19-01-27 Modes of Thinking worth Internalizing

Category: Idea Lists (Upon Request)

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1. Latticework of Mental Models

1. Ex., pushing How to Think into intuition
2. Systematizing Creativity
   1. Ex., Reframing, Questioning Assumptions, Abstraction & Generalization, Decomposition, Composition / Recombination, Generators, Leading Questions, etc.
3. Filter at the Intersection of Competing Worldviews
   1. Ex., Worldview Building
   2. Ex., Internalizing the conceptual style of intellectual giants
4. Intelligence Decomposition & Optimization Along All Axes
   1. Memory (Working, Episodic, Long Term)
   2. Attention (though this feels like a limitation)
   3. Having a model
   4. Abstract Knowledge Representation
   5. Ability to Generalize
   6. Learning / Adaptivity
   7. Creativity
   8. Information processing / Computation speed
   9. Goal accomplishment (ugh)
   10. Generality (over environments, tasks, representations)
5. Technical Consilience (Seeing the unity of knowledge behind every natural science) by internalizing:
   1. Information Theory (Cover / Thomas)
   2. Statistical Mechanics (Talman)
   3. Algorithmic Game Theory (Nisan)
   4. Nonlinear Dynamics and Chaos (Strogatz)
   5. Seven Sketches in Compositionality (Spivak)
   6. Mechanism Design (Borgers)
   7. Algorithms (CLRS)
   8. Neuroscience (Principles of Neural Science)
   9. Electromagnetics (Haliday / Resnick)
   10. Quantum Mechanics (Griffiths)
   11. Nuclear Physics (Krane)
   12. Chemistry (Brown)
   13. Intro Proof (How to Prove It)
   14. Analysis (Abbott)
   15. Set Theory (Halmus)
   16. Abstract Algebra (Dummit, Foote)
   17. Topology (Munkres)
   18. Category Theory (Pierce, then Awodey)
   19. Probability Theory: The Logic of Science (Jaynes)
   20. Machine Learning: A Probabilistic Perspective
   21. Computational Learning Theory (Kearns)
   22. Learning Invariant Representations (Poggio)
   23. Causality (Pearl)
   24. Computability and Logic (Boolos)
6. Thinking and Deciding (Baron)
   1. Types of thinking
   2. On the Study of thinking (meta)
   3. Rationality
   4. Logic
   5. Normative Theory of Probability
   6. Descriptive theory of probability judgment
   7. Hypothesis Testing
   8. Judgment of correlation and contingency
   9. Actively open-minded thinking
   10. Normative theory of choice under uncertainty
   11. Descriptive theory of choice under uncertainty
   12. Choice under certainty
   13. Utility Measurement
   14. Decision Analysis and Values
   15. Quantitative Judgment
   16. Moral judgment and choice
   17. Fairness and Justice
   18. Social Dilemmas: Cooperation vs. Defection
   19. Decisions about the future
   20. Risk
7. Path to Awakening / Enlightenment, ex. the intersection of:
   1. Shinzen Young’s The Science of Enlightenment
   2. Calduasa’s The Mind Illuminated
   3. Chapman’s Meaningness
   4. Wallis’s Trantra Illuminated
   5. Ingram’s Mastering the Core Teachings of the Buddha
8. Discover and internalize lost philosophical traditions
   1. Ex., Al Gazali, Mohisim, Presocratics
9. Rationalism (May be too similar to Thinking and Deciding…)
   1. As framed in SSC / LW / Sequences / HPMOR / Inadequate Equilibria
10. Turn machine learning into a fully fledged philosophy around how to think (May be a subset of technical concilience…)
11. Bias-Variance Tradeoff
    1. Overfitting
    2. Controlling complexity
       1. Model simplicity (restriction methods)
       2. Selection methods (over features)
       3. Regularization
12. Curse of dimensionality
13. Ensemble Modeling
14. Occam’s Razor (Formalized)
15. Training vs. Generalization Error
16. Interpolation vs. Extrapolation
17. Smoothness
18. VC Dimension
19. Variance Maximization
    1. Optimizing for Volatility vs Expected Value
20. Bayes Rule
21. Bayes Error
22. Exploration-Exploitation
23. Manifolds as Data Representation

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