recentpopularlog in

nhaliday : better-explained   55

Why books don’t work | Andy Matuschak
https://www.spreaker.com/user/10197011/designing-and-developing-new-tools-for-t
https://twitter.com/andy_matuschak/status/1190675776036687878
https://archive.is/hNIFG
https://archive.is/f9Bwh
hmm: "zettelkasten like note systems have you do a linear search for connections, that gets exponentially more expensive as your note body grows",
https://twitter.com/Meaningness/status/1210309788141117440
https://archive.is/P6PH2
https://archive.is/uD9ls
https://archive.is/Sb9Jq

https://twitter.com/Scholars_Stage/status/1199702832728948737
https://archive.is/cc4zf
I reviewed today my catalogue of 420~ books I have read over the last six years and I am in despair. There are probably 100~ whose contents I can tell you almost nothing about—nothing noteworthy anyway.
techtariat  worrydream  learning  education  teaching  higher-ed  neurons  thinking  rhetoric  essay  michael-nielsen  retention  better-explained  bounded-cognition  info-dynamics  info-foraging  books  communication  lectures  contrarianism  academia  scholar  design  meta:reading  studying  form-design  writing  technical-writing  skunkworks  multi  broad-econ  wonkish  unaffiliated  twitter  social  discussion  backup  reflection  metameta  podcast  audio  interview  impetus  space  open-problems  questions  tech  hard-tech  startups  commentary  postrat  europe  germanic  notetaking  graphs  network-structure  similarity  intersection-connectedness  magnitude  cost-benefit  multiplicative 
may 2019 by nhaliday
Sequence Modeling with CTC
A visual guide to Connectionist Temporal Classification, an algorithm used to train deep neural networks in speech recognition, handwriting recognition and other sequence problems.
acmtariat  techtariat  org:bleg  nibble  better-explained  machine-learning  deep-learning  visual-understanding  visualization  analysis  let-me-see  research  sequential  audio  classification  model-class  exposition  language  acm  approximation  comparison  markov  iteration-recursion  concept  atoms  distribution  orders  DP  heuristic  optimization  trees  greedy  matching  gradient-descent  org:popup 
december 2017 by nhaliday
Cultural group selection plays an essential role in explaining human cooperation: A sketch of the evidence
Pursuing Darwin’s curious parallel: Prospects for a science of cultural evolution: http://www.pnas.org/content/early/2017/07/18/1620741114.full

Axelrod model: http://ncase.me/trust/

Peer punishment promotes enforcement of bad social norms: https://www.nature.com/articles/s41467-017-00731-0
Social norms are an important element in explaining how humans achieve very high levels of cooperative activity. It is widely observed that, when norms can be enforced by peer punishment, groups are able to resolve social dilemmas in prosocial, cooperative ways. Here we show that punishment can also encourage participation in destructive behaviours that are harmful to group welfare, and that this phenomenon is mediated by a social norm. In a variation of a public goods game, in which the return to investment is negative for both group and individual, we find that the opportunity to punish led to higher levels of contribution, thereby harming collective payoffs. A second experiment confirmed that, independently of whether punishment is available, a majority of subjects regard the efficient behaviour of non-contribution as socially inappropriate. The results show that simply providing a punishment opportunity does not guarantee that punishment will be used for socially beneficial ends, because the social norms that influence punishment behaviour may themselves be destructive.

https://twitter.com/Peter_Turchin/status/911886386051108864
Peer punishment can stabilize anything, both good and bad norms. This is why you need group selection to select good social norms.
pdf  study  article  survey  sociology  anthropology  sapiens  cultural-dynamics  🌞  cooperate-defect  GT-101  EGT  deep-materialism  group-selection  coordination  religion  theos  social-norms  morality  coalitions  s:**  turchin  decision-making  microfoundations  multi  better-explained  techtariat  visualization  dynamic  worrydream  simulation  operational  let-me-see  trust  garett-jones  polarization  media  internet  zero-positive-sum  axelrod  eden  honor  org:nat  unintended-consequences  public-goodish  broad-econ  twitter  social  commentary  summary  slippery-slope  selection  competition  organizing  war  henrich  evolution  darwinian  tribalism  hari-seldon  cybernetics  reinforcement  ecology  sociality 
june 2017 by nhaliday
Principal Component Analysis explained visually
The PCA transformation ensures that the horizontal axis PC1 has the most variation, the vertical axis PC2 the second-most, and a third axis PC3 the least.

I think this is equivalent to variational characterization of singular values?
data-science  explanation  visual-understanding  visualization  techtariat  stats  methodology  exploratory  large-factor  better-explained  let-me-see  matrix-factorization 
january 2017 by nhaliday
soft question - Thinking and Explaining - MathOverflow
- good question from Bill Thurston
- great answers by Terry Tao, fedja, Minhyong Kim, gowers, etc.

Terry Tao:
- symmetry as blurring/vibrating/wobbling, scale invariance
- anthropomorphization, adversarial perspective for estimates/inequalities/quantifiers, spending/economy

fedja walks through his though-process from another answer

Minhyong Kim: anthropology of mathematical philosophizing

Per Vognsen: normality as isotropy
comment: conjugate subgroup gHg^-1 ~ "H but somewhere else in G"

gowers: hidden things in basic mathematics/arithmetic
comment by Ryan Budney: x sin(x) via x -> (x, sin(x)), (x, y) -> xy
I kinda get what he's talking about but needed to use Mathematica to get the initial visualization down.
To remind myself later:
- xy can be easily visualized by juxtaposing the two parabolae x^2 and -x^2 diagonally
- x sin(x) can be visualized along that surface by moving your finger along the line (x, 0) but adding some oscillations in y direction according to sin(x)
q-n-a  soft-question  big-list  intuition  communication  teaching  math  thinking  writing  thurston  lens  overflow  synthesis  hi-order-bits  👳  insight  meta:math  clarity  nibble  giants  cartoons  gowers  mathtariat  better-explained  stories  the-trenches  problem-solving  homogeneity  symmetry  fedja  examples  philosophy  big-picture  vague  isotropy  reflection  spatial  ground-up  visual-understanding  polynomials  dimensionality  math.GR  worrydream  scholar  🎓  neurons  metabuch  yoga  retrofit  mental-math  metameta  wisdom  wordlessness  oscillation  operational  adversarial  quantifiers-sums  exposition  explanation  tricki  concrete  s:***  manifolds  invariance  dynamical  info-dynamics  cool  direction  elegance  heavyweights  analysis  guessing  grokkability-clarity  technical-writing 
january 2017 by nhaliday
Learn Difficult Concepts with the ADEPT Method – BetterExplained
Make explanations ADEPT: Use an Analogy, Diagram, Example, Plain-English description, and then a Technical description.
thinking  education  learning  teaching  tutoring  better-explained  analogy  visual-understanding  examples 
july 2016 by nhaliday

Copy this bookmark:





to read