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Author of essays on learning, time, design, and humor, shares insights through scrapscript and blogs.hn.
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Town Hall #28: Noodle

2025-09-23 08:00:00

Hey! It's been a while. I'm alive. Life is good.

If you want more frequent updates, consider following me on RSS, X, Bluesky, and Mastodon.

I moved to Seattle earlier this year! It's a wonderful (and severely underrated) city. So much moss! Great people, great vibes, great weather, great culture, great food, and great parks. Let me know if you're ever in the area. Let's hang!

Anyway, I recently read Why Greatness Cannot Be Planned: The Myth of the Objective. It's a dull book that started a tiny circus in my skull. Its central argument is something like "objectives are counterproductive for solving many creative problems". Suddenly, so many of giant dreams/goals/plans seem silly. I've given myself permission to noodle again. Less pressure. It feels good.

Let this be a little reminder that you may noodle too.

Appearances

Exp. History Blog Extravaganza '25
Good Internet My website is ugly because I made it
UNSOUND '24 Towards Rigorous Responsibility (in Distributed Systems)
LIVE '24 Scrapsheets: Async Programs in a Reactive 2D Environments
DDD Europe '24 Timeless Way of Software
Kodsnack Failure of ergonomics

Projects

lede.me minimal og:image titles
pic.fish og:image screenshots
diggit.dev for architecture archaeologists

Writings

Books

★★★★★ The Road :: Cormac McCarthy
★★★★★ The Golden Compass :: Philip Pullman
★★★★★ Musashi :: Eiji Yoshikawa
★★★★★ Klara and the Sun :: Kazuo Ishiguro
★★★★★ Cadillac Desert :: Marc Reisner
★★★★★ A Naked Singularity :: Sergio de la Pava
★★★★ Wintersteel :: Will Wight
★★★★ Three Laws of Nature :: R. Stephen Berry
★★★★ Thinking with Type :: Ellen Lupton
★★★★ The Wisdom of Insecurity :: Alan Watts
★★★★ The Wager :: David Grann
★★★★ The Spider's War :: Daniel Abraham
★★★★ The King's Blood :: Daniel Abraham
★★★★ Steve Jobs :: Walter Isaacson
★★★★ Motivational Interviewing :: William R. Miller and Stephen Rollnick
★★★★ How to Talk So Kids Will Listen & Listen So Kids Will Talk :: Adele Faber & Elaine Mazlish
★★★★ How to Get Filthy Rich in Rising Asia :: Mohsin Hamid
★★★★ Everything is Tuberculosis :: John Green
★★★★ Children of Time :: Adrian Tchaikovsky
★★★★ Characteristics of Games :: George Skaff Elias, Richard Garfield, and K. Robert Gutschera
★★★★ Bloodline :: Will Wight
★★★★ Black Rednecks and White Liberals :: Thomas Sowell
★★★★ Become What You Are :: Alan Watts
★★★★ A General Theory of Oblivion :: José Eduardo Agualusa
★★★ Why Greatness Cannot Be Planned :: Kenneth O. Stanley and Joel Lehman
★★★ What Makes Sammy Run? :: Buddy Schulberg
★★★ Welcome to the Hyanam-dong Bookshop :: Hwang Bo-Reum
★★★ Waybound :: Will Wight
★★★ Unsouled :: Will Wight
★★★ Underlord :: Will Wight
★★★ Uncrowned :: Will Wight
★★★ The Widow's House :: Daniel Abraham
★★★ The Wealth of Humans :: Ryan Avent
★★★ The Tyrant's Law :: Daniel Abraham
★★★ The Mom Test :: Rob Fitzpatrick
★★★ The Impossible Man :: Patchen Barss
★★★ The Grid :: Gretchen Bakke
★★★ The Case Against Education :: Bryan Caplan
★★★ Supercommunicators :: Charles Duhill
★★★ Soulsmith :: Will Wight
★★★ Sirens & Muses :: Antonia Angress
★★★ Selfish Reasons to Have More Kids :: Bryan Caplan
★★★ Radical Abundance :: K. Eric Drexler
★★★ Prisoners of Geography :: Tim Marshall
★★★ On Bullshit :: Harry G. Frankfurt
★★★ James Acaster's Guide to Quitting Social Media :: James Acaster
★★★ Good Inside :: Dr. Becky Kennedy
★★★ Gideon the Ninth :: Tamsyn Muir
★★★ Ghostwater :: Will Wight
★★★ Factfulness :: Hans Rosling, Ola Rosling, Anna Rosling Rönnlund
★★★ Fab :: Neil Gershenfeld
★★★ Dreadgod :: Will Wight
★★★ Devil Take the Hindmost :: Edward Chancellor
★★★ Creation Lake :: Rachel Kushner
★★★ Complexity: A Guided Tour :: Melanie Mitchell
★★★ Blackflame :: Will Wight
★★★ An Elegant Puzzle :: Will Larson
★★★ An Absolutely Remarkable Thing :: Hank Green
★★ Zen and the Art of Happiness :: Chris Prentiss
★★ The The Prime Number Conspiracy :: Thomas Lin
★★ The Curse of the Mogul :: Jonathan Knee, Bruce Greenwald, and Ava Seave
★★ Soulhome :: Sarah Lin
★★ Skysworn :: Will Wight
★★ Reaper :: Will Wight
★★ Ministry of Time :: Kaliane Bradley
★★ How Innovation Works :: Matt Ridley
★★ How Evil Are Politicians :: Bryan Caplan
★★ Good to Great :: Jim C. Collins
★★ Give and Take :: Adam Grant
★★ Can't Hurt Me :: David Goggins

Music

★★★★★ Kendrick Lamar :: good kid, m.A.A.d city
★★★★★ João Gilberto & Stan Getz :: Getz/Gilberto
★★★★★ Bart Constant :: Tell Yourself Whatever You Have To
★★★★ Yoshihiro Kanno & アンサンブル・レニエ :: aspirazione e Sogni Di Firenze / Yoshihiro Kanno
★★★★ Yasuaki Shimizu :: Music for Commercials
★★★★ Windows 96 :: Empty Hiding World
★★★★ underscores :: Skin Purifying Treatment
★★★★ Two Door Cinema Club :: Tourist History
★★★★ The Evpatoria Report :: Golevka
★★★★ Tennyson :: With You - Single
★★★★ Tenebrae & Nigel Short :: Music of the Spheres: Part Songs of the British Isles
★★★★ Soul Glo :: Diaspora Problems
★★★★ Sally Shapiro :: My Guilty Pleasure
★★★★ ROSALÍA :: MOTOMAMI
★★★★ PM Today :: In Media Res
★★★★ Miranda Sex Garden :: Madra
★★★★ Metaroom :: Oxidized Archive
★★★★ Jyocho :: The Beautiful Cycle of Terminal
★★★★ Jerskin Fendrix :: Winterreise
★★★★ Hudson Mohawke :: Cry Sugar
★★★★ Dirty Projectors :: Swing Lo Magellan
★★★★ Deathbrain :: A Slice of Life
★★★★ Dash Berlin :: The New Daylight
★★★★ Clairo :: Charm
★★★★ Circa Survive :: On Letting Go
★★★★ Chuquimamani-Condori :: DJ E
★★★★ Between the Buried and Me :: The Parallax II: Future Sequence
★★★ Yung Bae :: Bae2
★★★ Windows 96 :: Glass Prism
★★★ WILLOW :: <COPINGMECHANISM\>
★★★ Tigran Hamasyan, Arve Henriksen, Eivind Aarset & Jan Bang :: Atmosphères
★★★ The Fearless Flyers :: The Fearless Flyers - EP
★★★ The Contortionist :: Clairvoyant
★★★ Supernaive :: Dazed & Confused
★★★ STAYC :: YOUNG_LUV.COM - EP
★★★ Spangle Call Lilli Line :: New Season
★★★ she :: Chroma
★★★ saoirse dream :: Everything✱
★★★ R3LL :: Fantasy - EP
★★★ Polyphia :: Renaissance
★★★ My Epic :: Broken Voice
★★★ Moe Shop :: Pure Pure - EP
★★★ Metá Metá :: MetaL MetaL
★★★ Master Musicians of Bukkake :: Totem One
★★★ Malte Marten & Yatao :: Meditation Compilation #1
★★★ Macross 82-99 :: Sailorwave
★★★ Lennie Tristano & Warne Marsh :: Intuition
★★★ Kaskade :: Dynasty
★★★ Hole Dweller :: Flies the Coop
★★★ Hammock :: Raising Your Voice…Trying to Stop an Echo
★★★ FLOOR BABA :: Bombs - Ball
★★★ Eric Dolphy :: Out to Lunch!
★★★ English Teacher :: This Could Be Texas
★★★ Elephant Gym :: Angle
★★★ Eatmewhileimhot! :: Mushroom
★★★ Eartheater :: Irisiri
★★★ Duo 505 :: Late
★★★ Dorena :: Holofon
★★★ DJ Seinfeld :: Mirrors
★★★ Deb Talan :: A Bird Flies Out
★★★ Deas Vail :: White Lights - EP
★★★ Cryptic :: Mono/Poly
★★★ Chanco En Piedra :: La Dieta del Lagarto
★★★ Ben Rosett :: Mellow Hype
★★★ Ben Howard :: Is It?
★★★ ATTLAS :: Out Here With You
★★ Yellowcard :: Ocean Avenue
★★ Wolf & Bear :: Everything is Going Grey
★★ THE NOVEMBERS :: Elegance - EP
★★ The Daysleepers :: Hide Your Eyes (EP)
★★ Tenue :: Arcos, bóvedas, pórticos
★★ Tenebrae :: Rachmaninoff Vespers: All-Night Vigil
★★ strxwberrymilk :: Eloise
★★ Son Lux :: Stranger Forms
★★ Silverstein :: I Am Alive In Everything I Touch
★★ Samantha James :: Rise
★★ Real Estate :: Real Estate
★★ POLIÇA :: Madness
★★ Owls :: Owls
★★ Osamu Sato :: Objectless
★★ MSWHITE :: Squares
★★ Mrkryl & Sorsari :: Story LP
★★ MONO :: My Story, The Buraku Story
★★ Malfet :: Alban Arthan
★★ Laurel Halo :: Atlas
★★ Itoki Hana :: Void
★★ Intervals :: A Voice Within
★★ Hammock :: Longest Year (2020)
★★ Go Motion :: Kill the Love
★★ Frank Sinatra :: Ring-A-Ding-Ding!
★★ Fearofdark :: Exit Plan
★★ FaltyDL :: Hardcourage
★★ Ellen Allien & Apparat :: Orchestra of Bubbles
★★ e.s.t. :: Seven Days of Falling
★★ dungeontroll :: Tales from the Northern Chamber - EP
★★ DJ Kuroneko :: Neko Garage 3
★★ desert sand feels warm at night :: သေမင်းတမန်
★★ Danny Paul Grody :: Sketch for Winter VI: Other States
★★ Daniel Deluxe :: Corruptor
★★ Dance With the Dead :: Send the Signal
★★ Charles Mingus :: Pithecanthropus Erectus
★★ CHANCE デラソウル :: Goodbye Future Funk
★★ CHANCE デラソウル :: All Together Now
★★ Anaïs Mitchell :: Xoa
★★ Aminé :: Good For You
webcage :: Heatwave
Vieux Farka Touré & Khruangbin :: Ali
The Acid :: Liminal
Tanaka Yuri :: City Lights 2nd Season
Slikback :: Tomo - EP
Midbooze :: Experience
Kinoko Teikoku :: Time Lapse
Home Is Where :: Our Mouths to Smile - EP
Hannah Blaylock :: Bandit Queen
Frazey Ford :: Indian Ocean
Evil Needle :: Cirrostratus
DZA :: Software
Death In The Park :: Death In The Park - EP
Cyro y los Persas :: 27

Do Not Shred Your Fingers In An Actual Blender

2025-09-16 08:00:00

I recently gave some bad advice in this essay:

Luckily, LLMs significantly reduce the effort/cost of therapy experiments. Consider trying the following prompt:

Please guide me through a round of ERP therapy. Start by listing universal sources of fear/discomfort/anxiety.

If you find this process useful, consider trying it with a licensed human professional.

I think this advice is dangerous if taken too seriously/literally, which is why I removed it.

This is how that passage sounded in my head:

  • I recently discovered blenders. Blenders are cool.
  • If you're curious about blenders, consider playing Blender Simulator 2000.
  • If you enjoy that game, I recommend purchasing a Vitamix and thoroughly following instructions.

That's how I felt, but that's not what I wrote.

To chat with Claude is to play Human Simulator 2000. It's a bag of words. It is neither friend, nor coworker, nor foe, nor therapist.

Yes, sometimes LLMs can simulate humans. Yes, sometimes those simulations can be useful. But be wary of a simulation if you can't verify its accuracy/efficacy. When you cannot yet distinguish fact from fiction, relying on a fiction pump seems unwise.

Do not shred your fingers in an actual blender.

ERP Therapy Sucks

2025-09-13 08:00:00

OCD is a cycle.

I was recently diagnosed with obsessive-compulsive disorder. I was like "woah" and then I was like "duh".

But "OCD" is just a diagnosis. I don't care about labels -- I care about treatment. I want results.

So I started NOCD's program a few weeks ago. It's good, but it's not what I expected. I thought it would be stuff like "tell me about your childhood" and "how does that make you feel?". Nah. It's just "enumerate your fears and let's go purposefully do all those things". It really sucks. But that's the whole point.

This is the essence of exposure & response prevention (ERP) therapy. You purposefully provoke fear/anxiety without resorting to your usual coping mechanisms. This feedback shows your brain the futility of familiar rituals. All this time, you've been experiencing anxiety with extra steps.

ERP therapy seems valuable beyond OCD treatment. I suspect that most people could benefit from listing fears and systematically tackling them.

ERP sucks. I hope you try it.

"I'm the type of person who..."

2025-09-07 08:00:00

I don't tend to hang with people who seriously play golf. I'm not a person who plays golf. I'm a non-golfer. I'm the type of person who lurks in online non-golfing communities.

This is truly dangerous stuff; do not tread lightly. You inevitably become your identities. You are simultaneously writing your D&D character sheet and becoming that person. This is your story.

Sometimes anti-identities are more powerful than identities. You can wield your tribal/disgust instincts via statements like "I'm not the type of person who…"

There are two ways to become a golfer:

  • naturalized: golf regularly then call yourself a "golfer"
  • methodical: call yourself a "golfer" then golf regularly

You accumulate naturalized identities via daily life. You are not a "soccer-mom", but your kids want to play soccer, and you are a mom. Life is an unforgiving dungeon master.

Sometimes naturalized identities are degenerative. First you are somebody who "only smokes at parties", and then you are somebody who "buys a pack every once and a while", and then "in denial about being a smoker", and then a "pack-a-day smoker", and then "smokes out of throat hole" type-of-person.

I used to be a heavy smoker. To quit smoking, I became the type of person who doesn't smoke, who doesn't hang around habitual smokers, who doesn't poison his children with vice, who overcomes temptation, etc.

But method-actors reverse this process. They imagine a different person entirely and then become that person.

Nobody accidentally runs triathalons. Triatheletes don't become that type of person by mistake. First they decide that they are triathaletes, then they train themselves. But training sucks. Along the way, these people remind themselves that they're the type of person who crushes challenges, who seeks discomfort, who never gives up.

If you adopt method-acting, beware becoming a "writer who never writes". These folks call themselves "writers" without doing the work. That's not method-acting; it's cosplay without charm.

That's why I'm the type of person who…

  • spends less than I earn
  • speaks up when something isn't right
  • publishes imperfect art
  • gives good apologies
  • creates mild mischief
  • chooses authenticity over approval
  • never complains
  • doesn't worry about an uncontrollable world
  • leaves places better than I found them
  • reacts compassionately
  • says "no"
  • exercises daily without thinking about it
  • listens to my body's signals
  • assumes positive intent
  • creates more than I consume
  • doesn't eat crap
  • solves problems
  • takes small commitments seriously
  • maintains things before they break
  • doesn't smoke cigarettes
  • makes careless mistakes
  • doesn't mess with sleep
  • is both dreamer and doer
  • maintains trust
  • stops gossip
  • tries new things
  • is 10 minutes early
  • remembers people's names and uses them liberally
  • protects my morning energy for my goals
  • maintains optimism without naivity
  • finishes what I start
  • lives by my values no matter what
  • makes people smile
  • does the right thing
  • distrusts hype
  • doesn't boast
  • does the hardest thing first
  • cares about epistemics
  • forgives liberally
  • drops everything to help a friend
  • really listens to people
  • doesn't drink to excess
  • wears clean and simple clothing
  • cleans up my accidents
  • gives back
  • is impervious to drama
  • doesn't avoid difficult emotions
  • chooses long happy over short happy
  • helps clean after parties
  • celebrates others' wins
  • sets boundaries and protects energy
  • fixes things instead of replacing them
  • checks in on friends
  • asks for help
  • remains forever curious
  • returns shopping carts

I'm the type of person who does these things. I'm the type of person who does these things. I'm the type of person who does these things.

100,000,000 CROWPOWER and no horses on the moon

2025-09-03 08:00:00

tl;dr: Humans have no damn clue how to measure intelligence.

Raising Water

Water is wet (and heavy). Because it's wet/heavy, it tends to flow downhill (and underground).

To continue living, humans often wet themselves ("drinking"/"bathing") and their plants ("irrigation"). But many humans live uphill (and aboveground) -- to maintain wetness, they raise water to their homes/farms.

Once you carry your own water, you will learn the value of every drop.

But water is heavy (and wet), so humans built machines ("horse mills") and forced horses to raise water.

Horses (and humans) are made of meat. Meat is great, but it's prone to disease, exhaustion, distraction, etc. Ever cleverer, humans built non-meat machines ("steam engines") and forced water to raise water.

Horse Numbers

So that an engine which will raise as much water as two horses, working together at one time in such a work, can do, and for which there must be constantly kept ten or twelve horses for doing the same. Then I say, such an engine may be made large enough to do the work required in employing eight, ten, fifteen, or twenty horses to be constantly maintained and kept for doing such a work…

-- Thomas Savery, The Miner's Friend (1702)

Horses can do work, i.e. exert force over distance. Work over time is "power".

To explain his steam engine to other humans, James Watt defined "1 horsepower" as "33,000 foot-pounds per minute", which approximates a typical horse's work on a typical mill.

The "foot-pound" is the worst unit of energy. Be careful not to confuse it with the "pound-foot", which is a unit of torque.

Horse numbers are convenient at horse-scale, but cumbersome in calculations for telegraphy and rocketry, so scientists/engineers literally removed horses from the equation. Humans now measure power in "Watts" -- named after the human who named the measurement after horses. 1 horsepower equals ~746 watts.

One SpaceX Starship exceeds 100 million horsepower, but 100 million horses probably can't pull a sleigh into orbit. Horse-force is not thrust, and Earth's ~60 million total horses are not enough.

Indeed -- scientists have yet to discover even a single horse living on the moon. Terra Luna's scant fossil record suggests that horses may have never even established a stable population beyond Earth's atmosphere. Biologists blame the moon's unforgiving atmosphere; physicists blame the tyranny of the rocket equation. Either way, the moon seems safe from equine invasion.

Microwave ovens run at roughly one horsepower. This sounds like nonsense unless you're familiar with math, energy, work, dimensional analysis, electromagnetism, radiation, dielectric heating, magnetron design, and thermodynamics.

Well, it sounds like nonsense until you microwave your hundredth frozen burrito and it becomes mundane magic. We learned to measure energy, then capture it, store it, and harness it.

One Intelligence, Please

But humans still have no damn clue what "intelligence" is. We can't measure it, can't capture it, can't store it, and rarely use it.

Sometimes intelligence smells like "cognitive horsepower", i.e. some people/machines seem to have better overall engines for doing brilliant thinky-things. "g-factor" researchers show that many positive cognitive traits tend to correlate with each other. But the world also creates counterexamples like AlphaGo and Kim Peek -- non-generalizable brilliance.

IQ demonstrates intelligence in the same way that horse races demonstrate horsepower.

We can't define intelligence, yet we desperately want it -- and pay handsomely for it. Institutions approximate cognitive horsepower (if it exists) via crude proxies:

  • headcount & "man" hours/months
  • age & total years of experience
  • processing power (e.g. CPUs, GPUs, clock speed)
  • portfolios & selected works
  • standardized tests (e.g. SAT, IQ, ARC)
  • reputation/klout/endorsements

It's unclear how these measures compare and interact. If I were to get a heart transplant tomorrow, should I prefer 5 medical students over 1 expert? Should I prefer 2 Harvard grads over 3 UCR grads? A human child or 10,000 crows?

Such comparisons sound like nonsense; we lack equations to convert absurdity into understanding. We want to convert cognition into mundane magic. We need crowpower.

Crows are a good unit of measurement. They're cute (awww), smart (whatever that means), portable (~500g), and consistent/fungible (no 10x crows).

Crowpower

Scientific revolutions are punctuated by paradigm shifts. These shifts often occur when thought-experiment crash into new mathematical tooling: Schrödinger's cat, Newton's cannonball, Hilbert's hotel, Bell's spaceship, Maxwell's demon, Mermin's device, Zeno's race, Heisenberg's microscope, Galileo's ship, Savery's horse, Turing's machine, etc.

In each case, mature mathematics hit the limits of human intuition. Consider crowpower a catalyst.

Difficulty

We don't know what it means to cognitively "raise water". We lack the tools to quantify (or estimate) intellectual work. Consider the following tasks:

We intuitively understand these as "challenges", but it's hard to explain how or why they're challenging. Concepts like computational complexity, logical depth, learnability, Kolmogorov complexity, etc. could be different parts of the same elephant.

There are no horses on the moon -- could 100 million crows solve Fermat's Last Theorem?

FLT was postulated in 1637. Despite countless attempts, it went unsolved until Andrew Wiles produced a proof in 1994. This was absurdly difficult; many rank Wile's FLT proof among the greatest feats in mathematical history.

Units

100M crows might not be able to prove FLT, but could 100 clones of Adam Sandler do it?

I know very little about Adam Sandler -- he could totally be as smart as Andrew Wiles. I specifically chose a comedic actor who plays an average Joe.

I fully expect that comparing Sandler to Wiles is like comparing a 10-watt heater to an 11-watt blender. Wattage clearly explains rotational vs. thermal energy; nobody blames their heater for frothing milk poorly.

Here are some crude units-of-measurement to consider:

1 crow < 1 gump < 1 joe < 1 wile < 1 oz < 1 hal

I shouldn't need to tell you that rhetoric like this is dangerous. Don't take this too seriously. Be kind to each other.

Since nobody knows how human intelligence scales, "oz" (superhuman intelligence) purposefully ambiguates Oz and Ozymandias. Of course this also ambiguates the accepted abbreviation for "ounces", but this is the best I can do with my limited joepower.

It took 1 wile to prove FLT. It remains unclear how many joes it would take to perform the same feat. Here are some common responses to this thought-experiment:

  • "1 joe cannot be compared to 1 wile. G-factor is misguided; intelligence is not a one-dimensional phenomenon."
  • "1 joe is functionally equivalent to 1 wile, but needs more time to complete the same task. It might take 100 joes to prove FLT in a similar timeframe."
  • "1 joe is functionally equivalent to 1 wile, but doesn't have the memory/stack-depth to complete the same task. It might take 100 joes to hold FLT in their heads."
  • "1 joe fundamentally lacks some mental machinery in 1 wile. There is no reasonable amount of joes that could prove FLT."

We still have no damn clue what we're measuring.

OpenAI's GPT models might illuminate our fragile human hierarchies. Is GPT-4 closer to 99 gumps or 0.8 joes?

We weigh horses because we don't know how to test strength. In this world, nobody can distinguish a strong horse from a fat horse.

Scaling

100 duck-sized horses are not equivalent to 1 horse-sized duck. 100 1MHz processors are not equivalent to 1 100MHz processor.

Neil J. Gunther's Universal Scalability Law formulates this phenomenon:

C(N) = N / (1 + α(N-1) + βN(N-1))

C : capacity or throughput
N : number of processors, threads, or nodes
α : contention coefficient (serialization)
β : coherency coefficient (crosstalk)

Note that β (i.e. "communication overhead") dominates parallelization gains. As team size increases, the cost of talking can exceed the value of the work.

Even if 100M crows could be motivated to prove FLT, the bandwidth of crow speech is probably insufficient.

Coordination is hard. Humans build tools like traffic signs and punch clocks and SMS to more efficiently communicate across spacetime. Likewise, crow communication could be augmented with specialized tools/devices. Imagine millions of crows wearing the cutest little VR headsets -- each bird working on their own microscopic math mini-game in exchange for grapes or whatever crows eat.

We also don't know how to measure motivation. How many kilowatt-hours (a proxy for economic value) would it take to incentivize a crow to solve equations? How many kW-hours would it take to make those crows flip burgers?

But we've got too many variables on the table -- let's assume all crows are telepathic and cooperative. When β is zero, USL is equivalent to Amdahl's Law.

α represents contention. This variable depends entirely on the problem (e.g. proving FLT) and solution (e.g. proof strategy/algorithm). Information "assembly lines" cannot be parallelized -- some work/processing/computing cannot begin until intermediate results are completed.

In some sense, all difficult problems are difficult because they are sequential. In ten coin flips, it is easy to get any head, but hard to get all heads.

Automated theorem-proving is hard. Because FLT was remarkably difficult, the proof is probably resistant to highly-parallel strategies. 100M crows can only prove FLT if they have enough compute/memory to complete its most difficult subsequence.

Emergence

With enough training and error-correction, an average crow could emulate a transistor. A sizable murder of crows could emulate a Commodore 64, an Intel i9, an Nvidia RTX 5070, a human brain, etc.

If you believe that a crow can emulate a transistor, it would only take a few thousand crows to build a CPU. With enough patience and mechanical prowess, crows could summarize PDFs and write novels.

The Chinese Room Argument is discussed ad nauseam -- few folks would consider individual crow transistors/neurons as "intelligent" despite their emergent behavior. But it's unclear how much intelligence (if any) each crow can contribute to a collective.

There is only one way to make salt; salt molecules cannot be "more salty" or "less salty". But there are infinite ways to make pepper -- a messy blend of biomolecules created by messy genomes created by messy selection pressures.

If intelligence is like salt, then crows are very expensive (and cute) transistors. If intelligence is like pepper, a murder could someday be President of the United States.

Phase-Changes

Many people view intelligence as a sudden "waking up" phenomenon. Ice melts; water boils. In this lens, evolution produced smarter ape architectures until a "phase-change" happened and Homo sapiens took center stage.

Whenever I glimpse phase-changes, I reach for universality in my mathematical toolbox.

It's hard to take this idea seriously if you've ever experienced childhood. Humans slowly grow intelligent. Even milestones like object-permanence and walking and literacy become gradual under scrutiny.

But ideas also "click" into place. It's hard to "unsee" ambiguous illusions. It's difficult to simultaneously understand why sqrt(2) is irrational and not understand it -- intelligence may be gradual, but the experience is sudden/frenetic.

But along some orthogonal axis, we've taught robots object-permanence and walking and literacy, but it's "not real general intelligence". It's "just AlexNet" or "just PID" or "just stochastic parrots" -- until AI performs some magic phase-change, many folks won't admit it into the Cognition Club; it's merely "artificial" intelligence until it's "synthetic" intelligence.

But if the Cognition Club is real, why is it so hard to describe its minimal entry requirements? How many crows would it take to make it into the club? How did a dead parrot obliterate the Turing Test?

Generality

Humans that excel at any subject tend to excel at all subjects. Researchers call this phenomenon "g-factor" or g.

This model compliments s-factors and contrasts theories of multiple intelligences.

But if 10K crows could comfortably beat every Nintendo game, would you trust that same murder to file your taxes?

Video games don't span the full gamut of human knowledge/ability, but they're arguably the most objective available measure of general problem-solving ability.

Many video games are harder than college-level courses. Whirlitzer of Wisdom involves lunar cartography.

Video games form an objective (albeit anthropocentric (and ethnocentric)) hierarchy for g:

  1. World 1-1
  2. Super Mario Bros.
  3. all NES "platformers"
  4. full NES catalog
  5. full SNES catalog
  6. all Nintendo games
  7. all video games

Typewriter monkeys could beat Super Mario Bros. given enough time, so this measure needs additional parameters. Because game-completion times can range from minutes to days, a reasonable time constraint might be "no more than 100x slower than current glitchless any% WR". For zero-shot attempts, it might be wise to allow ~10 lives/restarts within the total allocated time limit.

Let's try an example. Suppose you want to hire crows to beat racing games. Murder A beats 40% of Mario Kart installments. Murder B beats 100% of first-person shooters. Murder C beats 5% of all games. Which murder do you hire?

Intuitively, games are more similar when insights/learnings transfer, i.e. learning game A reduces the learning effort of game B. We'd expect the average "learning distance" between racing games to be smaller than the distance between all games. If learning distance is independent of players, we can arrange all these games in a high-dimensional "gamespace".

Extrapolating from this framework, g-factor does not measure the competence of players -- it measures the compactness (or maybe compressibility) of a gamespace region. The existence of a g-factor merely suggests that human school subjects are not so dissimilar: French, English, music, physics, mathematics, etc.

But what in the precise h*ck is gamespace? Surprise -- if our games are arranged by learning distance, then gamespace simply contains all learnable problems.

There are multiple ways to define "learnability": statistical learning theory, algorithmic learning theory, computational learning theory, etc.

Supersimulators

Learnable problems are a subset of computable problems.

The Church-Turing Thesis asserts that computable functions are precisely those that can be computed by a Turing Machine (TM) and anything that can simulate a TM. A system is [Turing-complete (universal)] if it can simulate any TM.

Many systems are unexpectedly Turing-complete, e.g. Dwarf Fortress, Minecraft, Conway's Game of Life, Magic: The Gathering.

Humans simulate computers, simulate conversations, simulate copulation, and simulate creatures.

To "think" is to simulate oneself. Memories simulate the past; dreams simulate the future. The hard problem of consciousness -- why subjective experience exists -- might be a mere side effect of simulating simulation itself.

If epiphenomenalists are correct, consciousness might be an unnecessary side effect of intelligence.

If true, all universal simulators ("supersimulators"?) are members of the Cognition Club. Simulation-depth might be a useful metric.

No two supersimulations are alike -- only a bat can be a bat, and only you can be you.

Learning is arguably an act of simulation: players sample examples, then predict (i.e. simulate) results. Difficult games demand more training; bad players require more training.

Andrew Wiles required 41 years of post-training to prove Fermat's Last Theorem. As it stands, 100M crows face fierce competition.

Things We Measure

We measure things we care about; we make units for things we measure. We made horsepower to sell steam engines. We made Watts to harness the [literal] power of electricity.

We needed energy beyond horses; we need cognition beyond crows, but we cannot measure intelligence. We think we know what intelligence looks like, but we have no clue when/how/why it happens.

Humans tend to confuse properties with processes. Illness isn't a divine curse; it's wild emergent behavior culminating from the struggle of countless organisms to survive a little longer. A frog is not a thing that hops; a frog is the phenomenon of frogging.

Measure difficulty. Measure motivation. Measure contention. Measure crosstalk. Measure collaboration. Measure gamespace. Measure compression. Measure learning. Measure simulation-depth. Measure everything. Measure anything.

Humans need intelligence. We get the units we deserve.

The Curious Case of Flunking My Anthropic Interview (Again)

2025-08-27 08:00:00

Here's a vague overview of what just happened:

  1. I recently applied for Anthropic's Developer Relations role.
  2. My friend who works there gave me a glowing recommendation (thanks again, dude!).
  3. I completed their secret take-home assignment.
  4. On top of their secret take-home assignment, I independently published diggit.dev and a companion blogpost about my [sincerely] positive experiences with Claude. I was hoping that some unsolicited "extra credit" would make me look like an exceptional/ambitious candidate.
  5. I posted diggit.dev to HackerNews and it hit the frontpage!
  6. I submitted my take-home assignment and my unsolicited extra credit.
  7. They sent me the "unfortunately" email.

Anthropic obviously didn't do anything wrong. I'm just bummed.

Claude Code truly is one of my favorite dev tools ever, and if you've suffered through my talks/interviews, you're probably sick of my enthusiasm for software. I was particularly excited to interview with Anthropic because I respect their approach to responsible AI adoption. This very blog is too often a crazed celebration of humans, of software, of AI, of progress, of sincerity -- I, I felt like I was a perfect fit.

The first time I flunked an Anthropic interview (ca. 2022), I accidentally clicked a wrong button during their automated coding challenge. It was easy to swallow that failure. I made an honest mistake; I expect companies to reject candidates who make honest mistakes during interviews.

This is different. I didn't misclick any buttons. My best wasn't good enough. I'm not good enough.

This essay started as a fantasy: some hero at Anthropic reads this on HackerNews and vouches for me and I get the job and I help them guide humanity toward post-scarity AI abundance, forever and ever, amen. I'm ashamed of these thoughts. It's the same folly of explaining to an ex-girlfriend why she's wrong about her own experience.

Dating was difficult for me. I don't mind feeling ugly or low-status or whatever -- I know my place. But it hurts to feel seen, feel considered, but ultimately rejected due to mysterious forces: "He's cute, but he's too weird."

Yes, I'm weird. My eccentric habits have been an overall boon for my career, for my relationships, for my well-being. But it's moments like these when I just want to turn all my weird off. I want to be a square peg for this square hole and do honest work and feed my family and help humanity thrive.

I can't turn my weird off, so I think I defensively dial it up sometimes. I exaggerate my eccentricities. It's easy to swallow criticism when it isn't the real me, when it isn't my best, when it's honest mistakes -- what a load of crap. This is me. This is my best. Hello, world.

Now it's all coming back in waves, in gasps -- I spent so much of my life being an unlikable jerk. Becoming somebody else has been slow/painful and I'm so deeply afraid of regressing. Over the past decade, I've been striving to spread joy, to do good, to be better. I'm trying so hard.

And all this keyboard vomit is a promise to myself that I'm not giving up. I am not regressing. It's just a corporation; this was just a job interview. I hate this feeling, and I'm staring these nightmares straight in their stupid eyeballs, and they're not blinking. This is what progress feels like. I am still alive, and I have so much more to do.

I'm okay. I mean it. I don't need (or deserve) your sympathy. I'm so lucky to be alive, at this time, at this place, in this body, with these people. My life is great, and it will get even better if I keep putting in this effort.

Spewing my insides like this onto The Internet is terrifying, but I suspect many strangers are facing similar feelings. It's rough out there. Whatever it is, wherever you are, I hope this helps. You've got this. You're not alone, and we're only human.