How NOT To Think About Cells

[@SubAnima]

Responses to some of the common critiques I've gotten: *1. I disagree with your definition of a "machine."* I was deliberately vague on how to define what a machine is. I plucked out two key features (has static + specific parts) purely because this is how the metaphor is being used to do work in biology today. These are both wrong and are actively misleading people, as I explained in the video. Sure, perhaps in the future we could build machines with jiggly, non-specific parts. Perhaps our future machines will even be inspired by biology. Fantastic, but I don't care (at least not in this video). Biologists don’t hear “cell=machine” and think “ah yes you mean a complex, unpredictable, fluid, self-organising, agential machine that we haven’t built before” (well maybe all but two biologists: doi.org/10.3389/fevo.2021.650726 ) All in all, the point of the video was to help us conceptualise the cell more accurately, not get into the metaphysical weeds about what a machine is. There was a long back and forth conversation on Twitter about this point, between some of the philosophers working exactly in this area: twitter.com/evantthompson/status/1581410077831233537?s=46&t=9h3xV4_73Scc6VP5P-4SGw *2. Drew Berry's animations are commonly considered to be very accurate, why did you call them misleading?* In terms of the biology they depict, Drew does a decent job of illustrating DNA replication (minus a few nitpicks about proteins being too static, seeming to appear to 'know' where to go etc.) The scientific animation community has come quite a way from these animations though - here's one of my favourite's depicting the true chaos of the cell (albeit with proteins still a bit too stiff). kzbin.info/www/bejne/q3nIhYSCg6uHnbc Nonetheless, I still call Drew's animations misleading. Not because they're inaccurate but because of how they influence us to think about the cell. We see proteins moving like clockwork and then begin to think that the whole cell behaves that way. Everything must be running on clockwork, with static, specific gear-like pieces. Case in point, the Veritasium comments I put on screen. This is wrong, and should not be the mindset we aim towards. Hence, the animations are misleading. *3. What's your solution then?* No theory will continue to produce knowledge forever. There comes a time when the gold begins to run out. Some may disagree with me on this stating that we seem to be in a 'golden age' of data for biology. I would counter that and say that we still have no idea how to put the data together. And we are no closer to answering the tagline of this channel: what is life? As I have argued in another video (kzbin.info/www/bejne/d2Xcq35jbbR6qsU ) The problem stems from the fact that organisms embody a very different kind of causality to the type we are used to in physics/mechanicism. Namely, they make themselves. This cannot be captured with the machine metaphor and we need to move onwards to get a better picture of life. Onto what you ask? Well, I hinted at it in the video and perhaps I should have outlined a positive case for an alternative but I wanted to keep it below 10 minutes. So I can only defer to the source material, Dan Nicholson's paper (philpapers.org/archive/NICITC.pdf ) particularly section 6: "The cell is not a machine, but something altogether different-something more interesting yet also more unruly. It is a bounded, self-maintaining, steady-state organization of interconnected and interdependent processes; an integrated, dynamically stable, multi-scale system of conjugated fluxes collectively displaced from thermodynamic equilibrium." There are also many alternate metaphors we could employ e.g. a stream, a vortex, a fire. None of these are perfect either, but they capture the processual nature of organisms that much better. *4. You've completely ignored how successful the machine metaphor has been!* Yes I have, because you can get that from pretty much any other KZbin biology channel, paper or high-school textbook. Machine talk in biology is everywhere, it needs no introduction. If you’d like to make your own video talking up how good the machine metaphor has been, be my guest. All I am saying is that the “cell=machine” seam is running out of gold. If we acknowledge that reality and begin to look elsewhere, we might just find a whole lot more gold.

[@johannbauer2863]

I was already wondering, where you'd get the definition of machines from. As someone from the field of theoretical Computer science, the definition I had in mind didn't match at all (I thought of it as more of stuff that's able to compute or decide stuff, that don't have to exist, no solid parts and parts don't really have to have a specific function) Thanks for clarifying!

[@SubAnima]

@@johannbauer2863 No worries! I would also say that organisms aren't like Turing machines or finite-state machines either. I've made a video touching on that too: kzbin.info/www/bejne/d2Xcq35jbbR6qsU

[@RenderingUser]

​@@johannbauer2863 yea I thought that too Machines actually have some really abstract definitions I'd consider anything that converts energy into any different from in a predictable fashion as a machine

[@tbraghavendran]

How many proteins do we have?

[@anthonymorena6259]

Lol lets open the ol' thesaurus and rape the english language shall we...hang on...what does jargon mean again.....and what is SubAnima exactly?

[@thomasmurphy9429]

Speaking as a budding biochemist, I agree with 90% of this video with the big exception that the pathway maps were made to “make us feel more optimistic about what we can understand.” At least for real scientists, no not at all. We use these maps to chart out what we know to be a subset of known protein interactions, from a much larger set of known and unknown interactions, in order to help designing experiments about particular interactions.

[@mathiasrennochaves3533]

True... thats a tool. Not a therapeutic aproach for our mental illness. Albeit there is a lot of researchers needing some help (me included) kkkcrying

[@cachelesssociety5187]

@@mathiasrennochaves3533 yes - he made the still very valid and important point that while the flow maps are a tool, they are probably sometimes leading less the informed to view things in an unrealistically mechanized way. Of course, we need to share what we know and if everything is an undefined noodle not much would be conveyed, so to me both perspectives are right.

[@HuckleberryHim]

I think he is saying the whole paradigm of viewing cell biology this way is what makes people feel optimistic. We know staggeringly little about the details of cell biochemistry, far less than many people might assume, although we also do know quite a lot about specific things. That can be useful in research. But imagine how useful all the things we don't know are? It is hard to fathom what that would unlock. We are nowhere near that, because, as we continually realize, this science is extremely messy and complex.

[@doc.rankin577]

Thank you for stating this. I'm a chemist and took Biochem courses. When studying chymotrypsin and other enzymes, these pathways really helped me keep track of functions.

[@mojo2968]

the only thing about you is your knob so remove that word or you'll get a strike

[@marceloorlando9547]

As a PhD student in biophysics I constantly use these analogies betweens biological processes and engineering systems, never have I claimed that the cells behaves exactly according to those models, but such analogies are incredibly usefull and allow us to apply shitloads of methods and protocols used for decades in systems engineering to better understand the complexity of living things

[@presto900]

This video is just a layperson who has never taken a formal biology course assuming that biology professors are teaching students that proteins are static, the lock and key model is accurate, proteins don't change conformation or have multiple functions, etc. The ACKSHUALLY outlook this guy has is crazy lmfao

[@tomprice5496]

This entire video is just a semantic argument. He's saying that the metaphors scientist use to describe biological processes aren't perfectly apt descriptions of these complex processes. Well no shit, that's why they're considered simplified metaphors. This conversation is a waste of time. Also, the best way to view DNA-binding proteins structure in solution is NMRI, not x-ray crystallography.

[@c0x2A]

​@@tomprice5496 I suggest you read Susan Sontag's 'Illness as Metaphor', you may change your opinion on the usefulness of such conversations.

[@tomprice5496]

I suggest you re-read my comment. I like using simple metaphors to describe scientific processes. I don't need to use metaphors, because I have a masters degree in chemistry, but it's very useful when explaining stuff to a layperson. @@c0x2A

[@mathiasrennochaves3533]

Maybe his intent was just to change the perception of the general public that won't take a biology degree. Idk...

[@CrazyLinguiniLegs]

My proteins don’t jiggle, jiggle; they _fold_

[@TemporaryAccountOK]

It's jingle, not jiggle. The lyrics refer to coins and cash. Coins jingle, not jiggle. Please spread the word.

[@CrazyLinguiniLegs]

@@TemporaryAccountOK dude, how high are you? The name of the song is literally “Jiggle Jiggle”-which perfectly rhymes with the next line: “I like to see you _wiggle wiggle”_ And even if it was “jingle” (which it’s not), you had no problem with me changing the lyric “money” to “proteins” to fit the context of this video, but “jingle” to “jiggle” would bother you? 😂

[@TemporaryAccountOK]

@@CrazyLinguiniLegs You should listen to what that song is sampled from. The title is a mistake.

[@CrazyLinguiniLegs]

@@TemporaryAccountOK lol dude, are you trolling? If you’re serious, just google “Jiggle Jiggle Louis Theroux”

[@JosueRomero_B]

Underrated coment fr

[@MJS-lk2ej]

the one critique I have is when you said "proteins aren't really solids but more jiggly liquids" this is a misnomer. phases of matter are an emergent macroscopic phenomenon, it emerges from layers of specific structures of molecules. calling proteins, which are singular molecules (admittedly a drastic simplification) a specific state of matter is akin to calling a chemical reaction a specific state of matter, you can't because they are both sub-macroscopic, they come together to form the macroscopic.

[@EternalFinity]

proteins arent molecules, 🅱️etard

[@uncertaintytoworldpeace3650]

Don't know what the fuck ur saying at all but if it is that when I said "the universe is liquid because planets are particles" i'm here for that opinion...

[@MJS-lk2ej]

I am not entirely sure what you are saying so we might just be speaking over one another but what I was saying is that line is a composition fallacy, to use an analogy it is like saying "cake is flour" the parts come together in a way that makes something different, this is a phenomena in physics called emergence. you may be familiar with temperature being the average velocity of the measured particles? temperature is an example of an emergent phenomenon, it doesn't exist on an individual level, but only on a collective level, (it requires multiple components with varying properties to exist). ​@@uncertaintytoworldpeace3650

[@kellymoses8566]

@@uncertaintytoworldpeace3650 He is saying that states of matter like solids, liquids, and gasses are macroscopic properties that have no meaning when applied to individual molecules like a protein.

[@duhduhvesta]

I hate how we went right to the one diagram (alpha helix) that never makes sense to most of us. Alpha helix diagrams are incredibly confusing and one of the reasons most people don’t get the whole protein folding thing.

[@oswaldcobblebot]

Well, your arguments make the machine analogy even more fantastic. It's stil a "machine", but even 100 times more complex than shown in these animations.

[@Saleca]

Just because its jiggly, multitasking and shapeshifting doesn't mean it isn't machine like. Ironically Veritassium also made a video on soft machines.. and after all its not man made machine, is just machine like metaphorically.

[@therealspeedwagon1451]

There’s a difference between a man made machine and nature’s machines. Mother Nature has a much different idea on what a machine is, and her machines can even be self aware and realize the dream they all share.

[@vicenteabalosdominguez5257]

​@@therealspeedwagon1451her machines can certainly convince themselves they are self aware.

[@WelcomsAge]

Mother Nature 🤣🤣@@therealspeedwagon1451 You are part of my mother nature thanks mom

[@bugjams]

​@@therealspeedwagon1451 We could theoretically replicate living animals 1:1 as machines, though. Just because our technology isn't there yet, doesn't mean organisms aren't machines. We can already make thin sheets of metal made out of living cells, that are simultaneously metal _and_ organic "Mother nature" also has no purpose when making life, unless you're a delusional cultist who believes in a creator. Evolution is simply a process in which machines with beneficial traits self-replicate more efficiently than machines with not-as-beneficial traits.

[@OmniversalInsect]

​@@therealspeedwagon1451Wait a few decades and man machines may be able to do the same.

[@PearlyBarley]

Nice! The metaphor is exactly backwards: living systems aren't complicated machines. Machines are extremely simple mechanical systems. Simple mechanical systems are qualitatively different from complex living systems. Very few people getting engineering degrees are being taught systems theory, so they approach the horse from behind and wonder why it doesn't seem to have any interest in hay.

[@BarryKort]

As soon as you have three interacting components, you can run into mathematically chaotic dynamics, as Lagrange, Poincaré and others appreciated with something as simple as three bodies strictly obeying Newtonian gravitational mechanics. You can even get chaos with something as simple as a univariate recursion law, as Mitchell Feigenbaum discovered with the logistic function. If the solar system contained only the sun and the planet Mercury, you can ponder whether the precession of the orbit of Mercury is inherently periodic, but then you'd also have to pretend that the mass of the sun is constant, in violation of E = mc². So even very simple dynamic models with deterministic laws are seen to be mathematically chaotic, even at macroscopic scales. When you get down to quantum scales, chaotic choreography is a virtual certainty. In other words, qubits are prone to decohere pretty damn fast.

[@ernstborse1278]

This shows how the ‘machine’ has a life ! Very educational: kzbin.info/www/bejne/qn6unYN6d7d9Z6csi=W7Yp-revlQ-x0Gfl

[@64MilestotheGallon]

By that logic, complicated machines are even simpler mechanical systems

[@YainVieyra]

There's no limit to the complexity of a machine. They don't need to be extremely simple or even mechanical to be machines. Complex systems are not necessarily different from living systems. This is not proved nor refuted (eg. emergency vs god hypotheses). They can be dynamic too, namely, their structures can change *while* they are at work. Thinking about machines and systems as those ordinary objects from day to day is as misleading as the animations with the simplified models of life that this video tries to scrutinize.

[@theguythatcoment]

​@@64MilestotheGallonPlastic is really really hard to make without a conscious entity making sure that no other polymer chain contaminates the resin. Even the most minimal contamination would be enough to change the physical properties of said material. Nature is extremely complex and we try our best to simplify things with a lot of effort and energy. Simple machines arise from complexity in the process of creation or by pure luck in a stochastic system, complex machines are just machines.

[@trimarcopolo]

From a molecular point of view those types of animations are extremely valuable. In the field, we are all aware that brownian motion and microscopic reversibility are always present. Depicting the overal trend, however, allows us to better understand the process. Of course, they dont depict the full picture, but in most cases this is not needed. Anyway we could say that molecules are so small we cannot directly observe them, therefore, any visual represenration of them is wrong. But we need some level of abstraction to understand and communicate things, don't we? Now about the definition of molecular machines, this term is widely used in academia (it was even awarded a nobel prize in chemistry in 2016). The fact that they are not static doesn't mean that we cannot regard them as machines, but rather a new type of them operating under a different set of rules due to their size. And I think that there is the beuty of these things, we don't limit them to the macroscopic description of machines, but we rather expanded the concept of machines to the molecular level.

[@Krispio666]

Yeah... I was completely lost by his definition of a machine. Since when do machines have to be rigid and static? Since when do parts have to play only a single role? I'm not sure why he used these arbitrary criteria. This is not even true of the machines being used to play back this video, so you don't really have to look very far. I'm also not at all sure what the point is... The cell can still be thought of as a deterministic system which is the whole character that the machine analogy is trying to capture.

[@jaredfieseler6654]

I agree, I think it's perfectly fine to call proteins nano machines. Just because it's complicated and you don't understand everything doesn't mean it's not a machine. If you took a computer or airplane a thousand years ago they'd see magic and might not even be able to understand that those are machines.

[@sissonvapour6156]

The problem sir is when these abstractions are incorrect and or misleading. As for your “beuty” statement, we have not expanded the concept of machines to the molecular level, we have simply projected our machroscopic mechanistic innovations upon our observations of much more complex molecular processes. Happens all the time.

[@Jay_Johnson]

@@sissonvapour6156 Ok sure for Cells it may be misleading but why does the idea of a machine have to rule out Flexibility and Promiscuity? It's only incorrect if you define 'machine' to exclude those.

[@trimarcopolo]

@@sissonvapour6156 OK, but then anything that doesn't depict a molecule as a wave function and displays the molecular orbitals is an incorrect and misleading abstraction, but turns out that depicting a protein with the balls and stick model (used for the very purpose of this video) is an extremely useful and powerful abstraction, even the cartoon model is super useful and nobody goes around saying that you cannot use it because is misleading, that's ridiculous. As for the term molecular machines, it's very well established, we used terms such as molecular pumps, motors, switches, tweezers, etc. all the time, for both synthetic and biomolecules. Have you heard of the membrane PUMPS? The ATP synthase MOTOR? the Kinesin molecular WALKER? The azobenzene MECHANICAL SWITCH? and the list goes on and on. I understand the question on a deep level, and yeah it's an interesting topic when doing research, you need to take into account microscopic reversibility, molecular conformers, solvent molecules, Brownian motion, etc, etc, but come on, that is getting lost in the details, the animations are cool and they show the overall bias of the system. For explaining the subject to a general audience that is just fine.

[@shaunmcinnis566]

Hard to say it's unpredictable when the end result is a function.

[@michaelmbutler]

Or n functions. He throws infinity around a lot. That means "uncountably large". Bold claim, humbling, and ultimately almost certainly wrong. "Unknown as yet" fits better.

[@unk4617]

@@michaelmbutler its like saying we can never map the world because it changes too much or we can never predict the weather since its such a big mathematical challenge yeah you may be right without something like a jupiter brain we cant But we are doing quite a great job so far arent we ?

[@222quiet]

​@@unk4617so proteins following the theme of natural order by adapting the same way every organism known to man has been observed to have followed since the beginning of life is hard to conceptualize?

[@unk4617]

@@222quiet no not really

[@KevinMannix-sf5zk]

But that function is never functioning alone, its always being influenced the point he is making, is that the belief that the LEFT PFC can separate the false from the true is nonsense and we need to start admitting to ourselves that belief system is wrong about everything

[@nathanthp]

I see Veritasium as a channel that promotes curiosity in STEM, providing dissectible information about subjects that give viewers a solid foundation to begin building their own research on. I don't expect him to go into the fine details about how each individual protein behaves because, the way I see it, it is now my job to find that information. He sparked my curiosity, I set out to learn more, I watched your video. You provided great information to expand on the points made in the Veritasium video, but to say this is "NOT" how to think about cells is a pretentious statement considering most people only know "mitochondria = powerhouse of the cell."

[@TheEpicRandomGuy]

While I do appreciate a critical view of science communication, this video seems to avoid engaging with the reason why models like this exist in the first place. They simply give us the best chance of making useful conclusions. If there is a superior model for something scientists will generally trend towards using it. By stating only “here is where all of the scientific models have failed.” This video seems to beg the question: “Maybe we should stop trying to understand things?” Kind of a suspiciously vague take imo. That being said, I do want to thank you for putting together a video about your thoughts, as it was well polished and brought up some interesting ideas.

[@lukelouisackerman]

I think the problem with Vertiasium's use of the video (and this is a common problem I see with that channel) is that his audience usually 1. Is composed of science enthusiasts, not scientists and 2. Take's Derek as an authority in science education. This leads people to see this "very loose analogy" as an "acutal explanation". This is illustrated by all the shown comments of people making the comparisons to nanobots and nanomachines- Derek should show the animation, but also explain that it is not an accurate model- we know that the cell does not operate like this, we just currently have no better way of illustrating the operation.

[@Player-pj9kt]

There will always be shortcomings with any models used to illustrate complex things - but it does not invalidate them

[@Bahama4444]

​@@Player-pj9ktbingo

[@maxfofax5471]

I definitely agree with this take - classical mechanics doesn't give the full picture but there's a reason all physicists start with it before moving onto more accurate but complicated theories. This one seems to be nitpicking that a channel dedicated to digestible science isn't a full course. You can always be more accurate in how you represent info but it comes with the tradeoff of losing your viewers engagement.

[@maxfofax5471]

​@@Player-pj9ktusually finding the shortcomings with the model is what lands you fancy prizes 😊

[@joaodecarvalho7012]

"Impossible" and "infinite" are strong words.

[@annaclarafenyo8185]

They're also wrong words, in this context, and this creator says such wrong things with such confidence, he must be doing propaganda.

[@ivoryas1696]

@@annaclarafenyo8185 "must be" and "propagnada" are strong words, nowadays...

[@TheInfectous]

@@annaclarafenyo8185 Ah yes because he didn't use words with entirely literal meaning he must be doing propaganda. It's fine to be autistic but you should understand that and be a little more charitable to other people given you know you're frequently going to miss the meaning of peoples words or at least just be a little less vitriolic in general.

[@annaclarafenyo8185]

@@TheInfectous I am not autistic, just perceptive. This person is doing propaganda. Fascist propaganda. Against scientists.

[@kinguin7]

​@@TheInfectousit's a video that's supposed to be addressing "misleading" aspects of another video on a science topic... Yeah, he should be more accurate with his word choice.

[@eileen24816]

This pretty much just proves that the cellular process is just a far more complex machine, one that we don’t fully understand; A machine doesn’t need to be simple or complex it just is a process fulfilling a purpose right?

[@annaclarafenyo8185]

That's not what this video is claiming. It is making the (false) claim that the continuous motion of the parts make the cellular function like an analog system, not like a digital one. This is a false argument used be neo-fascists to explain why you can't simulate a cell. It's an old, wrong, argument.

[@rainhadainglaterra8829]

​@@annaclarafenyo8185what the fuck does fascism have to do with it?

[@annaclarafenyo8185]

@@rainhadainglaterra8829 Fascism denies that biological systems can be modelled or understood aside from the "will to power", the mysterious fluid that fills great men and leads them to take power. Seriously. They hate science.

[@rodschmidt8952]

Yes, if we want to consider the question "are cells machines?" the first question we must answer is: what do we mean by "machines"?

[@timo.5449]

A “machine” can be loosely translated as a system designed to solve a function, which itself is also made up of smaller subsystems each designed to solve smaller functions. Artificial machines mimic biological “machines.” Both exhibit specified complexities.

[@SteveEwe]

There's nothing wrong with saying that living organisms are LIKE machines. Metaphors are not meant to describe exactly. That's why they are metaphors. They are used to describe something similar (not exactly the same), to convey some aspect(s) in an imperfect manner. Veritasium need only make a small disclaimer something to the effect of "this is a model of a functioning molecule", and it's fine. Oversimplified, perhaps, but that is usually the case when trying to explain complex topics to a lay audience. And all of this is for a lay audience. We still use Bohr's model eventhough we know electrons don't orbit the nucleus that way. This metaphor doesn't give us a false sense of confidence in how much we know, it dispels a false sense of ignorance in how much we don't know. A lay audience would not have know otherwise, and presumed the scientific community didn't either, unless you happen to be a conspiracist who things they know it all and just aren't telling you. "These animations would be an incredibly useful learning resource for students learning these processes for the first time." Precisely. As for all the comments, this is the same kind of cringe comments you get from creationists. "You think you're nothing more than atoms" or "just a bunch of chemicals". No. We are atoms and chemicals, but more. Not "just", not "nothing more". There is indeed much more. The error is in thinking a narrow explanation from one domain explains the totality. Only the incurious think this way. If researchers in the field are overusing the metaphor inferring more than is valid to use, then thats an issue among researchers using the metaphor. Correct me if I'm wrong but I don't thing any of those researchers are listing a Veratasium video as reference source for their papers. Also, definitions for what constitute a "machine" are our definitions. Like any word, it is subject to change, just as our world does. What happens when we invent "machines" that are not solid, or if we find ways to build them from generic parts. Will you deny "machines" built from lego or erector sets?

[@eddie1975utube]

I love what you wrote about it “dispels a false sense of ignorance”. In this day and age, we know so much and we all have access to said knowledge so there is no excuse for believing in a 2000+ year old book that states we came from Adam and Eve and the Universe was built in 6 days and implies the Earth is 10,000 years old along with a talking snake and a man in a big fish for 3 days, etc, etc.

[@dovahkiin2]

@@eddie1975utube low quality bait

[@Area51-y1d]

I’m not readin allat

[@SteveEwe]

@@Area51-y1d thank you so much for your informative and insightful post letting us know you won't read it. My world is complete and now i can sleep better knowing this.

[@deviliongamer2527]

Beautifully written. But even though it is extremely helpful and useful to think about cellular mechanisms as the that of a machine, students must be guided that whatever they are taught is still an oversimplification and that the actual mechanism is much, much more complicated. It's not about the animations/diagrams/analogies being useful, rather it's about what's the truth. What is it that's actually happening? We still study Bohr's model to this day, but with the disclaimer that it is now an outdated and false model. This does not disregard the fact that it is really useful as a stepping stone for students who are learning about the atom for the first time, just that they should be taught that it's false and that the more accurate models of the atom are much more complex and hence will be taught to them at a later stage in their academic life. Metaphors definitely do not describe the original matter exactly, but it should be taught to the students that they are metaphors because a lot of the time, students think that these analogies are what is actually happening, which is false. Now, researchers may not be listing Veritasium's videos but, Veritasium's videos are not for a lay audience. And even if they are, a lay audience does not watch Veritasium's videos, they watch something else. Students watch these videos. Apart from being truthful to learning students, this 'disclaimer' that the analogies are just a model imbeds a seed of curiosity in the student's mind. They will then want to know much more about the actual cellular mechanism, and might become researchers themselves. (Sorry about the poor English.)

[@Dave-id6dk]

@SubAnima This is an interesting video that contains some useful points, but also suffers from a reliance on narrow definitions. First the good points: 1) The warnings against overconfidence are certainly warranted. As exciting as the recent decades have been for microbiology, there remain massive gaps in our knowledge, including "unknown unknowns." 2) It's important to understand the boundaries between metaphor and identity. As a STEM professional, it's obvious to me that descriptions of "circuitry" in a cellular context are only metaphorical, especially as it pertains to enzymatic pathways. But that usage could create misconceptions. 3) The video highlights the stochastic nature of the cellular environment. 4) Dan Nicholson's paper is an interesting and thoughtful read, and I think the video represents it fairly. So now the issues with the video: 1) As several other comments have highlighted, the main point of this video is that cells & their constituents are not machines. But this assertion is critically dependent on an understanding of "machine" that adds extra constraints. Most common definitions of the word (i.e., the way most people understand the term) emphasize two principal aspects--the assemblage of parts and resultant functionality. So when distinct parts come together to form a functional whole (or system), that is a "machine" as generally understood. You have added in private qualifications to disqualify proteins from being identified as machines. That individual proteins can shift between conformations ("wiggle") and large protein complexes often contain modular parts in no way violates the standard definition of machine. Actually, flexible and even fluid components are essential to many machines that we build and use everyday (e.g., transmission fluid, fuel, coolant, motor oil, refrigerant, battery electrolytes, hydraulic fluid). Though you seemed to dismiss definitional criticisms in your pinned comment, you should do better, especially if you are primarily in addressing biology from a philosophical standpoint. 2) The analogy to your bike wiggling seems particularly poorly thought out. The structure and function of machines is inextricably bound up with their environmental context. At the scale in which proteins exist, Brownian motion is the norm; it would be weird if they didn't wiggle in that environment! If your bike could be measured in Angstroms, it would wiggle too. Disqualifying proteins as machines because they differ from macro machines is just as wrongheaded as an F-1 driver saying that street legal tires aren't "really" tires because they don't work in the context of an F-1 race. The forces at work in the cellular environment mean that a functional system will have different constraints to satisfy as compared to bikes, cars, etc. 3) Your characterization of Drew Barry's work as misleading seems to ignore the fact that he has given lectures addressing some of the criticisms in your video. He talks about the challenges inherent in creating videos based on the literature that accurately portray the stochastic aspects of cellular processes while still being visually intelligible. I believe he has commented below. There are always tradeoffs/simplifications to be made in addressing a complex subject. If everything moved at speed, it would be unwatchable. 4) Both your video and Nicholson's paper seem to ignore perhaps the most compelling reason for machine language in biology: it is extremely successful at the macro level. Hearts are not "like" pumps, they ARE pumps; eyes are not "like" cameras, they ARE cameras; etc. The machine view of organisms at the level of gross anatomy is the bedrock of modern medicine and surgery. It's why we can replace heart valves and bad hips, perform laser eye surgery, and develop pharmaceuticals to solve specific malfunctions. Perhaps more could be said, but if I were to suggest a way forward, it would be this: instead of rejecting machine language in a cellular context, augment such descriptions by emphasizing the dynamism of the cellular environment, compare and contrast molecular machines to macro machines, and where metaphors are being used, make it clear that they are metaphors. Just my two cents😏

[@fanchiuho1]

Based 🙏

[@BarryKort]

Werner Heisenberg was the first to point out that there is always some amount of unavoidable blurriness in taking a picture. Most of the time, this is of no consequence. But if you are trying to take a picture of something very very tiny, then it does matter. You can still tell that something very very tiny is dancing, and you can even reckon how much energy is wrapped up in the dance routine, but you can't extract the fine details of the choreography.

[@SubAnima]

Yes! One of Dan's best critiques in his paper is that the physics of the cell is just so different down there compared to what we are used to with our macroscopic machines. The Brownian storm hits proteins like a hurricane. Plus the floppiness of these wobbly proteins ruins any hope of them acting like levers or anything - there's just not enough torque. Scale matters a huge amount here. I'm no physicist but your mention of Heisenberg does make me wonder how much quantum mechanics might play an interesting role too. Certainly possible at that scale hmm..

[@BarryKort]

@@SubAnima ~ There is good evidence that biological systems exploit natural phenomena that we characterize as quantum mechanical aspects of nature.

[@burkhardstackelberg1203]

We already have found examples of quantum entanglement in living systems and processes, such as sensing magnetism - happening above room temperature! So, I would not be surprised a lot if we found entanglement and tunneling and other quantum effects acting at the core of molecular biology at virtually any instance. Protein folding e.g. is a process that is not well understood; the best models still give us astronomical estimates for the time a protein takes to get into a vakid conformation, but in reality this process is really quick. If tunneling and/or entanglement is involved, the time scale of the process is much more plausible.

[@BarryKort]

Statistical Correlations are ubiquitous in systems where components interact. And the closer components are to their neighbors the stronger their behaviors are correlated. That's a feature of dancing, especially if we're talking about fermions, where no two fermions can be in the same place at the same time. Ginger Rogers and Fred Astaire remained closely coupled when they danced together, and so their movements were highly correlated. But their physical bodies each occupied their own distinct (if nearby) spaces.

[@raymondlines5404]

Heidelberg told us the picture is blurry because the object, itself, is blurry. At these scales. It seems to me quantum behavior should be everywhere. The bonding that makes these processes work is quantum behavior. The warm wet world of the cell just makes identifying the underlying physics harder. But the useful random behavior certainly feels like quantum behavior.

[@rubenhillier770]

The definition of machine according to the dictionary: "A machine is a physical system using power to apply forces and control movement to perform an action" so proteins may be super complex and unpredictable in all actions they can perform, but they still fall under a machine. These diagrams of metabolic pathways are good for teaching as it would be too much to explain it in a fluidly, dynamically changing system to new students.

[@pyropulseIXXI]

Yes, they are quite literally machines. This entire thing is stupid. He doesn't seem to understand that claiming cells aren't machines is to claim they disobey the laws of physics... you know like Classical MECHANICS and Quantum MECHANICS. Gee, I wonder why _mechanics_ is in the name??? Physicists don't tend to work on cars!!! Thus, I just proved cells are not machines!!! His definition of 'machine' is so stupid and absurd. He literally defines machine in such a way as to make cells not machines, Then his entire argument becomes just a tautology

[@jugbrewer]

so are thunderclouds machines? they’re physical systems, they use electrical power to control movement of ions and perform an action. the general dictionary is a lexicograpgical reference and shouldn’t be used for technical understanding. if you’re studying botany and you only understand what a plant is according webster’s definition you aren’t going to get very far.

[@rubenhillier770]

@@jugbrewer yes a storm is a machine, it's a type of engine. It's probably not the best way of describing these things but that does not make it false just it can give the wrong expression.

[@pyropulseIXXI]

@@jugbrewer You oafs will never learn. A cell is a literal machine. Unless you think a cell operates not according to physical laws

[@ballboys607]

​@@jugbrewer...yes lol

[@WerexZenok]

Just because a machine is more complex than you initially thought, it doesn't mean it's not a machine. But I appreciate the point you are trying to make.

[@Calc_Ulator]

You completely did grasp his explanation and missed the point altogether.

[@Schopenhauer69]

Exactly what I thought. This video seemed pedantic.

[@zrakonthekrakon494]

Technically cells are machines he isn’t trying to cease the metaphor, he’s trying to bring awareness to the fact cells are unlike any man made machine and shouldn’t be thought of in similar terms

[@FlyWithAlex]

Our group of long-time friends has a guy that arguments in a very similar way to you. Whenever he starts his rants, everybody starts rolling eyes. He will always claim to be "technically correct", not to say enlightened... while COMPLETELY missing the point and annoying everybody while doing so.

[@marciodelbarco93]

This video is basically "Look how smart I am saying these analogies doesn't describe the true nature of the protein"

[@mexbutler1661]

Well, 1. he does seem pretty smart and 2. he wasn't disrespectful in anything he said, just furthered the discussion, which personally I found enlightening. I find all the comments here as interesting as the video. Thanks to all who are participating.

[@unk4617]

@@mexbutler1661 the video is too vague to understand anything meaningful , he sidesteps a bunch of glaring issues which his own wording like the implication that diffrent parts of a machine dont server diffrent functions when in locations and enviorments

[@Artyomi]

@@unk4617I think the video is pretty clear in stating that biological systems are very fluid, chaotic, and random with many more layers of complexity than you can imagine. This video would be useless to someone just learning the basics, but to me is very important in showing a higher level of complexity in biology that is overlooked in imagining a rigid structure. I don’t agree that this doesn’t make these proteins any less of a “machine”, but I find it useful to reimagine my perceptions of cellular/nanoscale processes. It’s like if the video was about how the animations are wrong because they don’t show the insane speeds at which this stuff happens - it’s definitely not “wrong”, but to be given interesting information like “DNA polymerase adds 500 nucleotides/second” or “molecules move at 10-500 meters per second in a cell” would be very useful and interesting to shape how you think of a cell as you learn about it.

[@KaippsCafe]

I think he was explaining why budding molecular biologists and researchers should not use over simplified videos to understand the complex structure and dynamic interactions of proteins. Popular science is for the general lay public. It certainly has a place in society. Derek Muller and Michael Stevens (Vsauce) has made immesuarable contribution to the public understanding of science.

[@duhduhvesta]

Agreed. Anyone who gets it knows it’s more complicated & the original video was made to help folks get the process in perfect state. No video can incorporate every thing including the various hiccups that could occur at any time

[@japhethkallombo3820]

I'm glad I have met another KZbinr who thinks like a biochemist. The cell is complex and proteins switch function based on so many things. The rigidity of proteins varies thats why we might never know all the functions of one particular protein. In addition some functions show up only in rare environmental conditions. Proteins also show quantum effects on the molecular scale like the generation of excitons by pigment protein complexes.

[@SubAnima]

It's all so stochastic! You're totally right. Brings back some sense of wonder into the universe right?

[@japhethkallombo3820]

@@SubAnima True. There is no end to learning.

[@objective_psychology]

The “we may never know” mindset is antithetical to science and only serves to imbue a sense of mystery and excitement. Just because something can be phrased in less boring way doesn't mean it's less than the full truth.

[@pyropulseIXXI]

Cells are machines though. To claim otherwise is to claim they do not obey the laws of physics. They undergo changes in motions due to a power source The fact they jiggle doesn't make them 'not machines;' the fact we cannot map all their functions does not make them 'not machines.' The point of saying a cell is a machine is that the entire universe is MECHANICAL. That is why physics is called CLASSICAL MECHANICS and QUANTUM MECHANICS

[@insertname5421]

still, no matter how complex the parts are, still just a machine

[@jonathanpicket124]

These animations are very cool! I agree. And, it's good to be a bit critical as, yes, they don't show everything and couldn't possibly do so... nor are they meant to. They are learning/teaching tools. As such, being overly critical of them rings a bit hollow. There are a few issues with your critics: Proteins, when interacting with binding partners, absolutely can become rigid and tightly bound. This isn't misleading. Most proteins have some intrinsically disorders regions. This doesn't mean that the functional or protein interacting domains don't have specific roles and confirmations, though.. even in highly disordered proteins. But yes, alpha fold and AI, in general, will never be able to predict a structure for IDPs or disordered regions, as those generally do not have structure, independent of their binding partners. X-ray crystallography doesn't just give us the structure of a protein in one confirmation. It gives us many confirmations so that we can see most of the states the protein is capable of assuming. Most papers that discuss crystallography results will include discussions on the distribution of confirmations in order to make sense of the proteins' potential function(s). Most proteins are not moving about randomly throughout the cell. Most proteins are highly localized to where they perform their primary function (with the caveat that they first need to be assembled and delivered to that location). For many proteins, this means that they are localized in the cytosol, which, granted, is a huge portion of the cell and proteins that are cytosol-localized move around a lot. Aside from these errors and being a bit too critical (IMO) of some cool animations, this was an informative and well-made video. Thank you for working to push science communication forward, truly! ❤😀

[@wenkeadam362]

Thank you for sharing this thought provoking video. I don't think that the machine metaphor is misleading, as long as the student is told repeatedly that "this is just a model, the reality is much more complex". We use schematic models all the time and switch between them according to needs. When I say "one hour before sunrise" I can use the simplest geocentric flatearth model. When explaining why my friend is in a totally different timezone I need to use a model where the Earth is spherical and turns around it's axis. To add the complication of seasons I have to imagine a tilted axis, and the Earth traveling around the Sun, etc. The problem is when people are told that a particular model is really how reality works... And they get stuck in the model...

[@hamsandwich1860]

And to sum up, the proteins and complex molecules in a living organism are just like machine parts in a mechanical object; its just that with organisms your dynamic is based on affinities and reaction rates (chemistry). And again, chemistry is just the visible surface of particle physics.

[@GigAHerZ64]

"Jiggling" is not a problem. Machines purposefully do it - look up accelerometers and gyroscopes. Machines also have multiple configurations even on molecular level. Simplest example is the all-familiar chemical batteries we use everywhere. More complex examples would be the hundreds and thousands of computing cores in your every-day gaming videocard. In-between there are CPLD and FPGA chips. All the flexibility is there. "Moonlighting" is just like a CPU core getting constant context switches to process multiple running applications on a single core. It's obvious that you are strong on one side, but the other side is weaker. For some reason, i expected more balanced approach.

[@KevinMannix-sf5zk]

Take 7 musician's tell them to jam, the same song, every day, for the rest of their life No song will be the same , ever ! Take 7 dancer's tell them to dance to the music randomly every day for the rest of their life No dance will be the same ever ! Now tell the dancers and musician's to play and dance the exact same way to a song every day for the rest of their life , The Truth is they cant, but they can delude themselves into believing they can , By imagining emotions don't exist

[@nateshrager512]

I don't think the "parts are solid" as the main difference is entirely accurate but more that "parts are single-action". There are plenty of non-solid and multi-state parts in machines we commonly use (springs, compliant bendy mechanisms, resonating crystals) but from what I can think of in any machine the individual parts are never complex enough to change their function entirely to something else. That results in fundamental differences in both flexibility and capacity for self-repair, in addition to an informational richness that our current high-tech machines are not close to

[@Drikkerbadevand]

He's overly analysing on the side of biology but oversimplifying on the side of mechanical machines. It's an excellent analogy. It's like yeah, does this protein have the ability to do these other things? Yeah. But does that mean its another of their main functions? No. Can haemoglobin bind to carbon monoxide or can the transport proteins of the mitocondria bind to cyanide? Yes. But does that mean it's a function? No. The intended function of these structures are still known lol. Does putting gas in a diesel truck mean the fuel nozzle or whatever has a new function? No it just sprays gas i to the engine instead of diesel (pardon my analogy, I am NOT a mechanic lol) and the car breaks. You can also nitpick machines. Take two washing machines of the same model and compare nuts and bolts and lids, measurements of where holes were drilled etc. You're bound to find some differences because things were built with tolerances, much like enzymes etc probably evolved to fit required 'tolerances'. Some things need tight tolerances some dont. Doesnt mean the machines dont do the exact same thing.

[@vmcprojects]

@@Drikkerbadevand I completely agree with you what you said. He has a very narrow and rigid definition of what machines are capable of being, to the point that he makes it seem inconceivable that machines could have multiple shapes that give multiple functions like a protein. And if you accept his limited, narrow and rigid interpretation of machines, then he makes it seem like it's inappropriate to compare proteins to machines. I think a more appropriate thing to do is to find a machine that has multiple shapes, that can give you multiple functions, just like proteins. The example I would use is a Swiss Army knife, because it's common knowledge that Swiss Army knives aren't limited to just a single function, but they have various shapes and functions depending on the item you want to use (screw driver, wire cutter, bottle opener, knife, pliers, etc...). So therefore, it wouldn't be a lie or misleading to say that proteins are like machines, that have various shapes and functions like a Swiss Army knife. This isn't a difficult concept to convey to people, so it was kinda bizarre to me that he would fixate and obsess over something that seems fairly simple and trivial.

[@nugget6635]

Machines are simply put.. Things HUMAN-MADE that uhm do something specific. Cells are not machines because they are "plentifully autonomous.". Unlike machines. Biological organisms exist and act beyond our control thus are not machines. "Are you saying that if humans create something that goes beyond human control and evolves into something else this something else is no longer a machine?" That's goddamn right that would be the emergence of life.

[@JimBalter]

Computers have components that serve virtually any function.

[@saf271828]

As others have pointed out, the machine metaphor has been resoundingly successful in other contexts. There's perhaps a closer analogy to the modern understanding of how a cell works: LINDA systems. These software systems consist of a plurality of widely disparate (what we call "highly distributed") software modules communicating with each other (where communication is left deliberately nebulous) through what's called a "tuple space." A module is able to perform work only if it finds a tuple that matches its desired characteristics, and in exchange, it places its results back into tuple space. It does not care one whit who produces its input, nor does it care who consumes its output. Data consumption and production is not at all guaranteed to be deterministic (and in fact rarely is). This seems to me to behave just like MMO example you gave, being used for 150 different purposes: in a LINDA system, a single software module can also be used for 150 (or more!) different purposes. And, yet, the whole mechanism is still considered a machine. I'm not saying your thesis is wholly invalid because of this; I find the topic very fascinating either way. But, I do invite you to reconsider your understanding of what a "machine" is, because it will affect your argument in potentially profound ways. Thanks for the video though! It's been a long time since I even thought of LINDA computation systems.

[@tylerdavis3]

See I kind of think you have it almost backwards here. Just a thought take it or leave it. But this isn’t a case of “life acts similar to a machine” it’s more like “this machine acts similar to life”. You chose a good example which blurs the lines between the two, for sure. I think your example highlights that we should make machines more like life, in that the more unpredictable the tools we use are, the more possibility for efficiency there is.

[@abizkit94]

@@tylerdavis3 I do not think @saf271828 has it backwards. Physics, especially quantum physics, tells us that we are living in a non-deterministic universe. None the less, every interaction follows the rules of physics. Physics does not care whether we understand all these rules, and we can never truly know if what we find to be "the laws of physics" are actually the laws. We can only inch closer to the true rules and maybe make some educated guesses what they are through exploration and rigouros testing. There is no such thing as 100% certainty in physics, but certainly everything 100% follows physics. Just because most people see "machines" as something manmade does not mean that what we call life isn't just a machine itself. Sure vastly more complex than any manmade machine in existence, but that is not an argument against life being a machine.

[@random6033]

​​​@@abizkit94 Quantum physics don't tell us that, the Copenhagen interpretation does, but it's not the only possible interpretation, there's many worlds interpretation, pilot wave theory and superdeterminism for example, and both of those are deterministic

[@abizkit94]

@@random6033 Thank you for clarifying this, I should have been more precise. Under the Copenhagen interpretation the universe is not deterministic. I did not think of other interpretations, since any deterministic interpretation automatically can be seen as the universe just being a machine. I would even argue the many worlds interpretation is also deterministic, since anything that can happen does, although not observable by us. I wanted to specifically address those who want to see the world as non-deterministic, and present them a scientific view point that is compatible with that view but still compatible with machine thinking.

[@timothycushing5473]

Biology and Chemistry do not reduce to Physics. This is a complete fallacy.

[@joebloggsgogglebox]

Seems to me that "stochastic machine" might be a better description, or perhaps "very stochastic machine". Computers chips are also stochastic (i.e. random) to a certain degree, and chip makers take this into account when designing them by adding redundancy, however the amount of randomness is far far less than shown in this video.

[@garrettmillard525]

Indeed and it's also important to note that stochastic != random. The protein's shape and function is a function of it's environment, which can be controlled. Very few biological processes actually have proteins that are jumping through vastly different states - a protein that has many slightly different arrangements can still exhibit the same exact functions on a given substrate etc. Anyway, the organic process is wrought with individual failures all over the place, the same reason it has so very many logic checks and redundancy measures itself.

I agree with you and honestly at first I thought this was the point he was trying to make in the video: that entropy plays a much more significant role in a cell rather than in a bike... but then it was just criticizing our limited human approach to all complexity: simplifying. Anyway, I think it's fair to say from now on we should be thinking of mol biology in terms of big data, as long as the computational power is available to scientists around the world. And about the educational videos that portray proteins as machines being used as learning resources, it can't be just said that they do more harm than good. There's got to be a study about that to make any claims.

[@joebloggsgogglebox]

@ perhaps biologists should also be making much more use of probability theory & models.

[@brotong42]

LINDA systems use stochastic programming to increase efficiency. effectively makes many multi-core CPU s stochastic machine by design.

[@anywallsocket]

Stochastic yes, but also chaotic in that these system dynamics make great use of attractors in their state space for functioning probabilistically.

[@proveritate1205]

I think the machine analogy is extremely useful, though not completely matching; but that's what an analogy is all about. Cells and its components are not designed or made by humans, that the difference with an actual machine for starters; but its workings and mechanisms (even with all its flexible parts instead of solid ones) are certainly the same of that of a machine for all we know, and extremely complex one that is.

[@joshuaestrada1665]

Shape shifting tools for different functions still outlines a machine at work. Just cause we don’t come close to fully understand it doesn’t invalidate engineering principles that are correlated. We just can relate more when we uncover advanced engineering concepts that’s been in the cell for so long. Hence computer software code & information encoded in DNA

[@jsimonlarochelle]

When I watched the original video I knew that it was showing a schematized version of the molecular process. I understood that the molecular machine metaphor was ... a metaphor. I think implying that the machine metaphor is incorrect will confuse some people even more. I think that often, when people use the molecular machine metaphor they intend to convey that there is no "ghost in the machine". No extra-physical process involved in the functioning of a living being. This is an important message in this age of alternate truth and moral relativism. The original video did a good job of showing some of the unbelievable complexity of living beings. It also did a good job of showing that although we don't understand everything we do understand a lot about the world. Human beings know enough about the world to understand each other and come to an agreement on most topics if everyone sticks to science and stays in touch with reality.

[@gerritvalkering1068]

The problem starts when people forget it's a metaphor and really assume it's a machine and it works as cleanly and efficiently as that, or comparing DNA to a computer code and forget *that* is a metaphor too

[@magic8269]

@@gerritvalkering1068 I don't think anyone is missing the complexity of life. A cell is a machine, arguing that it's not only serves to convolute and mislead more so. It has parts with separe functions, using mechanical mechanisms to achieve a purpose, be it jiggly or not.

[@Jay_Johnson]

@@gerritvalkering1068 Who Is doing that? Who is this video for? I certainly haven't seen that and I assume Biosciences undergraduates (like myself and all my friends) would be the people to be making this mistake? High Schoolers? they don't have time to learn a more complex model.

[@aidap4299]

@@Jay_Johnson It’s pretty obvious that the people making mistakes probably aren’t people taking biology at a university level. The video is for an updated view on biology that updates our social view of the inner-workings of a cell. It’s like when we conceived of PTSD as ‘shell-shock’. The same argument likely existed of ‘but us Psychology students know what PTSD is, why should we update the term when we already understand the difference?’ There’s a benefit to increasing general understandings of things, not only for people who wish to further their knowledge and have been provided a somewhat inaccurate model on which to build on, but also because those that don’t study the subject further will only have the inaccurate model to understand. If we all still believed in shell-shock and only those who studied it at university recognised it as PTSD, I feel as though we as a society would be deprived of so many resources and the ability for the public to self-educate themselves would be severely diminished.

[@joaomarcos2089]

The "ghost in the machine" is a modern model brought forth (or at least popularized) by Descartes, and is not the only alternative to materialism or the idea that there isn't any "extra-fisical" foundation to every body and, consequently, the universe. More and more biologist and physicists are taking interest in Aristotelian metaphysics, a paradigm thrown away by Descartes, to explain the "machines" around us.

[@InformationEngineer59]

Y'know there was a time when we didn't understand computers. Had we understood the relationship between DNA and protein, we would have said, "see, not a machine". Then we invented computers and the process appears fundamentally computer-like. As far as your argument that proteins play multiple rolls, I have two "machine" analogies for you: Consider the wonderful transformer class of toys. These things convert between multiple radically different toys -- kinda like the proteins you describe. The other day I went fishing. I didn't have the necessary fishing weight. I looked around and found a nut and bolt. Poof, fishing weight. Now nuts and bolts are "moonlighting" as fishing weights. Yes, all biology is far beyond our current understanding. Yes, multi-cellular life is leaps and bounds beyond "simple" bacteria. However, I have found no magic in there. Stuff moves around because of its interactions with the other stuff moving around. Virtually all the movement, at its core, comes from processing ATP. Beyond our simple understanding? Yes. A machine? That too.

[@tofunoodles]

I'm neither a biologist, nor an engineer. The way I understood why proteins are not machines is that proteins don't have a concrete easy to define function. Taking your example with the fishing weight: if it behaved like a protein, coming in contact with water the nut and bolt might change to 2 feathers. Having not only a completely different function, but altering it's properties in a changed environment. Feel free to correct, I just stumbled upon this video by the grace of the algorithm. :D

[@Medicalscape]

Yes I agree he is basically saying that because things are able to do multiple and dynamic things and have a broad range of apperances and purposes that they can't be used as an analoy for working like machines.... but this is pedantic, it's not that they do not act like machines they do just they are to complex for us to fully understand.... so I agree... beyond our understand at this point absolutly... a machine.. yeah that too

[@Medicalscape]

I think you are correct on the way you are interpreting this example but that is the fundamental point of his example "they don't have a concrete easy to define function" but they still have a function,and it is definable. We just are not able to figure out how yet... atleast not fully. The body does work like a machine it is just complex so if the nut comes in contact into water and turns into 2 feathers... that was its function, it was made to fit a piece of the larger machine(organism), so that it was capable of becoming 2 feathers. Just because a peice of a machine can change, have multiple purposes, even alter it's behavior and how it interacts with it's environment; does not make the analogy of the machine wrong... but rather just shows us how detailed and complex the machine is. @@tofunoodles

[@Drikkerbadevand]

@@tofunoodles I have studied bioanalytical science. I am not a biochemical engineer, but I know enzymes are routinely used for lab analysis. As are antibodies and other structures. While it is true that there are some randomness to them, they are still deemed quite predictable and most proteins do not randomly 'phaseswitch' between shapes. They have a main function. Just because the nuts and bolts CAN be used as fishing weights, their use globally in 99.99999% of instances are for their intended purpose. He's taken the exception and made it the rule. Does haemoglobin also bind to carbon monoxide? Yes, but does that mean it is its intended function? No, it's just a fluke of the mechanics (pardon the pun) of the protein. Does filling a gas car with diesel mean the fuel nozzle or whatever has changed its primary/intended function (being supplying the engine with GAS)? No it just sprays diesel instead of gas and the car breaks down. Yes, there are no exact alike 'parts' in biology as there are with machines, but if you nitpick machines enough, you could spot differences between the individual parts too, but if you look at the greater picture, both machines, despite being comprised of slightly different parts, both work in very comparable ways.

[@tofunoodles]

Hm. I didn't really take away "protein=machine is wrong" from the video. More like "protein=machine is incomplete". Then again, I'm not in the field, so I genuinely have no idea. @@Medicalscape

[@Rockyzach88]

1. Veritasium appeals to a much more general audience but I understand the need to be more correct. 2. Looking at a chemical, biological, or neurophysical system from the perspective of a machine is still a useful perspective in unlocking new discoveries. You don't have to do one or another. You need a spectrum of perspectives at least in the beginning.

[@jasperdodge6312]

This video was very good for me thanks a lot man, it put me back in my place where I/we all belong which is a humble place where we just don't know everything yet if ever. I really really took those animations to heart since I've seen them

[@juliamccoey7496]

Don't let this video dissuade you, those animations are fantastic. I'm a scientist. I was first trained in biochemistry. I'm no expert but I'm on a paper about protein structural disorder. Proteins aren't entirely unpredictable random shape-changing jellies that are incomprehensible to us, like this video seems to suggest. Their structures do matter, they do have specific roles because of their structures, even the intrinsically disordered proteins change to specific structures when they complex with things. It is completely fine to think of proteins as machines, just remember they're not 'just' machines. Please, whatever you do, don't take away from this one guy's video the idea that molecular biology is impenetrable and something we just can't understand. That's not the attitude of a discoverer.

[@petersmythe6462]

It's actually interesting looking at the proteins move because this really shows you how temperature is so important to enzymes and why most temperature-hardened enzymes physically look tougher.

[@puddlejumper3259]

I never had any issue understanding that they're much more complicated than the machines we're familiar with. And having had this analogy does not impair my ability to understand that cells are a soup of molecules floating about randomly, leading to complex interaction well beyond main functions. I think the claim that the machine analogy detracts from the actual complexity and that this complexity is not analogous to a machine is unfounded. I continue to argue that it is a machine but far far more complicated than any physical machines we've created... Even computers are very complex machines that operate on data with ridiculous scope of their capabilities due to emergence. But the CPU is only one small part of a computer. So again, still the complexity is nothing compared to a cell.

[@allanjmcpherson]

It seems to me the primary benefit of this metaphor for the layman is to understand that biology is deterministic. This is true even for the more complicated models you propose need to/are taking over in biology. It's apparent that biologists need to move beyond this theory, but as you pointed out it's a good entry point. It might even still be useful for some things within the field, I don't know. I'm not a biologist. But I do know that we still use Newtonian mechanics even though we know they're wrong. For most things, they're right enough.

[@PeloquinDavid]

Why do you say that cell function is deterministic? Certain functions (photosynthesis in the chlorophyll of plant cells, for example) are already understood to be a fundamentally quantum processes - and there are undoubtedly other examples. More to the point, living cells are VERY complex systems and are therefore inherently chaotic even to the extent that they are arguably deterministic at some scale of analysis. Most people think of deterministic systems as highly predictable, but the chaotic behaviour of complex systems means they are much harder to predict than simple mechanical or electronic devices designed to do a very limited number of things...

[@bugjams]

​@@PeloquinDavid Quantum fluctuations exist everywhere, and thus, their presence doesn't conflict with deterministic systems. "Quantum" simply means "true randomness" (supposedly, I should add. Perhaps quantum processes are just very complex, but ultimately also deterministic). And randomness can still be factored into deterministic equations, as a variable. All we need to do is calculate for the highest and lowest quantum fluctuations, and from there we can map out all possible deterministic outcomes.

[@anar.bastanov]

@@PeloquinDavid I believe quantum physics and everything it leads to are "superdeterministic." You might have heard of this theory already before, basically superdeterminism asserts that "fundamentally quantum processes" are not random but rather dependent on hidden values that we cannot detect or measure yet. Thus, all the existence and the "systems" in our existence, no matter how intricate they can become, can be "precomputed."

[@levih.2158]

@@bugjams It seems to me "possible deterministic outcomes" is oxymoronic. The ideas of: 1) possibility as "one state can lead to several possible next states" and 2) determinism as "one state can lead to one and only one next state" ... are incompatible as foundations of existence. Perhaps you adhere to the idea of branching parralel universes for every outcome of every "quantum event"?

[@hotmultimedia]

Saying that biology is deterministic is a bit misleading imo. As an analogy, think about a neural network with some 3 billion parameters. All affecting the output in some way that we don't understand nor have tools to understand. Sure, if it's running on a determistic subtrate, and you can set the initial conditions perfectly, you will get the same result. But if you have even slightly different condition at the startup, the result can be totally different, and it will be very hard to determine why. And now think of a biological system, where you can't even set any initial conditions. Does the distinction of determistic / non-deterministic even make any sense here?

[@felicitynotes8574]

Always leaving subanima mind blown 🤯🤯

[@ZandarKoad]

I don't care what other content you've put out, or will put out. I'm subbed for this video alone. WELL DONE.

[@profquad]

cringe

[@apburner1]

Essentially what you are saying is that because the animations aren't depicting everything going on in the cell, or could possibly happen in the cell, all at the same time that they are inaccurate...

[@makethisgowhoosh]

Thanks for your clarification of the bleeding obvious.

[@germanhoyos4422]

So basicly its EVEN MORE complex and detailed than most think. wow these protiens are beyond anything in complexity that we have invented or hope to invent

[@SubAnima]

Yes precisely!

[@dawnkeyy]

I mean everything is more complex than "most" think. Take a 4 stroke internal combustion engine for an example. There are a bunch of videos of explaining the basic principle - intake compression - combustion - expulsion. When you dive deeper into the operation and structure, you have a bunch of chemistry that goes into the development of fuel, the material science that goes into the development of the alloys of the engine block, pistons, seals, injectors. You have a bunch of physics that goes into design of the architecture of all those components. You have a bunch of computer science that goes into designing the control mechanisms that monitor and adjust the injection, the fuel mixture etc. etc. etc. The videos like the one by Veritasium is at the "intake compression combustion expulsion" level of knowledge. Biochemists literally spend years writing their PhDs on incredibly specific details that would be analogous to how the specific alloy used in just the injectors affects carbon buildup on them and how it effects performance, longevity and the fuel economy. This video basically argues that the "intake compression combustion expulsion" level explanations do more harm than good.

[@annaclarafenyo8185]

They aren't THAT complex, they just have Brownian motion. The real complexity is in the information carrying molecules, not the proteins.

[@germanhoyos4422]

@@annaclarafenyo8185 a single cell is more complex than any machine man has ever built... and its not THAT complex... lol ok guy...

[@germanhoyos4422]

@@dawnkeyy a single blade of grass is more complex than any machine man has ever built.... comparing an combustion engine to life/dna is like comparing a rock to an f35... but sure whatevs u say guy..

[@hatfieldrick]

I'm no biologist, just an interested savant -- but I always wondered about those diagrams, knowing the general human tendency to oversimplify. I suspect a far more pertinent metaphor than the machine would be cellular automata such as described by Von Neuman and Wolfram etc, in which nothing persists but the dynamic underlying pattern itself. They can appear completely chaotic, while constantly preserving some essential pattern of information and performing various operations.

[@therealspeedwagon1451]

In a way all life forms are a biological Von Neumann machine. A Von Neumann machine is in essence a man made self replicating grey goo gone rogue and spreading like wildfire. In my honest opinion the very fundamental meaning of life is simply to consume and reproduce. That’s what powers all forms of life from the smallest bacteria to the biggest blue whale. Human lives however are much different. We realize the world we live in, we all share the dream of consciousness and are the universe looking back upon itself. Human lives are different to all other forms of life, call it God if you will. But to humans the meaning of life is far more than just consuming and reproducing.

[@aidap4299]

please don’t go around calling urself a savant :///

[@therealspeedwagon1451]

@@aidap4299 you never know, he could very well be an autistic savant

[@hatfieldrick]

i am in fact an autistic savant. @@aidap4299

[@meinteybergen4617]

I am studying plant biotechnology and i have never heard someone critcally asses this topic. Wow! You just changed my view significantly.

[@tylerbakeman]

Just because their model was oversimplified, does it mean it deserves to be called misleading Every theory is technically axiomatically incomplete (for natural models). So, even if we had an updated model- it could also be called misleading which is paradoxical. Ideally, we should be able to recognize the accuracy of these models, and congratulate each other

[@DeeAnnPaulReskBunnell]

I teach high school and I see great value in the machine metaphor as an introduction to molecular biology to replace the naive model students hold which is, "black box magic and anthropomorphisms." They can unlearn the machine metaphor after they have "mined all the gold" there is to get from it, just as physics students unlearn much of classical mechanics. It doesn't mean we stop using it, it just means its not the final tool in the tool box.

[@mjolniron]

He’s splitting hairs. The molecular machine metaphor is completely applicable.

[@TucsonDude]

I'm an engineer and have also studied bio in college. However, to me, cell biology is so complex that it's almost MAGIC.

[@mlthornton1]

For sure, it's a wonder anyone ever conceives

[@jotabe1789]

This is my problem exactly with "biological processes are not machines". If you say that they're not machines, not mechanicist, then you're veering into "vitalism". Into magic.

[@TucsonDude]

@@jotabe1789 Thanks! I'm being facetious. I even wonder if mankind's mind can even fully comprehend the complexity of biological processes...even if a time traveler from the future tried to educate us. Thoughts?

[@malcolmscrivener8750]

@@TucsonDudeI don’t believe a finite creation can even remotely begin to understand the mind of its infinite Creator . That’s why Christians give Almighty God the glory , and worship Him !

[@dclarkchem]

The correct word is 'supernatural'.

[@jessica_ashlee]

You are incredibly well spoken and talented at simplifying complex subjects - thank you!

[@vernonbrechin4207]

Thank you for this fine critique. I appreciate this presentation that addresses some of the weaknesses of the mechanistic views presented in such wonderful videos. I believe that such videos appeal to most people who crave greater simplicity. I cherish knowing how much more complex such things are than what we already know.

[@Williamwilliam1531]

So it sounds like cells are basically tiny, wonderfully complicated machines.

[@BierBart12]

"You can take a blurry picture of someone, but you won't know how well they can dance" is such a brilliant line

[@prapanthebachelorette6803]

Exactly

[@fungushoney9958]

its absolutely the line of the video, maybe even the line of all time

[@chocolate_maned_wolf]

No it's not lmao, its like saying the sky is blue

[@JimBalter]

It's stupid. You can take a clear picture of them and you still won't know. You could have a video of them walking down the street and you still won't know. Think about Elaine of Seinfeld. The line is completely irrelevant.

[@sebastians3773]

> if my bike jiggled like that I wouldn't be able to ride it > pretty strange for your machine to be doing unpredictable jobs The thrust of these statements is somewhat confusing to me. Are you suggesting that because some parts of the cell have functions innumerable to human beings at the moment, they they do not qualify to count as a component of a machine? I agree that oversimplification is something that must be avoided in all complex fields. But is the machine analogy as a whole bad because the cell is far more complex than any functional machine that we've ever been able to make a species? Is it not the limitations you're placing on the definition of what a machine can look like thats the over simplification? I feel this video is throwing the baby out with the bathwater a bit. The cell performs functions on a mass scale more consistently and reliably than anything we've ever seen, if anything we could look at the cell and conclude that our machines could take a page from its book.

[@SubAnima]

This is a very fair critique and your sentiment is reflected in the literature, namely this paper: doi.org/10.3389/fevo.2021.650726 But the point of the video is not to get into the weeds about what a machine actually is. The problem is that biologists DO often think of the cell in the way I laid out, which is incorrect and what I wanted to fight against. Perhaps one day we will build machines that can do the things cells can do today. That’s totally possible, but not the focus of the video. Also if you’re interested, there was a long back and forth on Twitter on this, you can have a look at the main thread here: twitter.com/evantthompson/status/1581410077831233537?s=46&t=9h3xV4_73Scc6VP5P-4SGw

[@rikardk9387]

I didn’t know how much I needed a channel like this

[@ssnypzzct6479]

Mate. What a bloody brilliant video. I’ve been in this field of biomedical science for 15 years. I’ve cited those papers, watch those videos, taught from that perspective and came to the same conclusion you have. You seem at least 10 years younger than me and it’s so refreshing to see your generation come to this conclusion. Your philosophy is on point! Keep up the good work I think I might have to subscribe 👌🏾

[@minu42yu]

FANTASTIC video! I was blown away by dr Drew Barry's animation and not being a biologist I accepted it as a mostly accurate representation of the cell "machinery". I had a hard time wrapping my mind around the insane complexity shown in the animation, but was nevertheless left with the impression that we are on the cusp of deciphering and eventually "bio-hacking" our bio-hardware. With wobbly dancing proteins that change configurations and functions this achievement is probably further away in the distant future. Your explanation is very clear, the production style is also classroom--ready. The world needs much more material like this! You have a new subscriber (or actually two, because my son who studies biology will also subscribe, he also liked the video). You deserve 1000 x more subscribers. Keep up the good work!

[@SubAnima]

Thank you so much!! This is exactly the impact I wanted to have with this video, it’s so good to hear 🥰🥰. And thanks for the new subscribe!

[@aedeatia]

The only comparison to machines that I encountered in biology class was ATP synthase, where it seemed vitally important that the rotational motion is what causes ATP to be created. I don't remember being taught that everything that goes on inside a cell is mechanical.

[@LineOfThy]

That's the issue, because the average youtube watcher doesn't have access yo classes like that, and are more likely to be mislead into believing ideas like all cells are mechanical.

[@annaclarafenyo8185]

It makes no difference if it is "mechanical" or "jiggly", the end result is the same--- it's a machine.

[@annaclarafenyo8185]

@@LineOfThyThe characteristic of a cell isn't that it is "mechanical" like a gear-box, but that it is "mechanical" in the sense that there are parts in configurations that change in predictable ways into other configurations. That is undeniably true. The jiggling motion, the soft-motion, and the multi-tasking don't change anything about the predictable behavior of the device. It's a machine just like any other. This video is fascist propaganda.

[@LineOfThy]

@@annaclarafenyo8185 Fascist prop- are you actually kidding me?! I was formulating an argument but- Jesus that caught me off guard

[@Iamtheactuator]

@@annaclarafenyo8185 im interested in what you are talking about

[@Aqua2D]

but machines dont need rigid parts, in fact, in the examples listed, the machines have non rigid parts as *a feature*, not a bug (tires, bimetallic strips, etc)

[@cryo-maniac]

this video is really weird. It's more phlosophy than scientific fact. and argues for/about basicly nothing. Science will generally just retrofit a previous term or create a new one within some time if the need is there. it doesnt really matter if cells are machines as a technicality or not. It wont reallly change the way they function or the way they are modeled/understood

[@dy7296]

Although in lecture earlier this week I've already learned that the same protein can change depending on conditions, you changed my view of protein functions even further. Thank you so much for this video.

[@profquad]

don't listen to this guy he's a hack. Machines can have parts that perform multiple tasks, look at a computer chip

[@a199719971997]

As someone currently (as in sitting at the bench at this very moment) working with ELPs, I appreciate the IDP shoutout :) Much love from NY, USA

[@AJCEJ]

BABE! COME QUICK, NEW SUBANIMA VIDEO'S OUT!!

[@profquad]

Who said machines have to be solid? And how are you classifying proteins in terms of states of matter?

[@cryo-maniac]

I remember watching this video a year ago, it felt like a fever dream. I just wanted to come and check comments to see if free will still existed on youtube comments and was pleasently surprised. the whole video (and chanel) is a logical falacy made to support the authors belife that life is "un-imaginable", "un-explainable", "magical" or "above science"

[@profquad]

@@cryo-maniacglad I could inspire hope. the inane drive for likes and subscriptions casts a dark shadow on rational thought

[@stephenl9463]

Appreciate this video very much. Shows lots of hard work and insight. Thanks!

[@SubAnima]

Glad you enjoyed it!

[@dividead100]

Your explanation is cool, useful, it clarifies a lot and the level of complexity does make it feel distinctly different from what Veritasium showed but it still feels like a machine, just even more complex. Also, while it seems logical that the jiggling is very relevant and maybe also inherent to the function of the small machines and thus a relevant clarification, the reason they jiggle is because they're really small things in a fluid so the jiggling bikes are a pointless comparison because bikes can't jiggle because they're big.

[@nicolaskrinis7614]

Firstly, not a fan of veritasium. Concerning your contribution, I would say it's outstanding, and it should be required viewing for students at a very young age. Anything that can demolish the sand castle of hubris that creates an illusion that we understand, in depth, anything about how cells and their components function, is a great contribution. Thank you for this.

[@RandomAmbles]

I think you're wrong. But very constructively so! This is a response to several of your videos, not just this one. I think a lot of my issues with critiques of the machine metaphor and math & physics-based approaches to biology boil down to the assumption that these approaches are purely reductionist, static, analytical but not synthetic, and materialist - when in fact they needn't be. It over-simplifies math, machine thinking, and physics and then blames them for over-simplifying biology! The machine metaphor is a metaphor and all metaphors are misleading on some level. This I happily grant you. Machines are intentionally made by humans using the technologies we've developed - cells aren't, for now. However, the machine metaphor suggests that we can understand, disassemble, redesign, and repair biological organisms - as we most certainly can. I used the CRISPR Cas9 system (with HDR) to edit the genome of E coli. cells and turned (some) of them from blue to white. It didn't work perfectly. I don't know why it didn't (I suspect my streaking technique and the method I used to introduce additives to my plates of bacteria). But the success of others indicates to me that what was going on in the cell was highly predictable and determined by only a few controllable factors. There were doubtless many other processes occurring - but these simply didn't influence the outcome very much. I take issue when people use language like, "cells can't be *just* machines!" or "mere" machines, or "brute" machines. This is the perspective of someone who uses machines - but not someone who designs or makes them. No machine is perfectly rigid and solid. I'm not just talking about flextures here either. It's a settled fact in statics that everything is made of rubber and everything that moves vibrates. Slop is nessesary for assembling machines and allowing their parts to move. Issues of clearance for parts in different positions are in many ways analogous to different conformations of proteins. Oils are used to keep internals away from surrounding solvents. A flathead screwdriver is rarely ever used to turn flathead screws and nearly everything looks like a hammer when you need to drive a nail. The machine metaphor also helps to give people hope that very complex systems are ultimately explicable and that their experimental behavior depends on a finite number of factors. It's not just a heaping pile of protein spaghetti as some claim. Every knot was once straight rope, as they say. But sure, I hear you. Like all metaphors, the machine metaphor is limited. For deeper understanding we turn to math and to physics. The ordered structure of living things that emerges from a largely chaotic environment results from the pumping of entropy. This requires the concentration and dissipation of energy. Entropy in closed physical systems always increases, meaning that unlikely ordered states regress to the mean and become disordered. Yet living organisms clearly run backwards in this respect. They're growing ordered structures. This can only be explained by understanding that organisms are not closed physical systems. But that doesn't mean that they're not physical systems. It just just means they're Open physical systems that require interaction with their environment in order to survive and grow. There's some really interesting work being done in integrated metabolic theory - and even more fascinating work in understanding how organisms model their environments through embodied computation by understanding the process in terms of thermodynamics and information theory. Math and physics have absolutely no issue at all with treating objects as stable flows. In many ways the difference between a noun and a verb breaks down when you look at it in terms of physical behavior. This is perhaps most famously depicted in the case of light having both properties of a photon particle and properties of an electromagnetic wave. Mathematics is not the most empirical of the sciences... to say the least, but it can very neatly model processes and relationships that might be thought irreducibly complex, unapproachably abstract, or purely philosophical and beyond the reach of logic and rationality. Dynamics, chaos theory, information theory, and statistical mechanics are not easily escaped. I believe strongly that every phenomenon in the universe can, in theory, be boiled down to mathematics. Perhaps that mathematics has yet to be developed and the study of some very unusual physical systems will inspire its creation - or perhaps someone will invent the math in a flight of abstract fantasy only to discover that it's how the world actually works. But I think there is absolutely nothing beyond the grasp of math. Not consciousness nor love nor life nor death nor meaning nor purpose nor taste nor goodness itself is. Math is the ultimate metaphor - and it can represent reality arbitrarily closely. Brownian motion is statistical and follows predictable patterns, displaying regularity that can allow us to make conclusions about the nature of the things it influences. This is how Einstein developed strong evidence for the atomic theory of matter. It's not truly random - only complexly psudo-random. Relatedly, let's turn to supposedly "non-functional" non-coding genetic material. I understand biology largely from the perspective of the gene level. Genes built from nucleic acids, whether as DNA or RNA or whatever, are the fundamental units of replication in biology. They're probably not the only replicating units, but they are necessary for all living things to carry on from generation to generation. If the organism is the riverbanks, the gene line is the water it needs to flow. Consider that there might be environments in which it is beneficial to live in a series of organisms with greater or lesser susceptibility to genetic drift. The amount of genetic drift is clearly and noticeably different across different species that live in different environments. Some species of jellyfish have been around unchanged for more than 200 million years. In other cases we can see genetic drift in action. The genes decide which genes are conserved - and which aren't. It makes sense, then, that large stretches of genomes would sometimes be composed of experimental new sequences. Species in competitive environments requiring frequent adaptation would have died out if they weren't capable of trying out new, mostly useless or even harmful changes. And the conserved genes in those organisms would have died out - being out-competed by combinations of genes which make adaptations more likely. Circling back to proteins, we can still try to figure out how much of the time proteins spend in one type of confirmation vs every other, or how often they're close enough to do some particular function. Their motions are complex, but again, not completely random. There's still order there to be sussed out. I have my own thoughts on the formation of multicellular organization and the evolutionary pressures that give rise to it but it's beyond the scope of this comment and hasn't been tested. Consider the work of EO Wilson on mathematical modeling of ant hive behaviors. Or consider the work of Richard Dawkins on the extended phenotype to get a better idea of of how we can actually understand some of the more complex behaviors of organisms in their environments.

[@SubAnima]

Hello again, Random Ambles. I’ll respond point by point, sorry for the delay got spooked by this comment's length when it first came through and promised myself I'd respond later. Later is now :) 1. It *seems* as though we can ‘understand, disassemble, redesign and repair’ organisms but I would hesitate to say that we can do this in general. Do we really know what our genes do? Do we know what all their products interact with? Even things like lncRNAs (doi.org/10.3389/fgene.2022.831068 )? We have almost certainly deluded ourselves into thinking we know much more than we do. CRISPR is great, but there is way more unpredictability in the cell that we can begin know what is happening. “The machine metaphor also helps to give people hope that very complex systems are ultimately explicable and that their experimental behavior depends on a finite number of factors.” I think that hope is completely in vain. Yes there might be a finite number of factors, but they have chaotic, non-linear interactions a lot of the time (doi.org/10.1002/bies.201900226 ) Maybe we will have to agree to disagree on this point, but I don’t think we actually know that much about cells at all. Our inability to make synthetic cells is my key defence there. Do that and *maybe* I might reconsider my position. 2. See the pinned comment for my response on ‘not all machines have solid + rigid parts’ 3. “For deeper understanding we turn to math and to physics.” Really? I don’t know many anthropologists that need physics to get a deeper understanding of the indigenous nations of Australia. 4. "But I think there is absolutely nothing beyond the grasp of math." Sure if we buy into Pythagorean religious faith in math. But I don't think we have the mathematical tools to truly convey the self-referentiality/circular causality featured in organisms yet - Gödel's incompleteness theorem and Russel's paradox case in point. Category theory looks like a good start but we'll probably need more. DEs will not do: kzbin.info/www/bejne/eGaofZSegLp0h7M 5. The Extended Phenotype is a terrible, reductionist way of thinking about organisms. I'd explain more, but it's almost certainly going to be in the next video. Jake

[@kimboxdorfer7010]

My family has a genetic disease where proteins Misfold in the brain and become infectious or prions. The entire explanation for this disease process is proteins folding into an incorrect shape. Then those proteins touch other proteins causing them to also misfold. The disease is completely explained by the shape of the protein. Do you think misfolding proteins and the shape of those proteins is an accurate way to describe Cruetzfeldt Jakobs disease?

[@YtongT]

One vote for yes. Prions aggregate and get stuck in their diseased conformation. In that sense they're pretty solid

[@ShadowTechAlchemy]

This was great! Its always "Now we know such and such". Then 10 years later, "we used to think such and such but now we know", on and on. How about " We may never know reality but we continue to explore it" .

[@SubAnima]

Exactly. We used to look up at wonder at the universe and go "wow, we are so small and we know nothing." Now that we've impressed ourselves with these ingenious little things called machines we think reality must be just like that - the universe must be all clockwork!! We got arrogant, that's for sure and I think that's a shame. Anyway, sorry for the rant we clearly agree haha. Thanks for watching, appreciate the support!

[@stephenl9463]

Agree with this. It is a matter addressed by the philosophy of science, which does not strive to reach a factual conclusion, but further philosophical investigation as to how science is understood and practiced given its contemporary context. It is not news that the machine metaphor undermines science. This has been debated since Kant by philosophers.

[@Compulsive_LARPer]

As a Chilean Biologist that had the privilege of getting his degree at Varela's and Maturana's alma mater (Universidad de Chile), this video managed to hit me right in the feels, man. Liked and subscribed!

[@giannidjr4594]

I really liked your video, seems to be a couple of comments that are fixed on the catch phrase but what you say makes sense to me. Thinking of proteins in a more dynamic way is important in more advanced molecular biology courses. It seems like a detail, but I do agree on the idea that the analogy on machines is useful but it has its limitations. Every analogy has limitations and you simply point them in a polite and useful way. You didn't attack anyone, you simply share and I really liked and appreciate the examples you took (I am currently seeing them). You did not entered into the existential dilemma of "are we machines?" you simply pointed that an analogy of machine (the way the majority of us think about machines) has a limit and make you make an excellent video that relate several concepts. I don't know if this helps anyone but thank you for the video I liked it.

[@snakejuce]

I feel you have been wrongly represented by the comments on this vid. In fact I was scrolling down fully expecting praise, instead I was disappointed to find unjustified criticisms lol. It's all good, we're all human, it is what it is. Though imho I don't think 95% of it is warranted, but I guess that's just me 🤷. It appears that some are reacting without really knowing what they are reacting towards, thinking you are somehow throwing shade on the benefits that these animations could espouse. I totally get where you're coming from, and in fact this video is VERY IMPORTANT. So thank you, from the bottom of my heart, for reminding us that the beautiful "machinery" in our bodies is far more complex/nuanced than an animation reveals it to be. I also agree on the usage/definitions you've outlined in this video. Just discovered your channel, and I appreciate you doing this. Peace be with you my good brother. Thanks again for this awesome reminder.

[@SubAnima]

Thank you!

[@issouamine217]

Oh boy... Too many things to say here... But first things first... What is a machine? If you define a machine in wrong way then obviously you would conclude something wrong... For example if thermal jiggling makes molecular Machines not machines then No nano-machine can exist, that's just how things at a nano level must be, so yeah.. Protiens jiggle and that's not a problem. Another point, protiens don't have a fixed shape.. Yes they don't, their function is dependent on their ability to change shape (conformation) in a very discret way so they have a fixed number of functional states (state 1 to state 2 just like alot of machine parts do (think of a car cylinder changing its stages to function).. And by the way my friend what you have shown us in the video is not changes in conformation but changes in fold and those proteins are called Metamorphics proteins (very different from changes in conformation within the same fold). Also, Multiple functions is not something against a metaphor for machines : a wheel in a car have two functions depending on the situation!! It either makes the car roll or make it stop (creates friction with the ground) !! It is used to steer the car too... All moonlighting peoteins do there work in a regulated way... You make it sound like proteins go around the cell and do a bunch of random functions. A protein having multiple functions inside a cell has nothing to do with the accuracy of the machine metaphor. In conclusion you took some misuses of the metaphor and made a false generalization on the metaphor itself... The metaphor was and is still very useful for research I agree with you on one level the cell is not a machine, it has a machine logic to it certainly, but as a whole it is not a machine like human machines are.

[@SubAnima]

See the pinned comment for an answer to why I defined a machine like that. Indeed I am very dubious of nanomachines (at least in the sense that they will in any way resemble our macroscopic machines). The physics of the cell is just so different down there compared to what we are used to with our macroscopic machines. The Brownian storm of molecules hits proteins like a hurricane, shoving them around every which way. Plus the floppiness of these wobbly proteins ruins any hope of them acting like levers or anything - there's just not enough torque. Scale matters a huge amount here. As for functions, the problem is not just that proteins are doing lots of different jobs, it's that these jobs are unpredictable. The categorising you wish to do is not possible. You can describe categorically what the multiple functions of a car’ parts are. We can't do this with proteins. The cell is too messy. Moonlighting is not entirely regular as you say, how could we possibly know for sure we know all of a protein’s interactions? I am not denying that the machine metaphor has been useful in the past. It certainly has been, as you point out. But now that we know what we do about proteins and the cell in the 21st century, we should reconsider it and see if it really holds up to scrutiny. It's not just that the cell is a complex machine. It would quite frankly be the strangest machine we've ever known. Can you turn the cell off and on again? Can you get any machine we know to build itself completely? Can you program a cell completely from its genetic code?(thanks to single-cell studies we know there is a huge amount of heterogeneity amongst cells even with identical genetics, so the answer to this must be no). All in all, before you respond to this (if you do) I would plead you to read Dan Nicholson's paper first and then let me know what you think. Here's the link. philpapers.org/archive/NICITC.pdf

[@issouamine217]

@@SubAnima Thanks, The author of the paper and i assume you too, both have a probelm with the idea that cells have machines inside of them like those of manmade machines. I agree there is nothing like that inside cells. If that's the point of all of this then okay.. But i guess you and the author of the paper are criticizing the very concept of Machines inside cells (or cells as machines as a whole). I very much disagree and i ll explain why. The author of the paper from its start to its end is enumerating the many ways man made machines differ from Molecular assemblies (for me i call them molecular Machines). But I don't think that anybody with knowledge about molecular biology and about the very different conditions the Macro world and Micro or Nano worlds would impose on the characteristics of Machines that should operate under them, I say, no one with such knowledge would say molecular Machines are the exact and same as Man made machines or even will use the same strategies to solve problems (even similar problems). One famous example of the very different constrains the Macor and Micro/Nano worlds impose on its inhabitants and their machines (tools) is how would they swim for example? We humans and all swiming macro creature use the reciprocal motion AKA the power stroke mechanism (hand over hand or flippers and so on).. But in the micro/nano world that is a completely useless mechanism Micro organisms cannot use the power stroke mechanism to Swim because of the low Reynolds number the environment under their size imposes! So micro /nano systems cannot (or better not) use macro systems mechanism for very good reasons. See for Example this paper for. More on low Reynolds number www.nature.com/articles/ncomms6119 Anyway, the point is, when discussing the concept of molecular Machines itself one must take the very different constrains the macro vs nano Worlds present. For example, the pieces are "soft" and jiggling and are constantly bombarded by all sorts of objets (Brownien motion) is completely irrelevant to the concept itself, it only tells Us what we don't deny or misunderstand (and are fully aware of) that man made and biological machines are made using fundamentally different materials and have (must) very different properties and operateunder very different constrains. In fact let's use one Example from the paper, the one about molecular motors (kinesin), this motor is operating under very different conditions for those of man made motor, so even if the molecular Ratchet model is the correct one, that does not negate the fact that kinesin is a molecular Machine it still uses energy to do work , it's just a molecular machine that uses energy to harness Brownien motion energy rather than overcoming it (through its conformational changes), it is asking to a motor on a boat that uses energy to deploys a sail to harness wind energy, the difference is on a macroscale it is more useful and practical to use energy overcome wind than to harness its power (the wind is not like the Brownien motion that hits you from all Sides randomly and can take you wherever you want if you use It correctly.) In conclusion, the molecular machine concept is true. The molecular Machines of biology do not (and cannot ) have the same properties as man-made machines that's one misconception. when used correctly and by taking the relevant differences between the macro/micro worlds and what to expect from them, the metaphor is extremely useful (look at the amount of fruitful research that was and is still being guided by it) End Note : you said Moonlighting is not regulated and that the same protein may do Many functions at the same time, this is not true, first proteins can have many uses at the same time (that is not moonlighting as the protein have the same function that is just used in different ways in the same environment and conditions ), moonlighting is always linked to changes in environment and in conditions, Take the example of The enzyme Acotinase that is normally an Enzyme, but transform into an Iron responsive element when iron is low (the regulation here is inbuilt), the aconitase is not doing both functions all The time, but switch conditionally just when needed (regulated function). Well i hope that might help you, i enjoyed your video it was though provoking

[@SubAnima]

I think we agree on most of this actually, at least on what the cell looks like down there. Of course, scale matters a huge deal for all the reasons you mention. But the problem is that people are still using the metaphor incorrectly and that is what I wanted to fight against. For instance, we still don't fully understand how the prokaryotic flagella operates but the base assumption is that there must be some mechanism to generate a torque exactly like how macroscopic motors work. This seems like a very odd assumption given the Brownian nature of the microscopic world. And I would say this is a prime example of how the metaphor misleads researchers: doi.org/10.1016/j.tibs.2021.06.005 Second, every undergraduate biologist gets taught wiring diagrams for genetic regulatory networks. Again, given how much bumping around there is in the cell and the sheer amount of stuff here, it is very strange to conclude that proteins are only going to interact with one and only one substrate/protein. For this reason, I still disagree with your conclusion on moonlighting. It is very much NOT always linked to changes in environment/conditions. It is a natural consequence of the stochastic nature of the cell. Cross-talk and transient and unpredictable interactions are to be expected when we look at the cell like this: doi.org/10.1016/S0898-6568(01)00168-1 (see figure 1) Yet we still draw circuit diagrams in professional papers and textbooks when this is clearly an oversimplification. Is that not actively pushing research down the wrong path? What benefits is the metaphor adding here? I disagree that the machine metaphor is useful. I would say it does much more damage than good. It gives us a false sense of control over the cell and makes us think we know more than we do. I suspect you'll disagree with that, but hopefully I've clarified my point of view. Thanks for watching regardless, I'm glad it was thought provoking.

[@issouamine217]

@@SubAnima Yes we agree on the Data but we disagree on the interpretations and about the picture it paints. Speaking about Genetic circuits, calling them circuits is not wrong but it is not true either, it only captures a part of how proteins interact and its topology, that is jsut part of the truth. A more apt naming would be genetic or Signaling integrated circuits (or networks) for example "development gene regulatory networks" is a great naming for how transcription factors interact to guide development, So using better name that contain the circuit concept but more elaborated to give the idea that its not simple circuitry but an integrated one is much better so people expect many more possible interactions to exist. Google" integrated circuitry diagrams" and you will find diagrams that look very much like the ones in biology with components having many inputs and outputs... Biology is just much much more complex. Last point, i see that you (and the author of the paper you mentioned) are repeating the same claim, that protein interactions are unpredictable and chaotic... That's true only to some extent, It seems to me (from the citations provided) that he is confused between the fact that proteins have many interacting partners inside cells (some are even called Hub proteins or Inegrators) is the reason, but still at the same time most have only few. There are some general interactions that all proteins must undergo (for example they all must interact with the proteosome for degradation and with the ubiquitin system... Etc) those are not part of their function but rather non-specific fonctionnal interactions for maintenence, (the proteosome cannot be built in a manner where it has specific interaction with all the proteins inside the cell, that's just not possible, but all proteins must have a sort of signal that the proteosome recognize, and also an interactome studies cannot detect the difference ).. If proteins cannot avoid promiscuous interactions wich are just a result of the fact that we are dealing with entities at the Molecular level, their Functional interactions will be overwhelmed, no Signal transduction is going to be possible, no function is gonna be possible (imagine a protein competing with all other proteins for its functional partner inside a cell!) that's just Infomation Theory requirements and the cells are indeed informational systems. The nano world challenges must be solved and overcomed if any system is to be functional and cells are indeed functioning! The existante of weak promiscuous interactions in some proteins are tolerated, but those must not be confused with the non-specific functional interactions and certainly not with the many specific interacting partners a proteind could have inside a network. The matter is not simple, simply throwing the Machine Concept and the metaphor because some aspects of it are not understood or misused is not very helpful. The end.

[@garyhargis4627]

The machine metaphor is a tool to lend understanding to the non-technical like myself. The machine metaphor is meant to imply mission, intent, precision, inputs and outputs, non-randomness, complexity, etc. A schematic drawing is also useful to convey similar information. The advance science necessarily outgrows earlier explanations. Isaac Newton's apple too was a crude and humble beginning for physics. Curious to know if the machine metaphor swims too close to those pesky non-materialists who maintain that a machine requires a design.

[@SubAnima]

I disagree. The metaphor is actively misleading for all the reasons you list. The cell is not precise, it is hugely stochastic and operates because of random collisions, not deterministic laws. There is no schematic diagram for all the protein interactions. We don’t need to continue to teach the wrong thing to do better science when better ways of thinking are already available. Its not so hard to think of a cell like a hurricane with stuff bouncing around everywhere for instance! I talked more about the use of metaphors in science in this video if you’re interested: kzbin.info/www/bejne/sKGsooRmpaymZ6c And on creationism, well I’m not a materialist or a naturalist so im not too fussed there. But yes, Dan Nicholson the author of the paper I based this on, certainly argues that any argument against the machine metaphor is an argument against creationism.

[@DepletedUrbranium]

@@SubAnima So what? Fluid mechanics are chaotic, but it doesn't follow that ships don't work, or submarines, or any maritime machines. Yes the interactome is more complex than just one mind might hold, but that doesn't mean it doesn't function coherently at a local level. Your "nothing to see here" attitude is horrible. Tons of biomolecules are tagged for specific destinations.

[@alan1408]

@Prodigious147The term ‘living’ doesn’t work on molecular levels imo. What do you consider here as being ‘alive’?

[@alan1408]

@Prodigious147 Because you answered on a discussion about interactions (of molecules) within a cell. Maybe I don’t understand what you mean with your answer

[@jurel-enlatado1]

@@SubAnima I don't think you understand why we have scientific models and diagrams.

[@cjson]

I really appreciate the clarity and nuance of this video, it really conveys a more accurate understanding of how dynamic and complex cells truly are. That said, I feel like this deeper understanding of the cell’s dynamic components should qualify, rather than negate, the fact that a cell’s protein components have/are parts (1), which are solid (2) and specific (3). Namely, it should qualify them in the following ways: a cell’s protein components are not fixed parts in a single mechanism or process, but are part of many different mechanisms/processes (1*); these proteins are not rigid (whether rigidity equates to solidity is possibly a moot point), but flexible and dynamic, adopting many different (and often useful) conformations (2*); these proteins are often not monofunctional, but polyfunctional, playing a role in a huge variety of processes (3*). My fear is that negating, rather than qualifying that a cell has solid, specific parts (like machines) may cause someone to think that cells are less amazing, intricate, or worthy of wonder than artificial machines, when actually the opposite is true. (I believe the opposite is true because, to me, the co-option of proteins into many processes, their dynamic nature, and polyfunctionality makes them more worthy of wonder than artificial machines with less dynamic and integrated parts). Furthermore, having observed motor proteins (like dynein) in action using fluorescence microscopy, I would also say that, at least for a significant portion of proteins, there would still be relevant and helpful analogies which could be drawn between them and artificial machines. In summary, I would argue that a cell’s components are, in the main, unlike artificial machines, not because they are less amazing, but rather more amazing than such machines. I understand, however, that you probably believe the same thing, and so again I am very grateful for you sharing this information and getting it out there, as it is extremely helpful and interesting.

[@EricBLivingston]

I like this video; it basically reminds us that these mechanisms are quite complex and foreign and to be careful about oversimplification, even if the simplified metaphors prove useful. I think it’s a good thing to keep in mind!

[@michaelshea4834]

I think you are missing the point of the Veritasium video - mainly to strike awe and pique curiosity to know more.

[@SubAnima]

Sure, but the point of science communication should not just be to strike awe - it must also show the most accurate science. Else I could “strike awe” by showing how amazing it is that Earth is at the centre of the solar system. I also think it is much more awe inspiring to show how stochastic the cell can be and that it defies our attempts to analyse it like a machine.

[@michaelshea4834]

@@SubAnima I'll ignore the facetious parts of your comment, but I will point out that KZbin is NOT an education platform. Many think that it is, but it simply is not. It is a entertainment platform. Nothing more. Awe is a very good thing. Awe engenders respect. It piques curiosity, and for those who desire, can go find the more detailed truths. Try teaching the intricate details on a video here, and your audience will be very small. Do it the way Veritasium does, and not only will the audience be large, but it will also learn some basics unconstrained by minutia.

[@SubAnima]

I’ve learnt more on KZbin than anything I’ve studied in a formal context. I wouldn’t be the person I am, with the knowledge I have, without it. I dont want to entertain, I want to teach. If my audience stays small so be it. Also see my most recent video for some discussion on what I think pedagogy on KZbin should look like: kzbin.info/www/bejne/sKGsooRmpaymZ6c I think i mention it about 3/4 of the way through.

[@thom1218]

Strange for machines to be doing unpredictable jobs... and yet complex neural networks accomplish their trained tasks in a very similar black-box style where a single given neuron the network may be filling multiple different roles in delivering the solutions to different input problems in ways that we can't comprehend.

[@soylentgreenb]

This is not so surprising. A programmer would say that a piece of code that unpredictably interacts with distant parts of the code is bad and "spaghetti code" because it's all a tangle of things doing multiple functions and being called by other random bits of code with no clear structure or documentation. Nature doesn't document the source code or code intelligently; it just kills the mistakes. If it's helpful, it's not a bug, it's a feature. This is also the way neural networks function; they are not programmed, they are emergent out of the training algorithm and lots of trial and error where the fittest networks are retained to do further permutations and training. You end up with the same type of kludge.

[@marymccoy7035]

Neurons are a different can of worms

[@tobiaswilhelmi4819]

I don't know, I have mixed thoughts about the overall idea of this video. I can wrap my mind around the idea that this biological circuit boards can lead into wrongful thinking. On the other hand are these part of middle school curriculum and public edutainment and maybe they are at the right level of detail for these purposes. Complex enough to transport information while not being overwhelming and discouraging. It is only at academic level when they are to rough. When you learn a second language at school for the most part of it you learn 1 : 1 translations and it's fine. Only when you get to higher levels you have to correct your knowledge and you learn the fine shifts of meaning (due to different cultural contexts) when it comes to translating from one language to another. I think the same applies here. Molecular "machines" are "good enough" knowledge for Joe Average. Also: the animations are pretty cool. They are kinda the beautiful colorful pictures of galaxies. Not accurate, but engaging.

[@SubAnima]

Thanks for writing your thoughts. But I fundamentally disagree with this approach to biological pedagogy because it assumes that students are these naive souls that are only ready for the truth once they're older. Teaching kids the machine model does not train them to do science well. In fact, it actively encourages them down the wrong path. Surely the point of a good education is to teach students how to do modern biology. As minutephysics has mentioned in a video at some point, it would be like teaching students flat earth physics for their entire school careers and then showing them a globe and apologising for lying to them once they come to uni. I don't really see the advantage of teaching the machine model, besides pretending to budding biology students that we know more than we do. As for motivation, I think it would be much more interesting as a student to see how much we *don't* know. That would make me want to go into biology and do research to solve new problems, rather than it seeming like we already know all the answers. It need not be overwhelming or discouraging either - understanding what the cell *really* looks can be easily communicated to students with some much better animations (e.g. kzbin.info/www/bejne/q3nIhYSCg6uHnbc ) Quite frankly, if you can understand the concept of cooked spaghetti, you can understand what proteins look like. Students are not stupid.

[@RenderingUser]

​​​@@SubAnima "naiive souls who's only for the truth when they're older" There's a step by step process to understanding everything Machine model is the perfect way to get going with it. They can move onto the chaos later. I don't want my head to explode as I learn about the chaos before the predicable. Also, the flat earth analogy doesn't work since the earth being round is a very basic concept. Since we go in order of complexity, that is a non issue

[@SubAnima]

@@RenderingUser See my comments towards the end of this video r.e. “Shouldn’t we teach the easy stuff first??” kzbin.info/www/bejne/sKGsooRmpaymZ6c

[@EvilNeuro]

@@RenderingUser basic to the point it took humans thousands of years to learn

[@RenderingUser]

@@EvilNeuro it appearantly took em millions to learn how to talk Your point? Simplicity doesn't come from how long things took to be discovered or observed. Simplicity of a concept can come from how much content there is, and how detailed it is. Not necessarily how the info came about.

[@doglabdogtraining-gus.8873]

Dude, thank you so much for correcting previous assumptions on biology, it helped me a lot.

[@amirahadid7580]

What can I say... You surely deserve more subscribers.

[@StrangeCornersOfThought]

Ah snap! New @subanima video!

[@leslieviljoen]

I've read the pinned comment but I still think the cell IS a machine - just one made out of bits of interlocking multipurpose jell-o. What makes a machine is mechanisms, which the cell clearly has. Still, this is a great video, it's great to know that the animations only give a very simplified view of the situation.

[@technosins7123]

Every single machine you mentioned "jiggles" at that molecular level, what kind of semantic nightmare are you living in mate?

[@birdbites]

But this doesn't debunk the machine analogy, it just says it's a more complex machine than some of the animations and explanations have shown

[@olivrobinson]

This was great. Our models of the world are imperfect approximations, but they get better over time

[@kellymoses8566]

So Veritasium is wrong because he doesn't agree with the definition of machine that you created?

[@jamesthomas6984]

"From my personal definitions, everyone else is wrong because I think machine means something different"

[@conejeitor]

A flexible machine, is still a machine.

[@LuisAldamiz]

Is it?

[@conejeitor]

@@LuisAldamizwhy not?

[@LuisAldamiz]

@@conejeitor - Define "machine". A 1707 definition found in Wikipedia: "Machine, or Engine, in Mechanicks, is whatsoever hath Force sufficient either to raise or stop the Motion of a Body. Simple Machines are commonly reckoned to be Six in Number, viz. the Ballance, Leaver, Pulley, Wheel, Wedge, and Screw. Compound Machines, or Engines, are innumerable". So roiginally this implies certain simple machines and their combinations, but of course in the field of "mechanicks" (word that is at the root of "machine" anyhow).

[@conejeitor]

@@LuisAldamiz exactly

[@LuisAldamiz]

@@conejeitor - So how does my hemoglobin molecule work as a screw (or any other machine in that list)? Maybe we could find something that resemble levers of all those fundamental machines, much as we can find in our hands, but that's all and many of the interactions are actually more chemical and even quantum-mechanical than actually mechanical. It may have aspects of machine but I rather see those as binding the chemistry rather and always one step away from "kboom".

[@Clockworkbio]

I've been animating biochemical processes for years -- and I always loved the 'clockwork' metaphor as a way to help communicate the complexities here. But that way of thinking really boxes you in and keeps folks from grasping some of the essential complexities here. Great video and a great way to unpack that Nicholson paper. Not sure how I can rebrand here--but figuring it out.

[@SubAnima]

Hey thanks for the comment and the kind words! Really love your channel too, have watched all your vids 😍!

[@randomvintagemap160]

please do not rebrand I love your channel as it is

[@gabrielrodriguez6333]

My professor would really enjoy your video. Moving from an introductory bio class to an upper level cell bio course, I realized that most of what I had been taught was either a gross oversimplification or… wrong. As I take lab courses and read more literature, it’s obvious we generate more questions than answers. Which is not a bad thing, but we cannot overestimate how much know.

[@flytrapYTP]

I don't think im quite catching what the distinction is between a complicated machine and a cell. If a machine incorporates randomness, does it stop being a machine?

[@thetobyntr9540]

He's too focused on what we commonly think of and see as the definition of machine rather than the idea of a system made of interacting parts meant to accomplish a task or tasks. If he had questioned his definition of a machine and wondered how a machine using parts made of individual molecules would have to work then this would be a very different video.

[@InsideInterpreting]

As someone dealing with damaging machine metaphors in my own field, I have to say this is an excellent video and I agree that sometimes we have to be ready to drop metaphors, once the purpose they served is no longer being served.

[@mathiasrennochaves3533]

Could you explain what is the damage you see in your field? I am a evolutionary biologist and I don't see people taking this metaphor too seriously at the point of cause some harm. I am genuinely curious. Not trying to challenge your view or anything...

[@InsideInterpreting]

@@mathiasrennochaves3533 I'm a scholar of interpreting (often erroneously called oral translation) between languages. The whole "interpreters are translation machines" idea was practically universal until the 90s and is still common. As I explain in my second book, Interpreters vs Machines, it not only led to interpreters to talk about their work in ways that led users to think interpreters could and should be replaced by machines, but it underpins how machines try to interpret now. It has led to worse working conditions (machines don't need breaks or prepatory materials), as well as lower quality interpreting (machines don't need to adjust to their audience) and unethical research (we don't need to worry about ethics if interpreters are machines). Despite field research and resulting theory (and even some lab work) demonstrating that the machine metaphor doesn't represent reality anywhere for the past 30 years, we're battling inertia and the resulting damage it has caused.

[@JimBalter]

@@InsideInterpreting interpreters have already been replaced by machines, ever since software interpreters started being based on LLMs

[@InsideInterpreting]

@@JimBalter On the contrary, interpreting based on MLMs does not yet outscore humans on anything but the most restricted terminology tests (and even then only sometimes) and human interpreters are still being used. There have been reports of some clients choosing machines but this is marginal and may not last, given the obvious flaws in LLM models of interpreting.

[@MrChaluliss]

Really awesome video. I am always happy to have my mental model about something totally rewired in way that immediately makes sense and builds newfound curiosity!

[@SubAnima]

Thanks, glad it gave you a new perspective!

[@zalzalahbuttsaab]

Thank you. Also mindblowing is the unfatomable number of protein-to-protein interactions that could potentially take place that would contribute to total cell failure. And they say this all came about by chance. After ust a little self-study of genetics, I found that there was so many things done by those who study in this area vis a vis terminology and diagrams, that rather than make it easier for people to understand it effectively formed a barrier. Your video has been very useful.

[@gregorybatz7297]

Not chance = design. Shalom.

[@Jacob-sl6ur]

​@@gregorybatz7297If an engineer presented the entire network of cell signaling they would be out of a job. The "design" works but it is so so messy, i.e. indicative that it came about by stochastic means.

[@gregorybatz7297]

@@Jacob-sl6ur a similar argument was made regarding the eye, yet it is perfect for its function. We just didn't understand how well designed it was until recently.

[@Fido-vm9zi]

Protein to protein interactions-like two people meeting on the street. Can go bad. Do any of them try to take from the other?

[@Dj992Music]

This is an excellent video. Presented the argument very well and I completely agree. There is a fine line for science communicators between simplifying concepts and retaining accuracy. It's a tough job!

[@JessBonomo]

I love this. I'll share will all colleagues and especially students. There are way too many biological researchers who don't get how simplifications we use for teaching can impregnate how we think and affect our way of interpreting results and taking conclusions.

[@neithanm]

Biology is such a mess...! I'd love for some individuals to tell me how is that "intelligently designed", erjremmm... Now I perfectly understand why some biologist said alphafold is cool but the challenge it's not solved. Great lighting, script, vibes... everything! You'll go far my man. EDIT: Can I suggest you to break apart Michael Levin's Bioelectricity stuff? It's fascinating.

[@SubAnima]

Dan says that any argument against the machine metaphor is also an argument against intelligent design. I'd agree, but that's not to say I don't think that theology and biology are incompatible, just that theologians need to work a bit harder than calling the cell a machine/factory that requires a designer. Thanks so much for the kind words!! I do plan on covering Michael Levin's stuff eventually, but will probably be a long ways off unfortunately. On the upside, there's a bunch of other interesting stuff coming soon :)

[@neithanm]

@@ponderingspirit Are we still talking about bronze age myths? Come one, it's 2022!!

[@SubAnima]

@@ponderingspirit I'd have to see the argument. But most ID arguments start from Paley and his Watchmaker analogy and then add in a bit of irreducible complexity. Governance is not necessary. A lot of evolution can happen neutrally kzbin.info/www/bejne/eJPdqGiPop2cm9U

[@Littleprinceleon]

@@SubAnima I suppose theology will gladly accept the non-mechanistic views: Religious ones may simply fully reintroduce a "ghost in the shell", now that they don't have to bother with details. If in principle there will be no answer as to what causes (at least to some probability) certain nonspecific interactions and what is the overall influence of such on the regular activities of the cell, then a religious belief can easily slip in: a not satisfactorily explainable result can be attributed to whatever mysterious force as the "real" cause. Was the strengthening of such hopes one of the intended goals of this video? The more pragmatic persons on the other hand may use the implications as arguments against "Big Pharma" or the whole medical sciences. PS: I'm a philosophically based molecular biologist (even inclined to mysticism): the strictly mechanistic views have bothered me always, but... people are all too eager to "simplify" their worldview, so the content of this video (while I highly appreciate it) has its dangers, too.

[@SubAnima]

Again, I'd have to see the specific theology you're suggesting but I feel as though it's a bit of a false dichotomy to suggest that we either have science (in its mechanistic form) or religion. There is still plenty of science to be done WITHOUT defaulting to machine metaphors and mechanistic causes. Some useful tools are: process perspectives (global.oup.com/academic/product/everything-flows-9780198779636 ), naturalised agency (doi.org/10.1017/CBO9781316402719 ), relational biology (cup.columbia.edu/book/life-itself/9780231075657 ) and perspectival realism (global.oup.com/academic/product/perspectival-realism-9780197555620 ). If you'd like to see an in depth overview on what non-mechanistic biology could end up looking like, I'd highly recommend Yogi Jaeger's lecture series 'Beyond Networks': kzbin.info/www/bejne/eYqThqapnN2Mea8 There is no need to reintroduce a ghost in the machine.

[@myhamismad]

Fantastic, I've subscribed and I'm excited to go back and check out all of your vids

[@SubAnima]

Thanks so much, means a lot to have interested subscribers :)

[@nosson77]

I think you're very well spoken, very knowledgeable, have a great video production and have good understanding of certain things. On the other hand some things seem to just not be your forte. For example the rigidity of a machine depends on its use case. As long as its strong enough to do the job its a machine. Just because some proteins don't have a specific shape that doesn't mean you cant have molecular machines. Your arguments are simply logical fallacies.