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The Codex of Understanding

A personal quest to build the most complete, connected understanding of existence - uniting the scientific, philosophical, and humanistic worldviews.

learning

Published: Oct 13, 2025

Last Updated: Oct 13, 2025

Note: Work in progress.

General Idea

I firmly believe that the reason we seek more knowledge is to build a better model of the world - one that helps us predict, adapt, and thrive. For me, Education means understanding everything there is to know about existence itself. And since humanity has already gathered vast amounts of knowledge across millennia, the best place to start is by studying what we already know.

This space is my attempt to do that, to explore systematically how all areas of knowledge connect, evolve, and inform one another. Here you'll find structured explorations, self-created learning curricula, and reflections on how understanding grows when viewed as one coherent system rather than scattered disciplines.

Vision

An explorer of unknowns, a systems architect who builds bridges between disparate areas and creates entirely new ways of understanding intelligence, governance, and human civilization.

Meta Learning

Learning how to learn efficiently in any domain.

What is my definition of great people in history? inspired by Hamming

  • They have survived the passage of time and still hails in history we know of.
  • They were successful in multiple domains of life. They know how to balance and live a fruitful life.

Indian Knowledge Systems

Prologue

I am pretty ambitious ain't I. What can we do. We are here none the less.

Before human realized that he was different from any other thing that existed. A lot would have happened. Everything is quite intriguing. But we have fields like cosmology, astrophysics, astronomy, Nuclear Physics, Stellar Astrophysics, Planetary Science, Geology, Biology, Astrobiology and Paleontology.

Now everything is very intermixed, I can't say I will study physics first and then Cosmology. To begin with this are the constructs of human brain and have been developed over time in kinda following manner.

What Should I Do? (Efficient Learning Strategy)

  1. Find the Best "Top 5-10" First

    • Look for commonly recommended books in the field.
    • Check citations, reviews, or expert opinions.

  2. Skim & Identify Core Ideas Quickly

    • Not all books need a full read—skim to extract unique insights.
    • Look for overlapping principles across multiple books.

  3. Use "Meta-Learning" to Save Time

    • Read summaries, lecture notes, or expert interviews to validate a book’s importance before diving deep.

  4. Go Beyond Books

    • Engage in practical application, discussions, or real-world projects.
    • Books give theory, but mastery comes from doing.

Archive

Prehistoric Knowledge (Before 3,000 BCE):

  • Early tools and fire use
  • Cave art and early forms of communication

Ancient Knowledge (3,000 BCE - 500 CE):

  • Agriculture and animal domestication
  • Writing systems (cuneiform, hieroglyphics)
  • Mathematics (early counting, geometry)
  • Astronomy and the calendar
  • Philosophy (early Greek, Chinese, and Indian philosophies)
  • Early medicine and herbal remedies

Classical Knowledge (Antiquity) (500 BCE - 500 CE):

  • Greek and Roman contributions to philosophy, mathematics, and science
  • Euclidean geometry
  • Early developments in physics and astronomy
  • Early theories of ethics and politics

Medieval Knowledge (500 CE - 1500 CE):

  • Islamic Golden Age contributions to mathematics, astronomy, and medicine
  • Scholastic philosophy in Europe
  • Advances in medieval science and alchemy
  • Development of universities and formal education

Renaissance and Enlightenment (Early Modern Period) (14th - 18th centuries):

  • Revival of interest in classical knowledge
  • Advances in natural philosophy (precursor to modern science)
  • Scientific revolution (e.g., Copernicus, Galileo, Newton)
  • Enlightenment philosophy and political theory (e.g., Locke, Rousseau, Voltaire)

Industrial Revolution and Modern Era (18th century - early 20th century):

  • Rapid advancements in science and technology
  • Evolutionary biology (Darwin)
  • Physics (Einstein's theory of relativity)
  • Quantum mechanics
  • Modern psychology
  • Advances in computer science and information technology

Contemporary Knowledge (20th century - present):

  • Recent developments in genetics and genomics
  • Space exploration and astrophysics
  • Environmental science and climate change research
  • Neuroscience and artificial intelligence

I like the above given chart by ChatGpt and I will keep on updating as I learn more and more to make more accurate timeline to get bigger picture on how we have evolved as species and learned things to become what we are today.

Let's first define how are we going to refere to Timeline in years. Well guess what I don't know much about calanders and time keeping. Let's learn about [[Calendars]] first.

I feel like we don't know much about time at all and the way we should have our calendars and spans out our history.

Current Science can be branched into following

Out of all I think I will start with [[Cosmology]]

I'm realizing learning is going to be haywire no fixed path to be followed

Little did I know. Cosmology is part of Astronomy. I thought Cosmology to be fundamental subject as in Religious Cosmology it's beginning of everything. But doesn't look like that is how we categorize knowledge.

Astronomy is big domain having all these fields. Now I went to see the outline of Astronomy on wiki pedia and seems like It falls under space science which also encompass the Engineering aspect of it which is Astronautics. For some reason astronomy is branch of Physics as well.

Anyway will stick to cosmology and add Space Science as tag.

I think I should start learning about the subject with it's history and origin.

  1. Learn origins and History
  2. Find some good compendium and look through
  3. Course from Top University or online platforms, classcentral.org

🛠️ Principles to Guide in the Journey

  • Start with Universals, Move to Particulars
    • Begin with the most fundamental ideas that explain the widest range of phenomena (e.g., logic, math, and physical laws).
  • Embrace a Recursive Learning Approach
    • You will revisit core concepts repeatedly, each time with new depth and clarity. This reflects the way real discovery works—by spiraling deeper into the unknown.
  • Balance Theory with Experimentation
    • Knowledge without application is incomplete. As you learn, create models, test ideas, and engage with real-world phenomena.
  • Think Across Domains
    • Many breakthroughs arise at intersections (e.g., the birth of AI from neuroscience and mathematics).

[[Engineering]]

Make your own stuff with 3d printing, electronics and software.

History

  • Big History
    • [[Theory of Existence]]
    • Astrology from Big bang to solar system
    • Geology - Plate Techtonics
    • [[Origin of Life]]
    • [[Evolution]]
    • Anthropocene
    • Future
  • Intellectual History -> Evolution of Ideas

Languages

I want to learn languages.

  • Origin and Evolution of language

[[Philosophy]]

The roots of Inquiry -> how to ask questions, break down concepts, and understand the limits of human thought.

  • Epistemology -> What are landmark thinkers, books and papers?
  • Philosophy of Science
  • Philosophy of Mathematics
  • Logic & Reasoning
  • Metaphysics
  • Aesthetics
  • Philosophy of Language
  • Ethics & Morality
  • Existentialism & Meaning
  • Meta-science & Epistemology of Discovery
    • How do we invent new science?
    • How can we model the unknown?

Learn to ask questions that matter.

Formal Sciences

The language of reality -> Math is the most generalizable framework for understanding reality.

  • [[Mathematics]]
    • Set Theory & Foundations → Cantor, Zermelo-Fraenkel, Gödel
    • Abstract Algebra & Group Theory → Galois, Lie
    • Topology & Geometry → Euler, Riemann, Klein
    • Category Theory (for unifying ideas) → Grothendieck, Mac Lane
    • Probability & Information Theory → Kolmogorov, Shannon
    • Differential Equations & Dynamical Systems → Poincaré, Lorenz, Smale
    • Mathematical Logic & Computability → Turing, Church, Post
    • Complexity Theory & Nonlinear Systems → Wolfram, Mandelbrot, Bak
  • Complexity Science & Emergence
    • Chaos Theory & Dynamical Systems → Lorenz, Mandelbrot
    • Self-Organization & Cybernetics → Prigogine, Ashby, Kauffman
    • Complex Systems & Network Theory → Barabási, Newman
    • Emergent Phenomena → Anderson, Crutchfield
    • Artificial Life & Evolutionary Computation → Langton, Holland
  • Logic & [[Systems Science]] - Logic → Boole, Russell, Frege
    • Automata Theory & Formal Languages → Turing, Chomsky
    • Cybernetics & Systems Theory → Wiener, Ashby, von Neumann
    • Game Theory & Decision Theory → Nash, von Neumann, Kahneman
  • Computational Science
    • Algorithms & Computational Complexity → Turing, Cook
    • Artificial Intelligence & Neural Networks → Hinton, LeCun, Russell
    • Deep Learning & Reinforcement Learning → Goodfellow, Sutton
    • Robotics & Cognitive Systems → Brooks, Minsky, Dreyfus

Learn the ability to abstract, model, and simulate anything.

Natural Sciences

Understanding the physical universe

  • [[Physics]] -> Rules of reality, Understand the physical fabric of reality at every scale.
    • Classical Mechanics → Newton, Lagrange
    • Electromagnetism → Maxwell
    • Thermodynamics & Statistical Mechanics → Boltzmann, Gibbs
    • Relativity (Space & Time) → Einstein
    • Quantum Mechanics → Schrödinger, Heisenberg, Dirac
    • Quantum Field Theory & Particle Physics → Feynman, Weinberg
    • [[Cosmology]] & Astrophysics → Hawking, Penrose
    • Theoretical Frontiers → String Theory, Loop Quantum Gravity
  • Chemistry -> Structure of Matter, Understand how matter organizes into complex, life-supporting systems.
  • [[Biology]] -> Science of Life, universe learning to self-organize. Understand the principles of emergence, adaptation, and intelligence.
    • [ ] Virology
    • Evolution & Natural Selection → Darwin, Wallace
    • Genetics & Molecular Biology → Mendel, Watson & Crick
    • Neuroscience & Consciousness → Hebb, Edelman, Friston
    • Ecology & Systems Biology

Study of Intelligence

  • [[Psychology]] & Cognitive Science
    • Emotions & Rationality → Damasio, Lazarus
    • Decision Theory → Simon, Gigerenzer
    • Neuroeconomics & Motivation → Phelps, Loewenstein
    • Social Psychology → Milgram, Asch
  • Perception & Sensation → Helmholtz, Marr
  • Artificial Intelligence & Machine Learning → Hinton, LeCun, Schmidhuber
  • Brain & Cognition → Hebb, Sporns
  • Neural Networks & Synaptic Plasticity → Hebb, Luria
  • Learning Algorithms (Biological & Artificial) → Rescorla, Sutherland
  • Consciousness Studies → Dennett, Chalmers, Koch
  • Embodied Cognition → Clark, Varela
  • AGI Foundations → Goertzel, Yudkowsky

Social Sciences

Understanding human systems -> To shape the future, you must understand how people think, behave, and organize—this is crucial for ethical decisions and civilization-building.

  • Human History
    • [[Civilizations]]
  • Anthropology
  • Sociology
  • Sociology of Knowledge → Mannheim, Foucault
  • Complexity of Social Systems → Castells, Luhmann
  • [[Lifestyle]]

how collective intelligence and civilization evolve.