Chasing The Wind: Recent Episodes
Avi and Bugsby
In Chasing The Wind, Avi and Bugsby host a fast-paced, lightly-scripted discussion on topics ranging all across the ideological firmament. Listen in!
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