timelets

Факты – упрямая вещь, и эти факты говорят нам о том, что при «слабом» Байдене Москва не могла и близко позволить себе того, что сходит ей с рук при «сильном» Трампе.

Без Трампа у Путина не было уверенности в том, что «энергоцид» Украины и массовый расстрел городов-миллионников баллистическими ракетами сойдет ему с рук. Теперь она есть. Всеми своими действиями, какими бы благими намерениями он ни руководствовался, Трамп последовательно поощрял Путина к террору. Он создавал у него уверенность в том, что «ответка» от Америки не прилетит.

https://t.me/v_pastukhov/1809

«Полицейские не ходили по квартире, они ездили по льду»

Пережившая Холокост киевлянка замерзла в центре города, обесточенного российскими ракетами.

Никто не знает точно, когда умерла баба Женя. Знают только, от чего: от холода. Пережившая Холокост киевлянка умерла от Холодомора — в историческом центре города, на Подоле, в многоквартирном доме на улице Почайнинской. День памяти жертв Холокоста пополнился еще одним именем в мартирологе: Евгения Михайловна Бесфамильная.

Полиция отказывалась заходить в ее квартиру еще и потому, что «запаха нет — значит, и трупа нет». Был бы труп — вы бы уже почувствовали, объясняли полицейские. А соседи еще полночи сидели и придумывали аргументы, как заставить полицейских открыть дверь.

Разгадка оказалась проста: труп был замерзший.

https://novayagazeta.eu/articles/2026/01/27/politseiskie-ne-khodili-po-kvartire-oni-ezdili-po-ldu

Каким способом можно видеть тоску или радость, представлять себе, развеселит нечто другого или напугает?

https://ivanov-petrov.livejournal.com/2632133.html

“An alliance between 3Com and Huawei was attractive to both sides. Huawei would get the immediate legal protection of 3Com’s deep patent portfolio; 3Com would get Huawei’s lower production costs and its connections to the vast China market. Soon after the two announced their joint venture, called H3C, 3Com’s lawyers filed a motion to intervene in the Cisco case, calling 3Com an interested party.”

--- Eva Dou. “House of Huawei.”

“Ren told his trusted deputy, Guo Ping, who was now Huawei’s executive vice president, to get to the US as quickly as he could. Ren invoked the fable of ancient Chinese military general Han Xin*, who had accepted the humiliation of crawling between another man’s legs to prevent a deadly fight.”

* The fable of General Han Xin’s humiliation, known as "crawling between the legs" (胯下之辱), tells of a young, poor Han Xin being challenged by a bully in his hometown of Huaiyin to either kill him or crawl through his legs. Choosing to endure this shame rather than waste his life on a petty killing, Han Xin crawled through, later becoming a renowned military strategist and rewarding the man for testing his resolve.

“Ren saw a Russia devastated by hyperinflation... Ren felt that the United States was partly to blame: Washington had coaxed the leader of the new Russia, Boris Yeltsin, to apply “shock therapy” to the economy with a rapid shift to capitalism, he wrote, but Washington did not follow through with the financial aid it had dangled. “They always give you some bait to get you to change some policies, but when you’ve made changes according to their demands, they raise further demands,” Ren wrote. “You still cannot get ‘sincere’ help from the United States.”

At the end of the day, the Russians remained wary about installing Chinese switches in their networks. “We are still unsure how much we know about Russia and if we can really open up the market,” Ren wrote to staff.

( Read more... )

-- Eva Dou. “House of Huawei.”

“On January 28, 1996, Ren Zhengfei held Huawei’s first “mass-resignation ceremony.” Each head of a regional sales office was told to prepare two reports: a work summary and a written resignation. “I will only sign one of the reports,” Ren said.

Huawei had started out in rural markets, and many of its early sales managers were provincial in their experience and network of contacts. As Ren sought to go national and international, he decided to make the entire sales staff resign and reapply for their jobs. “The mountain goat must outrun the lion to not be eaten,” he had told them ahead of the event. “All departments and sections must optimize and eat the lazy goats, the goats that do not learn or progress, and the goats with no sense of responsibility.”

They were following the strategy that Mao had used to win the Chinese Civil War of “encircling the cities with the countryside.”[9] They’d won over villages and towns in the beginning, building their strength to take on the big cities.

Ren told his followers that demotions built character and that the demoted would only be stronger when they worked their way up again.... “Even Deng Xiaoping could go down and up three times. Why can’t you go down and up three times?”

-- Eva Dou. “House of Huawei.”

Mossing and others, both at OpenAI and at rival firms including Anthropic and Google DeepMind, are ... studying them [LLMs] as if they were doing biology or neuroscience on vast living creatures—city-size xenomorphs that have appeared in our midst.

Anthropic and others have developed tools to let them trace certain paths that activations follow, revealing mechanisms and pathways inside a model much as a brain scan can reveal patterns of activity inside a brain. Such an approach to studying the internal workings of a model is known as mechanistic interpretability. “This is very much a biological type of analysis,” says Batson. “It’s not like math or physics.”

Anthropic invented a way to make large language models easier to understand by building a special second model (using a type of neural network called a sparse autoencoder) that works in a more transparent way than normal LLMs. This second model is then trained to mimic the behavior of the model the researchers want to study.

Creating a model that behaves in predictable ways in specific scenarios requires making assumptions about what the inner state of that model might be in those scenarios. But that only works if large language models have something analogous to the mental coherence that most people do.

And that might not be the case.

...
Another possible solution ... Instead of relying on imperfect techniques for insight into what they’re doing, why not build an LLM that’s easier to understand in the first place?

https://www.technologyreview.com/2026/01/12/1129782/ai-large-language-models-biology-alien-autopsy/

The Journal identified 13 shootings involving ICE or CBP agents and civilian vehicles since July, using court records, news reports and gun-violence databases.

Footage verified by the Journal and a video shared on Friday by DHS show Ross moving in front of the vehicle while its engine was running, which former and current DHS agents say they are trained not to do.

The Minneapolis shooting shares characteristics with others the Journal reviewed: Agents box in a vehicle, try to remove an individual, block attempts to flee, then fire.

Footage from the shootings also shows officers approaching civilian vehicles with their engines still running—a situation police are trained to avoid. According to Kerlikowske, such training is designed to keep officers out of harm’s way.

Videos reviewed by the Journal show officers trying to open vehicle doors, reaching into vehicles and smashing windows, followed by drivers fleeing.

Police are trained to break a window only in specific circumstances, such as if the driver is armed or there is a medical emergency, said Alpert. In footage from the four cases closely reviewed by the Journal, none of the drivers had firearms, but DHS insists they were still dangerous.

Obstructing a moving vehicle
In at least three of the shootings, officers pursued a vehicle on foot. Footage also shows officers moving into the potential path of the vehicle or clinging on to it while it moved.

“It’s like policing 101. Don’t get in front of a car or in their potential pathway, especially if the engine is running,” said Jon Blum, a former North Carolina officer who now develops police training curricula.

Firing into a moving vehicle also creates its own danger, according to Alpert.

“If I shoot you, and I’m successful, now we’ve got an unguided missile,” said Alpert. “What if there are kids playing in the street?”

https://www.wsj.com/us-news/videos-show-how-ice-vehicle-stops-can-escalate-to-shootings-caf17601

Research shows real names curb toxicity. While not immune to misinformation and scams, LinkedIn lured people leaving X and Facebook as content moderation and fact-checking there declined. Many concluded it was worth trading rage bait on other platforms for earnest monologues about why getting laid off was a blessing in disguise.

The real-name rule doesn’t just stop jerks. It also pressures people to perform... the need to look professional has a hidden upside: smarter conversations.

https://www.wsj.com/tech/personal-tech/three-reasons-we-cant-get-enough-of-linkedin-31333eff

I think it’s not a coincidence, for instance, that so many kids really want to do music and sports, even though we all say, “No, learn how to code. That’s the thing that will actually be helpful to you.” Because music and sports are among the few examples where we actually do this kind of apprenticeship. You do the thing, you get feedback, you try and do the thing again.

One of the things I say is, imagine if we tried to teach baseball the way that we teach science. How do we teach science? What we would do is, we would tell everybody about great baseball games when they were little. Maybe when they were in high school, they could throw the ball a lot to second base. When they were in college, they could reproduce great baseball plays, but they wouldn’t actually get to play the game until they were in graduate school. If you taught baseball that way, you wouldn’t think that people would be as good at baseball.
...
I think the current way that we do schooling is a good example of Goodhart’s law. We teach kids — because kids are so good at wanting to be skilled — we teach them how to be good at school, which we think is going to be correlated with the ability to do a wide range of things as an adult. Then it ends up being a separate kind of skill.

...we know and we just take for granted that little kids like two-year-olds — we say that they don’t pay attention, but what we really mean is that they don’t not pay attention. They’re paying attention to everything at once. That’s why two-year-olds are really distractible.

Then, as we get older, we get this more and more focused kind of attention. People vary in how much they end up within that state of focused attention. I think there’re lots of reasons to believe that an industrial schooled society really pushes people in the direction of having very focused attention. We really want people to have very focused attention.