Raphael Volz (@ProfVolz) header
Raphael Volz (@ProfVolz) profile picture

Let's Open Science, Open Source, Open Data. Pro Freedom, Pro Democracy, Pro Responsibility, Pro Life. Who am I? See https://nitter.gq/t.co/ixjfaM8CC7

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Joined January 2025
Photo by Raphael Volz (@ProfVolz)Photo by Raphael Volz (@ProfVolz)Photo by Raphael Volz (@ProfVolz)Photo by Raphael Volz (@ProfVolz)Photo by Raphael Volz (@ProfVolz)Photo by Raphael Volz (@ProfVolz)Photo by Raphael Volz (@ProfVolz)Photo by Raphael Volz (@ProfVolz)Photo by Raphael Volz (@ProfVolz)Photo by Raphael Volz (@ProfVolz)
Someone is putting the law of every country into one git history. Git for Global Law turns each country's laws into a repository where every commit is a real law taking effect. So you can see exactly what the law said on any date, and which law changed every word. It started with the US Code, which hit #1 on Hacker News. The global version is growing country by country: Germany's constitution since 1949, Estonia and more so far. Free to use for anything, and perfect for feeding to an AI. github.com/lexifina/global-l…
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Das ist einer der absurdesten Widersprüche an der Linken: Sie nennen sich Autonome - und sind doch eigentlich nur abhängige, unselbstständige Menschen - gefangen in ihrer eigenen Opfererzählung. Meine Gedanken zur „Gen Z regelt“:
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#Abwärts: Deutschlands Industrie produzierte 2025 preisbereinigt knapp 11 % weniger als 2015; Polen legte um 54 %, Dänemark um 48 % zu. Das Wirtschaftsministerium nennt hohe Energie-, Arbeits- und Produktionskosten.
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The biggest industrial irony in one photo. Left: Oliver Blume, CEO of VW. Right: Wan Gang, the man China calls the "Father of EVs." In the 90s, Wan spent 11 years as an engineer at Audi. In 2000, he went back to Beijing and told the State Council: "We will never catch Germany on ICE. So let's change the game.” He became Minister of Science and Technology and architected China's entire EV push. Result in Q3 2025: VW China sales: -38.5% to 405k cars The biggest drop since Covid. The student didn't just beat the teacher, he rewrote the whole exam. Credit : Philipp Raasch
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Wait. What? Zelenskyy could have had a much batter deal if he accepted Istanbul +. But Boris Johnson and Joe Biden talked him out of that. A million people died for nothing? What a clown. Bye bye Zelenskyy.
Zelensky says he is willing to give up 25% of Ukraine to Russia to end the war It’s so over
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John Cowperthwaite did more for human prosperity than any development economist drawing a government salary ever managed, and he did it by refusing to do almost anything at all. As Hong Kong's Financial Secretary from 1961 to 1971, Cowperthwaite ran one of the most radically free economies the modern world has ever seen. He kept taxes flat and low (the top income tax rate sat at 15%), ran consistent budget surpluses, abolished import tariffs, and blocked nearly every subsidy request that crossed his desk. When British civil servants demanded economic statistics to justify intervention, he refused to collect them. Not out of laziness. He genuinely believed that giving planners numbers gave them excuses. The results? In 1960, Hong Kong's per capita income stood at roughly 28% of Britain's. By 1997, Hong Kong had surpassed Britain. That trajectory happened without natural resources, without foreign aid, and without a single five-year plan drafted by well-intentioned economists from Oxford. Hong Kong had a harbor, people willing to work, and a bureaucrat with enough intellectual discipline to keep the state out of their way. Capital flows toward secure property rights and reliable rules, and flees the moment politicians start allocating it. Every industry Beijing picked as a "priority sector" during those same decades burned through subsidies and produced junk. Hong Kong's industries emerged organically, serving real demand, building real wealth. You benefit from this history whether you know it or not, because Hong Kong's success gave the world a controlled experiment that still embarrasses every advocate of managed development. The control group thrived. The planned economies didn't. Cowperthwaite retired to St Andrews, received a knighthood, and gave almost no interviews. That restraint was entirely in character.
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German government folks celebrating their immunity to the cyber apocalypse as they’re still running on Fax
🤖 Made with AI
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Finanzministerium > 2000 Mitarbeiter. Übrige Ministerien. Kanzleramt. Bundesregierung. 630 MdBs. Bundesrat. Und KEIN EINZIGER ist willens/in der Lage, den Entwurf zur Erhöhung der #Tabaksteuer zu lesen + zu verstehen? Bei allem Respekt: Von was für Leuten werden wir regiert?
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claude code just reverse-engineered my hotel room's door lock in 90 seconds. the encryption is from 2014. the same protocol controls the smoke detector in the top right corner - that red light isn't a battery indicator. it blinked twice when i ran the scan. i'm lying in a $85/night hotel room right now. opened claude code and typed: "scan every bluetooth and wireless device in range. show me what's talking to what." it found 19 wireless devices. 18 were normal. device 19: a BLE controller running an unpatched firmware from 2014. it manages the electronic door lock, the smoke detector, the thermostat, and the room safe. all four on one controller. one protocol. zero updates in 10 years. i asked claude code to analyze the protocol. it took 90 seconds. the lock uses a 4-byte rolling key with no session tokens. claude code generated a valid master key on the third attempt. i heard my door click from the bed. then it found the smoke detector is on the same bus. the red light in the photo? that's the controller's status LED. it's not monitoring smoke. it's confirming the BLE handshake with the lock system every 8 seconds. that means anyone within bluetooth range - the hallway, the room next door, the parking lot - with one prompt and 90 seconds can: 1. unlock your door 2. disable the room alarm 3. open your safe 4. and the smoke detector confirms the connection with that little red blink the check takes 2 minutes: step 1 → open claude code → paste the prompt from the first comment step 2 → it scans every BLE device in range and flags unpatched firmware step 3 → if it finds one → request a room change → ask for a room with a physical deadbolt → and use it every hotel chain running ASSA ABLOY or Onity locks from before 2018 has this. that's roughly 30% of hotels worldwide. i tested 3 hotels this month. all 3 vulnerable. look at the photo. top right. that red dot blinking every 8 seconds. that's the handshake. save the prompt. next hotel you check into → run it before you unpack.
Readers added context they thought people might want to know
The post claims an AI reverse-engineered a hotel door lock's 2014 BLE protocol also controlling the smoke detector, but documented vulnerabilities required physical port access and smoke detectors are independent. arstechnica.com/security/2012/… github.com/lolptdr/onity-… digitaltrends.com/computing/how-… x.com/0xGoldTooth/st…
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On my way to the office this morning, I passed a group of young people protesting, a Palestinian flag draped over their shoulders. And I asked myself a question I can't shake: why does this generation always fall into the same trap? No matter the history. No matter the context. Even the ones from wealthy families, who went to the best schools, who were dealt every good card. Always the same trap. I don't think it's stupidity. I think it's a mechanism. And a mechanism can be taken apart, piece by piece. A. The observation: everything the state touches becomes unaffordable. Look at economist Mark Perry's famous chart, the one people call "the chart of the century." It tracks US prices since 2000. At the top, what explodes: hospital services, college tuition, textbooks, childcare, housing. Increases of +100%, +150%, up to +250%, far above general inflation. At the bottom, what collapses: TVs, software, phones, toys, clothing. A TV today costs a fraction of what it did in 2000, for an infinitely better product. Look at what separates the two groups. It isn't technology. It isn't complexity. It's one variable: how much the state is involved. At the top, sectors that are subsidized, regulated, shielded from competition, where the state funds demand and blocks supply. At the bottom, sectors where companies fight every single morning to serve you better and cheaper. B. The mechanism: why it's systematic. When the state subsidizes demand without freeing supply, prices rise. Every time. Guaranteed student loans, and universities raise tuition. Housing aid plus blocked building permits, and rents skyrocket. Administered healthcare, and bureaucracy eats the budget before it ever reaches the patient. In France it's even more vicious, because the price doesn't disappear: it hides. You never see the hospital bill, you pay it through payroll contributions. You never see the cost of school, you pay it through taxes. Public spending at 57% of GDP, one of the heaviest tax burdens in the world, more than €3.4 trillion in debt. And the result? Overflowing ERs, falling PISA scores, young people who can't afford to live in the city where they work. The market didn't fail in these sectors. It was never allowed in. C. Suffering demands a culprit. A 22-year-old lives all of this in their bones. They can't find a place to live. Their degree either buries them in debt or opens no doors. The future feels blocked. That suffering is real, and I don't deny it for a second. But human beings can't stand suffering without a culprit. They need a face. A scapegoat. And this is where everything is decided: who taught them how to read the world? D. Whoever tells the story picks the villain. Schools are public. Universities are public. Culture runs on grants. Film goes through funding committees. Public broadcasting shapes the narratives. The people handing down the interpretive framework are, overwhelmingly, paid by the very system that creates the problem. Do you really think that system is going to name itself as the culprit? No. It names the capitalist. The boss. The landlord. "The rich." The multinational. The commercial West. Same role, same casting, every time. E. One lens, a thousand causes. And this brings me back to that flag. A generation taught to read every situation through a single lens, oppressor on one side, rich, Western, capitalist, oppressed on the other, will apply that lens everywhere. To housing. To climate. To conflicts on the other side of the world. The cause changes, the lens stays. That's why the trap is always the same: it's not the cause that draws them in, it's the way of thinking that was installed in them. F. The perfect inversion. Here's the irony. Capitalism is the force that drove down the price of almost everything it touched. The state is the force that blew up the price of almost everything it captured. And young people blame the first for the crimes of the second. It's like blaming the firefighter for the fire because you saw him at the scene. G. The ballot box confirms it. In the US, a few weeks out from the midterms, a large share of urban young voters is getting ready to vote Democrat for more state, more spending, more regulation. New York elected a self-described socialist mayor, carried by young voters, on promises of rent freezes and city-run grocery stores. Rent freezes, the policy that has made housing scarcer everywhere it's been tried. The cure that worsens the disease. In France, it's the same play in two acts. Part of the youth votes for the radical left, which promises more state. Another part votes for the center, which promises to "manage" the state well, and has dug the debt deeper than ever. Two different ballots, one shared assumption: the problem is the market, the solution is the state. H. The way out. These young people aren't stupid. They're right to be angry. They're just aiming at the wrong target. The day they understand that their rent, their tuition and their hospital are expensive precisely because the state runs them, their anger will change direction. They'll stop protesting against those who create. They'll start protesting against those who capture. That day, the greatest intellectual scam of our time will be over.
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The newest painting in the Louvre. “The Girl with the Suicidal Empathy.” Oil on canvas. Go see it while the Louvre is still standing.
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We gave you C++. We gave you DHH, RoR and Omarchy. We gave you C#, PHP and TypeScript. Friggin’ Bluetooth. It’s. All. Danish. 🇩🇰 Now tell me again how technologically irrelevant Europe is. I’ll wait. What did you even ship??!
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Niemand wird mehr Bock haben, hier etwas zu leisten, etwas aufzubauen und zu investieren. Das ist die message. Ende. Der Verfall wird sich beschleunigen.
In Deutschland 🇩🇪 werden jetzt wohl wieder tüchtige Geschäftsleute von der Regierungspartei #SPD enteignet. Man hätte erwarten können das die Sozen aus ihrer Geschichte gelernt haben. Pustekuchen.
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Es fundamental que empiecen a entender la relación DIRECTA que hay entre estas dos fotos
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Replying to @ProfVolz @0Schone
Moulay Ismail Ibn Sharif (Sultan von Marokko, 1672–1727) hält den Rekord: Guinness nennt 888 Kinder (525 Söhne, 342 Töchter), Berichte sprechen von bis zu 1171. Mit 4 Frauen und rund 500 Konkubinen. Biologisch möglich laut Simulationen. Genghis Khan: Spekulationen von 1000+, aber historisch nur Dutzend belegt.
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Doing the napkin math on a sub-one-second 0 to 60 mph run explains the biggest engineering debate swirling around tonight’s demo. Hitting 60 mph in under a second takes more than 2.75 Gs of acceleration, while the stickiest street-legal tires on dry pavement max out around 1.5 Gs of friction. Past that limit, adding more motor torque just turns rubber into smoke. That is why everyone is arguing over the teaser image right now. When people flipped the teaser photo 180 degrees upside down, they realized the four plumes match up with US Patent 12,746,987 B1, granted to Tesla on September 29 for a skirtless four-fan rear diffuser that vacuums the car to the road. Whether tonight shows off SpaceX cold-gas thrusters, quad electric suction fans, or both, Tesla had to rewrite aerodynamics just to get past the friction limit of rubber.
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Die Kosten für Energiewende und illegale Migration (11,3 Billionen €) betragen umgerechnet auf einen Haushalt 280.000 €. In anderen Worten: Das ist der Gegenwert einer Eigentumswohnung mit ca. 85 qm Wohnfläche pro deutschem Haushalt. Das ist eine bewusste Verarmung der Bevölkerung und viele zusätzliche Ausgaben wie Klimaschutzausgaben im Inland und Ausland sowie die Finanzierung der Ukraine sind in dieser gewaltigen Summe noch nicht einmal mit drin.
This quoted post is unavailable.
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To reply properly, I need the full content and context of that post. Sorted by €/capita (lowest first): 🇸🇪-6/-567 🇩🇪-46/-550 🇳🇱-9.8/-543 🇮🇪-2.7/-496 🇩🇰-2.6/-434 🇦🇹-2.5/-272 🇫🇮-1.5/-266 🇫🇷+1.8/+26 🇧🇪+2.8/+235 🇮🇹+48.5/+823 🇲🇹+0.7/+1219 🇨🇾+1.2/+1225 🇵🇱+45.2/+1238 🇱🇺+0.9/+1320 🇸🇮+2.9/+1361 🇷🇴+27/+1418 🇪🇸+69.8/+1422 🇧🇬+9.2/+1429 🇨🇿+16.2/+1485 🇭🇺+16.8/+1761 🇵🇹+20.7/+1926 🇸🇰+11.9/+2196 🇬🇷+27/+2594 🇱🇹+7.7/+2664 🇱🇻+5.1/+2747 🇭🇷+11/+2839 🇪🇪+4.1/+2993
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Dusting off this tweet from April because this gap in shared understanding of LLM capability is *widening*. It's now less "two groups of people speaking past each other" and more a sharp funnel. - Napkin math somewhere around 6B people (~75% of the population) have barely come in contact with LLMs at all. - Around 1-2B (~20%) are casual and infrequent users of free-tier ChatGPT-like products. This group sees derpy chatbots and treats them a bit like a better Google search, a writing aid, or etc. Maybe an agent tries to book you a flight. I have non-tech friends who (reasonably, imo) say they have not much use for it at all. Even many professionals outside of math&code are in this tier. For example, execs and many other functions spend a lot of their time talking to other people, so while they understand what is happening intellectually, it is still second-hand and a bit abstract. - Now we get to professional use of frontier-grade LLMs in math&code. Somewhere around 20M people (0.2%) see first-hand that large, complex projects that used to take them weeks/months can now be completed by agents with a prompt. Building apps, copying apps, translating apps, decompiling apps from binaries... This has all happened very quickly and recently - less than 1 year ago, I was writing code manually by hand, typing memorized computer code commands into a code editor character by character, occasionally pressing Tab to autocomplete a little chunk of code. - And finally we get to the ~5,000 people (~0.00006%) with access to frontier-grade systems internally. The external world has seen the preview. It looks like swarms of thousands of agents collaborating over weeks on software mega projects: minting zero days, running cyber attacks and defenses at machine speeds, discovering new science, advancing the frontier of mathematics. Things that would have taken top professionals in the industry years of work. Meanwhile, human review and comprehension are starting to fall behind. For example, people are still involved in the "archeology" of the OpenAI-HF incident from many months ago. Mathematicians may be poring over the 722 manuscripts on frontier mathematics for a while. The funnel is driven by a combination of factors: 1. The impact scales with ambition, problem size, and horizon. A question with a paragraph answer barely stresses the system. You need a reservoir of big, difficult problems that you really care about. This aspect drives the consumer / professional dimension of the funnel. 2. The jaggedness of the system (which I have written about a lot separately). Capability peaks in domains that are digital, verifiable and economically valuable. This is because LLM capability emerges from reinforcement learning on verifiable rewards on a curated environment mixture driven by revenue potential. This aspect primarily drives the area (e.g. math&code) dimension of the funnel. 3. Access. Free-tier, paid-tier, internal. So this is the weirdness of the moment. The general public has mostly not interacted with these systems. When they have, it looks like a derpy chatbot. The majority of professionals still see only a modest uplift. And a small sliver of professionals are experiencing the vertigo of the curve going vertical. And it is all happening at the same time.
Judging by my tl there is a growing gap in understanding of AI capability. The first issue I think is around recency and tier of use. I think a lot of people tried the free tier of ChatGPT somewhere last year and allowed it to inform their views on AI a little too much. This is a group of reactions laughing at various quirks of the models, hallucinations, etc. Yes I also saw the viral videos of OpenAI's Advanced Voice mode fumbling simple queries like "should I drive or walk to the carwash". The thing is that these free and old/deprecated models don't reflect the capability in the latest round of state of the art agentic models of this year, especially OpenAI Codex and Claude Code. But that brings me to the second issue. Even if people paid $200/month to use the state of the art models, a lot of the capabilities are relatively "peaky" in highly technical areas. Typical queries around search, writing, advice, etc. are *not* the domain that has made the most noticeable and dramatic strides in capability. Partly, this is due to the technical details of reinforcement learning and its use of verifiable rewards. But partly, it's also because these use cases are not sufficiently prioritized by the companies in their hillclimbing because they don't lead to as much $$$ value. The goldmines are elsewhere, and the focus comes along. So that brings me to the second group of people, who *both* 1) pay for and use the state of the art frontier agentic models (OpenAI Codex / Claude Code) and 2) do so professionally in technical domains like programming, math and research. This group of people is subject to the highest amount of "AI Psychosis" because the recent improvements in these domains as of this year have been nothing short of staggering. When you hand a computer terminal to one of these models, you can now watch them melt programming problems that you'd normally expect to take days/weeks of work. It's this second group of people that assigns a much greater gravity to the capabilities, their slope, and various cyber-related repercussions. TLDR the people in these two groups are speaking past each other. It really is simultaneously the case that OpenAI's free and I think slightly orphaned (?) "Advanced Voice Mode" will fumble the dumbest questions in your Instagram's reels and *at the same time*, OpenAI's highest-tier and paid Codex model will go off for 1 hour to coherently restructure an entire code base, or find and exploit vulnerabilities in computer systems. This part really works and has made dramatic strides because 2 properties: 1) these domains offer explicit reward functions that are verifiable meaning they are easily amenable to reinforcement learning training (e.g. unit tests passed yes or no, in contrast to writing, which is much harder to explicitly judge), but also 2) they are a lot more valuable in b2b settings, meaning that the biggest fraction of the team is focused on improving them. So here we are.
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