In the beginning, there was computation
nautil.us
nautil.us
Not really true, our minds create approximate models of reality and in doing so divides the world into discrete objects that we can play with, but there's no reason to believe those discrete objects actually exist "out there" independent of our senses.
In this regard, even something as seemingly fundamental as arithmetic is just language. There's not really "two" "oranges".
I can write a function that explains what happens when a ball bounces off concrete, but nothing about that function is the ball bouncing off the concrete - the bouncing ball is not made of the function, nor is the function even a part of it. It's a totally outside replica that isn't even fully 1:1. Any attempt to completely model the ball or the concrete or the bouncing will fall short - they'll always be reductions.
So we're not made of functions. We don't know what we are. We use functions to model what's happening, but they're approximations or reductions of what it really is.
I don't like it when people assume perfect descriptions of reality are possible, but I also don't like it when people baselessly assume they're impossible.
Maybe one day we'll have a theory of everything and a solar system sized computer capable of perfectly simulating a bouncing ball at all levels, with no reduction.
Or maybe it's impossible.
We just don't know, and I don't know if it's possible to know you have the full picture.
Thought experiment:
I live on a planet near Star A and you live 6 trillion miles away on a planet near Star B. Each of us can see each other's host star as a bright star in our respective skies. Suddenly, both of our host stars supernova and burn out at the exact same time.
However, survivors on my planet observe that Star A supernova'd, and then about 1 year later Star B supernova'd (due to how long the light takes to reach Star A from Star B). And survivors on your planet observe the opposite: That Star B blew up first, and 1 year later Star A followed.
Only an observer precisely equidistant from both stars would have observed the stars burn out simultaneously. But there's nothing special about this vantage point - this vantage point isn't "the truth" either.
This means that a concept like the order of events is not an absolute measurement. To come up with a new function that explains what "really happened" here, accounting for relativity and lightspeed, would be to leave out at least that detail. Each additional function that answers new mysteries abstracts further and leaves out other details by necessity.
I think of it like fine-tuning a model to increase accuracy, it necessarily de-tunes it in other ways.
> simulating a bouncing ball at all levels, with no reduction
It wouldn't fully be the same thing (although could be a very good approximation).
2. Time as a linear description is the same, a way of sorting the physical world into a series of events.
Both have generalizations. Topos Theory generalizes Set Theory with different notions of what is "true." There are several variations on temporal logic with Linear Temporal Logic being only one such idea.
With all that in mind, your thought experiment does not cause any issues because you can say that the framework for reasoning about the example is _itself_ the problem. Hence, it fails as a counterexample for our inability to potentially understand reality without flaw.
In both comments I assert that phenomena cannot be wholly modeled (or replicated). The gist is that descriptions and replicas are always lossy to some extent.
The second comment just expands on why, relating it ultimately to physical limitations (features) of physical reality.
You can get uncannily precise and predictive with some knowledge - engineering, manufacturing, math - that any lossiness is truly negligible. Especially the smaller the scope and more "medium sized" the object or idea in question. But compounded, and at extreme scales, the incompleteness of our understanding of reality shows.
I agree with your 1 & 2.
You have it backwards. Events not having a globally consistent order is reality. Events seeming like they do is your intuition and leaves out details.
- A happened before B
- B happened before A
- A & B happened at the exact same time
- Neither / there is no "before"/"after"
Considering this is the case with anything measured, what explanatory "truth" would be left when you consider a perfect description of reality? One that accounts for the global reference frames of every possible metric (not just order of events)?
There's no absolute "truth" to any of the mainstays:
Where things are
When they happened
In what order they happened
Even whether or not they happened (there is a perspective where all the values of a measured thing can be zero - like mirroring the velocity of a speeding object to reduce its speed to zero, or rotating a plane to make its height zero - and the different physical implications therein).
We correlate observed "locations in space" and the "passage of time" to heuristical approximations that work (as scientific theories) for our intents and purposes on a hyper local level (a tiny fraction of just our galaxy), but they break down on macro levels because they aren't really accurate descriptions of reality. Our physics doesn't work at scale - not smaller than atoms, nor larger than ~solar systems, without theories falling apart.
Space
The XYZ coordinate system we understand as "3D space" works great for locating and measuring the size of objects locally, we could perfectly track a tiny marble bouncing down a huge mountain with a granular enough XYZ coordinate system and telemetry. But that wouldn't work on larger scales like comparing the movement of subatomic particles with the movement of stars in the same graph. The graph couldn't accurately chart that without normalizing data or adjusting the reference frame toward one bias or the other (see scale invariance, vacuum catastrophe). We can only neatly slap a fixed reference frame over a scoped area, invent units and call it a "field", if we expect any predictive utility.
Time
There's not really an absolute "arrow of time" with a past and future, where A happened, then B happened, etc. in an absolute sense. As shown in the star example, it completely depends on the orientation and velocity of the observer, and other factors. No one perspective is more true than the other.
We all happen to hang out in the same frames, so it seems like some of these are rigid laws - they effectively are, for us - but they aren't really, ultimately. When you eliminate the heuristics that give value to science there's nothing left - which as mentioned above is a possible and potential state.
Instead of living in a 3D universe with an absolute time, we are living in a 4D universe where time is a relative direction in the space-time. That doesn't mean we can't model things in principle, it just means we need to model them as things existing in 4D space-time.
True, really just meant "not absolute".
> such that C happened before D in every reference frame
If that's possible, considering the seemingly infinite number of instances where it'd have to both happen and in that way/order, I would consider those kinds of events to be the fundamental/baseline "forces" or asymmetries.
For example, the distance between Earth and Moon is about 1.3 light-seconds. That means that is A happens on Earth now, and B happens on Moon 1 second later (from our perspective), it is possible that from someone else's perspective B happened before A.
(Note that "someone else" in this example does not refer to the Moon, because its perspective is very similar to the perspective of the Earth. It refers to a hypothetical alien spaceship flying at an extremely high speed in a line parallel to the line between the Earth and the Moon.)
However, if C happens on Earth now, and D happens on Moon 2 seconds later (from our perspective), then C happened before D from everyone's perspective. Individual aliens would disagree on the exact time interval between C and D, where 0.7 would be the smallest possible value, but it could be any larger value. (You get the smallest possible value when you are not moving relatively to the Earth and the Moon.)
This is because a hypothetical light particle emitted at A couldn't reach B in time, but a hypothetical light particle emitted at C could reach D in time. The speed of light is the speed of causality, kind of. Events A and B couldn't possibly have caused each other (they could have a common cause X, but that's different), but C hypothetically could have caused D, which is why C happened before D from everyone's perspective.
Fascinating insights - it can be seen as causality, or at scale that there is a multi-dimensional reality where some timelines are inaccessible/impossible to each other (yet exist in their own right).
Perhaps in our neural net, we are also approximating functions that deal the approximated objects.
I think we know the brain doesn't just call an api. But it is doing some 'function' like things.
https://www.youtube.com/watch?v=zpIqQ0pGs1E
https://www.youtube.com/watch?v=jPhvic-eqbc
Referenced paper: https://philpapers.org/archive/NICITC.pdf
The author's notes on genetics: https://www.subanima.org/mendel/
But the videos are good, thank you.
> recent research on the cellular architecture demands that we look more carefully at what we have previously assumed were well-defined structures and reconsider them as stabilized processes. Because processes are temporally extended, it follows that they can only be understood by giving time due consideration... The structure of a machine, after all, can be grasped in abstraction from time (as it is not constantly changing), whereas the structure of, say, a whirlpool or a stream cannot. This explains why, when we have started using techniques that allow us to examine the cellular architecture in real time, we have found that many of the cell’s compartments and organelles are not fixed machineries at all, but stable macromolecular fluxes.
That the „parts“ do not only perform a specific function is not really surprising, because the machine does not need to be comprehensible or understandable. I would expect single-purpose parts only if that helps the function or if it helps evolvability (in the sense of not creating dead ends).
> The variable flickering of transcriptional activity in different cells is one of the major causes of heterogeneity in isogenic populations. But where exactly does this cell-to-cell variability in transcriptional activity come from? The answer becomes apparent when we remember that gene expression is a molecular process, and like all molecular processes, it is inherently stochastic, given that it takes place in an environment that is subject to the chaotic dynamics of Brownian motion. Each step in the process relies on fortuitous encounters between molecules that are randomly moving about as a consequence of thermal agitation. Evidently, these molecules must be at the right place and at the right time—not to mention in the right vibrational state—for them to be able to participate in the appropriate reactions. The unpredictability of the whole process is further amplified by the fact that the participating molecules in each step are present in the cell in very low copy-numbers, as this decreases the chances of successful interactions between them...
> as research into the non-genetic heterogeneity of cells continues, evidence for the biological importance of this phenomenon is mounting ever-rapidly. We now know that non-genetic heterogeneity plays key roles in both microbial and eukaryotic cells, in embryonic development, and in evolution. For one thing, it is a crucial generator of phenotypic diversity, which enables cell populations to adapt rapidly to changing environmental conditions. It does so by permitting the implementation of probabilistic diversification strategies within a population, such as bet-hedging and divisions of labour, which can confer considerable fitness advantages...
> One very important theoretical implication of the probabilistic nature of cellular behaviour and the observed heterogeneity of cell populations is that, quite literally, every cell (in an organism and elsewhere) is a unique entity. No two cells are identical, given that no two cells respond to a stimulus in the exact same way—even if they are genetically the same.
He had located the data he was working on
near the top of memory ---
the largest locations the instructions could address ---
so, after the last datum was handled,
incrementing the instruction address
would make it overflow.
The carry would add one to the
operation code, changing it to the next one in the instruction set:
a jump instruction.
Sure enough, the next program instruction was
in address location zero,
and the program went happily on its way.
Anyway the system call trap examined the caller stack, found the return address (to the trap table), picked out the combination of segment and offset used to construct a system-call index. Following so far?
We went paged. Changed syscall segment to indirect, 16 segment descriptors all mapped to the start of the jump table. Started failing on one particular system call out of thousands - it would page fault! Why?
The auto-increment and prefetch of the trap opcode in the jump table would fault, for only one syscall, the one that mapped to the last entry in the trap table where the offset came out to 0FFC. Wrapped to 1000, which with that particular segment meant next-page! Which was unmapped (system trap table was in low memory, alone).
My solution: change the syscall index for that operation to something else, and document in the syscall comments to never use it.
Do you really think modern computers are fully deterministic at the lowest levels?
But cells don't operate on such nicely bifurcated scales (small and random vs large and mostly predictable). If they did, the dream of cellular wiring diagrams allowing cells to be understood would be a lot more achievable.
Compare to loggers, floating trimmed trees down a river to the sawmill: the logs bouncing down the river are behaving in an entirely random manner, but it's within bounds and doesn't matter, because they'll still make it downstream where they get caught by another system. It's a "machine" with random behaviors. Maybe this (obligatory) xkcd illustrates my point: https://www.explainxkcd.com/wiki/index.php/2916:_Machine
I get the impression that what this is coming down to is massive complexity rendering the machine incomprehensible - but again, that doesn't mean it isn't a machine.
I believe that summarizes transistors, cells, and forest-to-sawmill machines.
Which is to say, yes: it is a system composed of comprehensible systems, which makes it, itself, a comprehensible system. And that's the whole point here: given knowledge and time, we can tease out exactly how it works.
Computers don't behave this way at all: you can be reliably sure that if two computers produce different results with the same input that one of them is wrong. If it's a stochastic algorithm at least the averages should be within a certain bound. You can't make the same conclusion with cells.
> No two cells are identical, given that no two cells respond to a stimulus in the exact same way—even if they are genetically the same.
That's just begging the question.
Wait until you hear about quantum effects in microprocessors!
I think when somebody says "machine", a lot of people just think victorian steam engines. Machines can cover a lot more. In fact in the future we will build devices that do work similar to what's going on in the cells, and these devices will have to obey the same laws of physics - they too will wiggle and randomly do weird things, but on average, they will do what we intend for them to do.
A machine can be arbitrarily complicated.
We designed computers to manage the quantum and thermal noise "at the bottom" so we can mostly ignore it. We go to incredible lengths to make the constituent parts of our machines predictable, and when they aren't, we layer error correction on top. Cells usually don't do that: noise is inherently part of their behavior and isn't suppressed nearly as much as was often assumed.
The fact is that an amoeba cell behaves in a certain way for all amoebas. It does not go around and behave like a stone or like a drop of olive oil or even like a cell of some random bacterium.
It has very clear and obvious functions and the mechanisms inside the cell are the reason it consistently shows amoeba behavior.
I'd hate to break it to DNA correction machinery.
I didn‘t say every single molecule in the cell acts predictably. I said that the cell „performs a task it should perform and does so using the same approach across all instances.“
That doesn't seem like they're "using the same approach over all instances" to me.
The one about genetics seems to force conclusions that are palatable to modern sensibilities. How does Mendel accidentally fudging his results using eugenics prohibit “talk of good genes and bad genes”? There clearly are good and bad genes, this is obvious to anyone. It’s practically the whole point of the olympics to showcase people who have the best genetic prerequisites for their discipline. None of the technical minutiae of inheritance prevent us from breeding better sprinters. In fact we’ve done it with several animals. Whether or not any of this is ethical is not the field of biology’s concern.
The video about cells has a similar problem, where it acts like it wants to invalidate higher levels of abstraction because reality is more complicated. Of course biology doesn’t operate like a designed and manufactured apparatus, but omitting complexities irrelevant to the question at hand is the entire point of making diagrams. Does the thing turn methane into methanol? Yes, it does. There is no problem here. These could be great educational videos if they weren’t strawmanning so hard. This is especially obvious in his carefully designed definition of a machine.
Biology is just stupidly stochastic, but this stuff is akin to “nooooo, systems don’t »prefer« low energy states, they’re not conscious qq”. Like, okay, use a different verb if that makes you happy??
Saying Gene's aren't machines, because Machines are rigid bodies?? That is wrong, that seems to be the crux of his arguments, that gene's flex, and can become different shapes. Hello, machines do this.
My fishing rod is flexible. And I can cast over hand, or underhand, or side arm it under some trees.
> First, machines can be described in terms of a list of parts and a blueprint indicating how those parts fit together, meaning that someone who has never seen a particular kind of machine should in principle be able to assemble any number of copies—each virtually identical in appearance and performance—provided they can consult the machine’s design specifications. Second, as machines are designed to perform highly specific functions, their operation is tightly constrained, which is why it is possible to predict and control their behaviour. Third, machines are highly efficient in what they do because they always follow the exact same sequence of steps in every cycle of their operation. And fourth, the operation of machines is not continuous; their functioning can be interrupted and their parts examined without thereby jeopardizing their structural integrity.
And argues that cells look more like this:
> according to this alternative view, the cellular architecture is regarded as a fluid, self-organizing process; protein complexes are considered to be transient, pleomorphic ensembles; intracellular transport is deemed to result from the harnessing of Brownian motion; and cellular behaviour is viewed as a probabilistic affair, subject to constant stochastic fluctuations.
And
> Viewing the cell as a machine allows us to think of its organization in terms of modular, solid-state circuits that can be approached reductionistically, and it also gives us the confidence to expect that when we eventually work out how all of the cell’s parts fit together, we will be able to completely predict its behaviour. If, on the other hand, we view the cell as a highly integrated, self-organizing, fluid system composed of densely interconnected processes ever-subject to stochastic fluctuations, we no longer have reasons to suppose that achieving such epistemic goals is even possible, let alone feasible. The stark contrast between these two outlooks is exemplified by their strikingly different ways of understanding causation in the cell (Bizzarri et al., 2019), and it serves to explain why some researchers find it easier than others to obtain funding and publish their work.
But just looking at mitochondria as an example, and ATP transport. That looks very repeatable, machine like. It isn't like mitochondria just suddenly change function, or form out of random goo and change shape and function, they are pretty much transporting ATP. That is what they do. It is highly regular and repeatable and built from a blue print.
The self regulating goo is nice idea, I think using it to say we aren't machines is the stretch.
> this conclusion does not imply that every entity or process within the cell is being (or needs to be) reconceptualized. To be clear, the thesis I have sought to defend is not that all organelles exist as irreversible steady states, that every protein complex is a pleomorphic ensemble, and so on. It is rather that a very large number of cellular and molecular phenomena that were traditionally interpreted in terms that support the MCC are now being explained in terms that directly oppose it.
Where's my medal?
Computational or mechanical analogies are not totally wrong but they're dangerously over-reductive.
I never used to understand this position, until I saw right wing snowflakes getting triggered over a woman looking too manly at the Olympics. They confidently explained XX and XY to whomever would read their little meltdowns, and even rode back on their usual line that genitals determine gender - suddenly they care about hormone levels.
So I'm having to come around to the idea that over-reductive can be a real thing. Although I'm not sure that the sort of dumdum that dive off the deep end with these things would do any better.
A biology professor of mine put it this way: pretend you are reverse engineering alien technology. The stuff you are trying to understand was not designed by human minds. It was designed by evolution over billions of years, literally an alien intelligence that doesn't "think" anything like you do.
A big difference between biology and human engineering is that humans like one-part-one-function and linear chains of cause and effect. Biology isn't like that at all. It's an analog causal matrix where everything affects everything else to varying degrees and most parts have multiple simultaneous functions.
With biology, the code is running against nature, so the instruction set includes assumptions like "but if these two get close enough, then this other reaction occurs first". I suspect it can get so complicated that the only way to find out what it does is to run it.
There are isolated aspects of cells that are analogous to computation, but it would be extremely misleading to try and think of the cell as a computer or life as a computer, it is far messier than that, and in particular, the analogy implies some teleology or purpose that just isn't there.
Hunting, fishing, agriculture, clockwork, steam, electronics, software... such rich sources.
(And then the metaphors are invariably taken literally, hilarity ensues...)
But no. It's off into early Turing and von Neumann land, which is more philosophical than useful.
It's turtles all the way down.
Also the article discusses CA, just more fancy and see the same behavior:
>Alex Mordvintsev created a two-dimensional bff-like environment where each of a 200×200 array of “pixels” contains a tape, and interactions occur only between neighboring tapes on the grid. The tapes are interpreted as instructions for the iconic Zilog Z80 microprocessor, launched in 1976 and used in many 8-bit computers over the years (including the Sinclair ZX Spectrum, Osborne 1, and TRS-80). Here, too, complex replicators soon emerge out of the random interactions, evolving and spreading across the grid in successive waves.
This is amazing. I think the next step is to build a compiler that compiles into cellular automata.
I have to say I'm skeptical when anybody with a background solely in the monasteries of the "materialist interpretation" of the Matrix declares that even energy is a form of matter. There's even a guy in the Matrix who says that so many Matrices have been built within the Matrix experimentally, that with all probability he lives in one of those.
(I'm not just making a formulaic joke; I believe the informational/computational universe is a much better explanation of everything we see. I'm not saying digital computers, or quantum computers, not trying to shoehorn anything; the computer has the nature of our universe. But you know how when we shake hands, at a particle level we have to reinterpret to where our hands don't actually touch, our electrons repel each other, and perhaps some jump the gap? that is more informational than it is material; there is no need for the imagining of material quantum-bollards interacting; we do physics with math (abstract) not billiard balls (physical). Mind-body problem? there is no mind-body problem if the body is as abstract as the mind. Or rather, there still are some mind-body questions, but they doesn't seem as intractable.)
The classic assumption of physics is that, at some level, things are simple. For a long time, that worked. From F=ma to Maxwell's equations, the basic rules were short, and most results corresponded to those rules. Engineering is based on those rules. Quantum mechanics had people upset for decades, but it was eventually understood reasonably well, and led to another generation of engineering that worked.
But basic physics has been somewhat stuck for decades now. There's still no unified field theory. Smolin is suggesting that maybe there are no underlying simple rules.
[1] https://arstechnica.com/science/2023/01/requiem-for-a-string...
Humans have an intuition for the existence of "material" because on our scale, we can reach out and touch something. But on the femto or atto scale, this does not happen, or when it does happen, we describe it with quantum collision math.
So why cling to this intuition?
I'm simply saying that an immaterial universe with the same properties such that it is isomorphic to the universe that most believe we live in is a better thought experiment to carry in your head. For one, you'll stop thinking "mind body problem, what is mind such that it is not body?" instead you'll say "well, body is not, so it must be the same substance as mind, it's not really that strange after all. It's VMs all the way down"
It's a terribly reductive process. And the foundation of biases is deep and invisible.
Moving in the opposite direction would reveal a lot.
Alternatively, the natural laws might simply contain an infinite amount of information, which could never be stuffed into a finite algorithm. E.g., if the ratio between the electron mass and one of the quark masses is an uncomputable real number. Or if there are infinitely many laws, governing deeper and deeper structure ad infinitum past the subatomic level. The latter has some philosophical arguments against it (why would we apparently be near the top of the infinite structure?), but the former is consistent with the apparent continuum that physical constants reside in.
Even if the second is true, there is still a question about whether cells are "computational" in the same way computers are (little robots programmed by dna), or whether they're computational in the same way the photosphere of the Sun is (complex, chaotic physical processes). Which of those it is matters when we try to eg assign causation to how cells operate and make predictions about them.
But ultimately DNA is a functional encoding of computational processes.
Whether those computational processes are “natural” is independent of the machine operating in that environment.
I was reading through to validate that it’s all pretty basic stuff without citations to any philosophers, which is true, but it’s great for what it is. No disagreements here. They even summarized the Imitation Game correctly, which is quite rare! (Most people frame it as “a computer is conscious when it can fool a human”, which is, somewhat impressively, missing the point in two ways at once)
For example, when I say, in the beginning there was light, Einstein law of light to matter and matter to light holds true.
Same way, how can or which other part can you relate computation to?