notes-someStuffYouMightLikeToKnow-someStuffYouMightLikeToKnow

history

This book doesn't include history. For a similar set of notes summarizing 'stuff about history that you might like to know', please see [1].

summarize

http://www.waitbutwhy.com/2013/08/putting-time-in-perspective.html

and

http://www.hyperhistory.com/online_n2/History_n2/a.html

and a history of ideas

futurology

demographics

economics

sigmoids

tech: things take longer than you think, but other things you didn't think of pop up (find that quote)

what else? i dont know much futurology

todo

https://en.wikipedia.org/wiki/Structuralism_%28philosophy_of_science%29

the ubiquity of power laws

99% of web pages are junk but that's okay b/c you can choose which ones to look at

https://en.wikipedia.org/wiki/Threshold_knowledge

https://en.wikipedia.org/wiki/A_Guide_for_the_Perplexed#Critique_of_materialistic_scientism

" The sort of mental processes described as cognitive are largely influenced by research which has successfully used this paradigm in the past, likely starting with Thomas Aquinas, who divided the study of behavior into two broad categories: cognitive (how we know the world), and affective (how we understand the world via feelings and emotions)[disputed – discuss].[citation needed] Consequently, this description tends to apply to processes such as memory, association, concept formation, pattern recognition, language, attention, perception, action, problem solving and mental imagery.[14][15] Traditionally, emotion was not thought of as a cognitive process. This division is now regarded as largely artificial, and much research is currently being undertaken to examine the cognitive psychology of emotion; research also includes one's awareness of one's own strategies and methods of cognition called metacognition and includes metamemory. " -- https://en.wikipedia.org/wiki/Cognition

topics:

intro to calculus (no integration methods i.e. partial integration)

div, grad, curl with "intuitive" pictorial pseudo-proofs

a condensation of some physics mechanics: start from noether's law EM: derive maxwell's eqs from experimental laws relativity: use the triangle derivation

LTI systems (convolution etc)

linear algebra (from a modern algebra pov)

some algebraic logic

formal logic, godel

backprop

finding maxima and minima with derivatives

mean, variance, estimators, bias, variance of estimators

Taylor series

NP-completeness

the artifice of real numbers (instead of integers), and continuity the artifice of imaginary numbers, and euler's EQ

category theory (once i learn it)

set theory, infinite ordinals and cardinals, surreal numbers

game theory

(diff

algebraic) (geometrytopology)

?: other VP-ish stuff? e.g. chu spaces?

scaling laws

wave equations

helmholtz's theorem

modern algebra

some analysis

compound interest, some diff eqs

entropy, information, mutual information, KL divergence

pictures of even simple things like linearity, distributivity, monotonicity, etc

https://medium.com/@yegg/mental-models-i-find-repeatedly-useful-936f1cc405d#.2ilhcl20n

the link has his one-sentence defn of each of these but i thought it would probably be better to come back and write my own defn and then compare to his, so i deleted them

" Notes

    Most of the mental models on this list are here because they are useful outside of their specific discipline. For example, use of the mental model “peak oil” isn’t restricted to an energy context. Most references to “peak x” are an invocation of this model. Similarly, inflation as a concept applies outside of economics, e.g. grade inflation and expectations inflation.
    I roughly grouped the mental models by discipline, but as noted, this grouping is not to be taken as an assertion that they only apply within that dicipline. The best ideas often arise when going cross-dicipline.
    The numbers next to each mental model reflect the frequency with which they come up:
    (1) — Frequently (61 models)
    (2) — Occasionally (41 models)
    (3) — Rarely, though still repeatedly (84 models)
    If studying new models, I’d start with the lower numbers first. The quotes next to each concept are meant to be a basic definition to remind you what it is, and not a teaching tool. Follow the link to learn more.
    I am not endorsing any of these concepts as normatively good; I’m just saying they have repeatedly helped me explain and navigate the world.
    I wish I had learned many of these years earlier. In fact, the proximate cause for posting this was so I could more effectively answer the question I frequently get from people I work with: “what should I learn next?” If you’re trying to be generally effective, my best advice is to start with the the things on this list.

Explaining

Modeling

Brainstorming

Experimenting

Interpreting

Deciding

Reasoning

For a longer list, see Thou shall not commit logical fallacies (I have this poster on my office door.)

Negotiating

Mitigating

Managing

Developing

Business

Influencing

Marketing

Competing

Strategizing

Military

Market Failure

Political Failure

Investing

Learning

Productivity

Nature

Philosophy

Internet

https://en.m.wikipedia.org/wiki/Joy%27s_law_(management)

some others from the HN discussion:

"

A big one, that helps me immensely, is that when I need to do a big/risky/complex task, is to imagine myself doing with with sped up time. Instantly creates an outline and list of tools that one will need. "

"

Lordarminius 1 hour ago

I would add to the list 'revealed preference'

'... an economic theory of consumption behavior which asserts that the best way to measure consumer preferences is to observe their purchasing behavior. Revealed preference theory works on the assumption that consumers have considered a set of alternatives before making a purchasing decision. Thus, given that a consumer chooses one option out of the set, this option must be the preferred option' http://www.investopedia.com/terms/r/revealed-preference.asp

In other words "observe their actions, not their words"

source99 14 hours ago

A technique I often use to test a theory is to change the inputs to be the maximum and minimum possible values and see if the model still holds true. I've found it to be incredibly useful in a few specific situations.

reply

taneq 14 hours ago

Or more generally, look for critical points in the model and see if it still holds. Max/min values (or odd combinations of max/min for different variables) are good candidates, as are zeroes, and anything which makes part of an equation go to zero.

reply

" Knight (1921) introduced an important distinction between risk and uncertainty. Risk is when there are multiple possible future states and the probabilities of those different future states occurring are known. Risk is well described by the laws of probability and statistics. Knightian uncertainty occurs when the probabilities of future states, or even the nature of possible future states is not known. " [2]

---

https://en.wikipedia.org/wiki/Triple_modular_redundancy

---

https://en.wikipedia.org/wiki/Wikipedia:Vital_articles

CategoryBookDraft

BayleShanks RecentChanges Bayle Shanks's website
Comments on notes-someStuffYouMightLikeToKnow-someStuffYouMightLikeToKnow This page is read-only View other revisions Administration
Last edited 2021-06-29 04:50 UTC by BayleShanks (diff)