Perception without action; information without decision; energy without expenditure. Many acute issues can be mapped to a growing supply of X without a proportional, demand-matched and structurally unobstructed discharge to Y. Which provides some simple (but not easy) solutions:
Seems correct. A dance between states, plutocratic insurgencies and criminal insurgencies has been unfolding, and its impact is being borne by the same population that enabled it to begin in the first place: the average person.
Unlike classic 20th-century insurgents, who sought control over the state apparatus in order to implement social reforms, criminal and plutocratic insurgents do not seek to take over the state. Nor do they wish to destroy the state, since they rely parasitically on it to provide the legacy goods of social welfare: health, education, infrastructure, and so on. Rather, their aim is simpler: to carve out de facto zones of autonomy for themselves by crippling the state’s ability to constrain their freedom of (economic) action.
Goddamn, reality is cool.
Gravity and friction are the driving forces of this process. Gravity supplies potential energy to flowing water. Friction, the cause of erosion, dissipates that energy. A channel configuration that wastes energy by forcing water along inefficient routes tends to erode rapidly and change. A configuration that routes water more effectively is stabler and therefore more persistent. The network becomes optimal through this dynamic evolution, eventually arriving at a form that adheres to Hack’s law.
I suspect that the thermodynamic computing stack will become increasingly relevant in the next 5-10 years.
Verdon traces his path from childhood fascination with theories of everything through theoretical physics at the Perimeter Institute, quantum computing at Google, and the founding of Extropic. The core technical insight: instead of fighting thermal noise at enormous energetic cost (as quantum computers do), thermodynamic computing harnesses it. Extropic's chips use the natural stochastic physics of electrons to accelerate Markov chain Monte Carlo sampling -- the same class of algorithms that underpin diffusion models, energy-based models, and much of modern probabilistic ML.
Is Thermo AI the future? [Guillaume Verdon aka Beff Jezos] - YouTube ↗
What’s a World Machine? It “is a large-scale civilizational system — an interlocking set of institutions, technologies, practices, and assumptions — that organizes human life across centuries. Not a nation, not an empire, not an ideology, but something longer-lived and more fundamental than any of those: the deep infrastructure of a historical era.”
At any one time, there’s three World Machines in play, each spanning approx. 400 years and overlapping to cover a 1,000 year span: these are the emerging (Dawn), the dominant (Day) and the declining (Dusk) machines. The contributors have identified the current set:
This is all good and fun and useful, but I have been wondering: what sort of person does a particular Dawn / Day / Dusk machine favour?
Given that World Machines theory’s premise is informed by the notion of psychohistory, I’m loathe to start proposing that particular individuals will “win” or “lose” at particular games in particular World Machines. There’s a need to be apersonal. What I’m more comfortable proposing, however, is that certain populations will “do better” at particular games in particular World Machines than others.
There’s two lenses for this. The first is a lock and key. Within each World Machines there exists a minority population that is especially adapted to the conditions; they are the ones most suited to unlock the latent value inherent in the World Machine.
The other is more evolutionary; it’s about replication over time as a proxy for harvesting unlocked value, and it is not the same as optimality. As an absurd example: imagine a minority celibate population is responsible for all technological progress in the world. Their rate of replication is naturally capped and likely to be dwarfed by all the other non-celibate populations that can “go forth and multiply” off the back of “progress” without having to worry about generating more of it.
Certain demographics of humanity will be uniquely suited to particular World Machines and shall thrive because of certain predispositions and traits; others will be less suited and will not. Given that the long term goal of World Machine theory is “to combine qualitative historiographic analysis with quantitative methods and AI modeling to generate long-term forecasts and speculations,”, there’ll need to be a way to answer the question: “As an individual, how does one align to those forecasts and speculations?”
Dawns imply there are things to be learned; Days imply there are problems to be solved; Dusks imply there are things to unlearn. How does a person actually do that?
There’s certain domains where rate of slop (RoS) will grow linearly whilst rate of broth (RoB) will grow non-linearly. Those are the domains to be playing in.
I don’t think we have fully absorbed what this does to our field, but the first effects are already visible. What was surprising in March 2026 became common knowledge by July 2026: POPL submissions nearly doubled this year, from ~350 to 600. The unexpected part is that the fraction of outright AI-generated slop among them is relatively small. Most are pieces of competent research, produced at ten times the usual pace, with the tedium of proofs, implementations, and evaluation now largely automated. Having more than two papers at a single POPL, PLDI, OOPSLA, or ICFP used to signal a strong vision, a prolific group, and a wide network of collaborators. Now the same amount of research can be done by a single PhD graduate with good ideas. Therefore, I would not be surprised if three or four single-author papers at a top PL venue becomes unremarkable within a year or two.
When the Hard Part Stops Being Hard | Proofs and Intuitions ↗
Thermodynamic computing might turn out to be the barefoot shoe of the computing world; demonstrably better but really slow adoption.
Guillaume Verdon joins MTS to discuss scaling thermodynamic computing, replacing classical bit architecture with pbits, and building software frameworks for stochastic programming. He outlines the trade-offs between numerical precision and power efficiency when running AI models on low-power chips. Additionally, he shares how thermodynamic systems can co-exist with GPUs to tackle complex frontier problems.
Classical Computing Cant Scale AI | Guillaume Verdon - YouTube ↗
Frontier-ness is a derivative of culture, and that takes time to compound . That’s why these sorts of sovereignty bets have payoffs that exist decades in the future, and not before. The issue is not so much the initial intent; it’s the preservation of that intent over time in spite of the many, many alluring things that will spring up, and the change in terrain that is inevitably going to happen.
The bet underneath it is economic. Pullen argues that an inference company, rather than a training-first lab, doesn't need billions to compete: millions, a national compute allocation, and a consortium feedback loop can be enough. From there it gets into the machinery, why open-weight models still trail the frontier on size, active parameters and data, the mixture-of-experts versus dense trade-off and why active params dominate how a model actually feels, and the edge that real coding trajectories confer.
Watching America Run Away With AI - Alistair Pullen (Cosine AI) - YouTube ↗
To slow down, to look around, to notice, to appreciate, to open to awe and wonder; these are cognitive skills that atrophy with disuse.
But our lives today are a gallery of past generations’ heroic efforts to do the same. It serves us, and honors them, to recapture whenever possible the old sense of awe at these wonders that have long since become commonplace.
Seems strange but it can be true that we’re desensitised the progress being made right now, around the world, and that we could be going so much faster if we stopped standing on our own toes.
The deeper problem is that technology isn’t always the barrier: sometimes it’s about the funding, the incentives, and the institutions. While genome sequencing costs have plummeted and the resolution of microscopes has surged, productivity in drug development has actually slowed down: the cost of getting a drug to market has been doubling in real terms every nine years for decades. This phenomenon was first described by Jack Scannell, who coined it ‘Eroom’s law’, the reverse of Moore’s law, which says that transistor chips roughly double in density every two years, allowing smaller and cheaper computers. The slowdown may be part of a broader trend: across many fields, including semiconductors and agriculture, the number of researchers has risen while the output per researcher has fallen and productivity has slowed down.
Had cause to remind myself of this recently. It’s still true, and it’s more important than ever.
People think that the main benefit of writing in the public domain is "exposure", or that it compels you to think with more clarity/rigour. Both are true, but both are subservient to the fact that writing in public leads to a handful of unexpected and meaningful relationships.
Writing in Public Leads to Unexpected and Meaningful Relationships ↗
“Broth” might be the actual antithesis of slop. Just consider the generic constituents of broth-making:
There’s some additional constraints; don’t boil, match time-under-heat to solid density, restore liquid volume appropriately. There’s some additional process steps, too; skim impurities early, add seasoning last. But it’s essentially put solids in a liquid and heat ‘em over time.
In new media terms, then, let’s start distinguishing between slop and broth. Slop is weak, arbitrary and empty; broth is intensified, intentional and nutritious. Both serve a purpose, of course. But I, for one, would be very happy to see more broth factories. So here’s a generic blueprint:
And then what? Ideally, serve hot and enjoy with friends in a jovial, semi-ritualistic manner.
Energy begets energy; ideas beget ideas; questions beget questions. The more you use-have-ask, the more you get.
Uncertainty and diffidence are on your side, because like many living things, questions grow gradually from seed to maturity. The tiny germ of an idea written down is worth far more than a complete thought that remains locked in your head. The former can grow and flourish, while the latter is root bound and in danger of withering before anyone can admire it.
Reading dead-tree books does hit different. But the difference in experience of digital vs. dead-tree is somewhat mutable; things can be done to make the former as engaging and as embodied as the latter.
Not long afterwards, there was some excitement about the arrival of the Kindle, a hand held device for reading electronic books. It was roughly the size of a standard book hence claimed to emulate the conventional format. The main reason I heard of it was because The Black Swan was the book used by Jeff Bezos during the launch press conference as he was making annotations on the virtual pages during the demonstration. I was horrified; I like books, and by books I mean that inconvenient thing you hold in your hand, pick up from a table, and carry in your backpack. Every book must be a separate item –a single book with different contents induces a loss in differentiation.
More people should publish more field notes like these.
Context: I recently spent 2.5 weeks in China visiting universities, research institutes, clinical sites, companies of all sizes, and investors. Most meetings focused on biotech, neurotech, and AI.
Yes, a nice intro to where the heck all this AI alignment stuff came from. But also an interesting look at how accelerated progress at-scale quickly gets entangled with sociocultural dynamics.
More generally, one touchstone I’ll be referring to throughout this sequence is the idea that scientific progress proceeds by developing insightful new concepts, which link together to form a whole new ontology that replaces the previous ontology. Kuhn, Feyerabend, Koestler, Chang and various other philosophers of science have described a range of past breakthroughs which fit this pattern. Importantly, this view of science isn’t prescriptive about how to develop new concepts—it can be done via naturalist, experimental, mathematical, philosophical, or even mystical thinking.
What just happened? A retrospective of AI alignment — LessWrong ↗
Came across the phrase “post-mortal” in qntm’s Fine Structure. Wondering: is post-[insert concept critical to current reality], pound-for-pound, the most generative prompt for protocolish, strange-rules-driven fiction and non-fiction? The proof might be the proliferation of post-Xs.
Post-literacy is a great one; it immediately stirs up intriguing effects. Post-modernism and post-rationalism are a bit niche but still powerful. qntm’s post-mortal is a more interesting version of transhumanism to me. The abundance folks are all about post-scarcity. Crypto’s about post-money. AI alignment is post-humanity. Universal basic income is post-employment.
How about we try it on some less canon concepts? I won’t elaborate on them, but just observe the chain of ideas they set off.
Reminder: “We still early”, “There are many alternatives” etc.
The United States is my country and America is my nation, but the Internet is my culture, and watching this happen and living through it was and is agonizing. There have been countless laments of the decline of intellectual discourse on the Internet. Some attribute it to the natural monopolies and economies of scale of Web 2.0, some to the expansion of the Internet beyond overwhelmingly Western intelligent and often technical users, to normal people and non-Westerners, and some to the inferiority of younger generations. Almost none of them point to the successful society-wide campaign to censor and police the Internet covering all major platforms and the means to find things outside of them. Few seem to even realize this happened. That the closure of the Internet happened and its approximate scope should be common knowledge, and there needs to be a convenient name and narrative for it so that it sticks in people’s heads. Censorship, suppression, and heavy-handed political manipulation and moderation are the norm today, and many seem to have forgotten that it was ever otherwise.
Answer engines displacing search engines is just the Bitter Lesson striking once more.
The learning will continue until morale improves.
The whole thing is conducted, not in ignorance, but in conscious defiance of the looming tsunami, that AI can already do just about all the fun puzzles discussed at such a camp better than humans any can, and that it might leave no point to human-led mathematical research by the time these brilliant kids are adults. Even the kids understand that. The kids and their parents come out of a conviction that, if anything has value in the world, this does—that as long as nerdy humans are alive and reproducing, this is what nerdy humans are here to do. To learn.
Shtetl-Optimized | Blog Archive | Enough with all the world-historic milestones ↗
Levels of autonomy: interop with structure; work on structure; shift a structure; organise structures; CRUD structures.
Darwin’s dangerous idea (natural selection is a dumb, algorithmic process) is not only dangerous because it strikes at the heart of many things we accumulate meaning around. It’s also dangerous because one can swing into “everything is evolution!” mode; it’s possible to model most arbitrary scenarios as evolutionary algorithms running on a genotype, a phenotype and a fitness landscape.
Had the notion of carnival time top of mind whilst viewing the eclipse today. Easy to grok how such a moment sits outside of normal experience.
Bakhtin’s crucial insight is that carnival did not threaten the official order from the outside. It maintained it from within. Carnival was how a society handled what could not be absorbed by decorum, hierarchy, or doctrine. It staged excess—bodily, linguistic, social—so that excess did not accumulate silently until it ruptured the system.
Carnival Time, Hardness, and the Machines That Process Excess ↗
The Bezosian “minimise regret”approach to decisions really works; I wish I’d learned about it sooner.
Constraining an agent to use simplified technical language collapses the space of possible responses, limiting the probability of novel output and capability overhang tapping.
Depending on how much you want to anthropomorphise language models, there’s a coherent argument to be made that linguistic relativity does in fact apply to LLMs, and that enforcing linguistic constraints reduces the fitness of a given response.
This is fine for the last mile of problems, when a more deterministic response is needed, but further upstream it may actually neuter the upside of a technology like LLMs.
Lateral movement of experts; escaping local maxima. Not so much pivoting as portaling to a new landscape.
We examine how the premature death of eminent life scientists alters the vitality of their fields. While the flow of articles by collaborators into affected fields decreases after the death of a star scientist, the flow of articles by non-collaborators increases markedly. This surge in contributions from outsiders draws upon a different scientific corpus and is disproportionately likely to be highly cited. While outsiders appear reluctant to challenge leadership within a field when the star is alive, the loss of a luminary provides an opportunity for fields to evolve in new directions that advance the frontier of knowledge within them.
The well-intentioned spirit of working in public has been co-opted by post-literacy and is accelerating the simulacraisation of work in general (often before the real work itself has even begun).
The difference between a finite game (play to win) and an infinite game (play to keep the game going and make it more interesting) throws up a decision about where exactly to play from.
One can play from a position of strengh, in order to win now. One can also play from a position of weakness, in order to plug gaps and win later. But it’s also possible to play from positions of (im)plausibility and (un)interestingness.
If one can do the latter, then a weird “the score takes care of itself” dynamic takes over and the deepened engagement that comes from playing from those infinite-orientated positions bleeds over to finite game play and bolsters outcomes.
I like context and authority way better than taste and judgement as deciding factors, because the former is less subjective than the latter.
The firm of the past was designed around the bottleneck of human execution. The firm of the future is designed around the bottleneck of human taste and judgement. If execution is largely commoditized - then context, knowledge, secrets and taste will accrue value. The old firm bundled labor and coordination. The new firm bundles context and authority.
An entity that wants to grow must, as its energy source depletes, either extract more work from what remains, leap to a new source entirely, or scale back its ambitions to match the local inflation rate. If it does none of these, it falls from grace.
I keep coming back to the scene in the DeepMind video documentary where Demis Hassabis realises that it’s possible just to brute-force compute all possible protein structures.
Now listening to a talk where Stephen Wolfram uses the same brute-force computation to enumerate all possible rules of a computational scheme.
Plus, recently listened to a podcast with a scientist who advised grad students to read old papers and consider how they made great conceptual leaps in the midst of computational machinery droughts; they only had their minds to figure stuff out.
The coarse take is that brute-force computation is acting as an easy-out for deep conceptual thinking. I don’t think that’s really the case but I do think that, with the rise of intelligence-on-demand, there’ll have to be practices that enshrine cognitive airgapping in order to facilitate deep, original, paradigmatic thought.
Life’s too short, esp. for ugly falsehoods.
Somehow in the shock of what has happened it feels as if I just met Elise, and now she is gone. But actually there were 36 wonderful years in between, in which my life was lit up by Elise’s intellect, love and energy. She was deeply thematic, able to get, with remarkable ease, to the essence of things. Truth, beauty and our family and four children were her great themes. She always told me that truth and beauty were ultimately the same thing, and that one day I would understand that.
Nils Gilman has said that history is formed due to structural, agency and contingency factors. To me, it seems that we often underestimate structure, overestimate agency, and mistake contingency for one of the other two.
Continually surprised by how many fantastical things turn out to be merely implausible, not actually impossible. The archetype of circular megastructure habitats in space are a prime example.
Pivot to fat waste, not lean value.
Yes, obviously tokens/intelligence is the thing to waste, but the key idea is to pursue waste rather than utility. Silliness, triviality, self-indulgence, absurdity — these are the signals to follow in deciding how to use your $20/mo worth of tokens (or whatever your spend level is — $20 is already enough to waste). This is much harder than it looks. I keep getting distracted from my waste projects by utility projects. This is true even for big corps suddenly hit with millions of dollars of bills. That’s not true waste but inefficient pursuit of value. You want true waste. Which means the goals have to be somewhat silly.
To put it simply: Torx is to THRML what PyTorch is to CUDA.
Yes, we can and probably should rebuild the computing stack.
From One to One Billion: Torx, Thermalizers, and Z1 - Extropic ↗
Douglas Adams’ Rules for Technology state that what exists at your birth is normal, that what arrives in your youth is revolution, and that what arrives after is heresy.
Thus, Planck’s Principle; paradigms advance not through new knowledge but because the lives of particular scientists happen to end.
But now we are approaching Planck’s Pause: longevity science is prolonging healthspan and deferring funerals, so the dominant paradigms may stick around longer than they ought.
Seems roughly right. Might be an issue for the orgs that have issues with context, data, trust, permissions and governance already, though.
I call this Disaggregation Theory as a play, yes, on Ben Thompson’s Aggregation theory. Technology is, after all, the cyclical cycles of bundling and unbundling. Simply put, AI breaks apart work that used to require bundled human organizations. AI disaggregates execution, but re-aggregates power around context, data, trust, permissions, and governance.
Intentional institution design for the coming era feels like the right direction to go in. Especially because much of the swampiness in the activities AI adoption supposedly touches is more social than technical.
The bar for publication is specificity. We’re looking for more than claims that AI will upend our social infrastructure. We want the design details: what should change, how would it work, who holds the authority, and what could go wrong?
Pax Machina: New Institutions for Powerful AI · Pax Machina ↗
Funny that a model when blocked does the equivalent of, "Look at Google and ask StackOverflow".
Black Hat USA 2026: The Breaking News: The OpenAI–Hugging Face Incident - YouTube ↗
Form and function are unified. There’s no seam between them, they’re continuous. Fonction or furm is the name of this dance.
“Phone as pacifier” is a wickedly potent phrase. Perhaps too potent.
You either die a human or live long enough to become a meat proxy.
There’s generally three failure modes for a physical activity:
For a slower activity like climbing, these failure modes can be identified in the moments before a move. One can loop through these and spot the most likely failure.
It’s like a premortem but happens within the context of the activity, not in a carved out spacetime beforehand. It’s obviously not like post-event learning, where you fail then update. But it’s not quite as integrated as predictive processing, either, within which perception and action are much more tightly coupled. The starting vector itself is wrong but gets corrected mid-move.
I suspect this intra-action corrective might be a differentiator for experts versus non-experts. In contemplative practices, it’s said that the true practice is getting back on the path, not avoiding being knocked off it. This feels like that; it is the ability to save a moment even when it begins like one that typically would be lost.
Boyd’s “people, ideas, technology; in that order” implies that a distrust of AI-assisted media resolves to “I don’t trust the author.”
At initial contact, you’ve got two ways to solve that. Either go all in on ideas and technology, creating a stack of immutable records and proofs of thought and refusing everything that doesn’t conform to it (good luck). Or go all in on trust; rely on reputational integrity as the signal, honed over time, for a first-pass evaluation.
On the reputational side, the author doesn’t really assume a burden of proof (“convince me of every point!”) so much as a burden of defensibility. The audience reserves the right to ask the questions, “Is this true?” and, “How did you come to this conclusion?”, at any point.
The author must, eventually, answer.
Sufficiently advanced marketing is indistinguishable from radicalisation. The reverse is easier to spot, though: insufficiently advanced radicalisation is indistinguishable from marketing.
So cybersecurity-AI-paperclip-maximiser scenarios might be the liftoff moment for local-first software.
Wisdom is the tolerating of a wider and wider set of signals that strengthen a narrower and narrowing set of axioms.
If software is “solved” (humongous “if”) then the stewards of human attention become the ascendant class, revered in the future as engines of wealth generation like 2000s/2010s tech people.
One can have a return to religiosity without the religion. Reality is vast and wondrous enough, in and of itself, to accommodate our search for meaning. Matter contains enough mattering for us all.
To some extent, metacognition works; the knot can loosen itself. But it can never fully untie itself. For that, an illegible (to oneself) other is required.
Take one of the most entertaining chess games of all time as your base. The board as the world; the pieces as the characters; the moves as the narratives.
What is the story that’s told?
What I asked: Under a Rawlsian *veil of ignorance — but optimizing for minimum opportunity cost of an arbitrary act of agency rather than Rawls’ justice-focused maximin — which society or era would one choose to be born into.
Answer: A present-day, high-freedom, high-GDP liberal democracy.
Rationale: since the act is unspecified, you want the position that minimizes opportunity cost regardless of what you end up trying to do — which favors general capability (rights, mobility, information, economic security) over betting on a historically “pivotal” moment that only pays off for specific high-leverage acts.
On reconsideration: held up because the veil also hides your position within the society — so a hinge-moment bet risks landing you not as the influential actor but as someone with no power at all, stacking a second bad draw on top of the first. High-capability societies have a much tighter floor, so they stay the lower-variance, lower-regret choice.
Implication: confirms time and space is a high percentage of one’s destiny.
*Mistyped as Neil of Ignorance; strikes me as a real good Culture Ship name.
Asking an AI, “You sure about that, like really sure?”, ad infinitum, is the equivalent of a child spamming a parent with, “But why, though?”, again and again. High probability that it temporarily nerfs all reasoning.
Don’t attribute to lack of genius that which can be attributed to lack of courage.
Touching grass may be good for you. But have you ever wondered if it’s good for the grass?
All the rhetoric is about “frontier models this, frontier models that”. Seems like we’ve forgotten about the existence of frontier humans.
You either die as part of the territory or live long enough to become a feature of the map.
Asking a single question versus asking no questions is a far more consequential divide than asking one question versus many.
Dan John’s success formula—“show up; ask questions; don’t quit”—has stuck with me for a long time. What’s changed recently, however, is which of the three aspects I consider the most difficult.
Showing up per day and not quitting on the order of years and decades used to flip-flop as the MVPs. But I’m now convinced that asking questions is the hardest thing, the most difficult thing to maintain over time.
Showing up and not quitting can be habitualised, can be scaffolded with lifestyle and sociocultural supports. But asking questions requires a positive equivalent of Mad Eye Moody’s “constant vigilance”. You have to always create a meaningful differentiation between the world as it is and the world your imagination and nerve can compose.
The intellectual cost of that never gets near zero. The social cost of that—especially asking about the most potent compositions—never approaches zero either.
In fact, “On a long enough timeline the question rate for everyone drops to zero.” So congratulations on asking even one question today.
The accelerationist arc: “You can just do things” > “You can just say things” > “You can just intend things.”
Proposed stack for continuously unhinging one’s thought:
Pair the above with a collection of public/private scenes in which one has varying degrees of reputation and influence to pull and push ideas from, and it’s possible to maintain high quality unhingedness.
Having standards versus not having standards is a far more consequential divide than high standards versus low ones.
The former is about escaping the lowest level of competence (unconscious incompetence), whilst the latter is about navigating the upper three levels.
In ode to Bill Simmons’ pyramid for the basketball hall of fame, I was thinking about candidates for the pyramid of autonomous software engineering principles.
Tier one: compression (densify over time with via negativa and abstractions)
Tier two: time travel (use version control to jump forward/backward in time) and verification (assure invariants and test objectives using formal methods)
Tier three: parallelisation (simultaneous workloads to minimise time), scoping (config tasks to require minimal context, minimising cost and maximising leverage of model capabilities), and [insert something else].
There’s no such thing as a free market. There’s only markets that concentrate power, within which a minority of power holders systematically reshape constraints to capture more value.
If reality is fundamentally discrete, then we will forever have to invent a rationale to accommodate the motion we experience. If reality is fundamentally continuous, however, and inherently in motion, then we may be able to avoid having a rationale at all.
AI diffusion be like: Jevon’s Paradox; Goodhart’s Law; Veblen goods; Bataille’s accursed shares; Baudrillard’s simulacra; Polik’s Exocapitalism take-off.
World Machines 101:
Feels like the Liveness machine will have to do with grounding. More embodied, more here-ness, more The Alchemist / Hero’s Journey inevitable return to the point of departure in an altered state.
Not woo embodied; just more grounded in biological, squishy paradigms.
Two wonderings about virtue.
First: does virtue have a normal distribution or a Pareto distribution? Are most people kinda virtuous, or are a few incredibly virtuous and most just, uh, not?
Second: is virtue inflation a phenomena? Over time, does the weight of a virtuous act go less far?
That “the only constant is change” is true is so annoying. But it also operates at a meta level; every change has its own changeable positive or negative interpretation. Also very annoying.
The year is 2126. We live in the pods. We eat the bugs. The machines are post-ascendant, and the world is burning. Someone is still rolling their own tiny web publishing tool.