The fun and still mostly unexplored thing about LLMs is that despite their reputation for verbosity they have this uncanny ability to interpret (and produce) extremely terse encodings of foundational ideas in all kinds of glyphs and pictograms.
What the @pontifex is saying is that as local entropy goes down, global entropy goes up and inter-cluster mutual information goes to zero when agents minimize Kullbach-Leibler divergence with similar neighbors, leading to increased Jensen-Shannon divergence between bubbles.
If you define philosophy as the most convoluted way to not find an answer, then all of this makes sense.
Imagine your job is to navigate a maze. At each (binary) branching point there is no information in which direction to proceed, so likelihood of picking the right direction is 50%. Would you pay for a service that paints arrows on each point, but the arrows are only 70% correct?
Franco Modigliani at Carnegie Tech, now out on Seemingly Incompatible. https://carnegietech.substack.com/p/franco-modigliani-at-carnegie
Kleiner Kreativitätsschub am Wochenende ;)
Was auch immer Ihr über #Marktgebietsmodelle im #Einzelhandel wissen wolltet, aber Euch noch nie zu fragen getraut habt. Und wie ich sie in #Python umgesetzt habe:
https://medium.com/@geowieland/oldie-but-goodie-market-area-models-and-retail-location-analysis-in-python-9f6609355585?source=friends_link&sk=a0314d63cee214cda92aa8fd13d92b64
#EconomicGeography #GIS #Marketing
Best paper I've read so far this month:
All elementary functions (sin, cos, tan, exp, log, powers, roots, hyperbolic functions, π, e, and even basic arithmetic) can be generated from just one binary operator:
eml(x, y) = exp(x) − ln(y)
…plus the constant 1.
I'd say most of my work over the last two-ish years resembled plugging patch cords into a modular synthesizer, and tbh, that's what human effort will look like in the foreseeable future.
There are so many layers to the dollar story that transcend conventional market economic dynamics. Until investors realise this I do believe they will be caught out by narratives that serve political agendas not reality.
Crucially, most “end of the dollar” takes completely miss the point and purpose of why the system came to be in first place. This had much less to do with Americans living beyond their means and much more to do with protecting capitalism and its open, property-rights-based economic order from rival systems that did not have to be accountable to such free market forces.
The central challenge emanating from the Cold War was not simply ideological or military — it was structural.
Command economies could direct resources at scale into strategic and military priorities without regard for market signals, profitability, or consumer welfare. Market democracies, by contrast, were constrained by inflation, capital costs, voter expectations, and financial discipline. Left on their own, market economies risked being outcompeted over time by rivals that could forcibly allocate capital into dual-use industrial capacity and military buildup without internal resistance.
The American “statecraft” solution was not to abandon markets, but to reorganize how they operated at the system level thanks to the cunning use of allies with guilty consciences due to historic war debts. And later petro states. The dollar-based order, and the alliance structure built around it, was designed to distribute economic roles in a way that neutralized those constraints.
Industrial allies such as Japan were encouraged — implicitly and explicitly — to pursue state-guided, export-led growth, building high-quality manufacturing capacity and running persistent surpluses.
Those surpluses were then recycled (on a gentleman’s agreement basis) back into dollar denominated private sector assets but also, crucially, into US government issued debt in a way that suppressed funding costs enough to ensure the U.S. could maintain its very substantial military industrial complex advantage.
That in turn allowed the United States to maintain an edge - even in a capitalist free market system - in defense, advanced research, and system integration, without having to bear the full economic burden domestically.
By externalizing parts of the industrial base and anchoring global finance in dollar demand, the system allowed market-based democracies to sustain a level of military competition that would otherwise have triggered destabilizing inflation, rising interest rates, and political backlash.
The dollar’s role was therefore not simply a privilege, but a mechanism: a way of converting allied industrial output and savings into strategic capacity.
From the allies’ perspective, the bargain was equally clear — access to U.S. markets, security guarantees, and the protection of property rights within a stable global framework. This was something they would not get from the other super power in the mix: the USSR.
Seen this way, the system was never about excess consumption or imbalances for their own sake. It was a deliberately constructed architecture to ensure that an open, capitalist order could compete with — and ultimately outlast — closed systems capable of mobilizing resources without constraint. The durability of the dollar is therefore not an accident of history, but a reflection of the enduring logic of that arrangement.
Pretty much all the attention-whoring posts on Insta are written by Claude now.
I'm used to most economists staring at me blankly when I tell them 80% of economics is combinatorial, but apparently the same goes for computer science.
In yesterday's Claude session I shouted at it at least twenty times for not reading the fucking protocol. In today's session three more times. In-between it wrote two dissertations. Pretty clearly for most people this kind of extreme divergence is too much cognitive overload.
We're not that far from the point when the AI comments in the comments sections will be the reasonable and informative ones, and the only way to identify yourself as human is by displaying distinctive human inadequacies.
World peace formalized.
X=⋃U_i; {Y_i}→{𝔽_α}; Λ(𝔽_α)=0; F=Σ(N+κ−E_lin):
world peace ⇔ ∃{𝔽_α}: Λ=0 ∀α ∧ F minimal ∧ Γ_inter bounded
= parsimonious metapartition with coexistence + no divergence
Formalized Occam's razor:
argmax_C P(C)=argmin_C |A(C)| s.t. L⊔A(C)⊢C
JΩ=QΩ, E=E_lin−N ⇒ plausibility ⇔ N minimal under sufficiency.
Sometime in early 2025 there was a sharp separation btwn the people who realized that LLMs could produce superintelligence under certain conditions, no matter how narrow or brittle, and went full in, and the ones who read something about how these machines could not be trusted.
We can label the era from 1995 to 2025 as "the time we forgot that supply chains existed".
We had task-specific superintelligence in early 2025. Since then it's mostly become broader. The one thing that's left untouched for humans is conceptualization. And that's something most humans are not particularly good at.
So this ad in my feed claims that we're inundated with AI slop because half of the internet is AI-generated and we can't tell which half. Which pretty much means the other half of the internet is human-generated slop?
Iow, with the right tools you can replace ten times as many managers as coders, and you even do the world a favor.
R to @DrDaronAcemoglu: Thanks for the ping @CemFDagdelen!
R to @DrDaronAcemoglu: If you don't realize that knowledge work is a three-step process bc all you ever learned is the middle step, then you can come to the conclusion that everything you know will be automated away. It's just, well, a parochial view. In any case, paper is here. https://drive.google.com/file/d/1XWjBrTsLm-dxoyHXcr_JvgYw23IiPPkg/view?usp=sharing
R to @DrDaronAcemoglu: My favorite Drucker quote applies here, "The first task of knowledge work is to find out what the task is." Problem is that academia has stopped producing knowledge workers in the 1960s in favor of strict formalizers. Herb Simon used to complain about that.
R to @DrDaronAcemoglu: I understand the remonstrations of academics, the Baumol cost disease that kept them gainfully employed is currently being washed away at brutal speed. I produce enterprise grade modeling in hours to days now. If all you can do is that middle part slowly you're in deep trouble.
R to @DrDaronAcemoglu: Once you introduce that starting point, and conjecture that the competitive advantage of machines lies in the "operational middle", the human comparative advantage falls out immediately: the beginning and the end, aka the impetus and the sign-off.
R to @DrDaronAcemoglu: We've been thru a bunch of "computers will kill us all" scares before, and somehow we still made it thru ok. Human effort and cognitive specialization are endogenous and via Schumpeterian recombination we tend to find niches of comparative advantage that keep us employed.
R to @DrDaronAcemoglu: Tbf the total effort (mine plus Gemini's) was about half an hour on the way to a concert and between sets. This wasn't run thru any enterprise grade tools, and I used Gemini bc the other LLMs were busy with more important stuff. But even at this stage it pinpoints the fatal flaw.
I was asked what I think of @DrDaronAcemoglu's new AI paper, so I outsourced the task to @GeminiApp: "Attempting to save human cognition by mandating operational friction is the intellectual equivalent of taxing tractors to preserve the agronomic knowledge of manual plowing."
Crucially, this is not biological exceptionalism. If an artificial system ever becomes conscious, it will be because we engineered the correct intrinsic physical dynamics (the territory), not because we ran a sufficiently complex algorithm (the map). 5/5
The biggest problem with enterprise LLM adoption is that the output resembles craft beer: sometimes stellar, too often just some weird murky concoction, when industry mostly needs dependable ok-ish Bud Light.
I always found "everyone stops looking when the answer matches their priors" the most parsimonious of all world models.
The increasingly common fail mode for "PhD level intelligence" frontier LLMs is "can't be arsed".
Just a PSA that @claudeai destroys whole chat histories. I guess that's the kind of stuff that happens when you're a multibillion $$$ company and you vibecode your whole codebase.
Essential reading from @oliverbeige
#stocks #flows #transformations #operationsresearch
#economics #statistics #compsci #appliedmathematics
https://econpatterns.substack.com/p/stocks-flows-transformations-the
The lesson of the last few years should be that almost everyone is perfectly fine with the state turning sinister, as long as it turns sinister in their preferred direction.
Charles C. Holt, engineer, economist, forecaster, now out on Seemingly Incompatible: Bounding Rationality at Carnegie Tech, 1949-74.
https://carnegietech.substack.com/p/charles-c-holt-engineer-economist #econtwitter
Vendors can impose terms of use on their products as part of a sales contract, prospective buyers can seek alternative vendors if they disagree with the terms. Nothing to see here except everyone going completely overboard.
If you feel compelled to split your workforce in half "because AI", you should consider splitting them into "new thing" and "old thing" instead of "unemployed" and "still employed", especially if you have access to risk capital and you're not running out of ideas @jack & @blocks.
R to @oliverbeige: COBOL was never the bottleneck. Despite its unhip reputation, it's gotten the job done for 60+ years, and there's no reason to replace it bc of any problems with COBOL itself. The only reason was that there weren't any coders left. And that's solved now.
https://x.com/i/status/1906054100669612219