What is the fundamental equation of intelligence? What is the fundamental equation of the universe? What is the state of the art in artificial intelligence theory and practice? How to apply AI for good as ideally as possible as much as possible? What is the fundamental equation of the brain? How does AI and biological intelligence compare? How to connect all sciences, formal and natural? What is the fundamental equation behind emergence and complexity? How does biology and other scientific fields emerge? What are all the concepts in mathematics? What is the fundamental equation of consciousness? What is the fundamental equation of building a great future for all where everyone flourishes? How to maximize the benefits, and minimize the disadvantages, of technologies and political systems? What are the answers to the problems in philosophy? [ChatGPT - Fundamental Equations and Intelligence](https://chatgpt.com/share/678d8873-740c-800a-95fb-b23cc7b90cf1) Why is there something rather than nothing? Why can we ask this question? Does asking this even make sense? Why did big bang happen? What if alternatives to big bang like big crunch happened instead? Did it actually happen? Why is universe governed by few fundamental forces between tens of elementary particles? Why is the standard model and general relativity the best current description of it that we have so far? Why do we struggle with unifying quantum mechanics and general relativity so much? Is theory of everything even possible? What even is space? What even is time? Is there such thing as "before the big bang" if time might not have existed before it? Why and how did chemical elements exactly emerge? Why and how did life exactly emerge and how does it work? Why is evolution such unreasonably effective algorithm? Why and how exactly is there such mindblowing specialized diversity of life? Why and how did intelligence emerge and how does it work? What are the best definitions of intelligence? Why are brains and AI systems so unreasonably effective in different complementary ways? How can they be upgraded? What happens to consciousness after death? Why and how did consciousness and experience emerge and how does it work? What are the best definitions of consciousness? What is the solution to the hard problem of consciousness? Does this question even make sense? What even is consciousness in the first place? Why are be able to design so many technologies that allow us to manipulate the universe to such degree? Why does emergence happen in the first place? How will the universe end? Is there such a thing as end of the universe? Is the multiverse theory true? Why is mathematics so unreasonably effective at describing and predicting nature? Is there a better mathematical foundation than set theory, type theory or category theory? Is mathematics invented or discovered? Is mathematics fundamental language of reality or just our mental tool to survive? What even is reality? What is being? Why can we even ask all of these questions? Do many of these questions even make sense and are they any final answers to them, or answers we get are just getting closer to to us incomprehensible "truth", or they have many parallel answers, or many answers are differently relatively valid depending on the assumptions we start with, or are they fundamentally unanswerable? Will quantum gravity be solved by mainly humans or AI or humans+AI and how soon would you predict? [What’s inside a black hole? U-M physicist uses quantum computing, machine learning to find out | University of Michigan News](https://news.umich.edu/whats-inside-a-black-hole-u-m-physicist-uses-quantum-computing-machine-learning-to-find-out/) "Matrix quantum mechanics plays various important roles in theoretical physics, such as a holographic description of quantum black holes, and it underpins the only practical numerical approach to the study of complex high-dimensional supergravity theories. Understanding quantum black holes and the role of entanglement in a holographic setup is of paramount importance for the realization of a quantum theory of gravity. Quantum computing and deep learning provide potentially useful approaches to study the dynamics of matrix quantum mechanics. If successful in the context of matrix models, these rapidly improving numerical techniques could become the new Swiss army knife of quantum gravity practitioners. In this paper, we perform the first systematic survey for quantum computing and deep-learning approaches to matrix quantum mechanics, comparing them to lattice Monte Carlo simulations." <https://journals.aps.org/prxquantum/abstract/10.1103/PRXQuantum.3.010324> More people should work on the intersection of AI and quantum gravity even tho im personally the most scared about technofeudalism currently (but i also give nonzero probability to risk of uncontrollable rogue AGI) https://fxtwitter.com/norabelrose/status/1873823909168242715 [By default, capital will matter more than ever after AGI — LessWrong](https://www.lesswrong.com/posts/KFFaKu27FNugCHFmh/by-default-capital-will-matter-more-than-ever-after-agi) [https://www.youtube.com/watch?v=-oZc8h5L--A](https://www.youtube.com/watch?v=-oZc8h5L--A) then Joscha makes building AI sound like the most beautiful grand scientific, engineering and philosophical quest of humanity, which resonates with my hypercurious nerd me [Imgur: The magic of the Internet](https://imgur.com/a/M1iSQbw) hypercuriousity gives my life so much meaning [https://www.youtube.com/watch?v=UjEngEpiJKo](https://www.youtube.com/watch?v=UjEngEpiJKo) Major part of my meaning of life currently is to try to understand: - The most complete fundamental equation/s of intelligence: human intelligence, diverse machine intelligences (all sorts of current and future subfields of AI), other biological intelligences, collective intelligence, theoretical perfect AGI (AIXI variants, Chollet's intelligence, Legg's intelligence, etc.), hybrids, etc. - The most complete fundamental equation/s of the universe and the world in general: How does the standard model and general relativity work? How does everything else in our world on other scales with other fields, such as chemistry, biology and sociology, emerge? What is beyond the standard model of particle physics and general relativity, how to solve quantum gravity? - best math and philosophical assumptions for the above [Imgur: The magic of the Internet](https://imgur.com/nICotqE) hmm, holes/loops v algebraický topologii na tvarech?, možná symetrie z částicový fyziky?, aerodynamics of a cow?, BSD conjecture (racionální solutions na eliptický křivce), navier stokes (na modelování tekutin)?, feynmanuv diagram s anihilujícím electronem a positronem do photonu becoming quark antiquark radiating gluon. p=np hypotézovaná rovnost rychlosti (komplexity) classes algoritmů 😄 btw ten týpek na obrázku je Grigori Perelman, což je mega based člověk, co v matice vyřešil poincare conjecture za co měl dostat $1,000,000 ale to odmítl a odmítá s kýmoliv komunikovat 😄 a jo, ten první obrázek bude relatovat k poincare conjecture, protože pokud tomu dobře rozumím, tak ta právě řeší, že libovolný 3D tvar co nemá díry, boundaries a je konečný, musí být deformovatelný do 3D koule (matematicky ekvivalentní topologicky) algebraickou topologii chci strašně moc víc pochopit, je to strašně fascinující podobor matiky, sem tam se k ní vracím, nedávno jsem si bookmarknul další lecture series na to já chci pochopit matematický vzory co jsou ve všem, a prozkoumat všechny možný matematický vzory! 😄 tak se mýmu mozku nejlíp chápe svět a všechno 😄 a furt se cítím že vím absolutní nic relativně k tomu všemu co jde vědět moji hypercuriousity do matiky nikdy nic nerozbije 😄 ta mi dává nekonečný joy btw dost těhle matik se zároveň různí lidi pokusili aplikovat na pochopení a tvoření AIčka 😄 understanding neural networks by quantum field theory, algebraic topology of/with neural networks, understanding symmetries of neural network architectures (moje zpráva před tebou) or learning symmetries of physical systems, liquid neural networks, physics informed neural networks, complexity classes of AI systems,... ale nejvýraznejší podobor z fyziky na tvoření a chápání AIčka bude asi statistická mechanika, a z čistější matiky to bude asi algebraická geometrie 😄 dost toho se aplikuje i na víc než jenom neuronky, ale obecně víc machine learning/AI podoborů 😄 všechno hodí nějaký výsledky když se to vygooglí 😄 [https://www.youtube.com/watch?v=8fEEbKJoNbU](https://www.youtube.com/watch?v=8fEEbKJoNbU) [TensorFlow Quantum](https://www.tensorflow.org/quantum) Guillaume Verdon: Beff Jezos Týpek dělal quantum machine learning v Googlu, kde pomohl vytvořit Tensorflow Quantum na quantum neural networks (a hybridy) na quantum počítačích, a teď si jede vlastní startup na hardware na thermodynamický machine learning pomocí out of equilibrium thermodynamiky. Leavnul quantum machine learning pro thermodynamic machine learning, protože to bude ještě doba, než budeme mít dostatčný kvantový počítače, aby se víc large scale kvantovej machine learning víc vyplatil, pokud vůbec, a biologický systémy možná jsou inteligentní právě díky out of equilibrium thermodynamice. Dost mě inspiruje víc grindit fyziku zároveň s AI. Jeden potential dream AGI systém pro vědce je physics based AIs (kvantový, thermodynamic, deterministický, hybridy) optimalizovaný pro perfektní modelování přírody (podobně jak příroda se řídí kvantově/thermodynamicky/deterministicky/hybridně na různých škálách) coupled s anthropomorphic humanlike synthetic agentic scientist AI, která by dokázala tu physics based AI používat optimálně a překládat výsledky do víc lidskýho jazyka pro lidi přes víc humanlike interface. One potential dream AGI system for scientists is physics based AIs (quantum, thermodynamic, deterministic, hybrids) optimized for perfect modeling of nature (similar to how nature is governed quantum/thermodynamically/deterministically/hybridly on different scales) coupled with anthropomorphic humanlike synthetic agent scientist AI that could use that physics based AI optimally and translate the results into more humanlike language for humans via a more humanlike interface. functional programming magicians have tried to apply their monad is just a "monoid in the category of endofunctors" runes to quantum computing wizardry [[2310.15735] The Quantum Monadology](https://arxiv.org/abs/2310.15735) https://x.com/burny_tech/status/1877031348143059371 So AI currently is basically: - We take the fundamental equations of physics that use linear algebra+calculus+probability theory+group theory etc., - take quantum mechanics, quantum electrodynamics, solid state physics, etc. from it - conquer the physics into transistors with p-n junctions that operate with electrons - arrange those those into boolean logic gates - combine logic gates into digital circuits - arrange the circuits into CPUs and GPUs that support machine code - build on top of it many logical programming languages that supports arithmetic based on automatas and turing machines - then we code linear algebra+calculus+probability theory (AI GPUs are optimal for matrix multiplications) - which is used to train a neural network that mainly does fuzzy pattern recognition with weak emergent generalization, but we also try to make the neural network do logic again and simulate automatas and turing machines to get more symbolic reasoning chains, usually in a neurosymbolic context (coupling neural networks with symbolic engines, o3 CoT RL, or MCTS,...). But more people are trying to start at the bottom of this stack instead, instead of having all these layers. There are attempts at: - hardwiring AI architectures like Transformers into ASIC hardware, like by Etched - hardware based more on biology with more biology-inspired architectures, like neuromorphic computing - physics based AI, that some try to hardwire into hardware more, and sometimes literally using the fundamental physics itself, like thermodynamic AI in Extropic and other labs, quantum ML maybe soon on quantum computers in Google, differential equations in Liquid AI that might have specialized hardware eventually, and others [https://youtu.be/3MkJEGE9GRY?si=PYZmXD2PuaDRhk0B&t=4348](https://youtu.be/3MkJEGE9GRY?si=PYZmXD2PuaDRhk0B&t=4348) pokud bys kvantifikoval všechny formy energie v libovolným fyzikálním systému, a všechny reducnul na fundamentální energie (ze standard modelu s electromagnetism, strong nuclear, weak nuclear, higgs, a k tomu nějak přidat gravitaci, a asi dark energii/matter, a možná ještě jiný co ještě existují o kterých nevíme), tak to by asi mělo být všechno co se týče energie, a komplexita je v tom irrelevant, kde různý systémy se stejnýma energiema můžou mít různou komplexitu, což taky sedí s conservation of energy, kde když v closed systému zvyšuješ entropii (která má souvislost s měnící se komplexitou), tak energie je pořád conserved, akorát mění formy (first law of thermodynamics) [Complexity - Wikipedia](https://en.wikipedia.org/wiki/Complexity) [Complexity - Scholarpedia](http://www.scholarpedia.org/article/Complexity) ale zároveň energie a komplexita je v biologických systémech (jako rabbit a human) dost related, tím jak to jsou vlastně out of equilibrium selforganizing open complex systems s hiearchickýma energy flow&transformation procesama na maintanance jejich komplexní organizace, co acquire&dissipate energy, exchange energy with the envionment, a bez energie chcípnou, a s moc energií jsou destroyed Intelligence,AI,brain,physics,math,neural networks,consciousness,philosophy,risks,well free flourishing future of sentience! TESCREAL! Intelligence,AI,AGI,brain,physics,math,STEM,cognitive science,consciousness,complexity,philosophy,foundations,futurology! TESCREAL! joscha has interesting theory of consciousness as spirits [https://www.youtube.com/watch?v=3MkJEGE9GRY](https://www.youtube.com/watch?v=3MkJEGE9GRY) i understand it as weak emergence of software patterns i like his analogy with computer software: you can't find minecraft in the transistors, but the causal structure of minecraft still in a way exists the same for consciousness but i guess he also argues for some top down causality, like RL agent being able to pick between policies according to a reward function, so choosing between recruiting new hardware maybe selforganization fits in there too i think: instead of causal structure of minecraft being engineered, you get weakly emergent causal structure of minecraft like gliders in conways game of life or like these lizards in neural celluar automata [Growing Neural Cellular Automata](https://distill.pub/2020/growing-ca/) From first principles understand and visit everything in the whole universe AI will make groundbreaking discovery in fundamental physics in less than 10 years i když spíš za light se spíš klasifikuje určitá část spektra oscilujících electromagnetických waves, ale elektromagnetismus v klasických tranzistorech je spíš statický/slowly varying ale obojí ovládají maxwellovy rovnice! stejně pořád absolutně nepobírám jak ta obrazovka na kterou teď čučím je absolutní witchcraft, že emituje oscilující electromagnetic waves ve visible light spektru do našich očí, co se zkonvertuje to action potentials apod. v mozku, kde vizuální kortex a zbytek mozku je ty informace schopnej interpretovat jako něco co dává smysl, a díky tomu plus zbytku hardwaru a softwaru v počítačích můžeme komunikovat s jinýma opičkama přes celou planetu WHAT IS THIS MAGIC a před tím ještě 13.8 miliard let sebeorganizujících se částic do zhruba větší a větší komplexity díky standardnímu modelu částicový fyziky, obecný relativtě, thermodynamiky, apod., kde se šlo z částic do atomů do molekul do komplexnějších živých a neživých struktur, až se z toho díky větší a větší komplexitě sebezorganizovaly tyhle opičky a jejich technologický hračičky včetně všech galaxií a zbytku vesmíru a kdo ví či velký třesk je fakt ten správnej kosmologickej model also, what kind of magical wizardry is gravity, and why can't we fit it with our other equations of the universe that we found so far?! and why and how are our monkey brains, with the assistance of our technological tools, even able to find all of these equations that we found so far in the first place?! there is still so much to ask, learn, know, figure out and how incomprehensible to us will the future of our civilization, of other civilizations, of the universe, etc., be? Jak řád a nepořádek tvoří realitu ve fyzice určitým způsobem formalizuje Langevin rovnice! [Langevin equation - Wikipedia](https://en.wikipedia.org/wiki/Langevin_equation?wprov=sfla1) A Fokker-Planck rovnice [Fokker–Planck equation - Wikipedia](https://en.wikipedia.org/wiki/Fokker–Planck_equation?wprov=sfla1) Popisování libovolnýho dynamickýho systému pomocí deterministickýho toku a náhodných fluktuací Tady to Karl Friston popisuje v 10:00 😄 [https://youtu.be/h4KeYkwcJoc?si=BjFzmxFJT896c8Ny](https://youtu.be/h4KeYkwcJoc?si=BjFzmxFJT896c8Ny) I can't stop wanting to understand the patterns behind the universe and everything There are beautiful patterns in everything [Muž, který poznal nekonečno (2015) - IMDb](https://imdb.com/title/tt0787524/) https://x.com/burny_tech/status/1892256257584558244?t=1APpve23kRD-8CganpYwfA&s=19 The world has infinitely nuanced, complex, nonlinear, chaotic, dynamic, etc. social dynamics that somehow arise from the interacting fundamental particles of the universe, and no one has the capacity to pick it up with complete accuracy from their one perspective with limited brain modeling ability and limited varyingly accurate data that come only from some angles Svět má nekonečně nuanced, komplexní, nelineární, chaotickou, dynamickou atd. sociální dynamiku, co nějakým způsobem vzniká z interagujících fundamentálních částic vesmíru, a nikdo nemá kapacitu ji z jeho jednoho pohledu s úplnou přesností pobrat s limitovanou modelovací schopností mozku a limitovanými různě přesnými daty jen z nějakých úhlů AI will help the fundamental physics crisis. It will not be current LLMs. It will be a more specialized or more general alien intelligence. I want to train giant neural networks for grokking fundamental physics, but possibly based on completely alien architectures compared to today's deep learning Will future AI eventually discover new physics on the level of first discovering classical mechanics, or general relativity, or quantum mechanics? I wonder if the theory of quantum gravity would allow us to create technologies that would use it: Quantum gravity computers: On the theory of computation with indefinite causal structure A quantum gravity computer is one for which the particular effects of quantum gravity are relevant. [[quant-ph/0701019] Quantum gravity computers: On the theory of computation with indefinite causal structure](https://www.arxiv.org/abs/quant-ph/0701019) [Shtetl-Optimized » Blog Archive » Quantum gravity computation: you, too, can be an expert in this field](https://scottaaronson.blog/?p=219) [general relativity - What would one use a theory of quantum gravity for? - Physics Stack Exchange](https://physics.stackexchange.com/questions/814235/what-would-one-use-a-theory-of-quantum-gravity-for) https://grok.com/share/bGVnYWN5_582a5459-2ba1-42ea-b2e9-cba4416af9ea But I'm also curious about the resolution of the singularity at the Big Bang and resolution of the singularity in black holes And I'm curious about more accurate models of spacetime, or possibly unifying gravity with other forces Are current AI approaches in the current paradigm enough for radical new scientific discoveries and paradigm shifts? AlphaFold technically isn't LLM, but it's an autoregressive Evoformer/Pairformer that uses transformer iirc and some diffusion, and it seems to have done big progress in protein folding research But i think for leaps in physics we might need to go beyond deep learning Or maybe some kind of selfplay could bootstrap more optimal models? Something like AlphaGo move 37? Or could you give future AIs for predicting physics a RL reward signal in the form of empirical predictive results from experiments? Could that bootstrap novel results? Would that be eventually feasible when you spend enough infrastructure and compute to do these experiments? Or could physics simulations find shortcuts in training, similarly how we train robotics in simulations using RL now? Or do we need fundamental architecture more based on biology or physics or mathematics of information processing? How to: Actually grokking currently known equations of physics and fundamental physics as circuits? Being able to more strongly generalize them in nonbrittle way? Possibly go beyond them? So many unanswered questions...