Incoming links and notes

Notes

I need to reclassify the bio computing links; that section has become confusing and there are too many nice ideas there not clearly distinguished.

“The problem with Bernoulli regression is that binary outcomes just aren’t very informative.” one of my colleagues said to me. Now I have decided that there is some meat on this bone. TODO: revisit the informativeness of categories about their covariates in the post-Imagenet era, from a classic vector quantisation perspective. Deep learning classifiers as a model for legibility.

To post to team chat

• Why proplot?
• ICML 2022 Tutorial on causality and deep learning
• Symmetry and Physics | Not Even Wrong
• Max Hodak - Avoid little leagues
• Lovecraftian intelligence - by Noah Smith - Noahpinion

To put in feed reader

None rn.

Links

• Cutthroat capitalism vs. cuddly capitalism - by Noah Smith

• Start Here: Commoncog's Best Posts - Commoncog

• Reduce Noise, Not Cognitive Biases - Commoncog

• How To Reduce Decision Noise - Commoncog

• 24: Monasteries - Monomythical

• Against Waldenponding

• Living systems grow from simple seeds - by Gordon Brander

• Via productiva - by Jan Hendrik Kirchner

• Subconscious | Gordon Brander

• How independent writers are turning to AI

• rhizome r&d | Kasey Klimes

• Markets Underinvest In Vitality - by Oshan Jarow

• Why Every Main Street Looks The Same - by Coby Lefkowitz

• A Call To Build A Better World - by Coby Lefkowitz

• How I Attained Persistent Self-Love, or, I Demand Deep Okayness For Everyone

• The Esoteric Benefits of School - by Judah - Be Wrong

• A Speech I would Like To Give Undergrads - by Judah

• Form is Fake - by Judah - Be Wrong

• Experimental History | Adam Mastroianni

• You'll forget most of what you learn. What should you do about that?

• The Five Tools of Hedonic Design - by Adam Mastroianni

• Good conversations have lots of doorknobs

• Psychology might be a big stinkin’ load of hogwash and that’s just fine

• Overfitting In Academia - by Maxwell Tabarrok

• Most advice is pretty bad - by Sam Atis - Samstack

• More notes on ADHD - by Sam Atis - Samstack

• GitHub - google/evojax

• The problem with raging against the machine is that the machine has learned to feed off rage

  Liv Bouree see also

• Toy Models of Superposition

• Zuckerman, Tips to article writers

• Ethics Explainer: The principle of charity

• How Affirmative Action Was Derailed by Diversity

• How to Copy a Song: A Handy Primer

• Long-term Dynamics of Fairness Intervention in Connection Recommender Systems

• Modulo | Secular Homeschooling Made Easy

• My family’s unlikely homeschooling journey

• Perfectionism

• PhD workflow

• Reject the Rules of the Social Media Game

• Spark the Mood You Want | Create a positive mental association | ClearerThinking.org

• Spirals of Delusion: How AI Distorts Decision-Making and Makes Dictators More Dangerous (not convinced tbh)

• The Carpentries Toolkit of IDEAS | Zenodo

• The Good Research Code Handbook — Good research code

• The gossip trap - by Erik Hoel

• The Rules of Civil Conversation

• The Sordid Saga of Hunter Biden’s Laptop.

• Tutorial on using LLVM to JIT PyTorch fx graphs to native code (x86/arm/risc-v/wasm) (Part I – Scalars) | Terra Incognita

• Toolfinder - Earth Defenders Toolkit

• Keet by Holepunch

  Keet only shares end-to-end encrypted data between participants in your calls. Without middlemen, third-parties, or servers, there’s nobody left who can snoop or leak data.

• Telios: Decentralized and Secure Email Communication Service

• Socket Supply Co.

  Transition away from expensive and complex cloud services to a rent-free P2P web! Request access for P2P features on our serverless, files, and data apps.

• datdot.org/

  DatDot team is building an autonomous hosting network for p2p data systems. Think of it as a Filecoin but for Hypercore protocol, built with Substrate.

• Ambigrams

• Satisficing vs Maximizing – @ASmartBear

• Spotting a toxic culture in tech - Tech Leading Ladies

• Creating an Autistic-Friendly Workplace · Public Neurodiversity Support Center

• Paint With Music — Google Arts & Culture

• AO3’s 15-year journey from blog post to fanfiction powerhouse - The Verge

• F1000Research | Open Access Publishing Platform | Beyond a Research Journal

• The Developer Certificate of Origin is a great alternative to a CLA

• pyribs

• 5 flavours of racism disambiguated

• Scaling Factors for Hidden Markov Models

• Should Effective Altruists Join the GOP?

• Sustainable building: The hottest new material is, uh, wood

• roboticcam/machine-learning-notes: My continuously updated Machine Learning, Probabilistic Models and Deep Learning notes and demos (2000+ slides) 我不间断更新的机器学习，概率模型和深度学习的讲义(2000+页)和视频链接

• Research Careers Tool | The University of Edinburgh

• The Social Capital Atlas

• Panel 3: Mathematical sciences to address societal challenges and issues

• Statistical Physics of Inference and Bayesian Estimation

• TPU Research Cloud - About

• wesselb/varz: Painless optimisation of constrained variables in AutoGrad, TensorFlow, PyTorch, and JAX

• Laplace’s Demon: A Seminar Series about Bayesian Machine Learning at Scale - Criteo AI Lab

• I. Risk Management Foundations - Machine Learning for Financial Risk Management with Python [Book]

• jkbren/einet: Uncertainty and causal emergence in complex networks

• Inform: A C library for information analysis of complex systems

• [2110.05038] Recurrent Model-Free RL Can Be a Strong Baseline for Many POMDPs

• [2110.14759] Regularized Frank-Wolfe for Dense CRFs: Generalizing Mean Field and Beyond

• [2112.12524] Emulation of greenhouse-gas sensitivities using variational autoencoders

• [2206.13637] Utility Theory for Sequential Decision Making

• [2207.06544] Volatility Based Kernels and Moving Average Means for Accurate Forecasting with Gaussian Processes

• Generalizing projections to Mahalanobis-type metrics | Mathematical Odds & Ends

• Weighted Least Squares

• Concurrent programming, with examples

• Democratizing the hardware side of large language models seems to be an advertisement for some new hardware, but there is interesting background in there.

• Darren Wilkinson’s Bayesian inference for a logistic regression model 1, 2, 3, 4, 5

• https://www.patreon.com/posts/taylor-modeling-70131808

• All Minus One an Australian ❄️🍑 club.

• Against Facebook

• When Giving People Money Doesn’t Help - by Zvi Mowshowitz. Troubling, needs follow-up.

• Computational Research Platform on Code Ocean

• nalgebra linear-algebra library | nalgebra

• Visual WYSIWYG versus functional or causal WYSIWYG

• Making Light

• Home | Absci

• Xyla

• Your Book Review: Public Choice Theory And The Illusion Of Grand Strategy

• Douglas Murray’s War on the West—A Review

• Jeff Maurer, It’s Always the Adults’ Fault

• Stephen Malina — Deriving the front-door criterion with the do-calculus

• DIY Collective Embeds Abortion Pill Onto Business Cards, Distributes Them At Hacker Conference

• The dangerous side of Munchausen’s - UnHerd

• Climate-Smart Mining: Minerals for Climate Action

• Understand how other people think: a theory of worldviews – Spencer Greenberg

• There Won’t Be a “Civil War”... - by Rachel Kleinfeld

• Cat and Girl on Distraction

• The Ising model in our dimension and our times

• Your Daily AI Research tl;dr

• https://downforeveryoneorjustme.com/

• Census tool which links all the weird different data storage systems and CRM stuff

• Michael Lewis podcast on illegible experts

• Hot money on complicated porn rules

• The Political Is Personal

• International Joint Conference on Neural Networks 2023

• Anonymous GitHub

• Chalk is a non-terrible calculator for macos, incorporating useful things like matrices and bitwise ops

• NeurIPS Conference: Historical Data Analysis | by Nemanja Rakicevic

• M Bronstein’s ICLR 2021 Keynote, Geometric Deep Learning: The Erlangen Programme of ML

• Communications' digital initiative and its first digital event

• flatmax/vector-synth: Old 2002 era vector synth code based on XFig

• Yanir Seroussi, The mission matters: Moving to climate tech as a data scientist

• PJ Vogt, Selling Drugs to Buy Crypto

• #1: In-group Cheems - by Keir Bradwell

• I Should Be Able to Mute America

• AAAI2022: Presidential Address: The State of AI

• Transactions on Machine Learning Research

• Emulation

• The Big Data Paradox in Clinical Practice

• Ax · Adaptive Experimentation Platform

• Why open science is primarily a labour issue - Samuel Moore

• EA Projects I’d Like to See | Fin Moorhouse

• Against All Applications - by Adam Mastroianni

• Have The Effective Altruists And Rationalists Brainwashed Me?

• Reading the news is the new smoking - by Adam Mastroianni

• Predicting Generalization using GANs

• The War for Eyeballs - by Anthony Lee Zhang

• Field Guide to the Curve Wars: DeFi’s Fight for Liquidity - Almanack - Every

• Homunculi and Moral Demandingness – Good Optics

• The text-to-image revolution, explained

• Digital artists’ post-bubble hopes for NFTs don’t need a blockchain

• Michelle Phan, Dan Howell, and why YouTubers never log off

• Curious About Everything | Jodi Ettenberg

• Making Deep Learning go Brrrr From First Principles

• Algorithms for Modern Hardware - Algorithmica

• Generative Flow Networks - Yoshua Bengio

• Flow Network based Generative Models for Non-Iterative Diverse Candidate Generation

• GFlowNet Tutorial

• https://melbourne.nerdnite.com/

• hckr news - Hacker News sorted by time

• ReproducibilityChecklist

• Execute Shell loop in parallel, but only N workers

• Playable Half Earth Socialism simulator

• Quasi-likelihood analysis and its applications | SpringerLink

• Cautionary Tales from Cryptoland

• I Do Not Think It Means What You Think It Means: Artificial Intelligence, Cognitive Work & Scale

• Smart technologies | Internet Policy Review

• When to Stop Exploring | The explore-exploit trade-off

• Equations of Motion from a Time Series

• Path Integrals and Feynman Diagrams for Classical Stochastic Processes

• Inference for Stochastic Differential Equations

• Modern Computational Methods for Bayesian Inference — A Reading List | George Ho is a good curation of modern Bayes methods posts. The next links come from there

• will wolf on neural methods in SBI

• will wolf, Deriving Expectation-Maximization

• will wolf, Deriving Mean-Field Variational Bayes

• Reality Is Just a Game Now

• Reformation in the Church of Science

• Why Your Understanding of Collectivism Is Probably Wrong

• ClearerThinking.org’s courses, e.g.

  • Introduction to Decision Academy: The Science of Better Decisions
  • Rhetorical Fallacies: Dodging Argument Traps
  • Learning from Mistakes: A Systematic Approach
  • Probabilistic Fallacies: Gauging the Strength of Evidence
  • Explanation Freeze: Interpreting Uncertain Events
  • Aspire: A Tool to Help You Improve Your Life
  • The Sunk Cost Fallacy: Focusing on the Future

• A good volunteer is hard to find - The GiveWell Blog

• How To Win Public Opinion, The VC Method

• My2050 calculator - create your pathway for the UK to be net zero by 2050

• Museum of Imaginary Musical Instruments

• Software is no longer sold; it’s adopted - Orbit

• Is Pandemic Stress to Blame for the Rise in Traffic Deaths? Nope apparently it is decreased congestion making drivers drive faster on shit roads.

• Preference falsification

• Let us never speak of these values again.

• Review of Joseph Heath, Enlightenment 2.0 on Habermas+Kahnemann ideas in the public sphere.

• Arturia — Efx FRAGMENTS

• It’s Your Friends Who Break Your Heart

• Agenty Duck: Intro To Naturalism Sequence

  Is naturalism nonparametric learning for mind-as-ML?

• Nick Chater, Would you Stand Up to An Oppressive Regime.

• Reddit for AI-generated and manipulated content

• Bayesian Neural Nets and how to effectively train them with Stochastic Gradient Markov Chain Monte Carlo | Simen Eide

• Lecture #8 - My Method for Defeating Procrastination

• Everything I wrote before now was overconfident

• Brutalita Sans >Brutalita is an experimental font and editor, edit in your browser and download the font.

• Social Desirability Bias: How Psych Can Salvage Econo-Cynicism (File under dunning-kruger theory of society, and survey analysis)

• OK, WTF Are Wordcels and Shape Rotators?

• That broken tech/content culture cycle

  I’m not there for 100% of this story about youtube/instagram/facebook/amazon/etc, but I will back a chunk of it. Also: compare to TikTok.

• Evidence of Fraud in an Influential Field Experiment About Dishonesty. Looks bad for Dan Ariely. Damn.

• on programming humans (Amir’s work)

• Crypto, NFTs, Web3: People Hate the Future of the Internet

• Apple acquires song-shifting startup AI Music, here’s what it could mean for users

• Are coevolutionary “Free Lunches” really free lunches?

• Autonomous Work Pod

• Butterfly Ideas

• TODOs from Paper Systems

• Tumblr Is Everything

• Michele Coscia, Pearson Correlations for Networks

• Penny Wyatt, Developer Innovation and the Free Puppy

• Elizabeth Van Nostrand, A Quick Look At 20% Time

• Oleksandr Nikitin is working on The Cortex, their Ultimate Productivity App Thing

• OSF | Protocol and plan for the development of the automated algorithm for choosing the best systematic review

• scottshambaugh/monaco: Quantify uncertainty and sensitivities in your computer models with an industry-grade Monte-Carlo framework

• Algorithmic monoculture and social welfare

• In Defence of the Boring Web

• DRMacIver’s Notebook: Norms of Excellence

• Silicon Valley’s New Obsession: Science Funding

• Marisa Abrajano has a provoking list of research topics. I would like to read the work to see her methodology.

• Busy Simulator

• Do normal people need to know or care about “the metaverse”?

• doing - BrettTerpstra.com

• Why Americans Are Dying from Despair

• External Music Services - ListenBrainz

• The DAIR Institute “The Distributed AI Research Institute is a space for independent, community-rooted AI research, free from Big Tech’s pervasive influence.”

• Dongkong track breakdown

• Hapgood | Mike Caulfield’s latest web incarnation. Networked Learning, Open Education, and Online Digital Literacy

• Dyscalculia

• Stream Jonathan Richetti music

• Machine Learning Trick of the Day (1): Replica Trick— Shakir Mohammed

• Machine Learning Trick of the Day (3): Hutchinson’s Trick— Shakir Mohammed

• Machine Learning Trick of the Day (7): Density Ratio Trick— Shakir Mohammed

• Chip in pressure HSBC to cut off Adani

• vscode-paste-image/README.md at master · mushanshitiancai/vscode-paste-image

• Gensim: Topic modelling for humans

• mhoye/awesome-falsehood: 😱 Falsehoods Programmers Believe in

• 10 years of… whatever this has been - apenwarr

• The Paradox of Choice in Computing-Research Conferences | November 2021

• ApplyingML - Papers, Guides, and Interviews with ML practitioners

• The War Nerd: Taiwan — The Thucydides Trapper Who Cried Woof - By Gary Brecher

• Learning About the Long Run

• Dive in

• Penzil — 3d sketching for the web

• Milan Cvitkovic — Things you are allowed to do

• 1DollarScan - FAQ

• Random-Feature Matching

• Information loss and entropy

• Why Facebook won’t let you turn off its news feed algorithm

• Useful inequalities cheat sheet

• [2111.00110] FC2T2: The Fast Continuous Convolutional Taylor Transform with Applications in Vision and Graphics

• The local minima of suckiness · Vicki Boykis

• Brave Wallet | Brave Browser

• The Art of Documentation – Chelsea Troy

• We were the unpaid janitors of a bloated tech monopoly - by Ryan Broderick - Garbage Day

• Mark Zuckerberg Is TNR’s 2021 Scoundrel of the Year

• A Perfect Storm: The Chocolate, Coffee, and Climate Crises

• How to incorporate observation weights into an estimator

• The Iraqi who saved Norway from oil

• Convex hull of zeros

• How should we compare neural network representations? – The Berkeley Artificial Intelligence Research Blog

• Marden’s theorem on complex roots

• Lambda School’s Job Placement Rate May Be Far Worse Than Advertised

• A fulsome aquifer swells imperfectly over the little songs of the mutilated. | Little Songs Of The Mutilated

• AI research: the unreasonably narrow path and how not to be miserable

• Pocket Science Lab

• Rumble in the Ensemble

• SimSWE 4: Wants, needs, and chasm-crossing - apenwarr

• Willingness to look stupid

• I would like to read the diaries of Usama ibn Munqidh

• The latest target of China’s tech regulation blitz: algorithms

• Spot The Outlier - by Rohit - Strange Loop Canon

• The Anxious Philosopher King

• The two sides of envy at work

• Facebook Is an Authoritarian State

• microsoft/hummingbird: Hummingbird compiles trained ML models into tensor computation for faster inference.

• Maxwell’s Relations (Part 1) | Azimuth

• Nelson’s Weblog: culture / generative-art-and-open-source

• The Analytical Edge

• Weekly Research — Verdad

• Sinkhorn and circular law

• Deleting unethical data sets isn’t good enough

• Jag Bhalla, Vaccine Greed: Capitalism Without Competition Isn’t Capitalism, It’s Exploitation

• Kostas Kiriakakis, A Day At The Park

• Nietzsche Faces the Modern Age

• ARiMA is not Sufficient

• AttentionFlow

• fastdownload: the magic behind one of the famous 4 lines of code · fast.ai

• Steven Buss, Politics for Software Engineers, Part 1, Part 3

• A from-scratch tour of Bitcoin in Python

• State Power and the Power Law, State Power and the Power Law 2

• Hosting SQLite databases on Github Pages - (or any static file hoster)

• Interview Questions Database (IQDb)

• DSHR’s Blog: The Data Isn’t Yours

• The Economics of Pseudonymity

• Reciprocal Convexity to reverse the Jensen Inequality - B.log

• Schneier, When AIs Start Hacking

• Conceptual Foundations of Statistical Learning, Spring 2021

• Big Tech’s guide to talking about AI ethics

• lab-ml/nn: 🧠 Implementations/tutorials of deep learning papers with side-by-side notes; including transformers (original, xl, switch, feedback), optimizers(adam, radam, adabelief), gans(dcgan, cyclegan), reinforcement learning (ppo, dqn), capsnet, sketch-rnn, etc.

• labml.ai Neural Networks

• Blackwell Approachability - Que-sais je?

• analysis - Metrizability of weak convergence by the bounded Lipschitz metric - Mathematics Stack Exchange

• What Is a Companion Matrix? – Nick Higham

• Multimodal Neurons in Artificial Neural Networks/ Distill version of Multimodal Neurons in Artificial Neural Networks

• https://cbergmeir.com/

• http://i.giwebb.com/

• Going beyond least-squares – II : Self-concordant analysis for logistic regression – Machine Learning Research Blog

• On “Geek” Versus “Nerd”

• How to Become the Best in the World at Something

• Why a Universal Society Is Unattainable is a rebadged and refreshed version of the “societies need common enemies” trope.

• The Computational Geometry Algorithms Library

• Yuling Yao, The likelihood principle in model check and model evaluation

• Algorithms for Decision Making: Decision making, in the sense of reinforcement learning

• Chowdhury-DSP/ChowMatrix: Matrix delay effect

• Chowdhury DSP is creating audio software

• “Understanding RL Vision”

• Algorithmic Trap

• On the origin of psychological research practices, with special regard to self-reported nostril width

• Liquid Information Flow Control, a confidential computing DSL

• The Cauchy residue trick: spectral analysis made “easy”

• On the Generalization Ability of Online Strongly Convex Programming Algorithms

Thomas Lumley visualises data pooling simply and well.

The Catalogue of Bias:

To obtain the least biased information, researchers must acknowledge the potential presence of biases and take steps to avoid and minimise their effects. Equally, in assessing the results of studies, we must be aware of the different types of biases, their potential impact and how this affects interpretation and use of evidence in healthcare decision making.

Global AI talent tracker

Illustrations