Chasing The Wind

References Adversarial collaboration Why do some people parse a space well and others get snowed? Energy landscapes Explore/exploit Global optimization Shape of space vs strategy for optimizing in it What are situations where you'll need to integrate a large data burden? Either data that you don't understand the structure of, or just too much of it. Quantum mechanics: different representations mastery can not translate Recognition of form Domain shear in programming architecture: components that haven't been designed with each other in mind. Domain Driven Design book. Rationality community's double cruxing. Umbrella topics: not thinking of the whole as the sum of its parts, e.g. Obamacare At what point do you need to do work in the space as opposed to just reading about it? Build a thing, visit a place, have an experience? Podcasting on a thing: what bar is needed for sufficient understanding to talk about it? Journalism: you have to actually touch primary source, not just other journalistic products. How? Go places, read textbooks, compute. Run numbers (as done often on Slate Star Codex). Observation vs Randomized Controlled Trial: build the thing to know what biases are built in. Potential topic areas Moral philosophy AI risk Visited OpenAI Education My dad Jesse Archery Science fiction and fantasy Physics simulation Should do this! Drug development Preliminary research: How do you do it? What to do after first-depth internet search hits limits. Make an actual research plan. Decide if e.g. you need experts, technical documents etc. Start drawing yourself a map. Written out decision tree process. Avi's map: Designing a House My goal is to learn what I would need to know to get a house that I would be happy with built. Re-read "A Pattern Language" carefully Find out the typical procedure for working with an architect - communication style, cost, time. Learn what major classes of housing site/lot there are (e.g. terrain type, climate, access, zoning). Find a set of example houses that have at least one thing I like a lot to draw parts from. Ideally, do Habitat for Humanity or in some other way get involved in the process of building a house. Make a list of activities and functions that are important to me for living in a house. Locate and speak with a professional architect and ask them what I should learn before embarking on designing a house. Bugsby's map: Space My goal is to learn about the past and present of space exploration enough to present an opinion about the future. Skim my old Astronomy textbook. Read a history of space exploration. Re-read a popular technical analysis of the good and bad things about the shuttle program. Find and read a book about the present state of space exploration. Find some opposing viewpoint articles about private space companies. Learn enough about SpaceX and Blue Origin to say what's different about each of them. Read James Michener's "Space" OR re-read Kim Stanley Robinson's "Red Mars" OR read the sequel "Green Mars".

Avi and Bugsby discuss Bugsby's data science process and brainstorm a design for a tool to improve it. There is a great deal of programming jargon and philosophy. References Command-line interface (e.g. bash) Bugsby's workflow Gather data Process data with commands/scripts Feed processed data to model building Produce output which may get piped to something else Python Visual programming XKCD - is time spent automating a task worth it  Semantic web GUI ("gooey") "repl" (read-evaluate-print loop) command line "typed"/"typing" Caching Pipes Macros Using Dynalist - store instructions in the form of a work log, be able to "tag" sections of it as "programs" Unit testing Users/groups/permissions Transaction log (in the sense of database or file system) Software liberal

We explore what a morality based on "good enough" means, what it would like, and whether we already follow it.  Discussed: genies, strong AI, and tech startups. References Effective altruism Rationalist community Satisficing utilitarianism Innumeracy Consequentialism and Utilitarianism Pascal's Wager Roko's Basilisk Repugnant Conclusion Peter Singer

We explore AI Risk, the notion that computer intelligence will cross the human level, start compounding exponentially, and, if not trammelled, mulch everything we hold dear into paperclips.  Why aren't Avi and Bugsby more worried about this? References Eliezer Yudkowsky Public figures who've expressed concern: Elon Musk, Bill Gates, Hillary Clinton Machine Intelligence Research Institute OpenAI Nick Bostrom - Superintelligence Value alignment problem Hippocratic Oath in software/civil engineering Iron Law of Oligarchy Superintelligence: the idea that eats smart people Principal-agent problem SSC AI risk persuasion experiment EY AI box escape experiment

References Master of the Senate Episode 3 - Legacy: the size of a science slice of the pie is shrinking Rationalists coordinating people on a project article Technical debt Kula Sushi LA, Silicon Valley Influence - Cialdini Things to Hang on your Mental Mug Tree Chan Zuckerberg Initiative Microsoft research announcement around the same time (note from Avi: Chan Zuckerberg was actually by far the more reasonable of these, the opposite of what I said in the episode.  Apologies!) Endeavors Moon landing Tennessee Valley Authority Manhattan Project Hoover Dam The Pyramids Human Genome Project Skyscrapers Civil Rights Act Affordable Care Act Standard Oil, Amazon, Google SpaceX Blue Origin Dragon Going to Mars Sea farming Growing a city (Bellevue) Starting a new country Starting a religion Starting a movement Occupy Wall Street/Tea Party Making old age not suck/fighting degeneration

References xkcd - ranking people Paul Graham cities essay Article - The urban archipelago Iron law of institutions Iron law of oligarchy Article about the significance of "again" in "Make America Great Again" Places The Barbican Seguin, Texas Sisters, Oregon

References Bret Stephens climate change article Arguments as soldiers California wine growers buying land in British Columbia States and cities offering to step in and honor US climate deals KSR - global warming as huge engineering project Reinsurance companies Bloomberg climate change NGO - covering US portion of UN budget  

References Elasticity of demand System I and II Achieving flow Failure mode of computer scientists in building tools: You Aren't Gonna Need It, Premature Optimization, Dominion (again) / Isotropic Overdamped/underdamped control.  For the short version, see this Quora answer.  For the math, see this.   Efficiency practices Making (and checking) checklists Series of many small efficiencies: bumping drawers closed with your hip, staying in touch with best balance contact point Pipelining Merging steps (in general, streamlining processes) Retrospection - which behaviors over last week could have been improved? When successfully correcting an error: what practices would have avoided that error in the first place? What would those practices have cost me, and would it be worth it? Scheduling - both making good use of time, and avoiding schedule failures that require costly correction Recognizing inefficient behavior patterns Main takeaway: the balance between optimizing for a value function and checking whether you need to update the value function is the key to efficiency.

References Goodreads Anathem Pythagorean Foundation - Asimov Doberman Neal Stephenson Clang video Gentlemen of the Road The Yiddish Policeman's Union Clown on Fire History of vanilla Lois McMaster Bujold Vorkosigan Saga A Civil Campaign Ursula K Le Guin   The Word for World is Forest Wizard of Earthsea Hornblower Gaudy Night Lord Peter Wimsey Among Others High Fidelity Neil Gaiman and Amanda Palmer Very Short Introductions Physical Chemistry Minerals (crystal habits) Psychology Existentialism Complexity Russell Einstein's Relativity Chaos - Gleick Anarchy, State, and Utopia Rawls A Theory of Justice C.S. Lewis Screwtape Letters Narnia Space Trilogy The Magicians - Lev Grossman Kingkiller Chronicle Jo Walton's close reading of the Kingkiller Chronicle Robert Jordan

References K-Blocks rm -rf Hardcore Linux (fencing accident videos are out there but we're not linking them) Pressure of an arrow tip - calculations, interesting comparison vs pistol Chuck/lathe Top roping Hang gliding New Republic Plato's Republic Electoral college SSC reverse advice article Manic Pixie Dream Girl Soviet seduction department

References Molecular gastronomy Why children dislike bitter foods Takoyaki (recipe) Oyakodon (recipe) Spelt (bread recipe) Levain Bakery (reconstructed recipe) The Great British Bake Off Baked cauliflower recipe (but Avi recommends slicing them thinner if possible) Nutrition restaurant James Morton's Macaron recipe Dario's pasta shop

References Sam Harris Kill the Buddha article Opiate of the masses Noble Lie Cycle of death and rebirth Deontology/moral forbiddences Stross/future shock

References Neil Gaiman Crisis in Syria Ayn Rand Alawites Othering Potter Puppet Pals - Neville's Birthday ("I speak from the heart: nobody likes you") Dunbar's number Slate Star - global culture vs local culture  

In this episode we start from scratch and build a world in which to tell stories.   References Dominion MTG Improv The Singularity Charles Stross Vernor Vinge Questionable Content Red Mars Mistborn Philosopher's zombie Last Night (movie, 1998) Quiverfull movement Ringworld HPMOR Talleyrand Foundation (Asimov) D&D Story of Your Life (Ted Chiang) Chase the wind (Name of the Wind).  Chasing the wind is hard to describe compactly, but mainly it's walking in the world and learning deep things by being open to experience. Cycle of death and rebirth Starchild Evangelion

In this episode we discuss the making of things, including things we want to make, maker spaces, how to learn to make, and safety when making.   References Fire staff Aang/Avatar Makerspace Artisan's Asylum Simone's bad robots Mythbusters Milling machine Terminal/command line Tested.com Bio makerspace PCR Open PCR machine Thermoelectric heating and cooling - peltier Bioluminescence Cellulose digestion Biomineralization Mandala

In this episode we discuss what it means to have a legacy, how it can inform your daily choices, the legacies of some modern day people, and how legacy has changed as a motivation in scientific work.   References Gates Foundation Elon Musk Jeff Bezos Amazon interfaces article: https://plus.google.com/117527659577068654649/posts/Gv6h93eBV5Z 10000 Year Clock Tesla Andrew Carnegie Gilded Age "Ems" Theoretical yield (biology/chemistry)

In this episode we discuss how we organize things for ourselves, and compare strategies.   References Evernote Workflowy "The Secret Weapon" Node.js Magisteria  

In this episode we discuss how to make things accessible to many people, whether this is a good idea, and who does it well. In an effort to make things more accessible, we are including a list of references with every episode so folks can understand what we're talking about!   References Slate Star Codex article on reversing advice you hear Yegge article