Ritsumasa Yasutomi 安富律征,共著書「複素関数」「フーリエ解析」「微分方程式」(共に村上雅人,安富律征,小林忍,飛翔舎),国許は遠州,Mamba Mentality,Miles Davis,亡父著書「未来の革命」(冨安健、国書刊行会)

Joined March 2011
2026年5月15日発売の共著書『複素関数:関数の本質を学ぶ』(村上雅人/安富律征/小林忍、飛翔舎)の見本が届きました! 私も共著者として執筆に参加しています。 宜しくお願い致しますm(_ _)m
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17日フランスでのデモに伴うリモージュ市庁舎放火で、容疑者の男を拘束。極左運動にかかわるパリ生まれの34歳。公務員への暴力ですでに知られ、テロリストと疑われるSファイル指定を受けていた。 rtl.fr/actu/justice-faits-di…
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"You reduce crime by eliminating poverty." This is one of the greatest intellectual confusions of our century. It sounds compassionate. It feels obvious. And the moment you actually test it, it falls apart. Let's look at the data. First, the correlation is real. Nobody serious denies that poorer areas have more crime. In Sweden, kids from the poorest 20% of families are about 7 times more likely to be convicted of a violent crime than kids from the richest 20%. But correlation is not causation. So Swedish researchers did something brilliant: they compared siblings. Same parents, same home, same upbringing, but different family income at different points in their childhood, because parents' income moves over time. Result, on more than 500,000 children (Sariaslan et al., British Journal of Psychiatry, 2014): once you account for what's shared inside the family, the effect of income on violent crime goes from 7x to nothing. The hazard ratio drops to 0.95. No effect. Finland ran the same test on 650,000 people. Same result: the income-crime link disappears when you compare siblings. What predicts crime isn't the bank balance. It's what travels inside families. Second test: what happens when poverty spikes for everyone at once? 2008. US unemployment doubled from 5% to nearly 10%. 15% of Americans officially poor. If poverty creates crime, crime should have exploded. Instead it fell. Year after year. Robbery, the most "economic" crime of all, dropped 10% in 2010 alone. Criminologists literally said they were stumped. Same story in the Great Depression: 25% unemployment, and crime went down in many cities. Third test: take families out of poverty and see. The US government ran a randomized lottery called Moving to Opportunity. Thousands of families in public housing got vouchers to move to low-poverty neighborhoods. For boys, violent arrests dropped at first, property crime arrests went up, and over time the effects faded. New zip code. Same behavior. Fourth: the claim that police don't matter. This one is just false. Chalfin et al. (American Economic Review: Insights, 2022): each additional police officer prevents about 0.1 homicides. And per capita, the lives saved are twice as many among Black victims as among white victims. The people who suffer most from "police don't matter" are the poorest neighborhoods. So what does predict crime? The Dunedin study followed 1,000 children from birth to age 32. Self-control measured between ages 3 and 11 predicted adult criminal convictions, even after controlling for social class and IQ (Moffitt et al., PNAS, 2011). Cognitive ability matters too: across 700,000 Swedish men, lower cognitive scores at 18 track with violent convictions, and the link barely moves when you control for childhood socioeconomic status (Frisell et al., 2012). And here's the part nobody quotes: in Dunedin, kids whose self-control improved over time did better than predicted. Behavior can change. Which means responsibility is real. Why does this matter? Because "poverty creates crime" isn't just wrong. It's toxic. It turns criminals into victims. The man who robbed you becomes a symptom of "the system," and you, the real victim, become a footnote in someone else's narrative. It merges two completely different things. "You're poor, we'll help you" is one policy. "You're poor and you committed a crime, so we'll excuse you" is another. Fusing them insults the millions of poor people who work, raise their kids, and never hurt anyone. The vast majority of poor people are not criminals. That alone kills the theory. It removes responsibility. Build a political system on "your circumstances made you do it" and you destroy the one thing that actually changes behavior: the certainty that you own your choices. Every excuse the state manufactures is an incentive. And it feeds the state forever. If every crime is a social failure, every crime justifies a new program, a new budget, a new agency. Crime becomes the business model of bureaucracy. The alternative is simple and old. A lighter state that protects instead of explains. The same rules for everyone, from the projects or from a gated community. Certain, swift punishment for anyone who commits a crime. And never, ever telling someone their crime was written in their social condition. Treating someone as responsible is respecting them. Excusing someone because they're poor is the most condescending thing you can do to them.
You reduce crime by eliminating poverty. The reason so called nice neighborhoods have lower crime rates is because people’s basic needs are being met. It is not because of police, alarm systems, or neighborhood associations. Poverty creates crime.
Readers added context they thought people might want to know
Sibling studies show no causal effect of childhood family income on violent crime after accounting for shared family factors. US violent crime declined during the 2008-09 recession despite rising poverty, and more police officers reduce homicides. pubmed.ncbi.nlm.nih.gov/25147371/ pubmed.ncbi.nlm.nih.gov/34050646/ fbi.gov/news/stories/2… pubmed.ncbi.nlm.nih.gov/37009208/
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トロント大学の研究チームによると、GPT-6 Astraでロボットを操ることで、本来難しかった科学実験の"物理的な自動化"に一定成功するようになるとのこと。 「人間研究者の役割は、科学の目標を指定することへ移る」と述べています。 彼らが今回実験で行ったのは量子ドットの合成です。 (光る極小の粒) 人間のやることは以下の3つでした。 ①「この実験をしたい」とAIに目標を伝える ②部屋の写真と機器の情報を渡す ③AIが出した計画を承認する AIはロボットの動かし方から実験の手順まで自分で組み上げ、実際の化学合成を最後までやり通したそうです。 液体を分ける装置のプログラムを書いて模擬環境で確かめ、ロボットアームで試料の板を封をする装置、測定装置へと順に運び、測定まで進めました。 これまでラボオートメーションといえば特定の目的に合わせた入念な設計が必要で、目的が少しでも変われば手間をかけて設定し直す必要がありました。 今は頭脳部分が柔軟性を獲得したことで、実験室におけるロボット操作においても汎用性を発揮しつつあるようです。 かねてより自動実験室の研究で知られる教授らによる報告でした。 この先AIが理論的な研究を行うだけでなく、物理世界にも干渉して科学を進めていく可能性を示唆する事例です。
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労働経済学
🧵1/10 Given the recent reactions of mathematicians over rapid advances in AI, I think it is important to remember that technological change has historically been a very personal event for people. Over the history of technological progress, looms have fallen silent, switchboards have gone dark, and factory lines have shrunk bringing with them a human crisis of identity and what it means to be a master of one's craft.
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講師の赤澤が論文を公開しました。 すうがくぶんかの講師陣、研究も頑張っています! ぜひご覧ください。
Ambient Chow Rings of Debarre–Voisin Fourfolds and the Beauville–Voisin Conjecture Ryo Akazawa arxiv.org/abs/2610.23376 [𝚖𝚊𝚝𝚑.𝙰𝙶]
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加えて、発がん(大腸)
「過度な飲酒が急速な認知機能低下と脳損傷を引き起こす」
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high opportunity cost
Why are French university students lining up for lunch at 11am when the cafeteria opens at noon? I took this picture on my way to work this morning because it is a good lesson in “shadow prices.” In May, France extended €1 university meals to all students. Previously, those not eligible for assistance paid €3.30. The result was not cheaper meals, but shortages. Demand surged, and students now queue an hour or more in advance to secure their lunch. What they used to pay with money, they now pay with time. And this is a lesson in shadow prices. It tells us that students are willing to sacrifice an additional hour to save €2.30, so they are implicitly valuing their time at €2.30 an hour or less. That's awful. 11 am is one of the best times to study. You are alert, but not yet tired. Even if a fraction of them studied at this time, there could be more value than the one saved by the “cheaper” meal. While the government did provide €50 million in additional funding for 2026, for a system serving more than 3 million higher-education students (about 8 cents per student per day), the problem illustrates something deeper about France. Don't get me wrong. I love living here, and I work hard every day to contribute to this country. But too many French institutions operate as though people's time were free. It is a system where enormous resources flow through the state, and simple transactions are replaced by forms, permissions, and waiting. People grow accustomed to this dependency, sometimes even demanding more of it. The implicit message of the system is that your time is cheap, your initiative is unwelcome, and your ability to decide for yourself is something to be managed. It is a sad situation because I genuinely believe France can be one of the best places in the world to live. But people are tired. And I'm not talking about those who looted sporting goods stores and vandalized public buildings over the weekend. I'm talking about the butchers, bakers, and produce sellers I meet every week at the market. The small antique dealers who worry that a mob could destroy the little capital they have. I talked to many of them yesterday. They are scared and they know there is nothing for them to do other than hide. A country that values its people should value their time. Vive la France!
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「プリンストン大学の物理学者だったホップフィールドは、新しい研究テーマを探していました。1960年代には固体物理や凝縮系物理の分野で先駆的な貢献を果たしていましたが、その終わりごろには「燃え尽き感」を覚え、そこで彼が向かった先は計算機科学……ではなく生物学でした。」
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報告が遅れておりますが、先月ZMCでは次の論文を発表しました。AIを積極的に使って結果の大枠を得て、論文としては人間の手で構成からやり直すことで、理解しやすさとアカデミックな重点を明確化するという方法を取り入れてみました。論文としてはヘンゼルスキームの理論の基礎に関する内容で、学術的な意義も高いと思います。 arxiv.org/abs/2609.30851
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統計検定で見過ごされがちな、複数テスト問題(multiple testing problem)を、温暖化加速について論じている、とても良い解説。複数テスト問題が、気候科学で意識されるようになったのはWilks (2016 BAMS)からと思う。統計検定に求められる頑健さは、格段に厳しくなりました。
While there is increasingly strong evidence that global warming is accelerating, we need to be careful about how we detect it. Unfortunately a newly published paper on the topic makes a number of mistakes in it approach, as I discuss over at The Climate Brink: theclimatebrink.com/p/how-no…
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#ClimateBrawl #ClimateCrisis Berkeley Earth released Sept 2026 data, very similar to the other majors- 2nd hottest ~0.08 below 2023. This year isn't going to break 2024's record high, but it'll be close to 2025, probably warmer as 2nd highest year.
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New "Back to the Future" sequel. 🤣🎃👻
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Bienvenue à Paris! 🇲🇫
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従妹の母、叔母は感染当時、「風邪をひいただけ」と思っていました。典型的な風疹の症状が出なかったからでしょうか。その後産まれた従妹に障害があったので調べたところ、妊娠中の風疹感染が判明した、という経緯があります。 「ただの風邪」という認識の怖さも痛感します。
私の従妹は先天性風疹症候群で、重度の難聴です。感染させた方は一時の発熱で済むかもしれないけれど、感染させられた側には、一生続く影響が残ることがある、というケースです。 自分が大丈夫だったから、他の人も平気だろう、という発想はナシでどうぞ。特にコロナはまだまだ未知の病気ですので。
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「お前が学べることは機械も全部学べるのに、今すぐ機械が学べないことの中で、お前は何を学んでるんだ?」
오픈AI 창업자 일리야 수츠케버 근황: 메타 $META 인수 제안 씹고 1년 만에 300억 달러짜리 회사 차린 뒤 모교 졸업식 가서 날린 뼈 때리는 팩트 폭격 ㅋㅋㅋ AI 씬에서 근본 중의 근본이라 불리는 일리야 수츠케버(Ilya Sutskever)가 본인 모교인 토론토 대학교 졸업식(2025년 6월 6일)에 명예박사 학위 받으러 가서 레전드 축사를 남김. 이 형 스펙부터가 그냥 인간계가 아님. • 16살에 캐나다 와서 고등학교 한 달 다니고 바로 토론토대 3학년으로 월반함 ㅋㅋㅋ • 2012년에 제프리 힌튼, 알렉스 크리제프스키랑 같이 현대 AI 붐의 시초인 알렉스넷(AlexNet) 만듦. • 오픈AI 공동 창업자 겸 수석 과학자로 지금 우리가 매일 쓰는 챗GPT 모델들 기틀을 다 닦아놓음. • 2024년 5월 오픈AI 빤스런 후 6월에 SSI(Safe Superintelligence) 창업, 2025년 3월 기준 기업가치 300억 달러(약 40조 원) 돌파. 주커버그가 침 흘리면서 인수하겠다고 달려들었는데 쿨하게 거절함. 이런 괴물이 단상에 올라가서 딱 10분 동안 연설했는데, 돈 얘기는 1도 안 하고 시간과 현실에 대해 묵직한 팩트를 날림. 핵심 논리는 단 두 줄로 요약됨. 인간의 뇌는 생물학적 컴퓨터인데, 디지털 컴퓨터라고 똑같은 걸 못 할 이유가 없다는 거임. 결국 인간이 배울 수 있는 건 AI도 전부 배울 수 있고, 머지않아 인간이 하는 모든 일을 AI가 다 하게 될 거라고 선언함. 일부가 아니라 전부 다 말임 ㅋㅋㅋ 보통 렉카들은 이 공포스러운 발언만 짤로 따서 나르는데, 진짜 중요한 건 그다음에 졸업생들한테 던진 생존 매뉴얼임. 1. 현실을 있는 그대로 받아들여라. 네가 바라는 세상이나 작년의 세상이 아니라 지금 당장의 현실을 직시해야 함. 2. 과거 후회하느라 시간 버리지 마라. 이미 조진 일에 쓰는 1시간은 앞으로 다가올 미래를 준비할 1시간을 날리는 거임. 3. 지금 당장 할 수 있는 최선의 다음 스텝이 뭔지 질문하고 바로 실행해라. 그리고 또 질문해라. 4. 네가 AI에 관심이 없어도 AI는 네 인생을 무조건 바꿀 거임. 눈 감고 귀 막는 건 전략이 아님. 5. 설레발(Hype)이나 공포 마케팅에 속지 말고 AI가 실제로 할 수 있는 진짜 성능을 직접 확인해라. 그게 너한테 남은 시간을 알려줄 거임. 수츠케버는 이게 인류 역사상 가장 거대한 도전이지만, 동시에 이걸 극복하면 역대급 보상이 따를 거라고 마무리함. 결국 이 형이 우리한테 던지는 불편한 질문은 딱 하나임. 네가 배울 수 있는 건 기계도 다 배울 수 있는데, 지금 당장 기계가 못 배우는 것 중에 넌 뭘 배우고 있냐? 이거 답 못 하면 앞으로 기술주 투자고 나발이고 밥그릇부터 걱정해야 할 판임 ㅋㅋㅋㅋㅋㅋ 지금 뭐 배우는거 없으면 좋아요❤️ 눌러라🤡 Not financial advice
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