Theory

not just that mubarak just went on holiday to sinai (i maintain my expectations on the subject). apparently he just took off with the country’s fortune.

but that’s not the only thing that apparently is old stuff. i also learned that a lot of my work has already been done, from another angle, by the influence of neural darwinism. there are many parallels to what i have been building, with a major difference. i use a more mathematical and physical definition of how information is represented, whereas this formulation is more empirical, coming from medical science which uses different methods.

there is a strong parallel, especially towards subjectivity and how subjectivity emerges in connected networks. i recommend checking out this interview with edelman about this subject. there are many other models on neural networks, and what i’ve been writing isn’t very original beyond the fact that it has sociological outlines beyond the simple pattern recognition. anyway, i’m not planning on sending my work to sinai anyway, but it’s always good to know the existing ideas.

some silly happy folk this time, a “llaço” from the north east

we recently saw how information exists in several levels, and how we suspiciously translate the outside world in a structure similar to the structure of our own nerve cells. perhaps it’s time to clarify.

a thing that exists on itself, before others, can itself be made of things. if we consider these things properties, for an atom for example, we could see it as mass, or dive deeper and see a specific arrangement of subatomic particles, each with its own mass, with the global “mass” as an emergent property, and so on. this is zooming in. information itself can then be encoded in several ways. the simplest and most basic alphabet would be the one comprised of the most fundamental quanta and their laws. since laws are patterns of things, they would be only available to the layer above of the simple quanta.

if things are not randomly arranged, but in specific, less likely arrangements, information is higher. i don’t want to bring in many equations, but basically the more specific (or surprising) an arrangement of things is, the more information it carries.

so the first layer of information is the physical information. the information that exists for the simple fact that things are non-randomly arranged in space and time. this is the lowest level of information possible (unless, of course, we dive deeper into what time and space are, and then we could find a deeper one, which i wouldn’t mind considering obviously).

and as these arrangements become more and more complex, so do their coherent patterns. one information is the one that exists from location, and another is the one that exists through work. work “creates” information (we saw how this is possible a long time ago), but does so using available energy and rearranging “lower level” information. so we have another kind of information, the computational agent information, or the information to encode the activities done by the said arrangements on other arrangements. this can be deduced from the “lower level” information, but it is very hard to do so. like explaining how a protein will fold based on its components, for now, our mathematics can’t model this properly, so they become abstracted for simplification. it’s not hard to imagine, though, that some alien culture has no such issues for having more advanced minds and science.

so information exists as part of things, and then on how things interact. this would be the case of DNA + Cells. they are information creating machines. they create arrangements of things, being things themselves. this is the second layer of information. not DNA, DNA is the first layer. the machinery is the second layer. but these machinery-like processes exist in simpler forms, like when gravity and magma interact creating different crystallizations, in fact synthesizing new shapes (or new information). in one case, we call the machinery “life”, in the other, we call “law of nature”. in both, information is synthesized. and both can be encoded as “transformation machines” that take information and create more information.

the same thing happens with the neuron. it has a coherent “work” function (that in fact consumes calories), which can be seen as a function that applies to a set of conditions {a,b,c,…} giving a “yes” or “no” answer, the name. when a connection is active, it becomes stronger, when a connection is useless, it tends to be discarded. like evolution, we have a system where neuron classifications evolve through death and selection. but what is making this selection?

this is where objectivity and subjectivity begin to split. so far, all our systems were objective (plus or minus scientific uncertainty). but once we have a system that classifies and creates names, what assures us that the “name” in one neuron is the “name” in another neuron? let’s not confuse these names with human names, human names will come later.

the way to know if name a and name b are the same is to see if the function that generates the names is the same, i.e., by reverse engineering the neuronal function. how can we do this?

consider the set of conditions {a, b, c} for neuron 1, and conditions {d, e, f} for neuron 2. they will represent the same information when (a and b and c) = (d and e and f). we have no way of separating the components of a name unless we have access to separate {a,b,c,d,e,f}. this is the case with black box minds like animal minds. we have no way of “tingling” every connection at a time on each subject.

so let’s see an example on how we can have equal classifications with different conditions, i.e., subjectivity. this is the case for a rudimentary classification system. as i said, i postulate that a lot of our way of thinking comes from essential characteristics of the building blocks of minds.

let’s say the “yellow t-shirt” pattern has been seen by both neurons in different situations. they both have a “yes” reply when they see a yellow t-shirt. so we can say, from the outside, that they both classify “yellow t-shirts” correctly. but how can we know they “know” the same yellow t-shirt or not? or, better put, how can we know they accurately contain the information for a t-shirt? my opinion is that we can’t. structurally, just having a valid classification might not imply valid inputs. let’s see it in practice in the above example.

neuron 1 takes {a and b and c} as inputs. when analyzed, we learned that {a} is triggered on the color yellow, {b} is triggered on the t shape and {c} is triggered on the sight of clothes. if we only had a posteriori knowledge, we could understand a t-shirt by looking up what {a}, {b} and {c} were, and in this case, end up with a working definition: “something that you can wear that is yellow and has a t-shape”. rather crude, but for a full definition we needed no more than one neuron and 3 inputs.

but what would happen if for neuron 2, their conditions were false, but out of coincidence, always true for the same situations as the classifier above? for example {d and e and f} could be {d} is a human standing, {e} is a yellow blob over the human, {f} the human is not cold.

for the overwhelming amount of the cases, the answers of both the classifiers are correct, because in every way they answer “yellow t-shirt” correctly. but if we were to break down neuron 2, we would be surprised. a “t-shirt” is a “warm human with a yellow blob”. hardly a definition of a t-shirt. but unless we had a human painted yellow and tested both neurons or had taken them to a store, we would never encounter the situation in which a contradiction occurs, and therefore, would accept the word “yellow t-shirt” as true, even though each one had different “definitions” of what it is. and it would allow us to operate with both until a contradiction, or conflict, would occur. if we never encounter it, we would never see it and expose the flaws in one of the classifiers. this would allow two classifiers to coexist with incoherent definitions of the same thing, but functionally equivalent, i.e., since they agree on the “name”, there is no feedback loop to check that {a,b,c} = {d,e,f}. this is subjectivity. we have two machines that accept a concept (the name) even though they have different definitions of them.

it might not be very clear by now how were these classifications constructed. in a perfect world, we would always have {a,b,c} = {d,e,f}. again, through educated speculation, allow me to provide another learning algorithm. to map the function {a,b,c}=name, we need some kind of feedback that says “ok” or “not ok” to a definition, i.e., something that connects the name “t-shirt” to a neuron that just fired. this, obviously, is somewhat tricky, but let’s reward the cell with chemicals instead. we feed it {a,b,c} for a t-shirt and it fires, we keep it. we feed it {a,b,c} for a t-shirt and it doesn’t fire, we don’t. it is easy to imagine the “t-shirt organism” as a simple one which has a sensory side (3 sensors for the features described), the classifier, and an utterer (says “t-shirt” whenever it sees one). and then, we define the evolutionary fitness of this concept as “when t-shirt is correctly classified, the organism survives, otherwise, dies”. over time, we can guarantee that the organism will classify the t-shirt correctly. how does it know it is correct? because our evolutionary law, which in our case is reality, is there to feed back correct and incorrect classifications.

for example, let’s say i classify a predator incorrectly. i’m dead. but if i do so correctly, i’m not. and, again, my definition of predator comes straight from my sensory input. the very symbols used are exactly the symbols that my sensory system can provide. not only they are subjective as we saw above, they are biased by their own physical constituents.

we have seen how we can demonstrate subjectivity objectively in small organisms. i will slowly approach human minds. but to recap the information levels, we have the information of things, the information of things acting on things, and now, the information of things acting on themselves. this last one is the role played by evolution (when it is “mindless”) or the role of a trainer when we deal with some kind of classifier.

whenever we feed back the “classification” to the organism as “correct” or “incorrect”, we have a new kind of information system, one that can “recode” itself, i.e., the work done is no longer just a consequence of its physical properties, but also a consequence of its own work on itself. i would consider all intelligent systems that exist today, animals, humans, etc, as part of this latter category, thanks to evolution. our machines themselves are, again, mindless algorithms tuned by another thing, us. we provide the “fitness” of machines, technology and algorithms, just like evolution did for us as animals. the principle is the same.

i hope to implement this algorithm properly and provide actual classification data for validity. even though this is more of a philosophical text, what i postulated is testable. i predict that a system composed of a classifier with n inputs and one output and a feedback loop through an environment defining fitness will, after training, provide information about the pattern it was trained to detect, but this information might or might not agree with other classifiers, hence an objective proof for subjectivity.

this is visible in neural networks as different local minimums for the cost function. in this case, i don’t have a good formulation yet for this problem, but i imagine it will end up being similar, if not equivalent, to a regular neural network.

i will move on to bigger minds, brains, and so on soon, standing on this idea that information exists as structural connections in the conditions for a name, and that they can be different in different individuals. if a neuron is already subjective, how can realities agree? this is the challenge for our following posts.

an old clip, mind your ears if you have perfect “western pitch”

as we’ve been seeing in previous posts, there is a seemingly fractal quality to things. we’ve seen how wholes become more than parts and we’ve slowly crept up the complexity ladder all the way to cells. i’ll go from cells today because they are a key part in understanding all of this.

the first agents that did work were the laws of physics that are responsible for our first structural increase (or gain in information). we went from scattered disorganized particles to big blobs of complex arrangements of particles from forces alone.

and as gravity tug everything together, and as the sun fed enough energy, we managed to get new agents, this time, molecules that themselves can exert effects on other molecules, making them agents.

and as molecules became more and more complex, so did their tasks, such as the ribosome that assembles coded proteins.

but today we focus on a particular kind of cell, the neuron. i will be approaching a simplified model of the neuron. i studied a few models, neural networks and so on, but i am going to provide a different model for the neuron, completely arbitrary an according to whatever i think is correct. pure speculation.

a neuron is a cell that performs a computation described by the following:

there are many other ways. and in fact, neural networks use a different model that yields a more elegant mathematical formula. the reason i choose this one is that i believe (but can’t really prove) that each above is not a weight, but actually a condition (true or false). i didn’t use thresholds or step functions to model the “firing” either. what i am saying, instead, is that this cell, the neuron, checks if a number of conditions is present, and if so, fires. this is similar to the formulation for neural networks, and i suspect they are almost equivalent. but my focus in choosing a logic formulation instead of a functional mathematical one is to make the following more obvious.

a neuron connects its conditional tendrils to whatever is around it. these can change over time, grow stronger or weaker depending on usage. and then, it has a very long response tail, that spreads this message through thousands of other neurons. i’m not discussing this in depth, and i’m sure there are many inaccuracies here, but for the sake of my point i’m willing to accept some rough edges.

so what the neuron does is to take a group of parts (let’s call them things of layer n) and tests if it is a whole (let’s call them things of layer n+1). so a neuron, being forward only, is an analysis machine, or categorizer. feed it black and white pictures, and a white neuron will fire on the white sections, whereas the black neuron will fire on the black sections. note that “black” and “white” are mere concepts, and since our brain is concept agnostic, meaning, all senses are translated to electrical impulses, these neurons, even though being naturally designed to be sensory processors, might eventually connect to each other, and since they can’t distinguish outside electricity from inside electricity, they would be just as likely to find fictional parts in a brain and in a sensory nerve. as long as there is tingling, there is a possibility of classification. this is why we are bound to find the “brad pitt neuron” (google it, it’s real), the “tangerine dream” neuron, the “smell of mom’s cooking” neuron and so on. that’s what they do.

in my opinion, the very structure of a neuron presents abstraction, since it can categorize correctly different patterns into a single “yes” “no” pulse. let’s call that pulse a word, and use words to go through a computation in a sequence of neurons. let’s say we want to know if something is “checkered”. we will have a layer of neurons that categorize colors into black and white, then we will have a layer of neurons testing if “black” and “white” are alternating in sequence (by using the categories of previous neurons as inputs), and let’s say a neuron that evaluates spatial arrangement and sees if two dimensionally something is checkered (by using the responses of the alternating neurons and aggregating them).

what we have here is a progression in abstraction, from parts to whole. let’s see it in detail in one dimension (look up visual region neurons very interesting and similar stuff).

1. input (k is black, w is white): kwkwkw

2. color neurons:

• if(k) fire black; if(w) fire white;
• turning it into: black white black white black white

3. transition neurons:

• if(black next to white) fire black white; if(white next to black) fire white black;
• turning it into: black-white white-black black-white white-black black-white

4. checkered neuron:

• if(black-white next to white-black) fire checkered
• turning it into: checkered

what we just saw, and this has been demonstrated scientifically analyzing the visual networks of our brain, is abstraction. abstraction is not something that only big brains do. it’s something that any small neuron does. it is essential to identify the patterns we’ve been describing. neurons are a natural consequence of a “layered” universe. if parts and wholes behave differently (i.e., the wholes have properties unpredictable from the parts alone), then it is only logical that some structure would evolve that demonstrates that hierarchical view.

my model, that things are made of things, is the exact model of what i am saying a neuron is good at categorizing and processing. it takes a series of parts (things), independent of whether they are real (sensory) or fictional (internally generated) and classifies them firing the appropriate concept.

i could say my model is a description of how the brain works and how reality works and how i know the meaning of life the universe and everything. isn’t this suspicious? isn’t it the other way around? isn’t my model a consequence of how the brain works?

let’s look at this wheel. i call it the concept ouroboros. i added only a few topics for clarity.

every human activity starts with a core part, the simplest concept that is recognizable and analyzed, and then abstracts and elaborates on it. since logic is the building block of math, it is taken for granted as an encapsulated thing. physics then uses math as its thing, then chemistry uses physics, then biology uses chemistry and so on. but if we go the other way around, by analyzing what things are made of (seeing what a thing is made of), we would see that math is made of logic, which is made of philosophy, which is made of societies, which is made of humans, which are made of organs and so on.

there is no higher and lower in my perspective. it is an orouboros, eating its own tail. any study or human abstraction claiming to be the “essential” one will be ignoring that its basically just feeding on other things and eating its own tail.

why would this be?

imagine now that this ouroborus is not vertical, but you lay it down on a table. all these points on the circle are instances of the same logic of reasoning: the reasoning of parts and wholes, and laws thereof. which is suspiciously similar to what neurons do. so either this is a coincidence, or we, humans, have mostly become very good at creating an ever expanding ouroborus in the same plane. we can grow our abstraction as deep and wide as we want to. what i see here is a permanent limitation of our own cognition. if we are conscious thanks to our neurons (our parts for thinking), then is it too much to say that the whole might share some properties with the parts? like the charges affecting both atoms and molecules?

what i am saying is that it is that our perspective on reality is more subjective than we like to think. that even accepted concepts such as molecules, atoms and so on, are part of our own categorizing system, and nature is well beyond that.

am i saying all i’ve been writing is nonsense? well, yes and no. i wrote it purposefully to demonstrate its own fragility. i made it generic enough so that it would be acceptable in many fields. and then i showed how this was exactly what our brain was doing, naturally.

so now that i closed a loop and broke the logic of my previous posts, let’s continue. i will continue as if nothing happened, because, unfortunately, i don’t know how we can step out of the ouroborus conceptual world. i do not know what it is to think beyond this plane. but it is a good question that might return in the future. for now, i am going back to our ouroborus plane, and circling around as usual.

as we saw, a neuron is a mapping between parts and whole. since that whole doesn’t seem to exist except in that neuron that fires, i will refer to that firing as a word that is stored in that neural structure. so our brains are a mess of connected words, concepts, connected to each other in hierarchies, and connecting from and to the real (sensory) and the virtual (other neurons).

this means that the brain has physical information. not the information in its genes, not the information in its molecules. the information it its specific sequence of conditions that yield a word. how can we convert a neuron into a word? we have to crack its code. a checkered neuron reads (black-white white-black (…)), so if we only knew the answer (checkered), we would have to find the inverse function that the neuron does. in this case, “checkered” would translate into “black-white white-black (…)”.

contrary to the direct operation, where several conditions yield one result, knowing a word and finding out all conditions that create it is hard, if not impossible. a regular neuron has thousands of conditions for a single word. that means each word can expand into thousands of others. this is going from the whole to the part.

let’s summarize. a neuron takes parts and creates a whole, the word. the inverse, takes a word, a whole, and finds which parts exist, expanding it. this is, respectively, the act of analysis and synthesis.

so the foundation of thinking is actually present in the simplest structures of the brain. in fact, since cortex bearing creatures like us can actually generate words that replace sensory input (i.e., we can feedback words back into the first categorizers, like when we lucid dream a new perception), we are dealing with a universal computer.

i will leave more of this for later, since for now it was a lot to deal with. we are closer than ever to minds, and to demonstrate how the objective creates the subjective, even though we slightly hinted at it.

i’m slightly concerned about the slow erosion of interest in wikileaks. the us have now asked for the personal information of all twitter followers of the wikileaks account, including a member of the icelandic parliament. even though twitter refused, this is a new, and even more concerning, perspective. not only the people publishing are being prosecuted, even though they are protected by international an national laws, but even people that read the said documents are now in danger of being put in threat lists, no fly lists, interrogation lists, etc. so not only publishing is a crime, but reading is too.

but what concerns me is not that a state is using every possible way to maintain control over its citizens and neutralize every threat to the status quo. that’s very common historically. i could go back only 40 years in the history of my country to see it play exactly the same way. maybe the us were just a bit naive, thinking a state could ever be different that every other tried in human societies. their rebellion from europe is nowhere to be seen anymore even though other countries still see it as a land of freedom. the power structures are the same, and so are the vices, including their own separatist terrorist groups, popularized recently by yet another shooting. this is, just like most european countries, just another sad truth about democracy that people continue to ignore.

what is worrying is that nothing happens. nobody is being prosecuted for the crimes published, nobody has stood up for the defense of the publishers, and especially, no state has intervened to stop the sweden/us love affair that is going on, or the fact that sweden is deliberately denying rights to someone so that the us can prosecute them. or that the us have kept a citizen under solitary confinement for 6 months without trial (also illegal according to international law).

i expected it, and as i see it unfold, it is almost too surreal. business as usual. we have crossed the bounds of legality and proven there is no such thing. laws are made to starve the hungry and feed the elites. if freedom of speech exists, it exists only to allow those in power to say the most obscene, down right horrible things, and to leave those that question them and seek the truth helpless in their own demise. it is not a crime for a president to decree a genocide but it is a crime for a citizen to denounce it.

how could we fix it? how could we pretend to want to live in such a world? how could we possibly believe that living in such a system would allow us to change it from the inside? it is a joke. fighting for a better society through standard politics and law is a joke. all judges are bought by money, influence or even just blood ties. all power remains in the hands of the few.

there is no future in the society we’ve constructed. i’ve been saying this for too long. we can do better. our failure as “good people” is to try to change a “bad system”. let it be bad and let it go on in a downwards spiral until it self destructs. let’s focus on building something independent and good. a place where law is for the common good, where power is for the best decision, a place where fame and power is not a goal but a consequence of ones devotion to a cause.

it isn’t hard to build these places. we’ve done a few so far with nothing more than our will power and bare hands. but it takes everyone to stop allowing this to happen. and i’m not naive to think it will.

the most oppressed are the ones that are the most essential to society. but when a farmer sells his food, or i sell my work, i do not care who it is sold to. this leads to an unfair advantage on the ruling class side. they have more money, they will always guarantee their own survival, because money doesn’t show the blood stains it costs.

so what would happen if a farmer was to refuse selling to rich? what would happen if i was to refuse to code immoral apps? what would happen if we decided not to be hypocrites for survival? a sure social collapse. but we can’t. we can’t because we are too afraid we’ll lose what we have. and yes, one could argue we can strive to have nothing. but almost no one is capable of that anymore. i know i’m just as guilty.

one could argue we must change everyone’s life. i don’t. i’m tired of this nonsense of everyone trying to force everyone else into being part of some kind of utopian political system, just because they were brought up or read that that would be a perfect society. no. this is exactly what is wrong. that we don’t leave each other alone. we don’t let differences be differences, we don’t let people be people. what unites us as humans is the fact that we can’t agree on anything. from the color of our shirts to the music we should hear, all the way to the food we eat and the people we love.

we force everyone into being part of a big mess called a globalized society. we use all tools possible. markets, politics, laws, bills of rights, music. everything because we want to spread our own personal “we them” mentality, our own narrow minded view of a problem and our specific solution that is inapplicable to other societies.

the problem is that we want to fix what is none of our business. that we want to have what isn’t ours. that we want more of what we don’t need.

like an old troubadour from the countryside used to say, playing his junkyard guitar made of a petrol tank, the only problem is that everyone wants to live without doing any work.

it would be easy to “steer” this behemoth away. all our upperclass activists would remain in their bubbles, no loss, all gain. but that’s exactly what sinks the ship. the fact that the ship itself is poorly designed. you can steer it in any direction, it will still sink.

we are seeing an erosion of all the rights fought for in the past century, and a slow return to feudalism, this time as a capitalist oligarchy. and all activism seems focused on specifics, instead of referring to the big elephant in the room. has it gotten so big that people don’t know there are other ways to live?

why aren’t we building cities with our bare hands like our ancestors, and making them resilient enough to be an example? why are we all trying to be neutral, when neutrality is systematically instrumentalized by our rulers and employers?

we need city states again, resilient so that nobody starves while refusing to sell to the highest bidder. we must learn to refuse business. to refuse selling our work forgetting about morals, selling our research for grant money, selling our crops for blood money.

i’m not naive. i know it is not going to happen. that’s why we started the places we started, and that’s why i won’t stop. i have seen a better world in the communities we lived in. they don’t scale up, but they can be independently applied.

i’ll be continuing this topic when we unravel the series on things. for now, just a silly bagpipe with a king’s head on it, i found it appropriate.

some mezoued from tunisia this time. its short range leads to a more rhythmic style of playing. i’d argue these pipes are somewhere between more melodic and more rhythmic instruments.

summarizing, first we saw how thermodynamics and information theory are similar, and how the latter is more abstract, applicable to both elementary particles, letters and numbers. by mixing the two, we have a quantitative metric for arrangements of things. then we defined things using a fractal equation. then, from the ground up, we visited the first realms of knowledge. today we continue our journey.

as molecules grow and interact, they develop strange shapes, this is, they become spatially arranged. like the water molecule, proteins for example are nothing more than very big molecules, exhibiting strange shapes. as molecules become bigger, their interactions become more complex. an example of this is a catalyst. we can see it as a special harbor of sorts. imagine you are learning to sail. you can try it in a big open ocean, plagued by storms, or you can try it in a safe harbor where the waves are not too high. a catalyst is a molecule that, for its simple properties, facilitates the reaction of other molecules.

let’s think about it for a second. different molecules can interact with each other, and their own properties (in this case spatial) can affect other molecules profoundly. note that a catalyst exists anyway, independent of whether it will ever affect other molecules or not. but for the other molecules the difference can be dramatic.

for example, though not very scientifically correct, would be using anti freeze in your car’s radiator. the anti freeze itself is just a molecule that does very little alone. but if mixed with water, it will lower its freezing temperature. this can be very important if you are trying to get to work and your car is frozen. so a tiny molecule sometimes can make a big difference.

one of these cases is life. it might be arguable whether certain moving molecules are “alive”, but as soon as molecules get big enough, they start doing work. the same work we talked about before, the one we can measure. an example of this work would be the work of the contents of a cell to assemble molecules. these are just like tiny robots. if a molecule can do work, and another can use the work to create other molecules, we can have molecular evolution.

i won’t try to explain how this works, i’m sure many experts would be better at it. but one thing i can say is that as information increases, so do these unintended consequences. the bigger and more arranged a molecule is, the more likely it can do work on others for example. so after many many years of molecular evolution, a good set of working producing molecules got together in things we call cells, . cells themselves are a multitude to explore, but what i am interested in is how to save and retrieve them, or, how to quantify them in terms of information.

it is common to say DNA (one of the in cells) is the script for life. i disagree. as the analogies i used before, it is not enough to store the alphabet, it is necessary to store the agents that can work with it (like the painter and the painting, or kolmogorov complexity). this would be a contribution of computer scientists that is overlooked. just read this interview of richard stallman (founder of the GNU free software movement), and how profound it is (search for quaternary).

DNA is a quaternary program that runs on a cell computer. to accurately describe a cell system, we need all the information of the DNA, but also the information of the computer it runs on. all the proteins, all the structure, all the constraints. DNA might be a key, but alone it is worthless.

so we have a new layer of agents. we have the laws that govern things both in groups and alone (laws), and we now have things that can do work independently. the why is easy, it is part of their properties, these small machines are just like elaborate catalysts, mindless automatons. but they function as new laws for bigger systems.

but more essential to them is the fact that their activity adds to the structure of their surrounding world. like the boy picking up pebbles to draw a circle, these molecules take in simpler forms of matter and energy and convert them in more arranged forms thereof. information must include not only the “actg” letters, but also all the machinery required. so to quantify a cell, we would have to quantify everything.

how much information are we talking about? i am leaving quantification for later. but if we survey all the constituents of a cell, which themselves are thousands, and if we compute how unlikely it is that they are all together versus apart, we can quickly realize that the information stored there is no short than a universally big number. note that physical information is not computing the “actg” unique sequence in bits, that is computational ignorance. that is not physical information, that is information we perceive as high level, us being humans. the real information includes all constituents and their structure. the names, as we’ll see soon, are a human illusion.

already we begin to see tiny minds at work. the molecules that move molecules around, following some anti-entropic imperative. that ensemble then, using the same rules, clusters itself in groups, becoming what we call organisms: . some of these will be specified, where large groups of similar cells can be called organs, systems, and so on. all these abstractions, as we’ve been saying, are just encapsulating names for things, since things themselves require no layers whatsoever.

so we continued our journey into the realms of the biochemist and now the biologist. to biologists, evolution and replication is about organisms. to a biochemist, it might be just about replication of certain molecules. either way, they are expressions of how entropy can locally be reversed, and slowly, we build up our complexity. soon, we will come full circle.