (invented the tablet/Xerox ALTO interface) was first a biologist. Thank you for the enlightened smalltalk! (;3)
You might be interested in Tinkercell, though at this point it may be somewhat outdated and old. There are lots of other more granular systems biology/chemical reaction network software tools, the most ambitious is probably OpenWorm which is still active.
Just keep in mind though that you have to think of cells as very slow, but massively parallel computers.
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.
Reminds me of Wolfram's "Principle of Computational Equivalence"[1].
1. Things in nature have a maximum complexity which is like computation 2. Most things get this complicated 3. Therefore most things are "computationally equivalent" 4. "For example, the workings of the human brain or the evolution of weather systems can, in principle, compute the same things as a computer. "
The leap between things being in an equivalence class according to some relation and being "in principle, the same" might present difficulty if you've done any basic set theory, but that's just because you lack vision.
[1] https://mathworld.wolfram.com/PrincipleofComputationalEquiva...
Yes, the article appears to be a short excerpt from a book and probably loses a lot of context because of that. I am interested in the questions raised by the author but will wait for the book to come out. The good news is that it appears the book will be open access - MIT Press seems to be encouraging this lately (at least by allowing this as an option for authors).
Oh great flag that it’s open access. Will give this a read.
> there's nothing resembling an argument, or even a definition of "computation."
"It's not even wrong" - Pauli
I felt reminded of Hofstadter's Goedel/Escher/Bach mysticism that somehow everything is recursion.
Including free will
In any case, he did fit that into a book! If only barely.
Edit: On further reflection, I suppose he didn't, if we consider the effort to span Gödel Escher Bach and I Am a Strange Loop.
I might not be a strange loop but I am indeed strange.
or the idea that the universe is a computer
https://en.wikipedia.org/wiki/Edward_Fredkin
Self-simulation.
I would say the answer is 'yes'. Mainly because organisms are reproducing and developing. However, if we just consider the adult form of an organism apart from reproduction, it is mainly focused on maintaining its state, which is pretty much the opposite of computation.
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....
This is the kind of evolved computer science that was going on when I was a teenager. Have an upvote eig!
My addition: it's funny for how much speculation we get in the, "hard cognitive science" (RIP) that in lieu of the big insights we get from Godel, Turing, Russell that many/most undergraduates and even post-graduates still haven't internalized Wittgenstein's work especially the Tractatus. I feel like it gets us to, "the questions you're asking about how life works and the questions about what is at the core of logic and mathematics (language) are definitely related but not in any of the fundamental ways you hope they are..."
For the uninitiated-- try reading the thing in one sitting. It takes about an hour:
https://wittgensteinproject.org/w/index.php/Tractatus_Logico...
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.
The title should definitely be "Is it possible to simulate living organism?" given the last sentence is "Simulations like these show how computation can produce lifelike behavior across scales".
Nothing about life is discussed here, it's not even defined once.
> Also, evolution itself is constantly optimizing organisms to best adapt to their environment, just like a computation.
There is no optimization, if organisms can reproduce, they'll continue to exist. That does not mean they are the "best adapted" or on a trajectory toward better adaptation.
It's entirely possible for a germ line to become less fit over time, even to the point of extinction, and that's still evolution. Time has shown that is the case for most germ lines.
> Time has shown that is the case for most germ lines.
This is true, but that sure seems unfair. ;) You have multiple competing systems, in the case of a germ. The system that human related germs are competing with is around 30 trillion times the size, with the advantage of some fairly incredible emergent properties that come from that. The germ is evolving, but in a system that completely overwhelms it, with evolved tricks to specifically force the germ along the "unhappy path" of evolution.
Also many numerical algorithms can fail when step size is not suited for their "environment", so I don't see why that should mean much.
Evolution is not optimizing anything. What's happening in the biosphere is a process of mutation & selection, it's not optimization towards any particular goal or objective. Furthermore & slightly more abstractly, b/c of conservation of mass & energy, what's actually happening is re-organization of existing biomass into different life forms enabled by solar radiation.
That's a rather strong statement, but incorrect in both result and formulation.
How is mutation and selection entail it's not optimization? Your motivating the lack of a goal for a process by describing it's composition. It seems like a logical (Non sequitur fallacy) and categorical erorr.
For reference
> optimization = the selection of a best element, with regard to some criteria, from some set of available alternatives
What's the selection selecting from, what's evolution evolving towards?
Moreover, you motivate with conservation. Conservation is an optimization criterion.
But genetic algorithms are used for optimization all the time. I don't see how evolution is much different from them.
A shark is pretty damn optimized bunch of molecules to survive in water, would you not agree?
I suppose this boils down to your definition of "optimize".
I suppose I fail to see why evolution through natural selection is not optimizing. That was Darwin's big idea, right? That given heredity, selection, and variation you end up with life forms we'd consider optimized for their environments?
Or do you mean that optimization by definition must include intent, and evolution as a mindless process has no intentionality?
I'm just not sure what you're driving at.
Optimization is by definition with respect to some cost function or goal. Evolution has none. Evolution happens, but has no goal.
That’s the claim. But are we sure about that?
I certainly have a goal when selecting my partner and creating my offspring; at the very least that they’re happy and healthy.
I would say the goal is survival. Which happens at the cell/dna.. level (mostly) not the organism. (nod to Dawkins)
Evolution has no goals, not even survival. Evolution is something that happens. Some species survive for a while, others don't.
Think of it like saying water has the goal of flowing down the mountain along the path of least resistance. Of course it doesn't, it's just something that happens. There's no goal.
Perhaps it's an over-anthrophormic term.
The goal is to accelerate Entropy
Ah! That makes sense. Thank you for explaining!
> what's actually happening is re-organization of existing biomass into different life forms enabled by solar radiation.
And the flux of geothermal and chemical energy
That's true. We wouldn't have fossil fuels w/o geological activity & mass churning.
Survival?
I think the article is a bit out of focus, but its premise reminded me about the discussions that we students had at the university many years ago. It was a popular view that the universe is a big all-encompassing computer, and everyhting happening in it is part of its computation. Not just life, but really everything. The big question was, is this computer a Turing machine? Not necessarily in the sense of a state machine and an infinite tape, but in the sense of its computational power. These days the question would be whether it is a quantum Turing machine, I guess.
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.
[1] Turing computability, lambda definability, primitive recursion, whatever.
I don't think it's necessary to completely discard the idea. However, I do think it's important, at the end of it all, to ask: Okay, so what's the utility of this framework? What am I getting out of setting up my point of view this way?
I'm reminded of an old YouTube video [0] that I rewatched recently. That video is "Every Zelda is the Darkest Zelda." Topically, it's completely different. But in it Jacob Geller talks about how there are many videos with fan theories about Zelda games where they're talking about how messed up the game is. Except, that's their only point. If you frame the game in some way, it's really messed up. It doesn't extract any additional meaning, and textually it's not what's present. So you're going through all this decoding and framing, and at the end your conclusion is... nothing. The Mario characters represent the seven deadly sins? Well, that's messed up. That's maybe fun, but it's an empty analysis. It has no insight. No bite.
So, what's the result here other than: Well, that's neat. It's an interesting frame. But other than the thought to construct it, does it inform us of anything? Honestly, I'm not even sure it's really saying life is a form of programming. It seems equally likely it's saying programming is a form of biochemistry (which, honestly, makes more sense given the origins of programming). But even if that were so, what does that give us that we didn't already know? I'm going to bake a pie, so I guess I should learn Go? No, the idea feels descriptive rather than a synthesis. Like an analogy without the conclusion. The pie has no bite.
[0]: https://youtu.be/O2tXLsEUpaQ
> I don't think it's necessary to completely discard the idea. However, I do think it's important, at the end of it all, to ask: Okay, so what's the utility of this framework? What am I getting out of setting up my point of view this way?
That's the important question indeed. In particular, classing life as a computation means that it's amenable to general theories of computation. Can we make a given computation--an individual--non-halting? Can we configure a desirable attractor, i.e. remaining "healthy" or "young"? Those are monumentally complex problems, and nobody is going to even try to tackle them while we still believe that life is a mixture of molecules dunked in unknowable divine aether.
Beyond that, the current crop of AI gets closer to anything we have had before to general intelligence, and when you look below the hood, it's literally a symbols-in symbols-out machine. To me, that's evidence that symbol-in symbol-out machines are a pretty general conceptual framework for computation, even if concrete computation is actually implemented in CPUs, GPUs, or membrane-delimited blobs of metabolites.
> 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.
Proteins can also be seen as sequence of symbols: one symbol for each aminoacid. But that's beyond the point. Computational theory uses Turing Machines as a conceptual model. The theories employ some human-imposed conceptual translation to encode what happens in a digital processor or a Lego computer, even if those are not made with a tape and a head. Anybody who actually understands these theories could try to make a rigorous argument of why biological systems are Turning Machines, and I give them very high chances of succeeding.
> These proteins are solving physical problems, not expressing symbolic solutions to symbolic problems
This sentence is self-contradictory. If a protein solves a physical problem and it can only do so because of its particular structure, then its particular structure is an encoding of the solution to the physical problem. How can that encoding be "symbolic" is more of a problem for the beholder (us, humans), but as stated before, using the aminoacid sequence gives one such symbolic encoding. Another symbolic encoding could be the local coordinates of each atom of the protein, up to the precision limits allowed by quantum physics.
The article correctly states that biological computation is full of randomness, but it also explains that computational theories are well furnished with revolving doors between randomness and determinism (Pseudo-random numbers and Hopfield networks are good examples of conduits in either direction).
> ... whatever.
Please don't use this word to finish an argument where there are actual scientists who care about the subject.
> a computation is a process that maps symbols (or strings of symbols) to other symbols, obeying certain simple rules[1]
There are quite a number of people who believe this is the universe. Namely, that the universe is the manifestation of all rule sets on all inputs at all points in time. How you extract quantum mechanics out of that... not so sure
our relationship to computation got weird when we moved to digital computers. Like, I don’t think anyone was saying “life is like millions of slide-rules solving logarithms in parallel”. but now that computers are de-materialized, they can be a metaphor for pretty much anything
Good point - maybe the analogy to computation arises simply because digital computation and the synthesis of DNA, RNA and proteins are all performed by discrete-state machines?
does DNA/RNA keep state other than the position of the read head?
I think you may be forgetting about analog computers https://en.wikipedia.org/wiki/Analog_computer
I don't think they are. The things analog computers work on are still symbolic - we don't care about the length of the rod or what have you, we care about the thing the length of the rod represents.
analog computers don't generally compute by operating on symbols. For example see the classic video on fire control computers https://youtu.be/s1i-dnAH9Y4?t=496
OP's specific phrasing is that they "map symbols to symbols". Analog computers don't do that. Some can, but that's not their definition.
Turing machines et al. are a model of computation in mathematics. Humans do math by operating on symbols, so that's why that model operates on symbols. It's not an inherent part of the definition.
> analog computers don't generally compute by operating on symbols. For example see the classic video on fire control computers https://youtu.be/s1i-dnAH9Y4?t=496
> OP's specific phrasing is that they "map symbols to symbols". Analog computers don't do that. Some can, but that's not their definition.
How is that not symbolic? Fundamentally that kind of computer maps the positions of some rods or gears or what have you to the positions of some other rods or gears or what have you, and the first rods or gears are symbolising motion or elevation or what have you and the final one is symbolising barrel angle or what have you. (And sure, you might physically connect the final gear directly to the actual gun barrel, but that's not the part that's computation; the computation is the part happening with the little gears and rods in the middle, and they have symbolic meanings).
There's a confusion of nomenclature.
Computers are functional mappings from inputs to outputs, sure.
Analog fire computers are continuous mappings from a continuum, a line segment (curved about a cam), to another continuum, a dial perhaps.
Symbolic operations, mapping from patterns of 0s and 1s (say) to other patterns are discrete, countable mappings.
With a real valued electrical current, discrete symbols are forced by threshold levels.
To what degree is the threshold precise? Maybe fundamentally there's not that much difference.
No, analog computers truly are symbolic. The simplest analog computer - the abacus - is obviously symbolic, and thus is also true for WW2 gun fire control computers, ball-and-shaft integrators, etc. They do not use inscriptions which is maybe where you're getting confused. But the turning of a differential gear to perform an addition is a symbolic operation: we are no more interested in the mechanics of the gear than we are the calligraphy of a written computation or the construction of an abacus bead, we are interested in the physical quantity that gear is symbolically representing.
Your comment is only true if you take an excessively reductive view of "symbol."
I'm not confused, and an abacus is a digital computer.
You keep referring to what we are interested in, but that's not a relevant quantity here.
A symbol is a discrete sign that has some sort of symbol table (explicit or not) describing the mapping of the sign to the intended interpretation. An analog computer often directly solves the physical problem (e.g. an ODE) by building a device whose behavior is governed by that ODE. That is, it solves the ODE by just applying the laws of physics directly to the world.
If your claim is that analog computers are symbolic but the same physical process is not merely because we are "interested in" the result then I don't agree. And you'd also be committed to saying proteins are symbolic if we build an analog computer that runs on DNA and proteins. In which case it seems like they become always symbolic if we're always interested in life as computation.
This is where you are confused - in fact just plain wrong:
Symbols do not have to be discrete signs. You are thinking of inscriptions, not symbols. Symbols are impossible for humans to define. For an analog computer, the physical system of gears / etc symbolically represent the physical problem you are trying to solve. X turns of the gear symbolizes Y physical kilometers.Surely an abacus is a simple form of digital computer? The position/state of the beads is not continuous, ignoring the necessary changes of position/state.
I think the notion largely boils down to another dogmatic display of tech industry's megalomania.
In what sense? I agree the tech industry fucking sucks right now, but I don't see how this has anything to do with that.
A physical computer is still a computer, no matter what it's computing. The only use a computer has to us is to compute things relative to physical reality, so a physical computer seems even closer to a "real computer" or "real computation" to me than our sad little hot rocks, which can barely simulate anything real to any degree of accuracy, when compared to reality.
I suspect what the parent is alluding to is that we tend to reduce everything to computer-world analogies, which we believe we're uniquely qualified to analyze.
It's sort of like a car mechanic telling you "SQL query, eh? It must be similar to what happens in an intake manifold." For all I know, there might be Turing-equivalency between databases and the inner workings of internal combustion engines, but you wouldn't consider that to be a useful take.
I understand that this post is actually about biology and DNA, but the headline asks a broader and more interesting question than what the article itself cares to address --
At the root of this question is whether life is entirely deterministic. Either position - yes it is, or no it isn't - is unfalsifiable.
And in either case, one must live as if life is not deterministic, or else one's sense of agency and meaning dissolve.
Just because something is computational doesn't mean it's deterministic. There are quantum effects and ghosts in the machine.
Also, maybe the goal of the computation isn't to generate a deterministic output. Maybe it's just to compress a lot of very random input, in a way that smooths out the noise. In this way life could be essentially random on purpose, because all the varieties of randomness are better at modeling the data (the observable universe) than a classical deterministic function would be.
> Just because something is computational doesn't mean it's deterministic. There are quantum effects and ghosts in the machine.
Maybe? It is correct according to the Copenhagen interpretation of quantum mechanics, but there are other interpretations that are deterministic.
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.
Above all, we mustn't torment the sacrosanct biological neuron center too much (they already have a hard time accepting that they're monkeys, so give them a little dignity, damn it).
“A man doesn't think. It's just probabilistic generation.”
Heretic!
I think Federico Faggin has a much better (imo, coherent and well-considered) take on this [1].
[1] https://www.youtube.com/watch?v=0FUFewGHLLg
Love the work the Essentia foundation is doing, thanks for sharing !
Reminds me of Wolfram's 'A New Kind of Science'. Specifically his principle of computation equivalence: https://en.wikipedia.org/wiki/A_New_Kind_of_Science#Principl...
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.
Classic John Von Neumann, inventing both the Von Neumann architecture and non-Von Neumann architectures.
What a brilliant irony. Excellent comment.
I suppose "non-Von Neumann architectures" would just instead have someone else's name associated with it had it been invented by someone else.
The title should be "Can life be modeled as computation". It doesn't mean life is computation.
Surprised the article didn't mention the most fitting sense in which life is computation, which is at the biosphere level. Life can be characterized as a (recursive) search function executing continuously over billions of years. It seeks out new environments, reacts to changes in the environment at all scales between molecules and mountains. Life is a vast, distributed visitor pattern whose payload is itself.
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.
[1] https://plato.stanford.edu/entries/computational-mind/#GodIn...
Douglas Adams had something to say about this, I think
I swear to you, at the moment I opened this there were 42 comments and your message was 42 minutes ago
Life is truly weird sometimes
Allegedly it can find the Answer, unfortunately it'll take so long to do it we'll forget what the Question was before life is done computing the Answer!
What do you get if you multiply six by nine?
42!
Only if you broaden the definition of computation to be so general it includes everything.
Physical phenomena seem to be algorithmic is an illusion, folks. We only have a model of the physical world. The model itself may be algorithmic.
It's just me or no one has a clue what "life" is.
Of course. It's a computer designed to figure out the question of life, the universe and everything to which the answer is 42.
And the question is "what do you get if you multiply six by nine?"
Showing that our concept of mathematics is slightly erroneous
Throw this random question in, does DNA spell out sentience
Could you pull out the specific list of ATCG and make a brain
From a neural networks professor:
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.
To me, the article just ask "Is it possible to simulate living organism features?" and say a small yes by saying "Simulations like these show how computation can produce lifelike behavior across scales".
I'm not expert to judge the result of "drawing a missing hand by using neural network on each pixels"(if it's what it's done? Again not an expert).
If true, will computers have rights?
What a pseudo-intellectual drivel, by that definition you can compute anything by blowing soap bubbles into thin air
Why can't you?
Anything can be used to implement aTuring machine
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.
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."
And so it falls to me to link the relevant SMBC: https://www.smbc-comics.com/comic/2011-02-17
Whenever I see such claims, it becomes obvious how philosophically and intellectually incompetent we are.
There are several notions that aren’t examined, which stands in the way of having a sensible conversation about the question.
1. The definition of computation.
2. The definition of life.
3. The difference between the real order and the logical and epistemic orders.
Searle famously pointed out that computation is observer-relative. Sure, we can establish some kind of abstracted correspondence between a computing formalism and a natural process, and this correspondence can be fun or even a useful metaphor, but it is senseless to ask whether life is computation. Objectively, without an observer, there is no computation going on. In fact, even your computer is not objectively speaking computing.
You can effectively draw this correspondence with anything (Seth Lloyd did this with quantum mechanics), and if everything is computation, then nothing is. It becomes a synonym for all of reality.
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.
Computation is a terminal life form that barely resembles life at all.
> terminal
Some prefer GUI
If you believe in Dust Theory then yes life could be a form of computation where consciousness is just a pattern of discrete states.
ha this is why it was read
It often seems that people think that the answers to the important questions must align with the subject they know best. Statisticians think life is all about probabilities. Economists think it's game theory. Computer scientists think it's computational.
"Everything can be understood through mathematics" is usually said by a mathematician.
I've noticed this – I'm a former software engineer, now a full-time priest. It's been fascinating to reflect on how the base of my analogies has shifted from software/tech to theology/the Christian tradition. Not entirely though, there are many times when I've found resonances in between.
One extension I'd make from your comment is how rich interdisciplinary work can be, because all the resonances between different fields can come to life and some really wonderful creativity happens.