I love to juggle different ontologies depending on what is currently pragmatically useful. Not being commited to any particular ontology feels extremely free and full of relief. In explorative analytical mode I am not loyal to any particular set of I love to explore what kinds of assumptions can exist and what are their advantages and disadvantages in as neutral way as possible. In explorative experiental mode I love to explore what its like to deeply experience different ways of being, such as being one with everything on open individualism or nonexistence on empty individualism or increased sense of agency and unlimited possibilities of statespace of consciousness in idealism because of less attachment to the "physical being". Being agnostic because of difficulty or impossibility of empirical testability can free oneself from not optimal lenses. Being sceptic can find out disadvantages efficiently. Seeing reality as fundamentally mysterious and nongraspable by any concepts generates tons of awe and generates openminedness and epistemic humility meaning one has no total certainity about truthness and accuracy and fundamentalism of his models by dereifying concrete beliefs. We are all one because we're all locally embedded in the global universal wave function but we are also it through fundamental interconnectedness, relationality, nonseparability of everything, no system can ever be fully isolated. We're all also slices in spacetime or nothing at all because nothing is ever permanent. We're all also observing and acting systems that are segments that come into existence and dissolve into entropy because that's pragmatic notion to navigate everyday world and to engineer neurotechnologies and do other science. Fundamental optimistic assumption that things will get better both tries to predict the future but also forms it because collection of agents with doom assumption will have lesser motivation to change the world for better and thus decreasing the chances of it by that belief existing! ===Assumptions for science=== Empiricism assumes that truthness of a model is determined by its predictive and explanatory power guided by occam's razor. Baysianism assumes that this model is slowly determined by slow updating of its structure according to what evidence in empirical data are presented. Approximating means that all our models we assume are finding regularities in dynamics by useful approximations. Raw concrete empirical measurements and predictive mathematical models build on top of them is the ultimate minimization of vagueness, filtering signal out of noise. Though measurement outcomes still depends on what tools we use to measure and what mathematical and philosophical assumptions we use to contextualize them in. ==Fundamental structure of reality for science== ===Classical physics=== Let's start with classical physics to make sense of macroscopic phenomena, which means lets not look at the quantum behavior of microscopic fundamental particles. Newton's law of motion helps us predict the future trajectory of an object. Thermodynamics helps us predict how contracted heat aka energy has tendency to distribute itself into the surroundings according to the second law of thermodynamics where everything goes towards entropy aka eqilibrium. There are many types of classical differential equations that help us predict behaviors of lots of types of systems, such as how computers work, dynamics of neurons or different variables when analyzing society such as evolutionary economical models. 4th law of thermodynamics: organisms accelerate 2nd by converting negentropy into entropy by dissipation looking like they resist it. ===Information theory, Classical formulation of the free energy principle formalizing conscious agents=== Now let's talk about the free energy principle (FEP) that I'm gonna use as both epistemological framework (bayesianism) and to define physics of survival. [ActInf Livestream #045.0 ~ "The free energy principle made simpler but not too simple" - YouTube]([ActInf Livestream #045.0 ~ "The free energy principle made simpler but not too simple" - YouTube]([ActInf Livestream #045.0 ~ "The free energy principle made simpler but not too simple" - YouTube]([ActInf Livestream #045.0 ~ "The free energy principle made simpler but not too simple" - YouTube]([ActInf Livestream #045.0 ~ "The free energy principle made simpler but not too simple" - YouTube](https://www.youtube.com/watch?v=9MQQKaKEXs0))))) [Dr. MAXWELL RAMSTEAD - The Physics of Survival - YouTube]([Dr. MAXWELL RAMSTEAD - The Physics of Survival - YouTube]([Dr. MAXWELL RAMSTEAD - The Physics of Survival - YouTube](https://www.youtube.com/watch?v=8qb28P7ksyE))) [Karl Friston's Unfalsifiable Free Energy Principle - YouTube]([Karl Friston's Unfalsifiable Free Energy Principle - YouTube]([Karl Friston's Unfalsifiable Free Energy Principle - YouTube]([Karl Friston's Unfalsifiable Free Energy Principle - YouTube](https://www.youtube.com/watch?v=jZ1fsXQz7M4)))) https://static.miraheze.org/qualiaresearchwiki/a/af/ActiveInference.png Free energy principle starts with defining a thing. It asks what must a thing that survives do? It must be stable. How it does that? It looks like as if its resisting the 2nd law of thermodynamics where systems tend to go towards entropy, towards disintegrated equilibrium. A thing is an open system, which means that its not fully isolated, where energy is coming inside and out of it via various entrances. It uses this energy to stabilize its structure to resist decay. 4th law of thermodynamics states that biological systems accelerate 2nd law by being a stable negentropic structure that serves as a machine that converts environment's negentropy into entropy through dissipation. For example us eating food which is basis for our biological machine. How do we systematically find food in our environment? We must be able to predict it and act on it. How do we do that? Our brain approximates bayesian mechanics. What is that? Bayes theorem tells us the optimal way of processing information that natural selection approximately recruited in us, where the probaility of our model of the causes of our perception (aka priors) given our measured input sensory data being true aka corresponding to how it is statistically in reality can be calculated by probability of our input sensory data given our predicted causes times probability of our predicted causes, all divided by the probability of our input sensory data. [The Bayesian Brain and Meditation - YouTube]([The Bayesian Brain and Meditation - YouTube]([The Bayesian Brain and Meditation - YouTube]([The Bayesian Brain and Meditation - YouTube]([The Bayesian Brain and Meditation - YouTube]([The Bayesian Brain and Meditation - YouTube]([The Bayesian Brain and Meditation - YouTube]([The Bayesian Brain and Meditation - YouTube]([The Bayesian Brain and Meditation - YouTube]([The Bayesian Brain and Meditation - YouTube]([The Bayesian Brain and Meditation - YouTube]([The Bayesian Brain and Meditation - YouTube]([The Bayesian Brain and Meditation - YouTube]([The Bayesian Brain and Meditation - YouTube]([The Bayesian Brain and Meditation - YouTube]([The Bayesian Brain and Meditation - YouTube]([The Bayesian Brain and Meditation - YouTube](https://www.youtube.com/watch?v=Eg3cQXf4zSE))))))))))))))))) Issue is that when analytically calculating the last term we get combinatorial explosion, leading to it not being computable. Evolution sidesteps this issue by partially by evolution preprogrammed priors, such as subconsciously monitoring and influencing our blood pressure, or doing lots of partitioning of sensory data, such as dividing into different senses, doing distinctions between self and other, modelling our own ability to influence the world and so on, all of which is maintained in an always active generative model that acts as a software that looks at sensory data, compares it with our priors, and sends a prediction error if there is a mismatch, which creates evolutionary pressure to update our model of the world, such as for example changing our perspective on some issue when presented with different evidence (certain ways of thinking are stuck in rigid attractor where this mechanism of updating is malfunctioning) or for example when we see a pink unicorn dancing on a rainbow when on psychedelics we get confused and see it as outlier that probably isnt real according to our priors, but seeing lots of unicorns overtime might change our priors. Or we can act on the environment for out sensory data to meet our prior expectations. This whole process reduces our uncertainity about the world. More generally and formally, a thing corresponds to a markov blanket, which is a graph of nodes that learn correlations from its surroundings where you can locate a statistical boundary, where depending on how this particle (an observer with a reference frame) is complex [Imgur: The magic of the Internet]([Imgur: The magic of the Internet](https://imgur.com/a/xHvym29)) you can locate nodes that seem to encode hidden states, meaning correlations encoding the outside world's (outside blanket's) structure, nodes that look as if they're just measuring and compressing the outside nodes, and nodes that look as if they're acting on the environment by statistical causal influence (doesnt exist in inert particles), and it tends to be nested a hieachy of markov blankets composed of markov blankets and so on, where you get dynamics of message passing and circular causal influence of the agent with the environment. Even more formally on this markov blanket a principle of least action is applied that minimizes statistical quantity of variational free energy that helps the model to be as accurate as possible while being the least complex as possible. It can be seen through the lens of thermodynamics as energy contractions and flow on this topology of information networks. You can crave certain neural classifiers or certain paths and then interconnect them via higher order nonlinear neural connections. The probability distribution which best represents the current state of knowledge about a system is the one with largest information entropy aka avarage amount of information or uncertainity inherent to the variable's possible outcomes. (generalization of thermodynamic entropy) [Principle of maximum entropy - Wikipedia]([Principle of maximum entropy - Wikipedia]([Principle of maximum entropy - Wikipedia](https://en.wikipedia.org/wiki/Principle_of_maximum_entropy))) All of those insights can be used for ideal rational epistemology! ===Quantum physics=== We've covered classical physics so far, now let's look at quantum mechanics. Quantum mechanics is a general framework that can be used to study evolution and dynamics of particles like in classical physics, but instead of objects and particles as deterministic points or shapes in classical 3D space, their classical information becomes inherently probabilistic and a concept of entanglement is introduced that says that any two systems that are entagled are inseparable. When we apply quantum mechanics to the fundamental particles level, particles are represented using complex valued wave function that evolves the probability distribution of the possible particle's classical properties. In quantum electrodynamics [Quantum - Wikipedia](https://en.wikipedia.org/wiki/Quantum)_electrodynamics or standard model or quantum field theory in general, particles are excitations of matter and interaction quantum fields that fill all of space. ===Unifying quantum with the classical, Quantum darwinism or other options=== Quantum darwinism [Quantum - Wikipedia](https://en.wikipedia.org/wiki/Quantum)_Darwinism piece connects the quantum and classical world by saying that classical states with any classical bits are those quantum states that survived the process of decoherence, where decoherence is system's interaction aka entagling with the environment which results in loss of information. To minimize decoherence in quantum computers so that particle entaglement performing parralelized quantum computations isnt broken, one has to isolate the system and cool it down a lot. The survival of classical states is usually implemented by creating a lot of redundant information, so information about spin, location, or space can be located in the entaglement network we measure. Space and time can be seen as a quantum error correcting code. [Is Spacetime a Quantum Error-Correcting Code? | John Preskill - YouTube]([Is Spacetime a Quantum Error-Correcting Code? | John Preskill - YouTube]([Is Spacetime a Quantum Error-Correcting Code? | John Preskill - YouTube](https://www.youtube.com/watch?v=SW2rlQVfnK0))) Quantum entaglement can be seen as the glue of spacetime. [Entanglement as the Glue of Spacetime - YouTube]([Entanglement as the Glue of Spacetime - YouTube]([Entanglement as the Glue of Spacetime - YouTube]([Entanglement as the Glue of Spacetime - YouTube](https://www.youtube.com/watch?v=bxY1PK4wW1I)))) Where local more entaglement encodes less distance and less local energy. [From Quantum Mechanics to Spacetime - Qiskit Seminar Series with Sean Carroll - YouTube]([From Quantum Mechanics to Spacetime - Qiskit Seminar Series with Sean Carroll - YouTube]([From Quantum Mechanics to Spacetime - Qiskit Seminar Series with Sean Carroll - YouTube]([From Quantum Mechanics to Spacetime - Qiskit Seminar Series with Sean Carroll - YouTube]([From Quantum Mechanics to Spacetime - Qiskit Seminar Series with Sean Carroll - YouTube]([From Quantum Mechanics to Spacetime - Qiskit Seminar Series with Sean Carroll - YouTube](https://www.youtube.com/watch?v=8-ct1IlGUOw)))))) Second law thermodynamics defines the arrow of time. Quantum version of second law of thermodynamics posits that entropy corresponding to entaglement is increasing overtime. The more overall entaglement there is, the futher global "time slice" of the universe it is. [How Quantum Entanglement Creates Entropy - YouTube]([How Quantum Entanglement Creates Entropy - YouTube](https://www.youtube.com/watch?v=vgYQglmYU-8)) I'm gonna stay with this framework. Other options in physics is loop quantum gravity, where spacetime is emergent from loops, more abstract quantized spacetime [Loop quantum gravity - Wikipedia]([Loop quantum gravity - Wikipedia]([Loop quantum gravity - Wikipedia]([Loop quantum gravity - Wikipedia]([Loop quantum gravity - Wikipedia]([Loop quantum gravity - Wikipedia]([Loop quantum gravity - Wikipedia]([Loop quantum gravity - Wikipedia]([Loop quantum gravity - Wikipedia]([Loop quantum gravity - Wikipedia]([Loop quantum gravity - Wikipedia]([Loop quantum gravity - Wikipedia]([Loop quantum gravity - Wikipedia]([Loop quantum gravity - Wikipedia](https://en.wikipedia.org/wiki/Loop_quantum_gravity)))))))))))))) , or string theory where spacetime is certain configuration of strings. ===Quantum formulation of the free energy principle=== What is the role of an observer? Let's formulate quantum version of the free energy principle. [ActInf Livestream #040.0 ~ "A free energy principle for generic quantum systems" - YouTube]([ActInf Livestream #040.0 ~ "A free energy principle for generic quantum systems" - YouTube]([ActInf Livestream #040.0 ~ "A free energy principle for generic quantum systems" - YouTube]([ActInf Livestream #040.0 ~ "A free energy principle for generic quantum systems" - YouTube]([ActInf Livestream #040.0 ~ "A free energy principle for generic quantum systems" - YouTube]([ActInf Livestream #040.0 ~ "A free energy principle for generic quantum systems" - YouTube]([ActInf Livestream #040.0 ~ "A free energy principle for generic quantum systems" - YouTube]([ActInf Livestream #040.0 ~ "A free energy principle for generic quantum systems" - YouTube]([ActInf Livestream #040.0 ~ "A free energy principle for generic quantum systems" - YouTube](https://www.youtube.com/watch?v=-qZYxSbJ38E))))))))) [Physics as Information Processing ~ Chris Fields ~ AII 2023]([Physics as Information Processing ~ Chris Fields ~ AII 2023]([Physics as Information Processing ~ Chris Fields ~ AII 2023]([Physics as Information Processing ~ Chris Fields ~ AII 2023]([Physics as Information Processing ~ Chris Fields ~ AII 2023]([Physics as Information Processing ~ Chris Fields ~ AII 2023]([Physics as Information Processing ~ Chris Fields ~ AII 2023]([Physics as Information Processing ~ Chris Fields ~ AII 2023]([Physics as Information Processing ~ Chris Fields ~ AII 2023]([Physics as Information Processing ~ Chris Fields ~ AII 2023]([Physics as Information Processing ~ Chris Fields ~ AII 2023]([Physics as Information Processing ~ Chris Fields ~ AII 2023]([Physics as Information Processing ~ Chris Fields ~ AII 2023]([Physics as Information Processing ~ Chris Fields ~ AII 2023]([Physics as Information Processing ~ Chris Fields ~ AII 2023]([Physics as Information Processing ~ Chris Fields ~ AII 2023]([Physics as Information Processing ~ Chris Fields ~ AII 2023]([Physics as Information Processing ~ Chris Fields ~ AII 2023](https://coda.io/@active-inference-institute/fields-physics-2023)))))))))))))))))) Entaglement is fully generally nonseparability of two quantum systems, therefore it is equivalent with bayesian coherence, correlation, emergence, conditional dependence, it giving information, it having causal influence. What exists is a network of conscious observers. An observer corresponds to a cone-cocone diagram, which is a mathematically abstract way of formalizing the notion of collective intelligence with various classifiers in hiearhical graph sharing same context in collective bayesian variational free energy minimization updating on a markov blanket. This observer is implemented by physics. Experiental subjective time and space is relativistic construct of each observer that can be seen as consequence of measurements of distances and causal structures [Qualia Research Institute](https://qri.org/)blog/pseudo-time-arrow [Qualia Research Institute](https://qri.org/)blog/hyperbolic-geometry-dmt [[1012.0535] Physics as Information Processing]([[1012.0535] Physics as Information Processing]([[1012.0535] Physics as Information Processing]([[1012.0535] Physics as Information Processing](https://arxiv.org/abs/1012.0535)))) and acts as error correcting code and gluing and relational contextualizing of internal states which corresponds to the general definition of entaglement. Spacetime that is objectively modelled in physics corresponds to very similar mathematical construct as written above. Relativity of time can be modelled as the speed of observer's internal state updating. Wavefunctions can be seen as nonrealist by superdeterminism, where the inherent uncertainity in the wavefunction is result from mathematically unpredictable chaotic behavior and if we knew initial conditions of the universe there wouldnt be randomness. I'm gonna assume no such hidden variables exist, wavefunctions can be seen as part of the observer's models and observers share wavefunction depending on the amount of entaglement, and shared to us nonchanging relativistic physical laws is what entangles us. When an observer, that corresponds to an open (nonequilibrium) quantum physical system, such as the cortical hiearchy or overall organism, is percieving, meaning its interacting with another system with a holographic screen, it becomes statistically inseparable with it, it entangles with it. Qualia experienced by observers is classical information.