forget the grind. small iterative steps. do things @halftroll

My team loves Claude from @AnthropicAI . But this new policy of retaining prompts and usage is a red line...we simply can't give over our usage. Prompts contain our IP; literally all our design files and docs. Why would this ever have been ok? It's sad because everyone was looking forward to using the new model. Sigh.

Claude 4.8 and Fable 5, without a doubt, formulates their responses in a dense form that isn't ideal for human consumption. This is your tell that you need to begin deep dives by constructing domain-specific language and having the LLM constrained to that domain. This is why, a while back, I came up with this book so you can bootstrap your own DSL. intuitionmachine.gumroad.com/l/notation

We’ve received $9.6 million from 265,000 small-dollar donations. Susan Collins received $9.8 million from 79 billionaires.

Quite interesting thread on capabilities of real biological neurons (spoiler: they're way more capable than classical artificial neurons in a perceptron) . Nice work @IdoAizenbud and collaborators!

Ido Aizenbud @IdoAizenbud

a day ago

What can a neuron compute? Real biological neurons are complex, but how capable are they? Using a new method, we found that a single cortical neuron can classify cats vs dogs, recognize spoken words, and solve 10-bit parity, all tasks thought to require entire networks. (1/15)

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For decades, neurons were modeled as point units in AI/neuroscience. But biological neurons have dendrites and nonlinear conductances. What capabilities are lost? With @DavidBeniaguev @noampnueli @Segev_Lab & @mikilon, we set out to find out (biorxiv.org/content/10.648…). (2/15)

Since taking office, Ken Paxton has become a multi-millionaire while our pay has stagnated. He owns 11 homes while most Texans can’t afford one. He trades favors with rich donors while blocking overtime pay for workers. Paxton doesn’t serve us — he serves himself.

THAILAND IMPOSED DEATH SENTENCES on two Uyghur bombers yesterday – and showed that China got it right on dealing with terror attackers. Turkic separatist terrorism is now feared in multiple countries—but NOT in China, where a program of vocational and language training for Uyghur radicals has dropped mass terror attacks to zero for eleven years. Peaceful, ethnically mixed Xinjiang is now one of the world’s top tourism centers, with 300 million visitors a year. This is a huge achievement, given that Uyghur separatists had been committing random acts of terror in China since at least 1990, with hundreds of innocents killed over multiple attacks across two and a half decades. But this has flipped 180 degrees. Xinjiang is at peace. The last mass casualty terrorism incident was in October 2015, when Uyghur knifemen killed at least 16 people. . STIFF POLICING How did China solve its problem? By stiff policing and compulsory vocational training for people associated with radicalism. The NED (a CIA regime-change spin-off) worked with BBC and other western news organizations to rebrand the program as “atrocities”, implying, without evidence, that “millions” had been locked into “concentration camps” and even murdered. But that has been well debunked, and it’s now impossible to avoid the hard fact that the Chinese system deradicalization system has worked. One can just look and see, as millions of visitors do every year. While in the past, visitors were almost all Chinese domestic tourists, these days more than five million international tourists tour Xinjiang every year. Today the Chinese Uyghur community is peaceful, with rising rates of health and wealth. The population is growing in size and in proportion to other ethnic groups. Uyghur longevity in China, at 77 years and rising, has significantly overtaken that of native Americans in the US, at just 70.1 years. Uyghur longevity is now close to that of white Americans, which is 78.4 years. . COMPARE CHINA AND OUTSIDE That’s inside China’s borders. But Uyghur separatists elsewhere? As we mentioned, China solved its problem in 2015, but outside China the problems simply continued unabated: - In 2015, Uyghur separatists bombed the Erawan Shrine in the centre of Bangkok, Thailand, killing 20 people and injuring 120. - In 2016, Indonesian authorities arrested Uyghur terrorists working with the Eastern Indonesia Mujahidin, a terrorist group affiliated with Islamic State. - After a pair of extremist suicide bombings in Brussels, Belgium, in March of 2016, China expressed willingness to work with European countries to combat terrorism. The offer was ignored. - In 2017, a Syrian ambassador warned that 5,000 Uyghurs were fighting in Syria for jihadist groups. Other analysts had different estimates—but all agreed the fighters existed. - In 2019, Four Uyghurs convicted of terror-related offenses in Indonesia were deported to China. - In 2020, risk analysts warned that ISIS-Khorasan had started working with the East Turkestan Islamic Movement. This group was known as TIP, for Turkistan Islamic Party. - In 2021, an ISIS-K fighter using the kunya “al-Uyghuri” attacked Shia Muslims in Kunduz, Afghanistan. - In 2022, ISIS-K members made a shooting attack on a hotel in Kabul used by Chinese travelers. - In 2025, the Economist reported that the rebels storming Syria in 2024 to topple Bashar al-Assad included fighters who “had roots in the Chinese region of Xinjiang and were members of the Turkistan Islamic Party (TIP), a group which aims to establish an Islamic state spanning Xinjiang and other parts of Central Asia”. . STORY CANNOT BE TOLD There are plenty of other examples, but the basic conclusion should be clear from those examples. China’s program to eradicate terrorism among its ethnic minority population and create a positive, low-crime community, has been remarkably successful. Unfortunately, this story simply cannot be told to the world. Look up the topic on Google, and you get link after link to the debunked NED/ BBC narrative of “millions” in “concentration camps” in China instead. Ask AI programs for information, and all of them regurgitate the debunked NED/BBC fiction too. Getting the truth out there is as challenging as ever.

Those who celebrate @elonmusk's $1 trillion fortune need to be reminded of a simple and vital truth: That there is a fundamental tension between extreme wealth and the very possibility of democracy.

In the 1980s, Reagan stopped government investment in American shipbuilding. 40% of yards shuttered. Today we need investment in our shipyards and a CHIPS Act for shipbuilding. Would MAGA folks admit that Reagan on this issue was wrong and we need to make more ships here?

Meet Kimi-K2.7-Code 👀 Here’s what developers should know to fully unlock K2.7-Code potential：

Kimi.ai @Kimi_Moonshot

9 hours ago

🌘 Kimi-K2.7-Code, our latest coding model, is now released and open-sourced! 🔷 Improved coding & agent performance over K2.6: +21.8% on Kimi Code Bench v2, +11.0% on Program Bench, and +31.5% on MLS Bench Lite. 🔷 Reasoning efficiency: Less overthinking, with 30% lower

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Amazing: KPMG wrote a report describing the successful use of AI by businesses. But the case studies turned out to be AI hallucinations. giftarticle.ft.com/giftarticle/ac…

When Obama bombed Libya, the justification was "humanitarian intervention." "Protection of civilians." "Responsibility to protect." The language of international law and moral obligation. Libya was subsequently destroyed. It has open slave markets today. The humanitarian outcome was catastrophic. But the language was immaculate. The syntax was perfect. The suits were pressed and the speeches were moving and the Nobel Peace Prize sat on the shelf while the drones flew. Trump bombs things and says it's about the oil. In terms of honesty, pure, raw, unmediated honesty about what American power actually does, Trump is more accurate than any of his predecessors. This is not a defense of Trump. This is an indictment of everyone who made the polished version seem acceptable. The lie was always more dangerous than the liar currently in office. Because the lie had good manners.

The CEO of Anthropic just predicted something that should make everyone uncomfortable. He is building the technology causing it. And he said it anyway. "I think we could have this very unusual combination of very fast GDP growth and high unemployment, or at least underemployment, a lot of low wage jobs, high inequality." Read that again slowly. The person building the most powerful AI in the world is not telling you everything will be fine. He is telling you the economy could boom at the top while collapsing underneath. He went further. "You automate 90% of the job, great, people are 10 times more productive in the other 10%. But eventually it gets close to a hundred percent. Now the sequel to that is, well then you have to find something else for them to do." That last sentence is doing a lot of work. He is not saying jobs change. He is saying at some point there is nothing left to hand off. And then what. Most CEOs in his position talk about new jobs being created. Dario is talking about what happens when that argument runs out. He is building it. He is worried about it. He said so publicly. That combination is rare.

This is a really fascinating paper that everyone interested in China's industrial policy should read. It destroys so many myths (see below), and is written by deeply credible people who conducted over three years of fieldwork in China and interviewed 60+ Chinese officials, entrepreneurs, and engineers. When it comes to China studies, it literally doesn't get more rigorous than this. First myth it destroys: contrary to popular belief, Beijing's industrial policy didn't build the companies that became China's EV champions. They rose largely **despite** it, through its cracks. For sure, Beijing did favor EVs as an industry and pushed hard for it but their big bet was SOEs (State Owned Enterprises): research grants, pilot programs, licenses, cheap credit - virtually all of it flowed to state firms. The result? China's actual EV champions - BYD, Geely, NIO, XPeng, Li Auto, etc. - are overwhelmingly private firms that succeeded despite Beijing favoring their SOE competitors. How so? Because, when favoring SOEs, the central government didn't just pick winning companies, it picked winning cities, each SOE being anchored in a specific city: Shanghai (SAIC), Changchun (FAW), Wuhan-Shiyan (Dongfeng), etc. Which means that every city not on the list, that wanted a piece of the auto boom, had only one option left: team up with private entrepreneurs who were equally excluded from central government favor. That's what truly fueled China's EV miracle: an alliance of the excluded, between local private entrepreneurs and local mayors. This is the biggest misconception this paper destroys: the reality is that the "Chinese state capitalism" that many in the West think powered the EV boom actually tried to block many of these companies from existing. In effect, it was closer to an obstacle course that local actors (mayors and provinces) learned to game. Geely - now the third largest automaker in China - is a fantastic example of this. First of all, it started off illegal since, to build passenger cars, you had to have a central government license and they couldn't get one. Zhejiang Province told them to go ahead regardless because the province had hundreds of auto parts suppliers but no carmaker of its own. It's only a couple of years later, recognizing the fait-accompli that Geely was producing cars and was competitive, that the central government admitted them to the National Sedan Catalog - effectively legalizing them retroactively because there were facts on the ground. Then there was the Volvo acquisition in 2010, which is fair to say - looking back - proved to be the most strategically valuable acquisition in Chinese automotive history. Despite it being presented at the time (and still described this way today) as "China buying Volvo", all 3 major state-backed banks in China (Export-Import Bank, China Development Bank, Bank of China) refused to finance the deal. The only state-bank money Geely managed to get was a $200 million loan from a provincial branch of China Construction Bank - a tiny fraction of what the deal required. Geely actually did the deal with Goldman Sachs money via Hong Kong plus loans and equity from four local governments (Chengdu, Zhangjiakou, Daqing, Shanghai's Jiading district), each of which bought in by securing a Volvo plant or headquarters for itself. In effect, the doors that Beijing controlled were largely closed to Geely, but it made it because the doors subnational actors controlled were opened. Which all means this paper destroys another very common myth: the big merit of the central government in all this was to be relatively chill about it, to NOT be dictatorial. I just imagine if that had happened in France and you had - say - the mayor of Lyon or Marseilles open, fund and promote an unlicensed carmaker against Renault: the préfet would shut it down within weeks, and the mayor would be lucky to escape prosecution. That's the irony: on industrial policy, the supposedly "totalitarian" Chinese state proved more tolerant of local defiance than most Western liberal democracies would be. Beijing's greatest contribution to the EV miracle wasn't the plan - it was looking the other way while the plan was being violated. To be sure, the paper doesn't hide the costs of this system: ferocious local competition also produced what's known today in China as "involution" (内卷-Neijuan, basically a hypercompetitive price war), as well as some spectacular failures. For instance one county lost 6.6 billion yuan on a carmaker that never really made cars. But that's precisely the point: this is a high-risk, high-reward model of decentralized experimentation, the very opposite of the careful central planning Westerners imagine. I've repeated this countless times but it bears repeating again: the single greatest misconception people have about China is - probably because we wrongly associate communism with centralized control - that it is a monolith run from Beijing. Some even say it's run by "one man." The reality is the exact opposite: China is, in practice, one of the most decentralized countries on earth. Roughly 85% of government spending in China happens at the subnational level - against about 30% in the average OECD country (and even less in France, which is actually one of the most centrally controlled countries on earth). A Chinese mayor commands fiscal resources, land, investment funds and policy latitude that virtually no Western mayor could dream of. Last but not least, I'd be remiss not to mention what the paper has to say on the positive legacy of Mao and its role in the rise of EVs (given I myself wrote an article titled "Mao's economic record wasn't bad, actually": arnaudbertrand.substack.com/p/maos-economi…). When it comes to China myths, none is more entrenched than the idea that Mao left behind nothing but ruins. This paper confirms a key argument of my article: Mao's deliberate dispersal of industry across China (during the Great Leap Forward and Cultural Revolution decentralizations) left dozens of cities with their own small auto works. Inefficient, yes - but these scattered factories survived into the 1990s and became the seed stock of everything that followed: the industrial base, the engineers, and the production licenses that EV startups would use to enter the market. The paper even says it outright: the fragmentation that industrial policy "sought to eradicate" is "precisely" what "ironically enabled" the EV sector's rapid rise. This is exactly the mechanism I described in my Mao article: structures built in the Mao era - communes becoming township governments, commune enterprises becoming TVEs, Third Front factories seeding interior industrialization - became load-bearing foundations of the reform miracle. Fittingly, the spark for China's first municipal carmaker adventure was literally a TVE (Township and Village Enterprise), the institutional descendants of Mao's commune enterprises: Tongbao, a kit-car maker in Wuhu whose success stunned local officials into building what became Chery (one of China's biggest carmakers today). You can't tell the story of China's EV miracle without crediting the legacy of Mao. What's the biggest lesson in all this for Western policymakers? The obvious one is that the part of industrial policy that most people assume China does and that they sometimes want to copy - i.e. the state picking winners - is actually the part that failed. The part that did succeed is the China nobody in the West believes exists: a radically decentralized system with a high degree of tolerance for disobedience and experimentation. We imagine China as a country where nothing happens without Beijing's approval when the reality is closer to the opposite: China's EV miracle happened precisely because localities asked for forgiveness rather than permission. All in all, and this is the lesson I often come back to, this is yet another illustration of the importance of understanding China for what it is as opposed to the caricature we've built of it. This matters whichever "camp" you're in. If you see China as a rival, you can't compete with someone you don't understand. If you see them as a source of lessons, you can't emulate what you've misunderstood. Whatever you want from China - to compete with it or learn from it - the entry fee is the same: genuinely understanding it.

Fengming Lu @FengmingLuPE

2 days ago

Why did private firms, not state-owned enterprises (SOEs), come to dominate China’s EV sector? My new @ChinaJournal article (co-authored with Xiao Ma @maxiaoalex) challenge the "top-down industrial policy" narrative. The real engine? Strategic alliances between local

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🌘 Kimi-K2.7-Code, our latest coding model, is now released and open-sourced! 🔷 Improved coding & agent performance over K2.6: +21.8% on Kimi Code Bench v2, +11.0% on Program Bench, and +31.5% on MLS Bench Lite. 🔷 Reasoning efficiency: Less overthinking, with 30% lower reasoning-token usage compared to K2.6. 🔷 Long-horizon coding: Improved instruction following, higher end-to-end coding task success rates. ⚡️ 6x High-Speed Mode coming soon! 🔌 Available today via Kimi API and Kimi Code. 🔗 Kimi Code: kimi.com/code 🔗 API: platform.moonshot.ai

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Dems have been looking for their message for years, and @AnnieAndrewsMD just did it (in under two minutes). Take note 📝

This really worries me A month ago in Wales I suffered a ruptured aneurysm in my abdomen. I lost over 2 units of blood But the Welsh ambulance service refused to send an ambulance. I was still breathing so apparently didn't need one I spent 7 hours lying on the ground in a car park. Every time I moved I threw up from the pain. The owners of the car park called 999 6x One of the people there was a fireman. He couldn't believe that 999 treated each call as a separate incident and couldn't see the details or link to previous calls. He was frustrated because they could see I was seriously ill but you can't see internal bleeding and so there was no way to persuade 999 that it actually was an emergency Eventually my husband arrived by taxi, journey of more than 3 hours from our home He gave me my pain meds (the car park people were worried about liability and I was too ill to get them myself). This meant I was able to crawl into the car and he drove me to A&E He got me into a wheelchair. We waited 75 minutes to see a doctor. I was shivering, heaped with blankets and threw up all over the floor As soon as a doctor looked at me I was taken straight to resus. The next day I was transfered by blue light ambulance to another hospital, had a blood transfusion and spent 5 days on the high dependency unit If my husband hadn't been able to come and look after me I have no idea how I would have survived. As it was I nearly didn't I would not have been able to get myself to hospital nor would I have been able to log into some digital triage system This scheme seems to assume if you're seriously ill you'll arrive by ambulance and if not you're well enough to navigate a digital portal My experience suggests that's a dangerous assumption A week later, back home in England I had another ruptured aneurysm. This time an ambulance came in 2 hours and again I was taken straight to resus It wasn't the same because I had a recent diagnosis of a ruptured aneurysm so we could tell 999 I was almost certainly bleeding internally. But I was too ill to get myself down the stairs and out to the car. We still needed that ambulance and I still wouldn't have been able to fiddle around with an ipad Proper triage REQUIRES an actual doctor to look at the patient. It takes a matter of minutes to differentiate between a life threatening emergency and not a life threatening emergency. That's not minutes to get a diagnosis but to know that the person is stable or not stable and if not that needs immediate attention Seriously ill people can't do it themselves. It doesn't matter how smart or articulate they are normally. Or how tough. Expecting people to manage their own emergency care isn't what a modern health service should do telegraph.co.uk/news/2026/06/1…

Really looking forward to digging into this new RAND report

Gerard DiPippo @gdp1985

a day ago

🚨🇨🇳🏭📈🚨 New @RANDCorporation report on China's techno-industrial policies under Xi! With @JonathonPSine and Benjamin Lenain. We detail the evolution, goals, and instruments. Lots of charts and summary tables! Please enjoy. rand.org/pubs/research_…

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🚨🇨🇳🏭📈🚨 New @RANDCorporation report on China's techno-industrial policies under Xi! With @JonathonPSine and Benjamin Lenain. We detail the evolution, goals, and instruments. Lots of charts and summary tables! Please enjoy. rand.org/pubs/research_…

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This would safe the republic. No step could be more important to save our democracy.

Democrats Deliver @DemzDeliver

2 days ago

🚨 Graham Platner calls for two-month, publicly funded elections in the U.S.

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