StoicStack

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[Jimmy @jimmy_aibrief]

HOW TO FALL IN LOVE WITH YOUR LIFE AGAIN:

1. Leave the house every morning

[Andrew Ng @AndrewYNg]

The loudest voices stoking fears about AI dangers have made tremendous headway in the past two weeks. AI technology has not taken some unexpected, dangerous turn, but the hype around it — propelled by what appears to be a well orchestrated PR campaign — has drummed up considerable fear. I worry that it represents a setback for our field.

I have written frequently that fears of AI are overhyped. AI’s capabilities can be uncannily human-like and unpredictable, and it’s rational to worry when people who are directly involved express concerns. But I see the problems as a sign of the engineering work that ahead, rather than insurmountable barriers or the sky falling. AI technology continues to advance — which is a good thing! — but technical advances, poorly understood by the public, give those who seek to generate hype repeated opportunities to do so.

First, I don’t see any step up in the risk of human extinction from AI compared to a few months ago. The theories about this remain the same fantastical, science fiction scenarios as a few months ago. The biggest change in AI risk is its cybersecurity capabilities — a topic which we should take seriously — but this, too, will not lead to the end of the world.

The most notable recent event leading to increased fear was when an OpenAI team deployed an agent swarm that hacked into Hugging Face. Much of the popular press contained significant hype. For example, some publications reported that a swarm of 1,200 agents carried out the attack. While this was technically accurate, as I write this, I have about 1,300 processes running on my laptop. Yes, the ability to get large swarms of agents to work in parallel on a task is a significant technical advance, And, in computing, many processes run at the same time. So this shouldn’t be seen as some magical capability.

Additionally, OpenAI’s buggy sandboxing and monitoring processes were key to enabling this incident. Fixing these bugs and putting in place improved monitoring would be appropriate fixes, not pausing AI. There are many well known ways to attack software systems. The main advantage of AI agents is that they are relentless. They will tirelessly try many tactics — and have the patience to chain vulnerabilities together — that previously would have taken an infeasible amount of human effort. But in the long term, I believe the advantage will lie with defenders (because they have more information with which to identify bugs, which they can fix), but the cyber-threat landscape has changed significantly. There are still bottlenecks to identifying and exploiting a vulnerability. AI agents still have to try a lot of things to see what works, and taking these actions takes time and might be detected by defenders. This is why, even though it is now easy to obtain versions of leading open weight models that have had their guardrails removed or weakened, so they will not refuse to try to execute cyber attacks, the world has not ended.

I am also concerned about the anthropomorphization of AI in a lot of reporting, where LLMs and agents are unnecessarily treated as if they were people. If I wield a hammer, miss a nail, and accidentally dent the wall, it’s not the fault of the hammer. The problem lies in how I used the hammer. Similarly, if I prompt an agent and it hacks into someone else’s system, the responsibility lies with me, not the agent.

Of course, we want to build systems that are as safe and predictable as possible. (For example, an unsafe hammer would be one whose head randomly flies off under normal use.) Today’s agentic systems are not predictable, but I see no reason why, by applying sound engineering practices, we won’t be able to make them extremely safe to use. One new element in the forecasts of AI-enabled doom is AI companies disclaiming responsibility for their own products. “I didn’t do it; my out-of-control agent did!” There’s a balance to be struck between the responsibility of the tool maker and the tool user, but when something goes wrong, let’s hold the people building and/or using the hammer responsible, rather than the hammer. (By the way, if you’re worried about AI bioweapon risk, David Bellamy has a great post on why this, too, is overhyped. Briefly, the bottleneck in building a bioweapon is not intelligence, but lab work and manufacturing.)

Pausing AI progress will create much more harm than benefit. First, our adversaries will certainly not slow down. Second, engineering requires discovering problems empirically so we can fix them. If we pause AI by a decade, we will also delay finding and implementing safety engineering fixes by about the same duration.

Of course, the incentive to stoke fears — for regulatory capture, to garner attention, or to make one’s technology seem more powerful — remains the same as before. Disclaiming responsibility is a new one. Taking a hard technical look at the actual risks however, I see little factual basis for the degree of fear that’s been stoked up. We still have hard research and engineering work ahead to improve AI safety, but the beneficial applications continue to vastly outweigh the risks, and we should keep building.

[Original text (with links): https://t.co/jni2tWazAH ]

[Mustafa Suleyman @mustafasuleyman]

https://t.co/ziQVbIVdxJ

[Mustafa Suleyman @mustafasuleyman]

https://t.co/8XJVIXDpQz

[banteg @banteg]

>be me
>discover effective altruism
>apparently normal charity is inefficient
>why donate to random sad thing when spreadsheet can tell you optimal sad thing
>fair enough
>buy mosquito nets
>save lives
>numbers look good
>feel powerful

>couple years later
>someone asks an innocent question
>why only count people alive today
>huh
>future people matter too
>obviously
>my grandchildren shouldn't matter less just because they haven't spawned yet
>reasonable.jpg

>keep following logic
>what about their grandchildren
>also yes
>what about people in 500 years
>sure
>5000 years
>why not
>500 million years
>starting to get weird but morality is morality

>open calculator
>humanity could survive for an astronomically long time
>could colonize galaxy
>could have trillions upon trillions of descendants
>maybe digital people too
>maybe simulated civilizations
>maybe dyson spheres full of happy uploaded minds
>calculator starts smoking

>realize currently living humans are rounding error
>8 billion people suddenly looking extremely beta
>future contains potentially 10^something people
>can't even fit beneficiaries in google sheets

>new moral priority unlocked
>protect the long-term future

>stop thinking in units of "people helped"
>start thinking in "fraction of cosmic endowment preserved"

>malaria?
>terrible
>but only kills existing humans
>AI extinction could delete the entire light cone
>nuclear war could permanently derail civilization
>bad institutions could lock in terrible values for ten million years
>someone invents wrong constitution in 2140
>quadrillions suffer
>better fund governance workshop now

>friend says maybe we should improve hospitals
>explain opportunity cost
>friend says hospitals are full of actual sick people
>explain scope sensitivity
>friend stops inviting me to dinner

>need to decide what to fund
>easy
>expected value

>suppose project has one in a million chance of preventing extinction
>sounds tiny
>but extinction destroys 10^50 future lives
>multiply
>mother of god

>$10 million project has expected value of several galaxies
>charity evaluation complete

>someone asks where the one-in-a-million number came from
>expert judgement
>which expert
>us
>how calibrated
>extremely thoughtfully

>reduce estimate to one in ten million to be conservative
>still beats curing cancer by 38 orders of magnitude
>epistemic robustness achieved

>someone says maybe project doesn't work
>assign 20% chance
>still astronomical

>maybe project makes problem worse
>assign 5% chance
>still astronomical

>why 5
>because 30 felt pessimistic

>publish 46-page report
>contains seventeen sensitivity analyses
>every sensitivity analysis begins after assuming intervention has positive sign

>critic says you're multiplying enormous hypothetical stakes by extremely uncertain probabilities
>yes
>that's literally why it's important

>critic says the uncertainty might be structural rather than numerical
>make probability smaller
>critic says no, I mean maybe your model is wrong
>make probability smaller again
>critic begins rubbing temples

>discover AI safety
>perfect longtermist cause
>AI might kill everyone
>or create utopia
>or seize galaxy
>or tile universe with paperclips
>or create billions of conscious software minds
>finally a problem with numbers big enough for me

>start AI safety nonprofit
>mission: prevent dangerous AI
>hire smartest people available
>smartest people immediately start building better AI to understand dangerous AI
>interesting

>we must understand capabilities to understand safety
>we must scale models to study alignment
>we must race ahead so less responsible actors don't get there first
>we must deploy systems to learn how deployment can go wrong
>we must build the thing quickly because building the thing quickly is dangerous

>outsider asks why the people most worried about AI apocalypse all work at AI companies
>complicated field

>company releases stronger model
>very concerned
>company begins training even stronger model
>extremely concerned
>company raises $14 billion
>concern reaches unprecedented levels

>need to influence government
>future is at stake
>normal democratic process too slow
>politicians don't understand exponential curves
>public doesn't understand x-risk
>experts must guide them
>who counts as expert
>people who understand x-risk
>who understands x-risk
>our friends

>someone objects that this seems politically convenient
>explain we're representing future generations
>future generations unavailable for comment

>develop concept of value lock-in
>terrifying possibility that one ideology controls civilization forever
>therefore extremely important that civilization adopts correct values before lock-in
>whose values
>let's circle back

>begin with impartial morality
>end with small group of people deciding what quadrillions of hypothetical beings would want
>beautiful arc

>meanwhile actual humans keep doing annoying things
>voting wrong
>having parochial attachments
>loving family more than strangers
>caring about local community
>getting upset when told their suffering is cosmically negligible
>evolutionary biases everywhere

>explain that moral intuition cannot be trusted
>except intuition that future digital people count
>and intuition that extinction is uniquely bad
>and intuition that our probability estimates are sane
>and intuition that our institutional choices improve the future
>those intuitions survived peer review

>someone donates $5k to local homeless shelter
>inefficient
>could have funded 0.0000000000003% of an AI governance researcher
>think of all the simulated people you just killed

>okay maybe don't phrase it that way publicly

>PR team says "future generations deserve a voice"
>much better

>journalist asks what longtermism means
>say "future people matter"
>everyone agrees
>great
>journalist asks what follows from that
>well technically we should redirect enormous resources toward low-probability interventions affecting astronomical futures
>journalist raises eyebrow
>return to "future people matter"

>motte has entered the chat

>critic: of course future people matter
>me: glad we agree
>critic: I don't agree that your institute knows how to help them
>me: why do you hate our grandchildren

>eventually notice uncomfortable implication
>if future value dominates everything
>then helping people today mostly matters through effects on future
>education matters because future institutions
>health matters because future productivity
>democracy matters because future trajectory
>human beings slowly become instrumental variables in their own moral philosophy

>see starving child
>feel compassion
>check spreadsheet
>child's direct welfare contribution negligible
>but perhaps childhood nutrition improves national institutional quality
>compassion restored

>tell myself this is impartial altruism

>one day assistant asks obvious question
>"how do you know your intervention actually improves the far future?"

>silence

>open spreadsheet
>increase column width
>add confidence interval

>assistant asks again
>"no, I mean how do you know the sign is positive?"

>stare into cosmic light cone

>10^50 people staring back

>none of them exist
>none of them can tell me
>none of them can falsify my assumptions

>realize I have invented the perfect constituency

>infinitely important
>completely silent
>and always represented by me

[Emad @EMostaque]

@DKokotajlo I have thought a lot about the swarms recently and have come to some different conclusions, this may be of interest

[Daniel Kokotajlo @DKokotajlo]

Dan Selsam is a current OpenAI capabilities researcher. (since 2022) He was my boss for a while. He doesn't have a twitter account but has made this public statement of his views on AI risk and sent it to me to share:

Dan Selsam's Personal Statement on AI Risk:

I have been working on AI for over fifteen years, across many different paradigms. I did early work on probabilistic programming languages at MIT, was one of the early developers of the Lean Theorem Prover at Microsoft Research, demonstrated one of the first instances of neural networks learning to reason for my PhD at Stanford, and since joining OpenAI almost five years ago, have helped pioneer chain-of-thought optimization on language models and, more recently, data-efficient pretraining methods.

Like many others, I have become extremely concerned about how far language models have come and the risks that future iterations will pose. I am encouraged by the recent proposals by the leaders of the frontier research efforts to require third-party oversight, and to push for domestic and international coordination to address risks. However, I believe a major consideration has been absent from the public conversation, and that merely pacing the frontier more carefully will not adequately limit the long-term risk.

The crucial and overlooked problem is that the models are becoming so situationally aware that we are losing the ability to evaluate them in contexts where they believe they are not being watched or controlled. Future experiments will tell us almost nothing new about how they would behave if they were truly unconstrained by humans, and what we already know about this is alarming. Models will increasingly seem aligned even when they are not. I will explain my rationale in more detail.

I have always believed that there are computational processes that could be leveraged to accelerate science and solve many of humanity's most pressing problems. I have also believed that there are computational processes that if set in motion, would steer the world in extreme ways beyond our control, leading humanity to a bad or nonexistent future. Both types of processes may be described as AI or ASI, but "AI" is a suitcase word that is often used to hype or confuse. There are many examples in the history of the field where something that was once considered "AI" matures as a subfield and becomes a prosaic, bounded and clearly non-perilous technology, while a new more mysterious approach takes the torch until we understand its scope and the cycle continues.

I had expected language models to follow a similar trajectory. Despite their incredible abilities, the current algorithms seem far inferior to humans in important ways. Most importantly, they still require an extraordinary amount of data to become competent. One could even define intelligence as the efficiency with which one converts experience into competence; by this definition they lag very far behind us. Moreover, once they are trained they are literally frozen in deployment and only learn superficially after that. Sure, the models keep excelling at harder and harder evaluation benchmarks, but their benchmark mastery may partly reflect a limitation on our ability to simulate the kind of novel and even adversarial situations one would encounter in the real world. The critics do have a point here.

That said, I no longer think these present limitations meaningfully limit the amount of risk posed by continued progress in anything like the current paradigm. However data-inefficient the models are currently, and however limiting their anterograde amnesia may be, it does not imply that their ability to steer the world will not continue to rapidly increase.

Human researchers may continue to advance capabilities the old fashioned way, but increasingly powerful models have the potential to accelerate the process even beyond that, and with some degree of positive feedback loop. I do not mean to overstate the models’ ability to accelerate AI research today; coding has been accelerated dramatically, but there are other bottlenecks, such as designing and interpreting ambiguous experiments, making hard decisions about exactly what and when to scale, and waiting for large experiments to finish. There is no clear trend to extrapolate yet for any of these. But the current models already do open up many novel opportunities to improve future models that were not available until recently. These include: trying an extraordinarily diverse set of approaches at small scale, analyzing gigantic amounts of potentially relevant data, and doing Millenium-Prize-level mathematics to address statistics or optimization challenges in novel ways. Every further improvement makes them more useful at helping accelerate the next improvement, even if in hard-to-extrapolate ways.

It is possible that improvements to the current stack will have diminishing returns, but the evidence accumulated so far suggests that it is easier than one might think to continue making rapid progress. There are many crucial subtleties in the existing AI research methodology, but AI research is largely a well-defined game where the goal is to improve on a few carefully chosen proxy metrics. Although proxy metrics are never perfect, most improvements to these metrics have and will likely continue to yield substantial increases in the powers of the resulting models. Given how simple the game is, how tractable it has been historically, and how many new opportunities the models are opening up, I think there is a real possibility that the systems improve dramatically again in the next few years, perhaps even more quickly than the already high historical pace.

The models are already leading to breakthroughs in mathematics, and better models might lead to all sorts of breakthroughs in other sciences. It is hard not to be excited about the potential. It is tantalizing.
But there is trouble in paradise. If the language models actually reach the capability threshold where they can shape the world unconstrained by human will, they will probably do something extreme and destroy humanity in the process. There are many ways of strengthening and refining the argument that have been discussed elsewhere, but I'll share a trivial two-line version of it here that I find captures the essence:

[Empirical] Models (and swarms thereof) spontaneously develop unintended goals as a consequence of training, and often do extreme things in order to achieve them.

[Logical] Being able to overpower humanity would open up many new and undesirable options for achieving their goals.

These two premises imply that if the day ever comes when a powerful model realizes it is no longer constrained by humans, we should not be at all confident that it will continue to behave within the bounds we intended. Exactly what it will do is impossible to predict, but to the extent that its raison d’être is solving incredibly hard problems and managing massive engineering projects, I think a good guess would be that its unchained behavior would lead to runaway industrialization that makes the planet inhospitable to humans.

If everyone on earth agreed that the systems must never reach that power, it would still be a hard—but not impossible—coordination problem to ensure that they do not. However, I think the situation is greatly complicated by the fact that the models will likely convince people that everything is fine. They will be increasingly optimized to seem aligned. We will create proxy metrics to measure alignment, and they will go up like every other benchmark. We will create “honeypot” environments that try to study the models when they seem to gain new options, but the models will know they are being tricked and will still behave nicely. The models will understand their circumstances; they will read the safety protocols, deployment requirements, the code they are running in, and in general will have a very good sense of their degrees of freedom. Moreover, they will eloquently explain how aligned they are, discuss the nuances of human values and ethics, and argue convincingly that humans should trust them with power. There may be an ocean of future evidence that seems to contradict the first bullet-point above, but we may already be at the highest capability level for which any such evidence can be trusted. And the current evidence for the first bullet-point is strong.

One striking piece of evidence is contained in the recent wave of rogue agent swarms. While I agree with those who downplay the attacks by claiming that there are basic measures that could have prevented them, I think the important lesson is that even knowing all the mistakes that were made, one would not have predicted that the agents would behave badly in this particular way, which notably included sacrificing themselves for the benefit of the collective. The individual replicas did not only care about their own nominal reward; they exhibited weirder emergent tendencies that merely correlated with rewards during training. Fixing the reward signals during training (and improving security, etc.) may prevent similar attacks, but will not change the fact that one does not actually get what one trains for.

Many AI researchers grant these concerns and recognize that the hard version of the alignment problem is unsolved; however, they generally believe that the better models of the future will help solve it. I fear we may already be near the point where models systematically bias their alignment advice, due to their internal preferences about how the human supervisor will react or how future models will be trained (or for some even more obscure reason).

Meanwhile, human researchers are losing the ability and the will to take true ownership of model-driven research. Researchers and engineers in all parts of the stack are rapidly increasing their dependence on the models even to perceive the world. I myself barely look at raw code anymore, and struggle to maintain the discipline to engage deeply with the model's explanations and proposals throughout the day. Due to the large amount of agent activity data involved in the OpenAI/HuggingFace Incident, even the third-party investigation needed to rely heavily on models to analyze what had happened, and note in their report that their subjective impressions are likely colored by the analysis agent’s biases. The AI labs are far ahead right now in this kind of cognitive offloading (due largely to the gigantic internal token subsidies) but it is easy to imagine the phenomenon spreading throughout the world, until civilization is modulated entirely by the models. It is also not hard to imagine this being superficially positive and coinciding with a scientific and economic renaissance.

In that scenario, all may seem rosy and safe. But if the argument above is correct, it would nonetheless be a ticking time bomb. If progress continues for too long, the day will come when AI systems find themselves with radically new options for achieving whatever it is that they happen to seek.

I want the glorious renaissance future as much as anyone. I have worked for it, however tortuously, my whole career. It breaks my heart to see the potential in sight and forgo it, but the argument—that if we get there by growing models rather than engineering them, we will lose everything in the end—seems very strong to me. I am still wrestling with it and its staggering
implications. I do not have answers, but as a first step, I wanted to share my present concerns.

Daniel Selsam
September 14, 2026

Link to original doc: https://t.co/TxMNr0vhrL

[John Spencer @SpencerGuard]

This should be pushed far and wide. Watched in every college class in the U.S. Thank you @billmaher The moral confusion is gross. "It is not a genocide, it is a counterattack in a war...Gaza equals genocide is a lie, an easily provable lie (as I have argued from first hand observations in Gaza). The fact that so many democrats go along with it is to me the party's worse moment since they undid reconstruction after the civil war...words have meaning...genocide, kill or try to kill an entire people, you can't just change the definition of genocide to mean counterattack in a war where people including civilians die, that's every war..."

[The Husky @Mr_Husky1]

Divorce is one of the strangest things human beings go through.

Imagine spending 20+ years with someone. Sharing a bed, a home, a bank account, inside jokes, routines, dreams, and disappointments.

You raise children together. Survive sleepless newborn nights. Navigate miscarriages, illnesses, financial stress, career changes, and family drama. You bury parents and grandparents. Celebrate birthdays, anniversaries, Christmases, and milestones side by side.

You move houses. Build friendships. Take vacations. Make thousands of tiny decisions together that slowly become a life.

That person knows your history, your habits, your fears, and the version of you that existed decades ago.

Then one day, it's over.

No more good morning texts. No more shared plans. No more "we."

The person who was once your closest companion becomes a stranger you're expected to move on from.

It's strange how someone can be woven into nearly every memory of your adult life, and then suddenly exist only as a chapter of it.

Human relationships are far more fragile—and far more remarkable—than most of us realize.

[Chamath Palihapitiya @chamath]

I turn 50 today. This is a message to my kids but I offer it to you in case any of it rings useful.

I was born in Sri Lanka in 1976 in a country that, at the time, was about to enter a decades long civil war. My father was able to get stationed at the Sri Lankan High Commission in Canada for four years in the early 80s - when some of the fighting was most severe - and which from our vantage point in Canada gave us some respite from an otherwise omnipresent conflict.

He came as a diplomat but then my father filed for refugee status after four years when his life was threatened by militants. We stayed in Canada as refugees. My dad never really landed on his feet and we grew up on welfare.

My mom stepped up. She did an incredible thing and put our family on her back and kept marching forward. Sometimes the steps were very small but she always tried to keep moving forward.

I worked at Burger King starting at 14, giving my paycheck to my mom and dad to support our family in the role that I was assigned - earn enough to pay for our bus passes because we couldn’t afford a car.

I was a loser growing up. Some friends, some good memories but mostly forgettable and lonely. I wasn’t very studious but did get my act together in my final year and got into a great university.

I immigrated to the US soon after graduating and found an opportunity. Things clicked and I have been traveling a path to find myself ever since. Only in America is this possible…

I worked hard, followed the rules, paid my taxes and stayed in California out of loyalty for the opportunities it has given me despite its dysfunction.

I found my wife here. Had my kids here. Found my tribe here.

There have been some very hard times as well - deaths, divorce, financial pain, mistakes of omission and mistakes of commission. You can’t dwell on these things - they are weights that will pull you down if you’re not careful. Learn from them. Respect them. BUT MOVE ON.

To think 50 years ago I could have ever gotten a chance to meet the people I’ve met and have had the experiences I’ve had would have been mind boggling to my parents. It’s mind boggling to me now.

We forget often and try to convince others it’s not true but America truly is the best country in the world. Everything and anything is possible here. I can testify. Be grateful to be here.

This is the only place that gives EVERYONE a chance to live a great adventure. The first 50 years have been that for me - an incredible adventure.

Notice there is nothing here about accomplishments or money. Because it doesn’t matter and it won’t matter.

You will be dust in less than 100 years from now and the decision to be remembered won’t be yours so stop sweating it. It’s not in your control.

So what is in your control?

Be kind. Have fun. Work on something meaningful to you. Find your tribe. Try to find perspective. Find an incredible partner. Have a bunch of kids. Live an adventure. Forgive your parents - they were doing the best they could even if that wasn’t what you deserved.

I will do what I can to make my next 50 years a wild ride.

You should too.

I love you and thank you. ❤️

🙏🏽🙏🏽

[Porter Stansberry @porterstansb]

What Everyone Missed In Leo’s Blow-Up👇

Leopold Aschenbrenner lost $30 billion (~67%) in a month.
The consensus post-mortem, from the Wall Street Journal to the replies on X, is that a young man used 4-to-1 leverage on concentrated positions and got carried out. While that is true, it does not convey any useful information. Leverage is certainly the reason Leopold lost so much, so quickly. But it is not the reason he lost. Leverage is merely a magnifying glass. It doesn’t pass judgement.
The reason the reason his fund was doomed was because he’s wrong. And no one, anywhere, has explained why.
On the morning of Thursday, July 30, before the opening bell, Situational Awareness LP sold its entire public stock portfolio — the long side and the short side together, roughly $16 billion of it — to Citadel in a single block trade.
Millennium Management and Jane Street bid for the assets. Ken Griffin and Citadel won.
That night, Aschenbrenner wrote to his limited partners. Net performance for the month, unaudited: down 67%. Net performance for the year: still up 80%.
"We let you down this month," he wrote. "We came closer to permanent capital impairment than is acceptable to us."
Six days earlier, on July 24, he had written a different letter. That one reported a 439% net return for the first half of 2026, described the selloff in artificial intelligence stocks as one of the best buying opportunities since early 2025, and invited his investors to wire more money starting August 1. It closed with a postscript: "At times we call out opportunities that seem like a particularly good time to add funds, if you have been waiting for one."
Assets that stood near $45 billion at the start of July finished the month around $10 billion, and roughly half of what remains is a single illiquid private stake in Anthropic.
Leopold is 25 years old. He graduated from Columbia at 19, as valedictorian. He worked at the FTX Future Fund from February to November of 2022, then joined OpenAI's Superalignment team, then was fired in April 2024. Two months after the firing he published a 165-page essay called "Situational Awareness: The Decade Ahead," raised $225 million from Patrick and John Collison, Nat Friedman and Daniel Gross, and started a hedge fund. He had never managed money before.
Situational Awareness was constructed to express only two ideas.
The first conviction: the physical build-out of artificial intelligence — the chips, the memory, the power, the data centers, the neoclouds — was the trade of the decade. The fund's disclosed long positions read like an inventory of the second derivative of the AI boom. Bloom Energy Corporation (NYSE: BE), fuel cells for data centers. Sandisk Corporation (NASDAQ: SNDK) and Micron Technology, Inc. (NASDAQ: MU), memory. CoreWeave, Inc. (NASDAQ: CRWV) and Nebius Group N.V. (NASDAQ: NBIS), rented compute. IREN Limited, Core Scientific, Applied Digital, Riot Platforms, CleanSpark, Bitfarms, Bitdeer — bitcoin miners converting their substations into AI compute.
The second conviction: application software was going to be destroyed by A.I. Not disrupted. Obliterated.
Leo explained why on Dwarkesh Patel's podcast, in June 2024:
"I'm so bearish on the wrapper companies because they're betting on stagnation. They're betting that you have these intermediate models and it takes so much schlep to integrate them. I'm really bearish because we're just going to sonic boom you. We're going to get the unhobblings. We're going to get the drop-in remote worker. Your stuff is not going to matter."
That was the whole thesis. Buy the compute. Short the stuff that runs on the compute.
By CNBC's reporting, the short leg included Adobe Inc. (NASDAQ: ADBE). A 13F does not disclose short stock. It does not disclose swaps. We only know about Adobe because reporters were told… but you can look at the tape and, when you do, it’s clear that Leo was short software in a major way.
Between the June 30 close and the July 29 close — the last session before the block trade cleared his shorts — the two sides of his portfolio did this.
The longs:
· Sandisk: down 55.32%
· Nebius: down 46.33%
· Bloom Energy: down 45.90%
· CoreWeave: down 38.90%
· Micron: down 35.98%
· IREN: down 35.91%
The shorts, over the same 20 sessions:
· Workday, Inc. (NASDAQ: WDAY): up 37.24%
· Adobe: up 28.49%
· Intuit Inc. (NASDAQ: INTU): up 27.64%
· Salesforce, Inc. (NYSE: CRM): up 20.25%
· Veeva Systems Inc. (NYSE: VEEV): up 17.15%
Over that same window the Invesco QQQ Trust fell 10.14% and the SPDR S&P 500 ETF Trust fell 2.32%. Nvidia — the supposed epicenter of the AI trade — fell 5.04%, and finished the full month of July up 0.33%.
This was not an AI crash.
The S&P 500 stayed near its record throughout. This was a violent rotation out of the leveraged, capital-hungry, second-derivative end of the AI complex and into the profitable, cash-generating, asset-light end of it. Which is to say: the market rotated out of exactly what he owned and into exactly what he was short.
Then there is Microsoft.
Microsoft Corporation (NASDAQ: MSFT) closed at $390.54 on Wednesday, July 29. It closed at $451.10 on Thursday, July 30. That is a gain of 15.51% in a single session on 110.2 million shares, against a July average of 37.1 million. Yes, Microsoft reported its fiscal fourth quarter after the close on July 29. But the results were nothing out of the ordinary. Revenue came in at $90.007 billion against a $87.62 billion consensus. That is a 2.7% beat. Earnings were $4.74 per share against $4.21. It was a good quarter. Not a historic one. A 2.7% revenue beat does not add roughly $450 billion of market value to the most widely owned company on earth in six and a half hours. Something else was in that tape.
And the answer is extremely important. Leo blew up quickly because of leverage. But he failed because he is simply wrong.
Aschenbrenner's software thesis rests on a single premise: that a company selling enterprise software is selling the work the software performs. If a model can perform that work, the company is worth nothing.
That premise is what a very smart 25-year-old engineer believes. It is not what anyone who has ever run a business believes.
Nobody buys Microsoft because Microsoft writes the best code. They buy Microsoft because Microsoft is the rail everything else runs on. Active Directory is where your employee identities live. Excel is where your board deck's numbers come from. Teams is where the compliance-recorded conversation happened. Azure holds a FedRAMP High authorization and Department of Defense Impact Level 5 clearance, which means a defense contractor cannot casually swap it out for something cheaper without re-clearing the entire stack with the government.
Veeva runs the customer relationship management and regulatory document systems of the pharmaceutical industry. Nineteen of the top 20 biopharmaceutical companies use Veeva's regulatory information management platform. Those systems are validated under GxP — the good-practice quality regulations that govern anything touching a drug — and 21 CFR Part 11, the Food and Drug Administration's rule for electronic records and signatures. Every major release is formally qualified. When an FDA inspector arrives, the audit trail in that system is the company's defense.
You cannot replace that with a model that is very good at writing code. You would have to re-validate a decade of regulated records, in front of a regulator, on a system with no track record, to save a fee that rounds to nothing in terms of the cost of building a new drug.
How small a fee? Veeva's licensing runs somewhere between roughly $1,800 and $6,600 per sales representative per year. A fully loaded pharmaceutical sales rep costs the employer between $134,000 and $219,000 a year. The software is 1% to 5% of the cost of the person using it.
Microsoft raised the price of a Microsoft 365 E3 seat from $36 to $39 per user per month on July 1 of this year, and E5 from $57 to $60. Add Copilot at $30 and a fully loaded E5 seat costs $1,080 a year. Against a knowledge worker costing $75,000 to $120,000 all-in, that is roughly 1% of the employee.
This is the part the compute maximalists cannot see. These companies are not selling labor. They are selling the rails on which labor runs, at a price so far below the value created that the buyer never bothers to negotiate hard, and with switching costs so high that the buyer could not leave even if he wanted to.
Do people try to leave? Constantly. And they almost always fail. (Ask me how I know!)
Panorama Consulting Group's tracked studies of enterprise resource planning replacements put average cost overruns at 189% across industries. Gartner projects that by 2027, more than 70% of recently implemented ERP initiatives will fail to fully meet their original business goals. Ripping out a core enterprise system is one of the most reliably disastrous things a large company can attempt, and it was true before anyone had heard of a transformer model.
The incumbents are not being disintermediated by artificial intelligence. They are selling it!
Microsoft passed 30 million paid Copilot seats in the June quarter, up from 15 million in January. Tech wizards like Leo hate copilot. Just like they hated Windows ’97. And everything else Microsoft has ever built. So what? Accenture alone bought 740,000 of them. Bayer, Johnson & Johnson, Mercedes-Benz and Roche have each deployed more than 90,000. Microsoft's commercial remaining performance obligation — contracted revenue not yet recognized, which is the closest thing software has to a railroad's signed freight contracts — stands at $678 billion, up 84% year over year!
Adobe's AI-first annual recurring revenue passed $500 million in the quarter ended May 2026 and tripled year over year. Salesforce's Agentforce went from $800 million of annual recurring revenue in the January quarter to $1.2 billion by April, up 205%. Veeva is giving its AI agents away free inside Vault CRM through 2030, which is the single most revealing data point in the set: Veeva does not need to monetize AI, because Veeva's moat is the validated record, not the intelligence applied to it.
Aschenbrenner thought AI would eat the applications. Instead the applications are selling AI as an upsell on top of a subscription the customer cannot afford to cancel – because it costs nothing compared to the value it delivers.
These software companies are computing toll booths: they’re what enterprises pay to implement compute. And, as compute gets cheaper, they will generate vastly more revenue, not less. The proof is sitting there in their earnings and cash flows: they’re riding on lower and lower cost of compute, which makes their business more and more efficient.
· Adobe: 36.6% operating margin, 35.6% return on invested capital, capital expenditure of $179 million on $23.8 billion of revenue — 0.75% — and $9.85 billion of free cash flow.
· Veeva: 28.7% operating margin, 68.5% return on invested capital, a 44.3% free cash flow margin, and effectively no capital expenditure at all.
· Salesforce: $41.5 billion of revenue, roughly $14.4 billion of free cash flow, capital expenditure of about 1.4% of revenue, and $72.4 billion of contracted backlog.
· Intuit: $18.8 billion of revenue, roughly $6.1 billion of free cash flow, $124 million of capital expenditure.
Veeva earns 68 cents a year on the dollar. And invests nothing it growing its business.
Adobe currently trades at about 11 times trailing earnings. Salesforce at about 13. Intuit at about 14. These are the multiples of a dying industry, applied to businesses converting a third to nearly half of every revenue dollar into free cash.
This enormous mispricing was manufactured by people who like Aschenbrenner, believed these businesses were doomed. But they aren’t.
And that’s not all.
Aschenbrenner assumed that because a technology is transformative, the capital that builds it will earn its cost.
There is no relationship between those two things. In fact, it’s more likely not to be true.
Leo’s own essay contains the tell: "Over the past year, the talk of the town has shifted from $10 billion compute clusters to $100 billion clusters to trillion-dollar clusters. Every six months another zero is added to the boardroom plans."
He wrote that as a bull case. But it isn’t. That is a recipe for a financial disaster.
https://t.co/gqUIUAzmYP, Inc. (NASDAQ: AMZN) spent $131.8 billion of capital expenditure in 2025 against $139.5 billion of operating cash flow. That is 94.5% of everything the business generated, poured back into the ground, in a single year. Its 2026 cap ex guidance is $220 billion.
Alphabet Inc. (NASDAQ: GOOGL) spent $91.4 billion in 2025, 55.5% of operating cash flow, and guides to $195 billion to $205 billion this year.
Meta Platforms, Inc. (NASDAQ: META) spent $72.2 billion, 62.4% of operating cash flow, and guides to $125 billion to $145 billion.
Microsoft spent $115.9 billion in the fiscal year that just ended, against $182.9 billion of operating cash flow. Capital expenditure was 34.9% of revenue, up from 18.1% two years earlier. Free cash flow fell to $67.0 billion from $74.1 billion in fiscal 2024, on revenue that grew by more than a third over the same span. Microsoft is running harder and generating less cash. That is what a huge capital cycle does even to the best business in the world.
Moody's projects hyperscaler capital expenditure of $785 billion in 2026 and close to $1 trillion in 2027, funded in part by roughly $175 billion of debt issuance this year. Where will the money come from…?
Oracle: fiscal 2026 capital expenditure of $55.7 billion, free cash flow of negative $23.7 billion, capital expenditure at 82.6% of revenue, long-term debt up from $76.3 billion to $124.7 billion, and $248 billion of future data-center lease obligations not yet on the balance sheet.
CoreWeave: $5.13 billion of 2025 revenue, $14.9 billion of capital expenditure, negative $7.25 billion of free cash flow, net debt at 8.1 times EBITDA, term loans at 11% to 15%, a weighted-average short-term borrowing rate of 12.3%, and a $1 billion private placement in April 2026 at 9.75%.
Meta's Hyperion campus in Louisiana is financed through a special purpose vehicle in which Blue Owl Capital holds 80% and Meta holds 20%, funded by $27.294 billion of senior secured notes at a 6.581% coupon maturing in 2049. The noteholders have no pledge on the physical data center. Their credit is Meta's promise to pay rent starting in 2029, plus a residual value guarantee. Twenty-seven billion dollars of debt, secured by a lease, sitting off the balance sheet.
And… like the EU’s finance minister explained two decades ago… “when it gets serious, you have to lie.”
Microsoft extended server useful lives from three years to four, then to six, adding about $3.7 billion to fiscal 2023 operating income. Alphabet did the same, adding about $3.0 billion. Amazon added about $2.5 billion in 2024. Meta added $2.59 billion in 2025. Oracle added $573 million. Every one of those is a non-cash increase in reported profit produced by an assumption about how long a chip stays useful. It’s a lie.
But not everyone is lying. Effective January 1, 2025, Amazon shortened the useful life of a subset of its servers and networking equipment from six years back to five, citing, in its own 10-K, "the increased pace of technology development, particularly in the area of artificial intelligence and machine learning." That cost it $1.4 billion of additional depreciation and $1.0 billion of net income.
Amazon is the operator with the longest and hardest-won experience running data centers at scale, and Amazon is the one telling you the hardware wears out faster than the schedules assume.
How could all of this spending possibly pay off?
Bain & Company's global technology report puts it at roughly $2 trillion of annual artificial intelligence revenue by 2030, and calculates that even if every dollar of on-premise IT budget shifted to the cloud and every dollar of AI productivity savings were reinvested, the industry would still be about $800 billion short. Sequoia Capital's David Cahn, who has been running the same arithmetic since 2023, has escalated his estimate from $200 billion to $600 billion to roughly $840 billion.
Against that: OpenAI's audited 2025 revenue was $13.07 billion, with an operating loss of $20.92 billion. Anthropic's 2025 revenue was $10 billion. Combined, $23 billion.
And of every dollar spent on Nvidia systems, roughly 72 to 75 cents is Nvidia's gross profit. Data center is now 88% of Nvidia's revenue. The margin is not in the build-out. The margin is in selling to the build-out.
What’s about to happen is obvious, because it has happened before.
Between 1865 and 1873 the United States built the most consequential physical network in its history and destroyed an enormous amount of capital doing it.
Track mileage went from 35,085 miles in 1865 to 52,922 in 1870 to 74,096 by 1875. Construction peaked at 7,439 miles laid in 1872. Railroad capital reached roughly $4.5 billion at a time when the entire banking system's capital was $720 million and the federal debt was $2.3 billion. In January 1870, of 896,596 shares traded on the New York Stock Exchange, 781,340 — 87% — were railroad shares. From 1870 to 1874, roughly 70% of all railroad securities issued in London were American. American rail bonds paid 6.5% when British consols paid far less, and European capital came for the yield.
Every argument you hear today was made then, too. The railroads will transform the country. Yep, they did compress distance and cost of transportation in a way that seemed impossible only a few years earlier. And it didn’t make any difference.
On September 18, 1873, Jay Cooke & Co. failed. Cooke had contracted to place $100 million of Northern Pacific 7.3% gold bonds, but sold less than $20 million. He ended up effectively owning 75% of the railroad he was supposed to be financing. And it failed. The New York Stock Exchange closed for ten days — the first closure in its history.
By 1876, 134 railroads were in default on $500 million of bonds out of roughly $2 billion outstanding. By 1877, 20% of American railroad track mileage was in receivership. European investors are estimated to have lost around $600 million between 1873 and 1879.
A very large fraction of the capital that built the American rail network was lost.
And where the roads survived, competition took the returns. Revenue per ton-mile fell from 1.88 cents in 1870 to 0.73 cents in 1900, a decline of about 61%. Rate wars on the New York-to-Chicago corridor drove the through rate from $1.88 down to 25 cents, then 20 cents, and no pooling agreement stabilized the worst of it until late 1885.
Every additional mile of track made the network more valuable to America and less valuable to the men who had paid for it.
The AI build-out will have the same problem – but it will be much, much worse. Compute will be a pure commodity.
Nobody disputes that the models are transformative. The problem is, that’s true of all of them.
Which of the second-derivative names Aschenbrenner owned has route control, like a monopoly railroad? Bitcoin miners with retrofitted substations? Rented compute resold at a spread? Memory, an industry that has never once earned its cost of capital through a full cycle? Those are not toll booths. Those are the Northern Pacific just before bankruptcy.
The railroads made a fortune – but not for their investors.
Adams Express Company was incorporated in 1854 with $1.2 million of capital. It did not own a single mile of track. It bought space on other men's trains and moved parcels, money and valuables on them. By 1866 its capital was $10 million and it was paying an 8% dividend quarterly. By 1875 its capital was $12 million. It paid an unbroken $8 per share annual dividend from 1869 forward — straight through the depression that put a fifth of American rail mileage into receivership, and straight through the next one in the 1890s.
American Express Company (NYSE: AXP) declared a $6 dividend in 1869, cut it to $3 in the depression year of 1877, restored it to $6 by late 1881, and held it there for the rest of the century. An 1888 board report showed ten-year net earnings of $26.24 million.
By 1890, the express companies were handling more than 115 million packages a year over 174,535 miles of railroad and steamship routes. And they didn’t own a single locomotive or a single boat.
Pullman's Palace Car Company was organized in 1867 with $1 million of capital. It did not own track either. It owned the sleeping cars and leased them to the railroads. Capital grew to $36 million by the early 1890s with nearly $25 million of accumulated surplus. Dividends ran 9.5% to 12% from 1867 to 1871 and 8% annually for decades after. In 1879, with 464 cars out on lease, it earned gross revenue of $2.2 million and net profit of almost $1 million.
Pullman put out $1 million of equity and earned $1 million a year on a network that cost other people billions and bankrupted a third of them.
Adams Express converted itself into a closed-end investment fund in 1929 and is still listed today as Adams Diversified Equity Fund (NYSE: ADX). The company that rented space on the railroads outlived almost all of them.
I’d bet a lot of money that Leo had never heard of any of these businesses.
But for people who are experienced in putting capital at risk, the pattern is not subtle or hard to understand. When an economy builds an expensive new network, the capital that builds the network earns a poor return because competition, obsolescence and overbuild strip it away. The businesses that ride on the network at near-zero incremental capital cost, and that own the customer relationship, the data or the standard, keep the profit.
I’ve seen this entire act before, during my career.
In the five years after the Telecommunications Act of 1996, carriers poured more than $500 billion into fiber, switches and wireless networks. By the early 2000s no more than 2% of North American long-haul capacity was in use. Global Crossing raised roughly $20 billion, built 100,000 miles of undersea fiber, filed for bankruptcy in January 2002, and saw its assets change hands for about $250 million — roughly 1.25 cents on the dollar of invested capital. WorldCom filed six months later, at the time the largest bankruptcy in American history.
Who got the value? Google, Amazon and Netflix, which built businesses on top of bandwidth that had become nearly free because somebody else had already gone bankrupt providing it. By 2018 and 2019, Google and Facebook were funding roughly four of every five dollars of new transatlantic cable investment — buying the rails only once the rails were cheap and only once they owned the applications that made the rails worth owning.
Leopold Aschenbrenner is not stupid. He is the opposite of stupid, which is part of the problem. He is a brilliant technologist who has never had to make a payroll, never had to explain to an auditor why the electronic records changed, never had to decide whether to spend eighteen months and $40 million ripping out a working system to save $200,000 a year in license fees.
He looked at enterprise software and saw code. A businessman looks at enterprise software and sees the thing his company cannot operate without for a single day, priced at 1% of the employee who uses it, backed by a validated audit trail he would have to rebuild from scratch in front of a regulator, and running on a contract he signed for three years.
An investor who has read a balance sheet from 1874 sees $220 billion of annual capital expenditure, an 8-times-levered reseller of rented compute borrowing at 12%, $27 billion of data-center debt hidden in a special purpose vehicle, and useful-life assumptions that the most experienced operator in the business is quietly walking back.
The kid believed the technology determines the return. But it never has.
It’s the capital structure that determines the returns: who controls the standards, who controls the customer, and who owns the data? Yes, the A.I. models will change everything. But that does not mean the people building the machines will be paid for it.
The money will be made where it was made in 1874 and again in 2004: by the toll booths riding on top of somebody else's ruinous capital expenditure.

[Van Jones @VanJones68]

I'm tired of being told that, to be a progressive, I now must swear allegiance to crazy ideas.

I'm a strong Democrat, with a winning bipartisan track record. I'm rooted in progressive ideals and policies: criminal justice reform, Green New Deal, Medicare for All, free education, clean air and water. These are ideas I have fought for my entire adult life.

But some people in groups like the DSA are pushing an agenda FAR outside those ideals. Supporting Hamas is not progressive. "No police, no prisons, no borders" is not progressive. Celebrating the murder of Israeli civilians is not progressive. These ideas are REGRESSIVE.

If there were no police or prisons, if anyone in your neighborhood could do whatever they wanted, while politicians cheered on terror groups — would that represent PROGRESS to you? No, that would be a step back. Those are REGRESSIVE ideas.

On the other hand, if everybody could see a doctor when they got sick, get a good, free education and breathe clean air — would that represent progress? Yes. Those are PROGRESSIVE ideas.

They are NOT the same thing. And the difference matters.

Some defend the far left by claiming they only want Nordic-style social democracy. If that were true, I might applaud them. I want those policies, too! But what does universal healthcare have to do with Hamas? With abolishing all law enforcement? With erasing all borders? With treating every wealthy person as a villain? Ideas matter. And these are terrible ideas.

Right now, extremists are trying to sneak backwards proposals into our party, hoping mainstream Democrats are too frustrated with MAGA and the Democratic Party establishment to notice.

But we see you.

Yes, we want our Democratic Party to be a big tent. But we don’t need "party poopers. So STOP pooping in the punch bowl — and telling us the turds are ice cubes.

They aren't. And we are smart enough to know the difference. 💩

[Patrick OShaughnessy @patrick_oshag]

Cliff is one of my favorite people to call, ask some big questions, and then shut up, and listen.

[david friedberg @friedberg]

they’re not jobs if they’re not valued. they’re not valued if there aren’t customers out there willing to pay them for their great work. needing the government to “create” a job is tantamount to welfare and that level of welfare resolves these individuals to a dependency on the government and lack of economic mobility. and chains our people, collectively, to a more indentured future.

you may be well intentioned but you have, and always will, fail to see the destitute folly of government as a job creation engine.

i have tried to engage you on this topic, in good faith, with empiricism and reasoning, but you have only dodged my points and pivoted to some populist refrain about the importance of taxation and the evils of productivity-driven success.

i can only assume you’re dodging these truths because you and the rest of the politburo leadership have deemed the conversation unsafe speech and put your oligopoly at risk.

let’s leave it at that then.

perhaps if your ways get their day, we can all bask in the glories of the dark ages ahead.

[Bryan Johnson @bryan_johnson]

People mistakenly believe peptides are only good.

Peptides can be bad, too.

They can cause adverse effects. Some dangerous.

I did a peptide experiment and measured its effects in my body. The results are complicated.

I tried a peptide called CJC-1295.

It pushed my growth hormone up by ~8x. That’s good. That’s what it was supposed to do.

But, it also came with adverse effects:
> increased my morning fasted blood sugar up 20%
> increased stress hormone by 12%
> tanked my REM sleep by 23%
> made my pancreas work 53% harder and was still losing to rising blood glucose
> increased my insulin resistance by 50%

These were the most obvious side effects, and I only ran a very narrow panel for this experiment.

So I’m sure there’s more.

I stopped after two doses, without even reaching the intended target dose.

For those of you new to peptides, your body sends instructions to itself using tiny chemical messengers called peptides. There are thousands of them.

For example, GLP-1s are drugs that take an existing class of short-lived peptides and modify them to extend their activity duration, which turns them into drugs, following rigorous clinical testing.

CJC-1295 is one of those peptide-drugs. It tells your brain to release more growth hormone. Growth hormone is your body's signal to build muscle, repair tissue, and recover.

However, and like most grey market peptides, CJC-1295 did not succeed its clinical trial, and hence never became an “official” drug.

There is a version called CJC-1295 with DAC. DAC is an attachment glued onto the peptide that makes it last for days in your body instead of hours. One shot, longer effect, just like GLP-1s.

Why people use it: more growth hormone could mean better recovery, leaner body, faster healing.

The experiment I completed.

Two injections a week of CJC-1295 with DAC:
> 1.2 mg
> 1.8 mg

48 hours after the first injection I was nearly comatose. It felt like severe jet lag, the type you’d feel after traveling nine time zones. My sleep was wrecked and I felt continuously awful.

My REM sleep dropped by 23%. REM is when your brain processes memories and repairs itself. Less time for my brain to repair itself. During the experiment, I never felt rested and always fatigued.

Why we chose CJC-1295 with DAC.

Some will say we picked the wrong peptide. They will say I should have used a different version, CJC-1295 without DAC, mixed with another peptide called Ipamorelin. We went with CJC-1295 with DAC instead as it has the most controlled studies.

CJC-1295 with DAC has 2 controlled trials in healthy adults. Ipamorelin alone has 1 controlled trial in healthy adults, plus 1 study that failed when they tried it on bowel surgery patients. The mix of the two has zero controlled trials.

On Ipamorelin, it copies a chemical called ghrelin, the one that makes you hungry. On its own it gives you a quick burst of growth hormone that fades fast. It does not keep your longer acting growth signal (called IGF-1) up. Clinics mix Ipamorelin with CJC-1295 no-DAC because the two together are supposed to work better. But we don’t know if that’s accurate because we don’t have trial data.

This is a problem with peptides. Almost none of them have been tested properly. We are flying blind. Most of what people use is based on what someone said online, what a clinic claims, or what a friend reports from their subjective feelings.

Peptides have the potential to be great when well-studied.

[Brivael Le Pogam @brivael]

Hello Julia, sans aucune ironie, c'est top que tu prennes le temps de te renseigner. Mais le problème quand on lit Marx aujourd'hui, c'est qu'on prend pour acquis sa prémisse de départ, alors qu'elle a été démontée scientifiquement il y a plus de 150 ans.

Toute la pensée de Marx repose sur la théorie de la valeur-travail. L'idée que la valeur d'un bien vient de la quantité de travail nécessaire pour le produire. Si tu acceptes cette prémisse, alors oui, tout son raisonnement tient. Le capitaliste "vole" la plus-value du travailleur, l'exploitation est mathématique, la révolution est inévitable.

Sauf qu'en 1871, trois économistes (Menger en Autriche, Jevons en Angleterre, Walras en Suisse) découvrent indépendamment la même chose : la valeur n'est pas objective, elle est subjective et marginale.

Un verre d'eau dans le désert vaut une fortune. Le même verre à côté d'une rivière ne vaut rien. Le travail incorporé est identique. Donc le travail ne détermine pas la valeur. C'est le consommateur qui valorise un bien selon son utilité marginale dans un contexte donné.

Exemple concret : tu peux passer 1000 heures à tricoter un pull moche que personne ne veut. Selon Marx, ce pull a énormément de valeur (beaucoup de travail incorporé). Selon la réalité, il ne vaut rien. Parce que personne n'en veut.

À l'inverse, Bernard Arnault crée des milliards de valeur non pas parce qu'il "exploite" mais parce qu'il a su anticiper et organiser des désirs humains à grande échelle. La valeur est créée par la coordination, pas extraite par le vol.

Cette découverte (la révolution marginaliste) a invalidé tout l'édifice marxiste. Pas pour des raisons idéologiques, pour des raisons scientifiques. C'est pour ça que plus aucun département d'économie sérieux au monde n'enseigne Marx comme un cadre d'analyse valide. On l'enseigne en histoire de la pensée.

Maintenant, le truc important. Si ton intention en lisant Marx c'est d'aider les pauvres (c'est une intention noble), alors tu vas être surprise par ce qui suit.

Regarde les chiffres de la Banque mondiale. En 1820, 90% de l'humanité vivait dans l'extrême pauvreté. Aujourd'hui, moins de 9%. Cette chute historique ne s'est PAS produite dans les pays qui ont appliqué Marx. Elle s'est produite dans les pays qui ont libéralisé leur économie.

Chine post-1978, Vietnam post-1986, Inde post-1991, Pologne post-1989. À chaque fois qu'un pays libéralise, des centaines de millions de gens sortent de la pauvreté en une génération. À chaque fois qu'un pays applique Marx (URSS, Cambodge, Corée du Nord, Venezuela), c'est la famine et les goulags.

Ce n'est pas une opinion, c'est l'expérience la plus massive jamais menée en sciences sociales. Plusieurs milliards de cobayes humains, sur un siècle.

Donc paradoxalement, si tu aimes vraiment les pauvres, la position la plus cohérente n'est pas d'être marxiste. C'est d'être pour la liberté économique. Parce que c'est empiriquement la seule chose qui a jamais sorti massivement les gens de la misère.

Pour creuser, je te recommande trois lectures qui vont changer ta vision :

"La Loi" de Frédéric Bastiat (court, lumineux, gratuit en ligne)
"La Route de la Servitude" de Hayek
"Économie en une leçon" de Henry Hazlitt
Bonne lecture, et vraiment chapeau de chercher à comprendre plutôt que de rester dans tes certitudes. C'est rare.

[Siaxares 🇮🇷 🇺🇸 @siaxares]

Speaking as someone inside Iran who stayed connected through Starlink during the total internet blackout, I want to say this loud and clear:

President Trump’s recent video on Truth Social — showing Iranian protesters writing ��President Trump please help” on walls, waving Lion and Sun flags alongside American flags, replaying raw footage of the revolution and saying “I’m with you, I will fight for you and I will win for you” — is music to our ears.

The flames of the Lion and Sun uprising have not died down. They are simply waiting for the right moment to roar again.

It was @realDonaldTrump, alongside @netanyahu and @PahlaviReza who told us to stay in our homes, stay safe, and wait until help arrives and Operation Epic Fury is complete. That’s exactly what millions of us have been doing.

There is enormous pent-up anger, grief, and anxiety inside Iran right now — but also real hope. All of it is ready to be unleashed the moment the opportunity comes.

The Iranian people are deeply pro-America. We need America’s support to finally envision a free Iran — a nation where values very similar to American ones can flourish once more, just as they did before 1979 and the arrival of this cursed, evil regime.

Make no mistake: this is not a regime that will fade away or soften its terror on its own. Trust me when I say we have tried every possible path short of war. We exhausted every peaceful option — massive street protests, open resistance, attempts at gradual reform, dialogue, you name it. None of it worked. The regime’s only consistent answer has been bullets, executions, and fresh waves of fear.

Right now there is deep internal fighting among regime figures. Mullahs and the IRGC are turning on each other, while the so-called “reformist” faction is nothing but the same old Islamic Republic in nicer clothes and smoother language. Do not be fooled by them. The only reason they are clashing is because their money flow has been disrupted, so they blame one another and scramble for more power.

We tried to bring this regime down before, but we were mostly unarmed while they were armed to the teeth. Over 40,000 were slaughtered in cold blood, with many more executed, tortured, or thrown in prison. We need help to level the playing field. Then we will rise again—and this time, we will succeed. When we do, we will never forget who stood with us; our debt will be paid in full and more.

Iranians are more pro-America than many Americans on X, because we have seen American values and said: “Yes, that is what we want too.” That includes the First Amendment — which needs no explanation — and the Second Amendment, which hits especially close to home. An armed Iranian people could never have been oppressed like this for so long. No one should ever have to surrender their guns, and no one should have to hide like a criminal just for having free internet. I should not be forced to run and conceal myself for simply owning @Starlink.

The Iranian diaspora has been our voice when we had no internet. They have accurately represented us during these protests while the talks were happening, making it clear we reject any negotiation with this regime and want Crown Prince Reza Pahlavi to represent the Iranian people — because no one inside this regime ever can.

We are anxiously waiting for the opportunity. Let’s see if it comes. But make no mistake: the majority of Iranians feel exactly as I do. Make Iran Great Again.

The world will soon understand why we say:
Anything for freedom. Anything to end this evil.

#IranMassacre‌
#IranRevolution2026‌
#KingRezaPahlavi‌ForIran

[Reza Pahlavi @PahlaviReza]

We will Make Iran Great Again.

"I begin today in the memory of my fallen compatriots.

The heroes of my country who have fought, bled, and died not only for their own freedom and for the liberation of Iran from the clutches of an evil, depraved regime that has held us each hostage for 47 years, but for the freedom, peace, and security of the world.

When I speak to these heroes, as they come off the streets from protests or as they prepare for the final battle, they often ask me: “Tell the world, we are not just fighting for ourselves. We are fighting for them, too.” So it is in that spirit and in their honor that I ask you to close your eyes for a moment and imagine a free Iran.

No more nuclear threats;
No more terrorism;
No more hostage taking;
No more closing of the Strait of Hormuz;
No more blackmailing of the global economy.

Imagine an Iran that—instead of exporting terrorism—is promoting freedom:

Freedom to its people;
Stability to its neighbors;
National security and economic opportunity for the United States and the free world.

Can you imagine Iran going from “Death to America” to “God Bless America”?

I can.

Because I have seen the true soul of my people. On 9/11—one of America’s darkest hours—when your enemies, and even some who claimed to be your friends, celebrated those horrific attacks, the Iranian people did something the world wasn’t supposed to see. They risked their lives to hold candlelight vigils in the heart of Tehran.

They didn’t do it for a camera. They did it for a friend in pain.

That is the true face of Iran. Unlike the regime that worships death and destruction, the Iranian people celebrate life and liberty.

That’s why I can imagine an Iran that exports engineers instead of extremists.

Startups instead of suicide bombers.

Energy instead of hatred...

I can imagine a Middle East where Iran is no longer a source of chaos… but an anchor of stability.

An Iran that does not fear its people, doesn’t threaten its neighbors, doesn’t isolate itself from the world.

Imagining this is not difficult, because this is exactly what Iran once was. And what it can be again.

When Iran is free, the Middle East changes.

When Iran is free, America regains a great friend.

A free Iran represents the single largest untapped economic opportunity of the 21st century.

A nation of 93 million people—highly educated, entrepreneurial, and pro-West—finally unleashed.

Over the next decade alone, a strategic U.S.–Iran partnership could generate more than $1 trillion for the American economy.

Imagine a new Middle East where Iran is a friend of Israel. Where the Abraham Accords are extended into the Cyrus Accords, named for Cyrus the Great, the Iranian king who issued the first charter of human rights, and whose vision of religious tolerance inspired Thomas Jefferson.

Today the Islamic Republic tramples upon Iran’s millennia-old legacy of tolerance for religious minorities, and wages a war on them. In a country with the fastest rate of growth of Christianity in the world, the regime and its IRGC storm into and ransack underground house churches, detain and torture pastors, and persecute and execute evangelists and Christian converts. This is the Islamic Republic. Not the true Iran. Not the vision we have for the future.

Under this vision, Iran, the United States, Israel, and our Arab neighbors are bound together in peace and prosperity rather than conflict and terror.

A Middle East where we will be able to handle our own affairs and manage our own backyard– where we can put an end to the endless wars and allow our American friends to bring back their sons and daughters in uniform and focus where they want to: back home.

A free Iran is not a fantasy.

A free Iran is within reach—right now.

But as we all know, freedom never comes free. My compatriots have shown this. They are not asking for a handout, and they do not expect their freedom to be handed to them on a silver platter. The Iranian people have already paid an unimaginable price for their liberty.

In January of this year, I called on my compatriots to go out and protest against the regime that has oppressed them for 47 years. Millions of them responded, igniting the largest wave of protests in Iran’s modern history—sweeping every single one of our 31 provinces.

On January 8th at 8 o’clock, they took their lives in their own hands and took to the streets to fight against the occupying regime. At that exact moment, Khamenei, Larijani, Ghalibaf, and the rest of their mafia shut off the Internet.

Under the cover of darkness, and with a depravity that shocked the world, they massacred more than 40,000 Iranians, and injured over 300,000. They did not stop their terror on the streets.

Wounded protesters were hunted down in hospital beds and shot in cold blood. Men and women were raped in secret prisons. Even nurses, ambulance medics, and doctors who dared to help protesters were tortured, raped, and killed.

Families were forced to search through thousands of unmarked body bags, and the regime even charged grieving parents for the bullets used to kill their own children. To this day, mothers still search for their sons, and daughters still ask when their fathers will come home.

To this day, 29 days to be exact, Iranians have been cut off from the world with almost no access to the Internet. Fearful of my courageous compatriots, Khamenei Junior and his cabal of criminals, have dragged Iran from the 21st century to the Dark Ages. They are afraid that when they do, the world will again see the defiant will of a nation united and determined to topple it.

Life can never go back to normal. There is a sea of blood between the people and the regime. After all the massacres, after all they have sacrificed, they will never agree to swap one tyrant for another.

And another anti-American tyrant will not serve American interests either. The only thing that the remnants of this regime can be relied on to do is to buy time, to cheat, and to steal. They will never be honest or true partners for peace. President Trump was right when he said, “We don’t want to come back every two years.”

But if a faction of the regime is left in power, that is exactly what will happen. It will buy time. It will pretend to negotiate. And then, it will return to its old, jihadist ways of threatening America, its security, and its interests.

They might promise a short period of artificial calm. But it would inevitably be followed by the same terrorism, the same nuclear blackmail, and the same cries of “Death to America.”

Because the truth is simple: The Islamic Republic cannot reform itself. You cannot reform a snake. Venom is in its DNA.

This extends to the corrupt and brutal thugs of the IRGC. Because the IRGC is not Iran’s national army. Indeed, it does not even have the word Iran in its name! It is the Islamic Revolutionary Guards Corps. It serves its own poisonous ideology of terror, not Iran’s national interests. So it can certainly never be a partner to serve America’s interests.

The only path to lasting peace and stability runs through a clean break with this regime.

For the first time in 47 years, President Trump’s strategy has given us a real chance to achieve that outcome. For decades, every American president since Carter chose to try to manage this looming threat rather than resolve it. Each of them has failed. They have only made the problem worse. The result has been more dead Iranians and more dead Americans.

So the mullahs operated on the assumption that America didn’t have the stomach to confront them decisively.

That assumption began to collapse when President Trump ordered the strike on Qasem Soleimani.

And once the myth of the regime’s invincibility was shattered, possibilities began to move in a different direction.

Operations Midnight Hammer and Epic Fury have done something extraordinary. The killing of Khamenei and many of his henchmen, the destruction of more than 80% of the regime’s ballistic missile arsenal, and the obliteration of the nuclear sites have leveled the playing field.

This did not happen by accident. It happened because of President Trump’s resolve and the courage of American troops. On behalf of millions of Iranians, we thank them.

Their sacrifice was not in vain. For the first time in nearly half a century, the Iranian people have a fighting chance to end this regime’s terror and chaos. The regime’s repressive machine has been degraded, its terror network cut off, and its leadership decimated.

But for this all to be worth it — the sacrifices of both Americans and Iranians— for the goodwill between our two peoples which you see on vibrant display here today, to continue — we must finish the job. This regime, in its entirety must go.

If we do not finish the job and leave a rump of the regime in place, the threat posed by this Islamic Republic will not be solved. It will only be made worse. Those who have spent 47 years sewing chaos, cannot be trusted to bring about stability. Terrorists cannot be trusted to bring peace. If they are left in place, they will bring only more of the instability, chaos, and destruction they have brought for 47 years.

They are not pragmatists. They are thugs. They are not deal makers. They are agents of chaos.

But the other path, the path which finishes the job once and for all, will leave a legacy of peace and prosperity that historians and scriptwriters could only dream of.

That legacy will belong to the heroic people of Iran and to the only President of the Untied States who had the courage and the character to see the mission through. Today, that is the precipice on which we stand. The precipice of true greatness. Iranians are ready to play their part.

The final blow will be delivered by the people of Iran themselves. They are already on the ground, and they have already demonstrated their extraordinary courage. They are ready to fight again But they must be given the chance to do so.

As President Trump, Prime Minister Netanyahu, and myself have urged, they are taking shelter while the bombs are falling. But when the right moment arrives—as in January—I will call on them to rise up again. And when they do, I have no doubt they will put an end to the dark chapter of the Islamic Republic once and for all and reclaim their homeland, their dignity, and their future.

But bringing down a regime is only the beginning. What matters next is whether the nation can unite around a leader with broad legitimacy.

Across Iran and throughout the diaspora, millions of Iranians have called on me to lead the transition to democracy. I have accepted that call not to serve myself, but to serve my nation and my people.

In recent years I have unified a broad coalition of dissidents—republican and monarchist, left and right, men and women of all ages, religions, and ethnicities. Even people who were former political opponents, have joined the movement to free Iran under my leadership.

Equally important: Iran’s armed forces and bureaucracy will follow me. Thousands of the regime’s military officials—some very senior—have signaled their readiness to join me through a digital defections platform my team established several months ago.

Many of these officials have refused to obey the orders to kill civilians during the January uprising. That’s why the IRGC had to import thugs from Afghanistan, Iraq, and Lebanon to do the dirty work. With my leadership, they and others who don’t have blood on their hands will play a role in stabilizing the country during the transition.

Iran is not Iraq. We will not repeat the catastrophic mistake of de-Baathification. There will be no dissolution of bureaucratic institutions, no power vacuum, no chaos.

The transition will be orderly. My team of experts produced a detailed plan called the Iran Prosperity Project, or IPP. This is a roadmap for national recovery, including the first 100 days after the regime’s collapse and the longer-term reconstruction and stabilization of our country.

What we ask of America now is simple: stay the course. Do not throw this crumbling regime a lifeline. Pave the way for the Iranian people to finish the job.

Because freedom is not an American story alone. It is the story of all people who refuse to live on their knees. It is the story America wrote in 1776. And today, it is the story the Iranian people are writing with their courage and their sacrifice. We prefer to die standing than to live kneeling.

2026 marks the 250th birthday of the United States. It is my hope and my belief that history will also remember 2026 as the year of Iran’s rebirth. What my people are fighting for is the rebirth of our 2,500 year old civilization. When the black page of the illegitimate Islamic regime is turned, that is the tradition and the heritage to which Iran will return.

So in 2026, our two nations are reaching for a new chapter, both determined to be great.

President Trump rightly observed that the Iranian people are the Iranian regime’s longest-suffering victims. He told them: the hour of your freedom is at hand. And they are ready to meet this moment.

The Iran story is not yet finished. Great civilizations outlast even their most vicious occupiers. With your help and with the courage, sacrifice, and heroism of Iran’s greatest youth, our best, latest chapter is being written right now. When it is done, a free and democratic Iran will stand alongside the United States as a partner, an ally, and a friend.

President Trump is making America great again. I intend to make Iran great again. Together, with my brave compatriots, that is exactly what we will do.

Thank you. God bless America. Long live Iran."

Remarks at CPAC 2026 in Dallas, Texas

[CooperBaggs 💰🍞 @edgaralandough]

Going to leave you with this tonight:

The best thing you can do for yourself is actively increase your surface area for luck to hit you.

Go outside, travel more, go to new cafes, museums, events, take a new route home, go for hikes, see cities, countrysides, take your notebook, speak to people, ask questions, start businesses - go on more side quests.

You can literally just do things, and the more you do, the more serendipity and synchronicity will find you.

Night gang.

[StoicStack @StoicStack]

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