The way I think about this comes from reading John Holland's "Hidden Order". If you read that book not as a book but as a way to build a Complex Adaptive System, then it comes down to a few essentials. An environment, a bunch of entities, a read/write messaging bus so the entities can interact. The entities need a set of rules and sensors. Put it together and what have you got? Thinking. Or intelligence. Try building one. Is the RIP routing protocol a complex adaptive system?
Part of our problem is the way we think. I am a person. I am not a complex adaptive system. And yet I am. I am made of entities. There is a messaging bus, the entities sense, act and interact. But I don't think of myself as a CAS or talk about We. Wecellfs?
Perhaps this a Sapir-Whorf thing. Our language limits what we can think. What is the difference between a pile of ants and an ant colony? A colony is collection of entities, but what do we call the entity that is the colony? Are the ants smart or is the colony smart.
As can be seen by the specializations between human brain hemispheres. There is a bus between them, but when that communication is cut, and you can see that a lot of what we perceive as a single thought process, is a bunch of independent computing entities with an OS layer on top creating the unity that doesn't really exist.
When Covid hit me, it felt like having a stroke and the effect was that I suddenly perceived that I don't have enough energy to sustain vision, instead I could perceive the delineation between object localization, object recognition, character-to-text conversion etc. It was like the brain was an engine that suddenly lacked fuel (I could force individual parts to "work" at the cost of immense pain) and dissolved into individual services competing for resources. The experience was both frightening and awesome. Not sure how I survived that (it took over 3 years to get back to normal). Diffuse MRI didn't find anything anyway.
>a lot of what we perceive as a single thought process, is a bunch of independent computing entities with an OS layer on top creating the unity that doesn't really exist.
How else could it be? At some level, it would inevitably be a top-level aggregation "creating a unity that doesn't really exist". The alternative would be for the whole brain to be a single elementary particle!
>a lot of what we perceive as a single thought process, is a bunch of independent computing entities with an OS layer on top creating the unity that doesn't really exist.
As described in Marvin Minsky's fascinating book "Society of Mind" ...
> I am a person. I am not a complex adaptive system. And yet I am.
Your adaptive system has a very complex model of the environment. You can model yourself as an agent in the environment, and you identify as parts of that agent. I say “parts,” because there is a ton of thinking and actions that your adaptive system performs which you do not identify as you.
It reminds me of this paper from MIRI a few years ago discussing models which treat themselves as an explicit part of the environment. I think it's a very productive approach - https://arxiv.org/abs/1902.09469
Yes - all of our conscious reality, including both the environment and our sense of self, are experiences of perception formed inside the mind by the body and brain. Our sense of an "external" world is very much an "internal" reality, and the boundary between self and world is a mental construct.
> Part of our problem is the way we think. I am a person. I am not a complex adaptive system.
I agree that, in general, we humans, downgrade the importance of external stimulus and interactions with our environment (including other people). My two cents is that this is downplayed where we live in cities and don't move too much, once you move to very distanct places and cultures (and not assuming yours is the best one) more things tick in the brain.
it's hard to forget about others in a city though. you have neighbors, traffic, etc. that's why the whole 'cabin in the woods' experience can be sold as a relative luxury nowadays.
that said, based on the status quo we definitely don't spend enough resources on making sure we can peacefully and sustainably live next to others.
> But I don't think of myself as a CAS or talk about We. Wecellfs?
I am a collector of theories of consciousness :) assuming your quote above is making reference to the "scale" at which "self" is understood, you might be interested in this theory:
> Consciousness (at least, consciousness(es) that we are familiar with) seems to occur at a certain scale. Conscious states doesn't seem to significantly covary with noisy schocastic activities of individual cells and such; rather it seems to covary at with macro-level patterns and activities emerging from a population of neurons and stuffs. We are not aware of how we precisely process information (like segmenting images, detecting faces, recognizing speeches), or perform actions (like precise motor controls and everything). We are aware of things at a much higher scale. However, consciousness doesn't seem to exist at an overly macro-level scale either (like, for example, we won't think that USA is conscious).
However I would like to mention that sometimes we do think so, as in "the will of the party", at least in some language's context.
Fun fact, when I tried to find similar sentence like "the will of Democratic/Republican Party", google returns 5 results for the former but followed by voters/members and thus not what I want, for the latter, there is no results at all. But as I find "the will of the party", I find an abstract of some paper from my area.
Maybe party is too small for this. It seems like "the will of the nation" is widely used.
Going at it a bit sideways, there's also a sense of self that's constructed in which narratives forms around it ... and yet, there's a way of experiencing the world without that separate sense of self.
Complex adaptive systems can be nested. Human families, communities, societies, governments all form greater gestalts in which humans, themselves complex adaptive system are a part of.
So as we add layers of language, intelligence goes down. (Of course, to the residents of that layer, only the residents of that layer are intelligent. The depths are inscrutable chaos. And further layers are ... Tools? Toys?)
But a human isn't a bunch of individual cells, it is a cell that cloned itself many times. Those cells all have the same base code and can thus become an intelligent committee.
Fantastic read!
If y’all are into this kind of stuff I highly recommend reading “The Song of the cell” by Siddhartha Mukherjee[1], it is one of the best books I’ve read that made the topic of biology approachable.
I found Song of the Cell a bit underwhelming. The Gene really was fantastic - I think he ran out of steam a bit with Song of the Cell. The majority of the cell related history is also contained in The Gene.
> I never liked the way biology was taught in high school. It was too much about the names of things. A subject so vast is spoiled by a textbook, which can only point at the endless parade of stuff-there-is-to-know.
Amen. You could easily teach quite intricate biology in grade school, if you focused on a fascinating example or two. How many more people would be inspired, rather than bored?
There's a nice discussion of this in Surely You're Joking, Mr. Feynman!
> I discovered a very strange phenomenon: I could ask a question, which the students would answer immediately. But the next time I would ask the question – the same subject, and the same question, as far as I could tell – they couldn’t answer it at all!
> Then I say, “The main purpose of my talk is to demonstrate to you that no science is being taught in Brazil!”
We had a student in class which was so brilliant at memorizing stuff.
But each test had one or two questions where you had to put together the knowledge, not just regurgitate, and that student consistently failed those question on each and every test.
Yet the student got top scores on each and every test, because the accumulated number of points was enough to get them into the top bracket.
I was so annoyed with that, asking the teacher how they could get top scores while clearly demonstrating they didn't understand the subject matter. Of course, all in vain.
Biology is just astoundingly complicated, especially micro-bio.
Lets look at the 'Central Dogma' of biology as a point to focus on a bit. It's the idea of 'information' transfer. DNA gets decoded into RNA which then gets decoded into Protiens, right? Easy peasy little discussion. You go into how DNA works a bit, it's structure, it's functions. Then you go a bit more into RNA and the various sub types, how the decoding proteins work, Slicer and Dicer, etc. You then talk about how three letter codons work to make amino acids, how you transport the mRNA out of the nucleus, etc. At each step you take a look at how the thing works and you mention some other launching off points for more research if the kids are interested. This is how a lot of education works, things like cooking, math, history, etc.
Except nearly none of what I just said about the 'Central Dogma' is considered true anymore. Sure, some of it is, but the vast majority of how proteins get made is not encompassed in it. Nearly the entirety of modern micro-biology is all about the 'exceptions' to the 'Central Dogma'. So much so that you can't really even say that there is any appreciable difference between RNA and proteins anymore. Every week, and I am not joking here, there is at least one new paper detailing some hybrid mess of RNA and proteins that has critical importance in how we understand how even the most common parts of a cell works. It's to the point that I would not call the 'Central Dogma' and outright lie, but more of a useful fiction.
Like saying that a 'for loop' is how the internet works. Yes, there are 'for loops' in the internet, yes they are critical, yes, you need to learn about them. But no, you cannot teach someone about the internet via a fascinating example or two about 'for loops'.
Understanding biology is Hard, it is the end result of 4+ billion years of literal life and death. It is not something that can be done in a few examples. Even an understanding at a 12 grade level does in fact take a full school year to get to, and even then, it's just the barest launching point into the wider field. The OP s wrong. Full Stop. You do need to learn the names of these things, you do need to get down and do the work of learning all the facts, you do need to fill your brain with these things that are going to affect you as the world gets more and more complicated, you do need to connect this incredibly vast amount of information together. It is going to affect you or the ones you love.
Edutaiment is not the way forward here. Hard work is.
Of course, the study of how living cells function is "hard". But that doesn't mean it has to be learnt without joy. We tend to explore things we enjoy. A lot of the writer's essays [1] are about finding some aspect of a topic intriguing and following that rabbit hole.
My own research centered on one subset of functions within E. coli. I was lucky that I found a carefully engineered subset of plasmids and adaptions of E.coli, that could be mathematically modelled [2] [3]. I didn't have to know the whole functioning of E. coli. I didn't have to use mathematics beyond algebra. That is, no calculus was needed. The key task was to put together the quantitative research of about half a dozen labs. Okay, I had a "mountain" of articles to read. And it took 5 years of effort. But it was only doable, because I was modelling a carefully constrained subset of cellular functions.
Modern biology is very much not an exception to the central dogma; it still remains central. Don't mistake the vehemence of the RNA biologists (of which I used to be one) for impact or significance (for example, the central dogma had no opinion of whether the ribosome was a protein machine, or an RNA machine, or a protein-RNA machine where RNA formed the critical core components).
The only really important detail that wasn't in the original dogma is reverse transcriptase, and they added a dotted line to support that once it was found in physical form.
So, just to simplify your argument, you're saying that grade school students should not be taught biology in a way that GP finds more engaging, because:
> You do need to learn the names of these things, you do need to get down and do the work of learning all the facts, you do need to fill your brain with these things that are going to affect you as the world gets more and more complicated, you do need to connect this incredibly vast amount of information together. It is going to affect you or the ones you love.
It turns out the curriculum was made by a bunch of teachers that has been old school taught. Seniority and entrenchment, nobody in that group risking their heads to suggest any deviation from old beliefs
This kind of unicellular complexity & intelligence has long been my soapbox material in the AGI debate. Even long before the current LLM craze, people were counting neurons in the brain and making bold claims about machine intelligence - in just X years, we'll have a machine with the computational power of the brain!
But of course, every neuron in the brain is bafflingly complex and we still don't know or understand how that complexity manifests itself in thought and intelligence. Given physics and the interactions of "things", every cell in the brain is more complex than the LLMs we're using today. Not to say that every cell is capable of producing the same output as an LLM of course, just that the behavior that it contributes to the overall system is that complex.
> But of course, every neuron in the brain is bafflingly complex and we still don't know or understand how that complexity manifests itself in thought and intelligence.
Indeed.
Biophysics of Computation: Information Processing in Single Neurons challenges this notion, using richly detailed experimental and theoretical findings from cellular biophysics to explain the repertoire of computational functions available to single neurons. The author shows how individual nerve cells can multiply, integrate, or delay synaptic inputs and how information can be encoded in the voltage across the membrane, in the intracellular calcium concentration, or in the timing of individual spikes: https://www.amazon.com/Biophysics-Computation-Information-Co...
Though, I feel that ANNs' number of neurons are under-represented is some ways:
- In the example case of a CNN, the total weights of a kernel is of [Input Number of Channels * Input Kernel Size * Number of Filters], which can be a pretty small amount when it comes to for example a 3x3 kernel with 3 channels with 128 filters coming to a total of 3,456 parameters (3 * 3 * 3 * 128), however in the case of an ANN the same filter is strided across the entire 2D input feature map (or 3D for 3D CNNs). If the input image is of HD resolution of 1280 * 720 and the stride is 2 across both dimensions, then the number of strides is 230,400. The effective number of parameter activations is 796,262,400 (3,456 * 230,400). The reason for this example is that it is sort of a known thing for likely decades now that CNNs are inspired in part by the human visual cortex [0]. For the human visual cortex which needs to be fast, there cannot be parameter sharing across a single kernel, and likely the weights would need to be parallelized to an extent, which would theoretically imply duplicating the weights across the human brain. Thus, the advantage out here lies with ANNs.
- The neurons in the human brain would have to have a certain level of redundancy in place due to the constant cellular repair work.
- The neurons in the human brain can seemingly only be updated by Hebbian learning rather than direct updates which is in the case of the computer memory of ANNs.
- Finally, a significant part of the human brain is for non-logical but environmental reasons, such as movement and touch, and non-logical things such as fear, jealousy, lust, etc; parts which ANNs do not need to possess in the same way (eg: the fight-or-flight response of the amygdala part of the brain).
In fact we know precious little about the mechanisms inside any given cell. We can describe the outcomes of many processes but we couldn’t replicate them if our lives depended on it.
Brain is basically running a matrix-like simulation with a central person in it, for AGI we just need to simulate the thinking parts which is a simpler problem. But who knows how much simpler...
I was introduced to the idea of even single cells can exhibit "learning" and "culture" via John Bonner excellent book The Evolution of Culture in Animals.
Instead of thinking in terms of a discontinuity between animals or putting humans categorically different, Bonner builds this idea of a continuum instead for both culture and learning. Of course there are differences,
* Both receptor cooperativity and accurate adaptation can be described quantitatively by simple mathematical models.
* An integrated model (the “standard model”), which contains both signal amplification and adaptation, is developed to predict responses of it E. coli cells to any time-dependent stimuli quantitatively.
* Exponential ramps induce activity shifts, which depend on the ramp rate through the methylation rate function F(a).
* Responses to oscillatory signals reveal that E. coli computes time-derivative in the low-frequency regime.
* E. coli memorizes the logarithm of the ligand concentration and the Weber-Fetcher law holds in E. coli chemotaxis.
It also goes into cooperative phase transitions in the receptor complexes as a means of signal amplification, using the same model as in Ising ferromagnetic spin-spin interactions in physics.
> We don’t yet have the technology to just observe all of the activity inside a living cell.
How close are we to being able to make a map of all atoms within a cell? There are 1E23 atoms in 1 ml of water, and an ecoli is about 500nmx500nmx1um. That means there are only about 2E10 atoms in the whole cell!
Would it be possible to somehow freeze a whole cell, then use an electron beam to knock off and identify (via mass) every atom there?
Key word here is activity. Even if you froze a cell and mapped it down to an atom, you'd need to do it again for a cell you somehow managed to freeze in the state immediately after the first one, and so on. What granularity would be significant? What branching of what process would you like to follow?
Readit News
Part of our problem is the way we think. I am a person. I am not a complex adaptive system. And yet I am. I am made of entities. There is a messaging bus, the entities sense, act and interact. But I don't think of myself as a CAS or talk about We. Wecellfs?
Perhaps this a Sapir-Whorf thing. Our language limits what we can think. What is the difference between a pile of ants and an ant colony? A colony is collection of entities, but what do we call the entity that is the colony? Are the ants smart or is the colony smart.
How else could it be? At some level, it would inevitably be a top-level aggregation "creating a unity that doesn't really exist". The alternative would be for the whole brain to be a single elementary particle!
Also, I think you are talking about the corpus callosum for the 'bus' right?
As described in Marvin Minsky's fascinating book "Society of Mind" ...
Your adaptive system has a very complex model of the environment. You can model yourself as an agent in the environment, and you identify as parts of that agent. I say “parts,” because there is a ton of thinking and actions that your adaptive system performs which you do not identify as you.
I agree that, in general, we humans, downgrade the importance of external stimulus and interactions with our environment (including other people). My two cents is that this is downplayed where we live in cities and don't move too much, once you move to very distanct places and cultures (and not assuming yours is the best one) more things tick in the brain.
that said, based on the status quo we definitely don't spend enough resources on making sure we can peacefully and sustainably live next to others.
I am a collector of theories of consciousness :) assuming your quote above is making reference to the "scale" at which "self" is understood, you might be interested in this theory:
Information Closure Theory of Consciousness (2020) https://www.researchgate.net/publication/342956066_Informati...
This reddit comment sums it up better than the paper seems to be able to: https://www.reddit.com/r/MachineLearning/comments/dco3t1/com...
> Consciousness (at least, consciousness(es) that we are familiar with) seems to occur at a certain scale. Conscious states doesn't seem to significantly covary with noisy schocastic activities of individual cells and such; rather it seems to covary at with macro-level patterns and activities emerging from a population of neurons and stuffs. We are not aware of how we precisely process information (like segmenting images, detecting faces, recognizing speeches), or perform actions (like precise motor controls and everything). We are aware of things at a much higher scale. However, consciousness doesn't seem to exist at an overly macro-level scale either (like, for example, we won't think that USA is conscious).
However I would like to mention that sometimes we do think so, as in "the will of the party", at least in some language's context.
Fun fact, when I tried to find similar sentence like "the will of Democratic/Republican Party", google returns 5 results for the former but followed by voters/members and thus not what I want, for the latter, there is no results at all. But as I find "the will of the party", I find an abstract of some paper from my area.
Maybe party is too small for this. It seems like "the will of the nation" is widely used.
Complex adaptive systems can be nested. Human families, communities, societies, governments all form greater gestalts in which humans, themselves complex adaptive system are a part of.
Individuals are smart, committees are dumb.
Fundamental particles must be geniuses.
But a human isn't a bunch of individual cells, it is a cell that cloned itself many times. Those cells all have the same base code and can thus become an intelligent committee.
Dead Comment
[1] https://www.amazon.com/Song-Cell-Exploration-Medicine-Human/...
- The emperor of all maladies - about cancer research, for which he got a Pulitzer
- The gene - about the evolution of the field and the discoveries and what is the latest thinking
Amen. You could easily teach quite intricate biology in grade school, if you focused on a fascinating example or two. How many more people would be inspired, rather than bored?
> I discovered a very strange phenomenon: I could ask a question, which the students would answer immediately. But the next time I would ask the question – the same subject, and the same question, as far as I could tell – they couldn’t answer it at all!
> Then I say, “The main purpose of my talk is to demonstrate to you that no science is being taught in Brazil!”
https://v.cx/2010/04/feynman-brazil-education
But each test had one or two questions where you had to put together the knowledge, not just regurgitate, and that student consistently failed those question on each and every test.
Yet the student got top scores on each and every test, because the accumulated number of points was enough to get them into the top bracket.
I was so annoyed with that, asking the teacher how they could get top scores while clearly demonstrating they didn't understand the subject matter. Of course, all in vain.
edit: Great read BTW
Biology is just astoundingly complicated, especially micro-bio.
Lets look at the 'Central Dogma' of biology as a point to focus on a bit. It's the idea of 'information' transfer. DNA gets decoded into RNA which then gets decoded into Protiens, right? Easy peasy little discussion. You go into how DNA works a bit, it's structure, it's functions. Then you go a bit more into RNA and the various sub types, how the decoding proteins work, Slicer and Dicer, etc. You then talk about how three letter codons work to make amino acids, how you transport the mRNA out of the nucleus, etc. At each step you take a look at how the thing works and you mention some other launching off points for more research if the kids are interested. This is how a lot of education works, things like cooking, math, history, etc.
Except nearly none of what I just said about the 'Central Dogma' is considered true anymore. Sure, some of it is, but the vast majority of how proteins get made is not encompassed in it. Nearly the entirety of modern micro-biology is all about the 'exceptions' to the 'Central Dogma'. So much so that you can't really even say that there is any appreciable difference between RNA and proteins anymore. Every week, and I am not joking here, there is at least one new paper detailing some hybrid mess of RNA and proteins that has critical importance in how we understand how even the most common parts of a cell works. It's to the point that I would not call the 'Central Dogma' and outright lie, but more of a useful fiction.
Like saying that a 'for loop' is how the internet works. Yes, there are 'for loops' in the internet, yes they are critical, yes, you need to learn about them. But no, you cannot teach someone about the internet via a fascinating example or two about 'for loops'.
Understanding biology is Hard, it is the end result of 4+ billion years of literal life and death. It is not something that can be done in a few examples. Even an understanding at a 12 grade level does in fact take a full school year to get to, and even then, it's just the barest launching point into the wider field. The OP s wrong. Full Stop. You do need to learn the names of these things, you do need to get down and do the work of learning all the facts, you do need to fill your brain with these things that are going to affect you as the world gets more and more complicated, you do need to connect this incredibly vast amount of information together. It is going to affect you or the ones you love.
Edutaiment is not the way forward here. Hard work is.
My own research centered on one subset of functions within E. coli. I was lucky that I found a carefully engineered subset of plasmids and adaptions of E.coli, that could be mathematically modelled [2] [3]. I didn't have to know the whole functioning of E. coli. I didn't have to use mathematics beyond algebra. That is, no calculus was needed. The key task was to put together the quantitative research of about half a dozen labs. Okay, I had a "mountain" of articles to read. And it took 5 years of effort. But it was only doable, because I was modelling a carefully constrained subset of cellular functions.
[1] https://jsomers.net/
[2] https://pubmed.ncbi.nlm.nih.gov/8078069/
[3] https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5425810/
The only really important detail that wasn't in the original dogma is reverse transcriptase, and they added a dotted line to support that once it was found in physical form.
> You do need to learn the names of these things, you do need to get down and do the work of learning all the facts, you do need to fill your brain with these things that are going to affect you as the world gets more and more complicated, you do need to connect this incredibly vast amount of information together. It is going to affect you or the ones you love.
Do you mean molecular biology instead, which includes the study of central dogma?
(That's a common terminology hiccup, lots of people get this wrong)
But of course, every neuron in the brain is bafflingly complex and we still don't know or understand how that complexity manifests itself in thought and intelligence. Given physics and the interactions of "things", every cell in the brain is more complex than the LLMs we're using today. Not to say that every cell is capable of producing the same output as an LLM of course, just that the behavior that it contributes to the overall system is that complex.
Indeed.
Biophysics of Computation: Information Processing in Single Neurons challenges this notion, using richly detailed experimental and theoretical findings from cellular biophysics to explain the repertoire of computational functions available to single neurons. The author shows how individual nerve cells can multiply, integrate, or delay synaptic inputs and how information can be encoded in the voltage across the membrane, in the intracellular calcium concentration, or in the timing of individual spikes: https://www.amazon.com/Biophysics-Computation-Information-Co...
- In the example case of a CNN, the total weights of a kernel is of [Input Number of Channels * Input Kernel Size * Number of Filters], which can be a pretty small amount when it comes to for example a 3x3 kernel with 3 channels with 128 filters coming to a total of 3,456 parameters (3 * 3 * 3 * 128), however in the case of an ANN the same filter is strided across the entire 2D input feature map (or 3D for 3D CNNs). If the input image is of HD resolution of 1280 * 720 and the stride is 2 across both dimensions, then the number of strides is 230,400. The effective number of parameter activations is 796,262,400 (3,456 * 230,400). The reason for this example is that it is sort of a known thing for likely decades now that CNNs are inspired in part by the human visual cortex [0]. For the human visual cortex which needs to be fast, there cannot be parameter sharing across a single kernel, and likely the weights would need to be parallelized to an extent, which would theoretically imply duplicating the weights across the human brain. Thus, the advantage out here lies with ANNs.
- The neurons in the human brain would have to have a certain level of redundancy in place due to the constant cellular repair work.
- The neurons in the human brain can seemingly only be updated by Hebbian learning rather than direct updates which is in the case of the computer memory of ANNs.
- Finally, a significant part of the human brain is for non-logical but environmental reasons, such as movement and touch, and non-logical things such as fear, jealousy, lust, etc; parts which ANNs do not need to possess in the same way (eg: the fight-or-flight response of the amygdala part of the brain).
[0] https://msail.github.io/post/cnn_human_visual/
Deleted Comment
Instead of thinking in terms of a discontinuity between animals or putting humans categorically different, Bonner builds this idea of a continuum instead for both culture and learning. Of course there are differences,
https://press.princeton.edu/books/paperback/9780691023731/th...
This post of course goes deep in the rabbit hole so to speak.
[1] https://www.amazon.com/Biophysics-Computation-Information-Co...
"Quantitative modeling of bacterial chemotaxis: Signal amplification and accurate adaptation, Yuhai Tu"
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3737589/
The main points are:
* Both receptor cooperativity and accurate adaptation can be described quantitatively by simple mathematical models.
* An integrated model (the “standard model”), which contains both signal amplification and adaptation, is developed to predict responses of it E. coli cells to any time-dependent stimuli quantitatively.
* Exponential ramps induce activity shifts, which depend on the ramp rate through the methylation rate function F(a).
* Responses to oscillatory signals reveal that E. coli computes time-derivative in the low-frequency regime.
* E. coli memorizes the logarithm of the ligand concentration and the Weber-Fetcher law holds in E. coli chemotaxis.
It also goes into cooperative phase transitions in the receptor complexes as a means of signal amplification, using the same model as in Ising ferromagnetic spin-spin interactions in physics.
How close are we to being able to make a map of all atoms within a cell? There are 1E23 atoms in 1 ml of water, and an ecoli is about 500nmx500nmx1um. That means there are only about 2E10 atoms in the whole cell!
Would it be possible to somehow freeze a whole cell, then use an electron beam to knock off and identify (via mass) every atom there?
It’s stupid expensive though, and you can only really identify whole proteins. But you can do that in context, which is massive