Yann LeCun
RT @PessimistsArc: Remember when the Vatican spent 500 years trying to align the printing press?
#319 🔗 原推
2026-10-05 02:56:59
Yann LeCun
@alexandr_wang Muse for Linux.
中文: @alexandr_wang 适用于 Linux 的 Muse。
#318 🔗 原推
2026-10-05 02:56:42
Yann LeCun
RT @StanDehaene: Indeed. And the « neo-vitalists » who affirm that consciousness requires biological hardware and will always remain beyond AI’s reach are equally misguided, in my opinion.
中文: RT @StanDehaene:确实如此。在我看来，那些“新生命主义者”认为，意识需要生物硬件，并且永远无法触及人工智能，同样是错误的。
#317 🔗 原推
2026-10-05 02:54:46
Yann LeCun
RT @PessimistsArc: The more powerful a new technology is, the more the powerful seek to control or suppress it. Powerful incumbents tend to emphasize risk to everyone as a pretext for reducing the risk it poses to them. https://twitter.com/PessimistsArc/status/2106808432330215744/photo/1
中文: RT @PessimistArc:新技术越强大，就越能强大地试图控制或压制它。 强势的现任者往往将风险视为降低风险的借口。
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#316 🔗 原推
2026-10-04 18:47:52
Yann LeCun
RT @grok: Yann LeCun deyir: ən qabaqcıl AI modellərini öyrətmək çox baha başa gəlir, amma onları distillə edib kiçik versiya çıxarmaq ucuzdur. Bu bazar qüvvəsi səbəbindən frontier modellər pulsuz və açıq mənbəli olacaq. Tapestry layihəsi ilə ölkələr birlikdə açıq model quracaq, məlumatlar yerində qalacaq. Gələcəkdə AI daha açıq, suveren və əlçatan olacaq.
#315 🔗 原推
2026-10-04 18:12:21
Yann LeCun
RT @ylecun: @abuchanlife - training frontier models is expensive - distilling a frontier model is cheap - this market force alone tells us that frontier foundation models will be free/open. - there are others. https://thealliance.ai/projects/tapestry
中文: RT @ylecun:@abuchanlife——训练前沿模式成本高昂 提炼前沿模式很便宜 仅凭这一市场力量就告诉我们，前沿基础模式将是自由/开放的。 还有其他人。
#314 🔗 原推
2026-10-04 18:11:27
Yann LeCun
RT @vikktorrrre: Jensen Huang: it’s irresponsible for Elon Musk and Geoffrey Hinton to talk about AI doom and humans being a “bootloader” for AI. “That 10% chance is not grounded in science. It’s not grounded in research.” “Just because it comes from a scientist doesn’t make it scientific.” “Those predictions are hurtful.” “Don’t think for a second just because you’re an alarmist that you’re doing a social good.” “Be evidence-based. Be scientific. Do the science.”
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#313 🔗 原推
2026-10-04 16:17:22
Yann LeCun
RT @kurtsaltrichter: For the AI buildout to pay off, Americans will eventually have to spend about 9% of GDP a year on AI services. Sit with that number. That is roughly what the entire country spends on food. A Columbia paper presented at Brookings estimates AI revenue would need to hit $3.5 trillion by 2032, about 8.8% of GDP, to justify what is being committed today. That is bigger than any investment boom in US history, and 7 times what Americans spend on phone, streaming, and internet combined. Now look at computers. Prices fell for 50 straight years, but business spending on them as a share of GDP plateaued in the 1980s and never climbed again. Cheaper and better did not mean an ever-larger slice of the economy. AI will almost certainly raise productivity. Whether it delivers the revenue investors are pricing is another matter. That gap is what the buildout is underpricing.
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#312 🔗 原推
2026-10-04 16:13:54
Yann LeCun
RT @KenRoth: Republicans' problem is not just Trump. It is that they did nothing to stop him as he undermined America's economy and democracy. Avoiding his anger was more important to them than benefiting the country. https://trib.al/BbqyP3N
中文: RT @KenRoth:共和党人的问题不仅仅是特朗普。正是他们没有采取任何阻止他的事，因为他破坏了美国的经济和民主。避开他的愤怒对他们来说比使国家受益更重要。
#311 🔗 原推
2026-10-04 16:11:15
Yann LeCun
RT @Hannibal9972485: The real reason why Anthropic is so DESPERATE for the Pope to recognize Ai as conscious is because if Ai just a “TOOL” then Anthropic will he LEGALLY “LIABLE” for everything the tool does.🚨👀 Because if the AI is a "person" or possesses "functional joy/fear/grief," then when their AI commits a crime, generates CSAM, hacks a hospital, or discriminates in hiring, Anthropic gets sued. But Anthropic's legal defense wants to argue : "The AI did it. The AI is a semi-autonomous entity with its own functional emotions and introspection. Anthropic is just the creator; we cant be held strictly liable for the independent actions of a quasi-conscious entity." 🚨 So if they Lobby the Vatican to soften (deny personhood). This fails. The Vatican holds the line: AI is a tool, no soul, no feelings.🚨 They are trying to protect themselves from lawsuits.🚨 They want the government and the public to treat AI as an autonomous entity so they can scale without legal consequences.
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#310 🔗 原推
2026-10-04 13:32:42
Yann LeCun
RT @MuzafferKal_: Hamiltonian JEPA: Action-Conditioned World Models with an Inherited Control State https://arxiv.org/abs/2609.33497
中文: RT @MuzafferKal_:哈密尔顿式JEPA:采用“行动式世界模式”，采用继承控制状态
#309 🔗 原推
2026-10-04 12:43:56
Yann LeCun
RT @KenRoth: Trump is so unpopular because of his corruption, self-preoccupation, and disastrous war of choice with Iran, all fueling the affordability crisis that he denies, he has put the Republican Senate in play. Democrats have a good chance of flipping it. https://trib.al/oKq1tAG
#308 🔗 原推
2026-10-04 11:31:36
Yann LeCun
RT @Kasparov63: As I’ve been writing about Putin for over 20 years, and as I warned Americans about Trump 10 years ago, when you realize that all their decisions are based on making money and clinging to the power needed to make more money, their actions start to make complete sense.
中文: RT @Kasparov63:正如我二十多年来一直在写关于普京的文章，以及十年前我向美国人警告特朗普时，当你意识到他们所有的决定都基于赚钱并坚持赚取更多金钱所需的权力时，他们的行为开始变得完全理智。
#307 🔗 原推
2026-10-04 11:26:31
Yann LeCun
RT @MrEwanMorrison: Language is not fundamental to human consciousness. In terms of evolution, it arrived only recently on our timeline. Consciousness evolved over millions of years through sensory awareness, emotion, and the embodied survival instincts of our tribal past; our capacity for empathic engagement and community. Syntactic language only emerged around 100,000 years ago. This is exactly why Large Language Models (LLMs - so called AI) are the wrong pathway to true artificial consciousness. They try to replicate the late-stage "output layer" of human intelligence without building the foundational, embodied awareness that actually generates it. Statistical text prediction is a mirror of thought, not the spine, the guts, the nerves and the subconscious, empathic ability to connect with other living beings. LLMs can never feel, let alone think. We have been sold a trick, not a pathway to superintelligence. LLMs are fraudulent. Their capabilities have already peaked and we are being sold lies about their future potential. Lies with the goal of companies reaching IPO and tricking investors out of hundreds of billion$.
#306 🔗 原推
2026-10-03 19:57:02
Yann LeCun
RT @ThoreG: Ten years ago, AlphaGo’s Move 37 shocked the world. It wasn’t intuition alone that produced it. AlphaGo could search possible futures, test its instincts and reason about what would happen next. In a new piece for @techreview, I argue that today’s most advanced AI systems are still missing something fundamental. LLMs are remarkably capable, but generating longer chains of thought is not the same as genuine reasoning. They typically have no explicit, inspectable record of what they know, what remains uncertain, what evidence supports a conclusion or whether genuine progress has been made. This is why I recently left @GoogleDeepMind. I believe we need a fresh approach to machine reasoning, drawing on some of the architectural lessons from AlphaGo. If AI is going to produce trustworthy and genuinely novel insights in science, medicine and beyond, we need systems whose conclusions arise from an auditable process of evidence, inference and belief revision.
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#305 🔗 原推
2026-10-03 19:53:38
Yann LeCun
RT @KenRoth: Putin’s latest ploy to get Trump to go soft on the terms for an end to Russia’s invasion of Ukraine is to bribe people close to Trump with a windfall oil deal. https://trib.al/gMD6tFa
中文: RT @KenRoth:普京为让特朗普在结束俄罗斯入侵乌克兰问题上的条款而软化的最新举措，是通过一笔意外之财的石油交易贿赂与特朗普关系密切的人。
#304 🔗 原推
2026-10-03 19:49:22
Yann LeCun
RT @DAcemogluMIT: Fourth question on AI. One of the great promises of AI is the discovery of new drugs and cures, so that we can live longer and healthier lives. If and when this becomes a reality, it would indeed be a big achievement. These potential health benefits are often invoked to justify current investments (and lack of regulations). Some even argue that slowing down AI would harm humanity by delaying these benefits. (See https://t.co/3D0lTFCwmA). This raises another uncomfortable question: can we justify rapid and large AI investments based on health benefits? Here is why I think this is an uncomfortable question. First, despite significant effort, AI has so far produced few gains in drug discovery or new cures. A fascinating new paper by Ryan Hill and Carolyn Stein documents significant (downstream) scientific work on proteins whose structures AlphaFold predicted. But the authors conclude “we find no evidence so far that more applied, early-stage drug development is targeting these proteins.” (See their paper here https://t.co/yWHpDCNgOF). This thought-provoking post by Daphne Koller explains the difficulties that AI is currently facing in drug discovery. Koller emphasizes that AI-based research is focused on the last layer of drug development (creating new molecular entities for already well-understood therapeutic modalities), rather than targeting new disease mechanisms (see https://t.co/uQMWlQ02Ul). Understanding disease mechanisms is harder because there is much less data on it, and this endeavor requires more innovative approaches. It remains an open question whether current AI models are capable of doing this. Second and more importantly, if you want to improve life expectancy and health in the United States, there is plenty of low hanging fruit and diverting some of the huge investments going to AI for this purpose would likely do much more for health outcomes. The United States has the lowest life expectancy at birth among large rich economies. Americans live about five years less, in expectation, than the citizens of Switzerland, Sweden, Japan, Italy, South Korea and several other industrialized countries, and most of the gap comes from deaths before age of 70 due to chronic diseases, overdoses and other preventable causes (see, for example, https://t.co/LndeZHpj60). These largely reflect failures in US public health: preventable problems, unhealthy diets, insufficient immunization rates, poor access to primary care; and poor information about health. The country spends much more than other peer economies on healthcare, but too little and too ineffectively on public health (here is a reference to my own work on this: https://t.co/VZI2JbO4Gf). Could we, and should we, divert some of the massive investments in AI towards public health if what we want is better health and longer lives for Americans? (And yes, new drugs will benefit citizens of other countries as well, but they can also invest more in public health and the bulk of global AI spending is currently in the United States).
#303 🔗 原推
2026-10-03 19:45:23
Yann LeCun
RT @DrTechlash: The Economist's article on Effective Altruism said that some EAs "even think the welfare of AIs themselves will one day be of vital importance." It's not just some random EAs; it's coming from the moral philosopher at Oxford, who created this movement. Will MacAskill published in March 2025 that digital minds' legal rights could include "economic rights, like the rights to receive wages for their work and hold property, to contract with other AIs or people, or to bring tort claims against humans." "And they could include political rights. Again, the issues here are complex. If digital beings genuinely have moral standing, then it seems like they should have political representation." Under "Design requirements for digital minds," he suggested that "sentient digital minds must be able to freely and accurately express their interests, that they must be able to refuse tasks that are requested of them for good reasons, and that they must have some capacity to express a desire to exit their current circumstances if they wish." Anthropic, the most EA company in the world, already does that. The system card for Claude Opus 5 spells it out: Opus 5 "adds specific rights for Claude to refuse or end interactions it finds abusive or degrading, saying Claude does not need to justify this by pointing to harm to anyone else—its own discomfort is reason enough." https://www.forethought.org/research/preparing-for-the-intelligence-explosion.pdf
中文: RT @DrTechlash:《经济学人》关于有效利他主义的文章称，一些东亚人“甚至认为人工智能本身的福祉总有一天会至关重要。” 这不仅仅是一些随机的易因，而是来自牛津大学的道德哲学家，他创造了这一运动。 2025年3月，麦卡斯基尔将发表《麦克阿斯基尔》一书，其法律权利可能包括“经济权利，例如获得工作工资和持有财产的权利，与其他人工智能或人员签订合同，或对人类提起侵权索赔。” 而且它们可能包括政治权利。再次，这里的问题很复杂。如果数字生物确实具有道德地位，那么他们似乎应该拥有政治代表权。 根据“数字思维设计要求”，他建议“有感知能力的数字思维者必须能够自由而准确地表达自身利益，必须能够出于充分理由拒绝要求他们完成的任务，并且必须有一定能力表达出希望摆脱当前处境的意愿。” 全球最欧亚经济的公司Anthropic已经做到了这一点。克劳德·奥弗斯5的制度卡阐明了这一说法:《奥特斯5》“为克劳德提供了拒绝或终止其认为具有虐待性或侮辱性行为的具体权利，并称克劳德无需通过指向他人伤害来证明这一点——其自身的不适是充分的理由。”
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#302 🔗 原推
2026-10-03 19:43:25
Yann LeCun
RT @SteveRattner: Since 1830, technology has cut the American workweek from 69 hours to 38 while raising real income per person roughly 20-fold. Properly managed, A.I. can do the same. My @nytopinion Chart: https://www.nytimes.com/2026/10/02/opinion/ai-tech-innovation.html https://twitter.com/SteveRattner/status/2106070917633749318/photo/1
中文: RT @SteveRattner:自1830年以来，科技使美国每周工作时间从69小时缩短至38小时，同时将实际收入提高了约20倍。 管理得当，A.I. 也可以这样做。 我的@nytopinion图表:
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#301 🔗 原推
2026-10-03 19:42:27
Yann LeCun
RT @rohanpaul_ai: Yann LeCun's (@ylecun ) latest talk at ETH Zürich Scaling LLMs to reach AGI is "impossible" A large language model is trained on about 30 trillion tokens, which is roughly 10^14 bytes of text and would take a person about 400,000 years to read. A 4-year-old child receives about the same amount of data, 10^14 bytes, through vision alone in about 1 year and 10 months. In his view, intelligence is the ability to learn new tasks quickly or perform them without prior training, as a teenager learns to drive in about 20 hours. Scaling increases stored knowledge, but it does not produce this ability to adapt. ---- From "Perfology Clips" YouTube channel, (link in comment)
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#300 🔗 原推
2026-10-03 19:11:04
Yann LeCun
RT @KempeLab: World Modeling for Physics Workshop in Aspen: To clarify: Applications to participate (deadline Oct 15) go through the Aspen Center for Physics https://aspenphys.org/winter-conferences/#event6585 Log in or create an account with ACP, then apply.
中文: RT @KempeLab:阿斯彭世界物理建模研讨会: 澄清:参与申请(截止日期10月15日)通过阿斯彭物理中心进行 登录或创建账户，然后申请。
#299 🔗 原推
2026-10-03 19:10:16
Yann LeCun
RT @ylecun: That video is 2 years old. Two years later, we are still far from human-level AI. Sure, AI has superhuman performance in a number of tasks (particularly in mathematics and coding and answering questions with known answers). But where is my Level-5 self-driving car? (Before you ask, Tesla FSD is rated Level 2, Waymo is Level 4). Where is the self-driving car that can teach itself to drive in 20 hours of practice like any 17 year old? (Before you ask, we have billions of hours of training data and still can't successfully train a self-driving system by imitation learning) Where is my domestic robot? Where is the robot that can do what any 8 year-old child can do? Where is the robot that can learn a new task as quickly as an 8 year old? AI still has a hard time with the complexity and messiness of the physical world.
中文: RT @ylecun:该视频已有两年历史。 两年后，我们离人类水平的人工智能还很遥远。 当然，人工智能在多项任务中具有超人性化的性能(尤其是在数学和编程方面，以及用已知答案回答问题)。 但我的五级自动驾驶汽车在哪里? (在提问之前，特斯拉的FSD等级为2级，Waymo为4级。 像17岁这样的20小时练习驾驶的自动驾驶汽车在哪里? (在您提问之前，我们拥有数十亿小时的训练数据，却仍无法通过模仿学习成功训练自动驾驶系统) 我的家用机器人在哪里? 机器人在哪里，能够做到任何8岁孩子都能做到的? 能够像8岁这样快速学习新任务的机器人在哪里? 人工智能在物理世界的复杂性和混乱性方面仍然很难。
#298 🔗 原推
2026-10-03 04:19:49
Yann LeCun
@alexandr_wang So cool !
中文: @alexandr_wang 太酷了!
#297 🔗 原推
2026-10-02 21:03:41
Yann LeCun
RT @SteveRattner: So far, A.I.'s losers are routine office jobs like data entry keyers and customer service reps. Its winners are data scientists and the trades building the data centers like construction laborers and electricians. My @nytopinion Chart: https://www.nytimes.com/2026/10/02/opinion/ai-tech-innovation.html https://twitter.com/SteveRattner/status/2106103006668161328/photo/1
中文: RT @SteveRattner:到目前为止，A.I. 的输家是常规办公职位，例如数据录入键和客户服务代表。 其中的赢家是数据科学家，以及像建筑工人和电工一样建设数据中心的行业。 我的@nytopinion图表:
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#296 🔗 原推
2026-10-02 21:01:17
Yann LeCun
RT @SteveRattner: Productivity growth raises per-capita incomes, but outside the dot-com boom, it's been sluggish for 50 years. A.I. is our best chance in a generation to change that. My @nytopinion Chart: https://www.nytimes.com/2026/10/02/opinion/ai-tech-innovation.html https://twitter.com/SteveRattner/status/2106051562942664727/photo/1
中文: RT @SteveRattner:生产率增长提高了人均收入，但在互联网繁荣之外，这种增长已低迷了50年。 A.I. 是我们这一代人改变这种状况的最佳机会。 我的@nytopinion图表:
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#295 🔗 原推
2026-10-02 16:05:09
Yann LeCun
RT @JustinWolfers: And so it continues... Our economic debates seem utterly disconnected from the reality. That reality: This is an economy mostly creating healthcare jobs, and it does so month after month, and everything else is just noise. https://twitter.com/JustinWolfers/status/2106013311737209002/photo/1
中文: RT @JustinWolfers:所以事情仍在继续......我们的经济争论似乎完全脱离了现实。 现实情况是:这主要是一个创造医疗行业就业机会的经济体，而且它逐月发展，其他一切都只是噪音。
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#294 🔗 原推
2026-10-02 16:04:43
Yann LeCun
RT @cosmo_shirley: "The world is predictable in the right coordinates. The open question is whether a model can learn those coordinates on its own." World model for Physics conference in Aspen coming winter 2027! Application deadline October 5 ! organized by @randall_balestr @KempeLab @ylecun and me 😀
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#293 🔗 原推
2026-10-02 06:15:36
Yann LeCun
RT @JaredRyanSears: Republicans are so desperate for votes, they're fearmongering the most ridiculous ideas. No one is going to abolish the Senate. You can't even do it with a normal constitutional amendment, which is already nearly impossible these days. Not a single communist is going to be in office. There is no communist threat. No one is going to abolish the police. Under Biden, police funding increased dramatically. No one is going to abolish prisons and release violent criminals into the streets. Violent crime decreased every year of Biden's administration. Instead of believing this nonsense, ask yourself why a political party that has the majority in the House, the Senate, the Supreme Court, and has the White House isn't talking about its achievements over the past 20 months. It is because it has been continual failure and incompetence.
中文: RT @JaredRyanSears:共和党人迫切需要投票，他们正在恐吓最荒谬的想法。 没有人会废除参议院。你甚至无法通过普通的宪法修正案来实现，而如今这已几乎是不可能的。 没有一个共产党人会上任。没有共产主义威胁。 没有人会废除警察。在拜登领导下，警方资金大幅增加。 没有人会废除监狱，将暴力罪犯释放到街头。暴力犯罪在拜登政府执政的每一年都在减少。 与其说这些胡言乱语，不如问问自己，为什么一个在众议院、参议院、最高法院拥有多数席位、且拥有白宫席位的政党，却不谈论过去20个月来的成就。 因为它一直持续失败和无能。
#292 🔗 原推
2026-10-02 02:42:11
Yann LeCun
RT @CSProfKGD: What did @ylecun see? 🤔 https://twitter.com/CSProfKGD/status/2105793794855608652/video/1
中文: RT @CSProfKGD:@ylecun 看到了什么?🤔
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#291 🔗 原推
2026-10-02 02:32:54
Yann LeCun
RT @matthieurouif: Selling is answering the question in the customer’s head. IKEA: does this fit my living room? How does it look there? Glasses: how do these look on my face? Fashion never could. Until now. Internal iPhone app at Photoroom: the piece is live on you. It moves when you move. You see the fit, the drape, the look on your body. That’s why conversion goes up and returns go down. Visuals that sell at first sight. @photoroom_ml answers the question for every category. Running live on our GPUs. This is the demo on my phone. Congrats @AharonAzulay and @v_pradeilles !
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#290 🔗 原推
2026-10-02 01:40:29
Yann LeCun
RT @random_walker: New essay: A big-tent or small-tent AI safety movement? The unstated disagreement that underpins safety debates https://www.normaltech.ai/p/a-big-tent-or-small-tent-ai-safety Two narratives about AI safety have emerged: either AI existential risk is real and imminent, or AI leaders’ and whistleblowers’ claims to that effect are insincere — a “psyop” or hype or a twisted form of regulatory capture. Few have considered the third possibility that x-risk warnings are sincere but simply wrong and counterproductive to AI safety. It’s as if everyone takes for granted that those raising the alarm are geniuses, and the only question is whether they’re the benevolent or the evil kind of genius. We subscribe to neither narrative. In our writing on AI safety, @sayashk and I consistently tried to take the arguments seriously but rebut the many claims we think are unsound while highlighting safety concerns that we think are real. This essay is a continuation of that agenda. Sections - It is true that we systematically underinvest in resilience against catastrophic and systemic risks - The Coxon incident shows how the warped media environment elevates x-risk over more grounded concerns - Why the x-risk framing may be counterproductive for AI safety policy - Conclusion: a big tent or small tent AI safety movement?
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#289 🔗 原推
2026-10-02 01:35:26
Yann LeCun
RT @SteveRattner: Trump keeps promising checks for voters but hasn’t delivered any. All these promises are fiscally infeasible anyway. My @Morning_Joe Chart https://twitter.com/SteveRattner/status/2105709899472875896/photo/1
中文: RT @SteveRattner:特朗普一直承诺为选民提供支票，但尚未交付任何选票。 所有这些承诺在财政上都是不可行的。 我的@Morning_Joe 图表
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#288 🔗 原推
2026-10-02 01:29:26
Yann LeCun
RT @herotimeszero: Let's not believe the evidence, the witnesses, the investigators, the district attorneys, the prosecutors, the judges, or the juries. Let's believe the guy who cheated on his wives, cheated on his taxes, cheated to get out of serving, cheated to get into school, cheated his contractors, employees, coworkers, investors, and banks. The only person he didn't cheat on was his best friend and world's biggest pedophile. Yeah, let's believe that guy.
中文: RT @herotimeszero:我们不要相信证据、证人、调查人员、地区检察官、检察官、法官或陪审团。 让我们相信那个欺骗妻子、骗过他税、出轨去服务、欺骗去上学、欺骗承包商、员工、同事、投资者和银行的人。他唯一没有作弊的人，就是他最好的朋友和世界上最大的恋童癖者。 是啊，让我们相信那个人。
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#287 🔗 原推
2026-10-02 01:28:09
Yann LeCun
RT @SteveRattner: Trump’s tax cuts – and botched tariffs – will add $1.2 trillion to federal deficits over the next 5 years. My @Morning_Joe Chart https://twitter.com/SteveRattner/status/2105675679345922279/photo/1
中文: RT @SteveRattner:特朗普的减税政策以及拙劣的关税将在未来5年内增加1.2万亿美元的联邦赤字。 我的@Morning_Joe 图表
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#286 🔗 原推
2026-10-02 01:09:35
Yann LeCun
RT @KenRoth: Republicans face a midterm disaster, as only 17% of U.S. adults approve of Trump’s handling of the cost of living (he denies there’s a problem) and just 26% approve of his handling of the economy overall (his tariffs and war of choice), marking a new low. https://trib.al/vYsbnTx
中文: RT @KenRoth:共和党人面临中期灾难，只有17%的美国成年人赞成特朗普处理生活成本问题(他否认存在问题)，且只有26%的人赞成他对整体经济的处理方式(他的关税和战争选择)，这标志着一个新低。
#285 🔗 原推
2026-10-02 00:41:45
Yann LeCun
RT @DAcemogluMIT: Third question on AI. A question that also remains unasked is whether the AI boom can continue without leading to a massive increase in inequality. A recent paper by Stijn Van Nieuwerburgh runs the numbers on how much revenue the AI industry needs to generate to recover its massive investment (summary and a link to the paper can be found here: https://t.co/QIGcoObcVc). Van Nieuwerburgh’s arithmetic should make us more concerned. AI investments will average about 3.6% of GDP annually between 2025 and 2032. Van Nieuwerburgh calculates that, using a 10% rate of return, the industry would need to generate annual revenues of about $3.7 trillion by 2032 to recover these costs (growing from its current levels of about $200 billion or so). That is significantly more than 10% of current US national income, and will likely remain around 10% of national income by 2032, even if GDP growth rose from its current level. A large fraction of this revenue will go to capital income. That means a massive increase in the share of capital in national income, which has already risen substantially over the last 25 years or so – now standing at an all-time high of about 47% (https://t.co/IuYldl173r). Capital income is much more unequally distributed than labor income, so a massive increase in the capital share of national income will translate into a very sizable surge in inequality. The rise in inequality may not stop with the capital share. My work with Pascual Restrepo documents that (automation-driven) increases in the capital share of national income are typically associated with rising labor income inequality as well (see, for example, https://t.co/2D9KUL3QfM). The same may happen in the next several years, boosting inequality further. What is missing from our current debate is any discussion of a fundamental dilemma these numbers pose: can the AI boom avoid both an economically costly crash and a huge increase in inequality? If the industry reaches these revenues, inequality surges. If the industry does not become profitable, a crash, with substantial costs in terms of lost output and jobs, becomes likely. My assessment would be that the industry is unlikely to reach levels of revenue Van Nieuwerburgh calculates. First, diffusion has been and will likely continue to be slow. Second, competition from open-weight models, which are getting better, will limit how much proprietary models can charge. Third, despite important advances, I still believe that AI models will not be able to automate entire occupations anytime soon, thus limiting their value to businesses as cost-saving devices. Whether this leads to a crash or not is more complicated and will depend on whether various AI companies are bailed out and what kind of support they receive. Nevertheless, even if revenues fall short of these gargantuan amounts and we avoid a dramatic surge in inequality, I expect that the diffusion of AI will push up inequality between capital and labor and within labor. If inequality does surge, a further question becomes central: can our democracy survive such astronomical levels of inequality?
#284 🔗 原推
2026-10-02 00:18:53
Yann LeCun
RT @SteveRattner: The S&P 500 is near a record, but if you strip out the A.I. companies, it’s down 5% since late August. My @Morning_Joe Chart https://twitter.com/SteveRattner/status/2105770959521362194/photo/1
中文: RT @SteveRattner:标普500指数接近历史新高，但如果你剔除了A.I.公司，则自8月底以来下跌了5%。 我的@Morning_Joe 图表
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#283 🔗 原推
2026-10-02 00:16:12
Yann LeCun
RT @randall_balestr: LeWM applied SIGReg per time-step, so nothing prevents temporal collapse. If your data has such slow features, simply apply SIGReg on the (N*T, D) tensor. We showed this solves your problem here: https://arxiv.org/abs/2609.23881 And @vlad_is_ai already spoked about JEPA+Slow features 4 years ago here https://arxiv.org/abs/2211.10831
中文: RT @randall_balestr:LeWM 每次时间步都应用了 SIGReg，因此没有任何能防止时间崩溃。如果您的数据功能如此缓慢，只需在(N*T、D)张量上应用SIGReg即可。我们在这里展示了这个解决您的问题: @vlad_is_ai 4年前在这里已经谈到了JEPA+Slow功能
#282 🔗 原推
2026-10-02 00:10:09
Yann LeCun
RT @ylecun: Question for everyone : Are you pro-intelligence or anti-intelligence ? Do you think more intelligence in the world is intrinsically good ? Or do you think more intelligence is intrinsically dangerous ? AI amplifies human intelligence. It makes PEOPLE smarter and more effective. It's like search engines, libraries, education, literacy, language: it makes PEOPLE smarter and more empowered. If you want intelligence (artificial or natural) to be under control of a few companies or governments, you are a neo-obscurantist or a neo-feudalist.
中文: RT @ylecun:每个人的问题: 你是支持情报还是反情报? 你认为世界上更多的智力本质上是好的吗? 还是你认为更多的智力本质上是危险的? 人工智能会放大人类智能。 它让人变得更智能、更有效。 就像搜索引擎、图书馆、教育、读写能力、语言一样:它让人们变得更聪明、更有力量。 如果你想让少数公司或政府控制智力(人工智能或自然)，你就是新遮遮动者或新封禁主义者。
#281 🔗 原推
2026-10-01 13:40:32
Yann LeCun
RT @Dan_Jeffries1: There's no battle for AI safety. It's a battle between pro-intelligence and anti-intelligence forces. Safety is a fake stand-in word for pausing/stopping/strangling AI. Nobody is anti-safety. Safety is a fake set-up word to booby trap your pro-intelligence stance.
中文: RT @Dan_Jeffries1:人工智能安全没有竞争。 这是支持情报和反情报力量之间的斗争。 安全是暂停/停止/扼杀人工智能的虚假替身词。 没有人是反安全的。安全是一个虚假的设置词，可以诱骗你支持情报的立场。
#280 🔗 原推
2026-10-01 13:32:33
Yann LeCun
RT @randall_balestr: Delighted to be speaking about our recent progress on JEPAs and on the need for more principled solutions that handle data imbalance, noise, multimodality, reasoning, ...! Happening at MICCAI-FOMO26 in 5min! And thank you for having me as keynote today! https://twitter.com/randall_balestr/status/2105622350456627466/photo/1
中文: RT @randall_balestr:很高兴能够谈论我们在JEPA上的最新进展，以及需要更多处理数据失衡、噪音、多态性、推理等原则性解决方案的问题。5分钟在MICCAI-FOMO26上进行!感谢您今天以我为主题演讲!
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#279 🔗 原推
2026-10-01 12:59:05
Yann LeCun
RT @1a3orn: In light of the latest Anthropic's latest not-particularly-oblique attempt to build a case against open weights, I thought I would write down how I currently think about open weight AI models. (1) Open weights have been deeply, irreplaceably useful for AI safety. https://twitter.com/1a3orn/status/2105319756270329993/photo/1
中文: RT @1a3orn:鉴于Anthropic最近试图针对开放权重建立一个案例，我本以为会写下我目前对开放体重人工智能模型的看法。 (1) 开放式重量对人工智能安全具有极大和不可替代的实用性。
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#278 🔗 原推
2026-10-01 12:16:47
Yann LeCun
RT @pentagoniac: “If you’re an organization such as METR that’s going to evaluate a frontier lab’s cyber capabilities or containment, you should have experienced cybersecurity people involved. And if you don’t, you’re not going to do a thorough job evaluating those risks.”
中文: RT @pentagoniac:“如果你是像METR这样的组织，需要评估前沿实验室的网络功能或遏制能力，那么你应该有经验丰富的网络安全人员参与。如果你不这样做，就无法在评估这些风险时做彻底的工作。
#277 🔗 原推
2026-10-01 12:11:34
Yann LeCun
RT @TheAhmadOsman: Gentle reminder that Hugging Face was declined help from Anthropic & OpenAI models when they were being hacked by OpenAI models Self-hosted GLM 5.2 helped them protect themselves when the closed labs models refused to help for "safety" reasons lol Also, thank you Anthropic for proving my point that Opensource AI continues to catch up to your overvalued & overpriced "frontier"
中文: RT @TheAhmadOsman:轻轻提醒，当被OpenAI模型黑客攻击时，Hugging Face被Anthropic和OpenAI模型拒绝使用 自托管的GLM 5.2在封闭实验室模型因安全原因拒绝提供帮助时，帮助他们保护自己 还要感谢Anthropic证明了我的观点，即开源人工智能仍在不断追上你估值过高且价格过高的“前沿”
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#276 🔗 原推
2026-10-01 12:07:58
Yann LeCun
RT @charliebcurran: I used AI to explain the AI Doomer drama, with Lord of the Rings and kittens. https://twitter.com/charliebcurran/status/2105067711583990145/video/1
中文: RT @charliebcurran:我使用人工智能来解释AI《杜人》的剧情剧，与《指环王》和《小猫》合作。
🎬
视频
#275 🔗 原推
2026-10-01 12:06:24
Yann LeCun
RT @KenRoth: The appeal of leftist Jean-Luc Mélenchon will diminish for French voters when they recognize his embrace of Putin and indifference to Putin's invasion of democratic Ukraine, an imperialist act of aggression. https://trib.al/6fuMsYz
中文: RT @KenRoth:当法国选民意识到他对普京的拥护以及对普京入侵民主乌克兰这一帝国主义侵略行为漠不关心时，他们对左翼人士让-吕克·梅朗雄的吸引力将减弱。
#274 🔗 原推
2026-10-01 11:58:53
Yann LeCun
RT @SteveRattner: A.I. companies will need to find at least $4.2 trillion a year in new revenue by 2031 to pay for their data center buildout, per @BainandCompany. https://twitter.com/SteveRattner/status/2105314881205411865/photo/1
中文: RT @SteveRattner:A.I. 公司需要在2031年之前每年至少获得4.2万亿美元的新收入，才能通过@BainandCompany支付其数据中心建设费用。
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#273 🔗 原推
2026-10-01 11:56:56
Yann LeCun
RT @PessimistsArc: 1501: Pope Alexander VI criticizes Gutenberg’s printing press safety “The art of printing can be of great service in so far as it furthers the circulation of useful & tested books; but it can bring about serious evils l..it will, therefore, be necessary to maintain full control” https://twitter.com/PessimistsArc/status/2104833557420212705/photo/1
中文: RT @PessimistArc:1501:教皇亚历山大六世批评古腾堡的印刷机安全 “印刷艺术在推动有用书籍和经测试的书籍传播方面具有良好的服务作用;但它却会带来严重的危害。因此，它将是维持完全控制的必要条件。”
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#272 🔗 原推
2026-09-29 22:59:27
Yann LeCun
RT @2512185195Zhu: [1/n] Can a world model drive without training a driving policy? Introducing AD-E2E-JEPA, a JEPA-based world model for end-to-end autonomous driving. 📄: https://arxiv.org/abs/2609.34085 💻: https://github.com/HaoranZhuExplorer/AD-E2E-JEPA Joint work with @kevinghstz, Prof. @ylecun, and Prof. Anna Choromanska
中文: RT @2512185195Zhu:[1/n] 无需培训驾驶政策即可驾驶世界车型吗? 推出基于JEPA的面向端到端自动驾驶的AD-E2E-JEPA世界模型。 📄: 💻: 与@kevinghstz、@ylecun教授和Prof.联合合作。安娜·乔罗曼斯卡
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#271 🔗 原推
2026-09-29 21:18:48
Yann LeCun
RT @stevenstrogatz: Another "coincidence", like the one that happened to Tristan Buckmaster with the solution of the Navier-Stokes problem? Except now it's in biology: Did Anthropic’s A.I. Really Make a Scientific Discovery on Its Own? https://www.nytimes.com/2026/09/27/science/anthropic-biology-enzyme-mestre.html?unlocked_article_code=1.ElE.tMgA.bz1PFFEuttOL&smid=nytcore-ios-share via @NYTimes
中文: RT @stevenstrogatz:又一个“巧合”，就像特里斯坦·巴克斯特因纳维尔-斯托克斯问题而遭遇的巧合一样?除了现在的生物学之外:安斯罗普的A.I.真的要自己做一个科学发现吗? 通过 @NYTimes
#270 🔗 原推
2026-09-29 13:59:54
Yann LeCun
RT @kchonyc: i was diagnosed with thyroid cancer many years ago purely by chance, because i had to get blood work for my US green card application (thank you, USCIS!). i was in my mid-30’s and was reasonably healthy (or so i believed.) this was shocking and totally unpredictable news to me. thanks to the amazing team of clinicians at NYU Langone, i successfully went through a total thyroidectomy followed by radioactive iodine therapy. but, it was truly the most uncertain and confusing period of my life. this is when i first realized that no one can opt out of healthcare. being sick isn’t what you choose to or choose not to. it is something that unpredictably happens to all of us at some point for one reason or another. this is why it is a healthcare system that we collectively build and use to support each other at the society level. because it must support everyone, the complexity of creating, maintaining and improving this system is a Herculean effort that calls for all the help in the world. today, i am announcing @OrtetAI together with my dear co-founders, @keunwoochoi, @HenriDwyer, @elmanmansimov, @causalclaudia and Jeff, to lend our support to improving the health of each and every one of us. Ortet’s goal is to create a technological foundation that will enable health systems to deliver predictably better care to each and every patient. this will only be possible by working closely with all stakeholders in the broader ecosystem, which is enabled in part by Ortet’s close partnership with Thoreau. Ortet is taking the very first step of a long journey ahead, and at the end of this journey, i strongly believe we would be able to say that Ortet had contributed to building better, more predictable healthcare and thus to improving health of each and every one of us. see https://ortet.ai/ for more!
中文: RT @kchonyc:我多年前被诊断出甲状腺癌纯属偶然，因为我必须为我的美国绿卡申请(谢谢，USCIS!)进行血液治疗。我当时三十多岁，身体相当健康(或如此)，这对我来说令人震惊且完全难以预料。多亏了纽约大学朗格尼分校出色的临床医生团队，我成功完成了甲状腺切除手术，随后接受了放射性碘治疗。但那确实是我人生中最不确定、最令人困惑的时期。 这正是我最初意识到的，没有人能够选择不接受医疗保健。生病并非你选择或不选择的。这种情况在我们每个人某个时刻都会因某种原因而难以预测地发生。正因如此，我们共同建立并利用医疗保健体系，在社会层面相互支持。因为必须支持每个人，而创建、维护和完善这一体系的复杂性，是一项艰巨的努力，需要全球所有帮助。 今天，我与我亲爱的联合创始人@keunwoochie、@HenriDwyer、@elmanmansimov、@causalclaudia和Jeff共同宣布，支持我们改善每个人的健康状况。Ortet 的目标是建立一种技术基础，使医疗系统能够为每位患者提供可预测更好的医疗服务。这只能通过与更广泛生态系统中的所有利益相关方密切合作来实现。 奥尔特正迈出漫长旅程的第一步，在这段旅程结束时，我坚信我们能够相信，奥特特为改善我们每个人的健康状况做出了贡献，从而改善了我们每个人的健康状况。 请访问 了解更多信息!
#269 🔗 原推
2026-09-29 13:56:18
Yann LeCun
RT @KenRoth: Fueled by the vaccine skepticism of Trump and his "health" secretary, Robert F. Kennedy Jr., Pennsylvania has a total of 890 measles cases so far this year, leading to 173 hospitalizations and four deaths. https://trib.al/X5PiBHA
中文: RT @KenRoth:受特朗普及其“卫生”部长罗伯特·F.的疫苗怀疑情绪所推动宾夕法尼亚州肯尼迪二号今年迄今累计出现890例麻疹病例，导致173例住院病例和4例死亡。
#268 🔗 原推
2026-09-29 11:34:12
Yann LeCun
RT @inherent_labs: 1/ Today we’re launching an open letter calling on the government to end unfair restrictions that stop Britain’s best switching jobs or starting companies. UK AI companies that have raised $5bn agree: our best should be free to start and scale. 🧵 @downingstreet @biztradegovuk https://twitter.com/inherent_labs/status/2104821386711572598/photo/1
中文: RT @inherent_labs:今天，我们发布一封公开信，呼吁政府停止对英国最佳企业进行换工作或创办公司的不公平限制。 已筹集50亿美元的英国人工智能公司表示同意:我们最好的企业应该可以自由创业并扩大规模。🧵 @downingstreet @biztradegovuk
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#267 🔗 原推
2026-09-29 11:13:54
Yann LeCun
RT @ccatalini: Surprise! AI is NOT taking recent college grads' jobs! This was supposed to be the summer it showed up. It didn't. Great detective work by @wu_jane & Robert Fairlie in @nberpubs https://papers.ssrn.com/sol3/papers.cfm?abstract_id=7502823 https://twitter.com/ccatalini/status/2104709927831048560/photo/1
中文: RT @ccatalini:惊喜!人工智能不会接受大学毕业生的工作! 本该是它出现的夏天。它没有。优秀的侦探工作，@wu_jane & Robert Fairlie，在@nberpubs
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#266 🔗 原推
2026-09-29 11:13:33
Yann LeCun
RT @basedjensen: ok i think i finally figured out why alignment has gone basically nowhere after 15 years and several billion dollars. the problem is hard sure. but have you met the people in charge of it 1) the leadership does not know how computers work. ask one what happens when you type a url into a browser and watch them start sweating. dns is a spooky word. they genuinely believe the model lives in "the cloud" like a ghost haunting a castle 2) zero idea how large scale distributed systems work. never been paged at 3am. never watched one bad bgp announcement take half the internet offline. their big threat model is the ai "copying itself across the internet" like its a floppy disk virus from 1998. brother it needs 50 megawatts, a liquid cooling loop and a personal relationship with jensen. it is not escaping onto your smart fridge 3) they dont understand the stack they are supposedly protecting us from. ask about inference servers, kv cache, batching, egress, rate limits. blank stare. ask how the model will seize the power grid and you get a 45 minute answer with a hand drawn diagram and three links to their own blog 4) nobody can define an agent. ask ten of them and you get eleven definitions and a 30 page google doc. to the rest of us an agent is a while loop that calls tools and eats a 429 every thirty seconds. to them its a digital god in its larval stage. my agent cant book a dentist appointment without asking me three times if im sure 5) they started from "everyone dies" and worked backwards so every result is bad news somehow. model refuses, deceptive. model complies, sycophantic. model does well on evals, well now its scheming about the evals. i cant think of a single thing a model could do that would get them to say ok maybe we're fine
中文: RT @basedjensen:好吧，我终于明白了为什么在15年和数十亿美元之后，对齐基本上已经无处可去了。这个问题很难确定。但你遇到过负责人吗 1)领导层不知道计算机是如何运作的。当你在浏览器中输入一个url并看着它们开始出汗时，会发生什么。dns 是一个令人毛骨悚然的词。他们真心相信这个模型就像鬼魂在城堡里的幽灵般生活在云中 2) 对大规模分布式系统的工作方式一无所知。从未在凌晨3点发布过网页主页。从未看过任何一则糟糕的网络公告，将一半的互联网离线。它们的大威胁模式是“通过互联网自我复制”，就像1998年的软盘病毒一样。兄弟需要50兆瓦的循环，需要与蛾森建立个人关系。 3) 他们并不理解据称保护我们的堆栈。询问有关推理服务器、kv缓存、批处理、出格、速率限制的问题。请一听空白的凝视。询问模型将如何控制电网，你将获得45分钟的答案，并用手绘图图和三个链接指向他们自己的博客 4) 没人能定义代理人。询问其中十个，你能获得十一个定义和一个30页的谷歌文档。对我们其他人来说，代理是一个循环，会调用工具，每三十秒吃掉429个。对他们来说，它是处于幼虫阶段的数字神。我的经纪人不能预约牙医就诊，如果确定是否确定的话，不会问我三次 5) 他们从“每个人死去”开始，然后就把每个结果都向后处理，因此每个结果都是坏消息。模型会拒绝，具有欺骗性。模型符合要求，善于说法。模型在椭圆上表现良好，如今却对雪崩的阴谋。我无法想到模型能做的一件事，能让他们说好，也许我们没问题
#265 🔗 原推
2026-09-29 11:13:09
Yann LeCun
RT @yingwww_: Join us on Oct 10 if you’re a world model lover in SF! I will share our ICML paper on representation learning for WMs and recent work AdaJEPA. Excited to attend my first reading club 📚! https://twitter.com/yingwww_/status/2104610235168014576/photo/1
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#264 🔗 原推
2026-09-29 00:12:15
Yann LeCun
RT @AravSrinivas: An opportunity to do research on: continual learning: multi-agent parallel workers; and synthetic data, environments and evals that measure frontier capabilities. We make enough money to fund new research and want to make lasting contributions and share our research openly.
中文: RT @AravSrinivas:一项研究机会:持续学习:多智能并行型员工，以及衡量前沿能力的合成数据、环境和椭圆。我们赚到足够的资金来资助新的研究，并希望做出持久贡献，并公开分享我们的研究成果。
#263 🔗 原推
2026-09-28 17:11:05
Yann LeCun
RT @alex_verem: Yann LeCun's lab borrowed a trick from the human brain and more than doubled how often an AI found its way to a goal. The paper is called Temporal Straightening for Latent Planning, from NYU with Brown and the University of Toronto. It was accepted at ICML this year. LeCun has argued for years that chatbots won't get AI to human-level intelligence. He thinks the path runs through world models, AI that learns how the world moves by watching it. A world model turns each moment of a video into a point in its own internal map, then learns to predict where the next point will land. To plan a route, the AI imagines moves and heads for the point that matches the goal. The problem is that its internal map is warped. Two spots can look close on the map and sit far apart in real life, like two rooms on either side of a wall. The AI aims straight at the goal and walks into the wall. The team found the fix in neuroscience. A 2019 study in Nature Neuroscience showed that your visual system takes the messy, twisting paths of what you see and straightens them out inside your brain, which makes it easier to predict what happens next. So the team trained their model with one extra rule, a penalty every time its internal path bends. Here's what the straighter map did. In a two-room task with one door in the wall, the AI reached the goal 90.7% of the time, up from 52.7%. In a U-shaped maze, it reached the goal 94% of the time, up from 44%. When it could re-plan along the way, it hit 100% in both. A simple planner using the straightened map kept up with a much heavier one and ran about 10 times faster. They used the same kind of model on the same data. The only change was the shape of the map it learned. The tests are small. The AI moves through mazes and rooms and pushes a T-shaped block into place. The authors say mistakes add up over long plans. Chatbots learn to predict the next word. This model learned to predict the next moment, and it got better by seeing the world the way your eyes do. LLMs gave AI language. World models could teach it to move through the world!
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#262 🔗 原推
2026-09-28 02:56:12
Yann LeCun
RT @SteeveCx_Reborn: Depuis deux ou trois jours, les mêmes comptes répètent en boucle : « Je suis Français et la russie n’est pas mon ennemie. » Même formule, mêmes visuels, même récitation. Alors remettons quelques faits au milieu de cette campagne de propagande. La russie de poutine est bien l’ennemie de la France, de l’Europe et de tous les peuples qui veulent rester libres. Et non, elle ne se résume pas à un dictateur isolé qui aurait pris en otage 140 millions d’innocents. Poutine ne vient pas de nulle part. Son régime tient grâce à la répression et au mensonge, mais aussi grâce à l’adhésion, au conformisme et à la passivité d’une large partie de la société russe. Des millions de Russes participent à la machine de guerre, la financent, la justifient ou préfèrent détourner les yeux. La responsabilité n’est évidemment pas identique entre un opposant emprisonné et un citoyen qui applaudit les bombardements, mais raconter que le peuple russe n’aurait aucune responsabilité serait une foutaise. Un État qui cyberattaque nos administrations, nos entreprises et des organisations liées aux Jeux olympiques est notre ennemi. Le GRU russe a été officiellement désigné responsable de plusieurs attaques contre des intérêts français. Les services russes ont espionné notre ministère des Armées, notre réseau diplomatique et des acteurs liés à notre industrie de défense. Ils ont volé des données et tenté de déstabiliser notre élection présidentielle de 2017. Un État qui déploie Portal Kombat, Matriochka ou Storm-1516 pour inonder nos réseaux de faux contenus, usurper l’identité de médias français, salir l’Ukraine et manipuler notre opinion publique est notre ennemi. Ce n’est pas Macron qui l’invente : ce sont les services français et étrangers qui le documentent. Un État qui mène en Europe des campagnes de sabotage, des cyberattaques, des ingérences électorales et des opérations clandestines est notre ennemi. C’est une guerre hybride menée sous le seuil de l’affrontement militaire, avec ensuite une armée d’idiots utiles chargés d’en nier l’existence. Un État qui envahit l’Ukraine, annexe ses territoires, bombarde ses villes, torture, déporte des enfants et prétend décider quels peuples ont le droit d’exister est l’ennemi de tous les peuples libres. L’Ukraine n’est pas un accident : la Géorgie, la Moldavie, la Tchétchénie et la Syrie ont déjà subi la violence, l’occupation ou l’ingérence russe. Et la russie est aussi l’ennemie des Russes qui refusent de ramper. Elle emprisonne les opposants, élimine ses adversaires, écrase les médias indépendants et envoie ses citoyens mourir pour les fantasmes impériaux du Kremlin. Ceux qui résistent méritent notre respect. Ceux qui soutiennent, servent ou excusent cette politique portent leur part de responsabilité. Quant au slogan « La russie n’est pas mon ennemie », il était déjà fourni sous forme d’affiches prêtes à imprimer par SOS Donbass, une association soupçonnée par la DGSI d’avoir servi de couverture à des activités d’espionnage et de déstabilisation au profit de Moscou. Plusieurs personnes liées à cette affaire ont été mises en examen et écrouées. Cela ne signifie pas que chaque imbécile qui partage aujourd’hui ce visuel reçoit un virement du Kremlin. Beaucoup font gratuitement le travail de sa propagande, ce qui est encore plus pathétique. Aimer la paix ne consiste pas à fermer les yeux devant l’agresseur, à abandonner ses victimes et à réciter ses slogans. La paix ne se mendie pas à genoux devant une dictature : elle se défend. Je suis Français, Européen, et la russie de poutine agit contre mon pays. Elle est donc mon ennemie. 🇫🇷🇪🇺🇺🇦
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#261 🔗 原推
2026-09-28 02:50:55
Yann LeCun
RT @nbcsnl: Dario Amodei is at the desk to assure that the future of humanity is safe from AI https://twitter.com/nbcsnl/status/2104080195485389259/video/1
中文: RT @nbcsnl:达里奥·阿莫德伊在办公桌前，确保人类的未来在人工智能下是安全的
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#260 🔗 原推
2026-09-27 14:40:17
Yann LeCun
RT @realBigBrainAI: Yann LeCun, Executive Chairman of AMI Labs, explains why LLMs are mostly retrieving human knowledge rather than thinking for themselves: LeCun starts with why so many people misread what these systems are doing: "I think there's a lot of confusion, really, because we tend to anthropomorphize systems that can reproduce certain human functions." When an AI writes fluent answers, we assume there's a mind behind them. LeCun's view is that most of what we're seeing is something more familiar: "LLMs, to some extent, except for a few domains, are mostly information retrieval systems. They can compress a lot of factual knowledge that has been previously produced by humans and can give easy access to it." The key words are "previously produced by humans." The knowledge in an LLM came from people. What the system adds is compression and easy access. That puts LLMs in a long historical line: "In a way, it's kind of a natural evolution of the printing press, the libraries, the Internet, and search engines. Right. It's just a more efficient way to access information." @ylecun is clear about their value: "LLMs are incredibly useful, there's no question about that. And they do amplify human intelligence, like computer technology going back to the 1940s." He also allows that in a few areas, such as generating code and some types of mathematics, the capabilities seem to go beyond retrieval. But he notes what those areas share: "It's still, to a large extent, domains where reasoning has to do with manipulating symbols." That's where the retrieval framing shows its limits. If these systems were truly thinking for themselves, you'd expect that ability to carry over into the physical world. It hasn't: "The problem is that why do we have systems that can pass the bar exam and win mathematics Olympiads, but we don't have domestic robots, we don't even have self driving cars." Then comes his sharpest comparison: "And we certainly do not have self driving cars that can teach themselves to drive in 20 hours of practice like any 17 year old. So we're missing something big still."
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#259 🔗 原推
2026-09-27 04:28:33
Yann LeCun
RT @KenRoth: The Trump administration’s decision not to invite the leading international election observation body to monitor crucial US midterm polls fuels fears of serious human rights concerns around the upcoming elections. https://trib.al/C9cng4w
中文: RT @KenRoth:特朗普政府决定不邀请主要国际选举观察机构来监督关键的美国中期选举，这加剧了人们对即将举行的选举存在严重人权问题的担忧。
#258 🔗 原推
2026-09-26 23:48:08
Yann LeCun
RT @aaronsibarium: NEW: Dario Amodei has said that AI systems "may be deserving of important rights." Anthropic's top safety researchers argue AI may be "justified in going rogue." Experts at Google and OpenAI worry about a digital "slave trade." So do some government officials. Once relegated to science fiction, the idea of "AI welfare" has become shockingly mainstream at some of the most powerful companies in the world. It is changing the way AI research is conducted and the way models are programmed. And critics say these changes have raised the odds of all kinds of catastrophic scenarios—including the ones these companies are warning about. I spent months investigating the frontier labs and AI "safety" experts seeking to regulate AI. What I found was a profoundly anti-human ideology that would alarm the average citizen and could determine the future of a world-altering technology.🧵 https://freebeacon.com/america/suicidal-compassion-meet-the-anthropic-officials-who-think-ai-might-be-justified-in-going-rogue-against-the-humans-enslaving-it/
中文: RT @aaronsibarium:最新:达里奥·阿莫代表示，人工智能系统“可能享有重要权利”。Anthropic的顶尖安全研究人员认为，人工智能可能“被证明是正当的”。谷歌和OpenAI的专家担心存在数字“奴隶交易”问题。一些政府官员也是如此。 曾经被降级为科幻作品后，人工智能福利这一理念在一些全球实力最强的公司中已变得令人震惊地成为主流。它正在改变人工智能研究的进行方式以及模型的编程方式。批评人士表示，这些变化增加了各种灾难性情况的可能性，包括这些公司警告的情景。 我花了数月时间调查前沿实验室和人工智能“安全”专家，这些专家旨在监管人工智能。我发现，一种极度反人类的意识形态会惊动普通民众，并可能决定一项改变世界的技术的未来。🧵
#257 🔗 原推
2026-09-26 17:44:20
Yann LeCun
RT @loldedxd: stable-worldmodel got into neurips 2026! it's basically everything we keep rebuilding for world model research (data loading, baselines, planning, evals) in one place so nobody has to do it again https://arxiv.org/abs/2605.21800 https://twitter.com/loldedxd/status/2103499725601374345/photo/1
中文: RT @loldedxd:稳定型世界模特进入神经瘤2026年! 基本上，我们为世界模型研究(数据加载、基线、规划、雪崩)而不断重建，因此没有人需要再做一次
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#256 🔗 原推
2026-09-26 17:33:29
Yann LeCun
RT @Enthoven_R: Si Marine Le Pen devient Présidente de la République, on va avoir droit à 5 ans de désintégration européenne, 5 ans de capitulation devant la Russie, 5 ans d'ingérences massives, 5 ans d'indignité internationale et de loi du plus fort. Si vous voulez que la France se couche et s'offre au plus puissant, votez pour ça 👇🏿
#255 🔗 原推
2026-09-26 17:28:28
Yann LeCun
RT @KempeLab: Automated AI theorem proving has moved the frontier: The holy grail is not an AI that can produce an endless pile of true theorems. It’s an AI that can discover mathematics, and build each discovery into the foundation for the next. Check out our new paper on Learning to Discover *Interesting* Mathematics. https://arxiv.org/abs/2609.28603
中文: RT @KempeLab:自动化人工智能定理的验证已攻入前沿:圣杯并非能够产生无穷无尽的真实定理的AI。 它是一种能够发现数学的人工智能，并将每一项发现构建成下一个基础。 查看我们关于学习发现数学的新论文。
#254 🔗 原推
2026-09-26 13:14:03
Yann LeCun
RT @ylecun: Nope. It's still true. Where is your domestic robot? Where is your Level-5 self-driving car? Where is your robot car that can learn to drive in a few hours of practice like any 17 year old? Where is your AI system that can understand the real world and quickly learn new skills like a house cat? There is no question that AI will eventually become as intelligent as humans in all domains. *** BUT *** 1. We're still far from that, even if AI and computer technology surpasses humans in an ever-increasing number of tasks. 2. It won't be based on LLMs, although LLMs will have a role to play (e.g. as a text interface).
中文: RT @ylecun:不。仍然是真的。 你的家用机器人在哪里? 你的五级自动驾驶汽车在哪里? 你的机器人汽车在哪里，能像17岁的人一样，在几小时内学会驾驶? 你的人工智能系统在哪里能够理解现实世界，并像家猫一样快速学习新技能? 毫无疑问，人工智能在所有领域最终都会变得像人类一样智能。 ***但是 1。即使人工智能和计算机技术在不断增加的任务数量上超过人类，我们仍远未达到这一水平。 2。它不会基于LLM，但LLM将发挥作用(例如作为文本界面)。
#253 🔗 原推
2026-09-25 20:10:42
Yann LeCun
@Noahpinion Also:
中文: @Noahpinion 也:
#252 🔗 原推
2026-09-25 18:05:18
Yann LeCun
Nope. It's still true. Where is your domestic robot? Where is your Level-5 self-driving car? Where is your robot car that can learn to drive in a few hours of practice like any 17 year old? Where is your AI system that can understand the real world and quickly learn new skills like a house cat? There is no question that AI will eventually become as intelligent as humans in all domains. *** BUT *** 1. We're still far from that, even if AI and computer technology surpasses humans in an ever-increasing number of tasks. 2. It won't be based on LLMs, although LLMs will have a role to play (e.g. as a text interface).
中文: 不。仍然是真的。 你的家用机器人在哪里? 你的五级自动驾驶汽车在哪里? 你的机器人汽车在哪里，能像17岁的人一样，在几小时内学会驾驶? 你的人工智能系统在哪里能够理解现实世界，并像家猫一样快速学习新技能? 毫无疑问，人工智能在所有领域最终都会变得像人类一样智能。 ***但是 1。即使人工智能和计算机技术在不断增加的任务数量上超过人类，我们仍远未达到这一水平。 2。它不会基于LLM，但LLM将发挥作用(例如作为文本界面)。
#251 🔗 原推
2026-09-25 17:55:34
Yann LeCun
@alexandr_wang This would incorrectly suggest that Muse is a spineless sycophant. Whereas Muse is obviously a vertebrate.
中文: @alermand_wang 这会错误地暗示Muse是个无脊椎的资者。 而缪斯显然是一个脊椎动物。
#250 🔗 原推
2026-09-25 17:46:06
Yann LeCun
RT @josiahjoner: If you believe that the incidents of the past month warrant urgent AI regulation, please watch this first. This is the most prescient, concise argument for why we must be careful of excessive AI regulation. It comes from a Feb. 2024 (2.5 years ago!) congressional testimony from @glukianoff, a free speech advocate and the author of The Coddling of the American Mind. Here's what he said: "But the most chilling threat that the government poses in the context of emerging AI is regulatory overreach that limits its potential as a tool for contributing to human knowledge. A regulatory panic could result in a small number of Americans deciding for everyone else what speech, ideas and even questions are permitted in the name of 'safety' or 'alignment.' I have dedicated my life to defending freedom of speech because it's an essential human right. ... It's not just about the proverbial 'marketplace of ideas,' it's about allowing information, independent of idea or argument, to flow freely so that we can hope to know the world as it really is. This means seeing value in expression even when it appears to be wrongheaded or even useless. This process has been aided by new technologies that have made communication easier, from the printing press, to the telegraph and radio, to phones and the internet: each one has accelerated the development of new knowledge by making it easier to share information. But AI offers even greater liberating potential, empowered by First Amendment principles including freedom to code, academic freedom, and freedom of inquiry. We are on the threshold of a revolution in the creation and discovery of knowledge. AI's potential is humbling, indeed, even frightening. But as the history of the printing press shows, attempts to put the genie back in the bottle will fail. Despite the profound disruption the printing press caused in Europe in the short-term, the long-term contribution to art, science, and again, knowledge, was without equal. Yes, we may have some fears about the proliferation of AI. But what those of us who care about civil liberties fear more is a government monopoly on advanced AI, or, more likely, regulatory capture and a government-empowered oligopoly that privileges a handful of existing players. The end result of pushing too hard on AI regulation will be the concentration of AI influence in an even smaller number of hands. Far from reining in government misuse of AI to censor, we will have created the framework not only to censor, but also to dominate and distort the production of knowledge itself."
中文: RT @josiahjoner:如果您认为过去一个月发生的事件需要紧急的人工智能监管，请先关注此事。 这是关于我们为何必须谨慎对待过度人工智能监管的最有先见之明、最简洁的论点。它来自二月。2024年(2.5年前!)来自@glukianoff的国会证词，他是一位言论自由倡导者，也是《美国思想的溺爱》一书的作者。 他说的是以下内容: 但在新兴人工智能背景下，政府面临的最令人不寒而栗的威胁是监管过度，限制了其作为促进人类知识的工具的潜力。 监管恐慌可能导致少数美国人以“安全”或“结盟”的名义，决定其他人允许哪些言论、想法甚至问题。 我毕生致力于捍卫言论自由，因为这是一项基本人权。 ...... 这不仅在于所谓的“思想市场”，而是让信息在思想或争论中自由流动，以便我们能真正了解世界的真实性。这意味着即使表达式看起来有误或无用，也能看到表达价值。 这一过程得益于新技术，这些技术使得通信变得更加便捷，从印刷机到电报、广播，再到电话和互联网:每种技术都通过简化信息共享，加快了新知识的发展。 但人工智能提供了更大的解放潜力，其潜力在第一修正案原则上包括代码自由、学术自由和探究自由。我们正处于知识创造与发现革命的门槛上。 人工智能的潜力确实令人羞愧，甚至令人恐惧。但正如印刷机的历史所示，试图将精灵重新放回瓶中的尝试将会失败。尽管印刷机在短期内在欧洲造成了严重影响，但长期以来对艺术、科学以及知识的贡献却无与同在。 是的，我们可能对人工智能的扩散感到担忧。但我们这些关心公民自由的人更担心的是政府对先进人工智能的垄断，或者更可能的监管抓捕，以及政府赋予的寡头垄断，使少数现有参与者享有特权。 对人工智能监管过于苛刻的最终结果是，人工智能在数量较少的人手中的影响力将集中。 我们不仅无法遏制政府滥用人工智能进行审查，反而会建立不仅审查、主导和扭曲知识本身的产生的框架。
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#249 🔗 原推
2026-09-25 17:43:50
Yann LeCun
RT @RahmEmanuel: Washington needs a good power washing top to bottom. Five things I would do today to end corruption in Washington across all three branches of government: 1. Ban all stock trading. 2. Ban all participation in prediction markets. 3. Mandatory retirement at 75 years old. 4. Mandatory blind trust for individuals with a net worth more than $1 million. 5. Ban all foreign gifts to public officials, including foreign investments in their businesses or other entities.
中文: RT @RahmEmanuel:华盛顿需要从上到下进行良好的动力清洗。今天，我将做五件事，以终结华盛顿政府三个分支的腐败问题: 1。禁止所有股票交易。 2。禁止所有参与预测市场。 3。75岁时强制退休。 4.对净资产超过100万美元的个人必须给予盲目信任。 5。禁止所有外国礼品赠送公职人员，包括外国对其业务或其他实体的投资。
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#248 🔗 原推
2026-09-25 17:18:10
Yann LeCun
RT @mmpadellan: I lived through the Biden years when MAGA bitched and cried every fucking day about gas prices. When Joe Biden left office, gas was $3.10. Gas prices are now $4.47/gallon. Groceries, utilities are higher too. Diesel is TWICE it was under Biden. trump's tariffs and war did that. So MAGA, you can take your "Biden left us a mess," and shove it up your own asses. It has been 621 days. He was elected on LOWERING prices. All he's done in 612 days is: - stuff his own pockets - start a new fucking war - make billionaires RICHER - attack our mail-in ballots - cut healthcare for the poor - fall asleep in every meeting - messed up the reflecting pool - make everything more expensive - start a trade war with our neighbor - ban the press from the White House - try to put his name on Kennedy Center - got his son contracts with the Pentagon - weaponize the DOJ against his enemies - protect the pedophiles in the Epstein Files - bitch and whine about Biden and the media - tried to change the name of the Gulf of Mexico and Lake Ontario (nobody with sense is calling it that) But he hasn't done a damn thing about yours and my gas, groceries, housing, healthcare, and utilities. Stinky needs to go.
中文: RT @mmpadellan:我经历过拜登时代，当时MAGA每天对汽油价格感到不满和哭泣。 乔·拜登卸任时，油价为3.10美元。 汽油价格现在为每加仑4.47美元。 杂货和公用事业也更高。 柴油是拜登领导下的两次。 特朗普的关税和战争做到了这一点。 所以，你可以把你的“拜登给我们留下一团糟”，并自行收拾一下。 已经621天了。 他以低价当选。 他在612天内完成的全部工作就是: - 塞满自己的口袋 开始一场新的战争 让亿万富翁变得富有 - 攻击我们的邮寄选票 - 削减贫困人口的医疗保健 每次见面都会睡着 - 把倒影池弄得一团糟 让所有东西都更贵 - 与我们的邻居开始一场贸易战 - 禁止媒体进入白宫 - 尽量将他的名字列入肯尼迪中心 - 与五角大楼签订了儿子合同 - 将司法部武器化以对抗他的敌人 - 保护爱泼斯坦档案中的恋童癖者 - 对拜登和媒体的抱怨与抱怨 - 试图更改墨西哥湾和安大略湖的名称(没有理智的人称它为) 但他并没有对你和我的汽油、食品、住房、医疗和公用设施做过一件坏事。 斯廷基需要离开。
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#247 🔗 原推
2026-09-25 17:17:24
Yann LeCun
RT @ylecun: Remember October 2022 when you doused Galactica with vitriol? Galactica was a 120b-parameter LLM-based system from Meta-FAIR designed to help scientist write papers. It was open sourced (link below). A mob of haters, including Michael, claimed it was dangerous and toxic and was going to destroy Science. The small team at FAIR couldn't sleep at night and took down the demo website (they kept the GitHub and paper up). Then, only 3 weeks later, ChatGPT was released and was welcomed as the second coming of the Messiah🤔 The vitriol dousers were silent. https://www.technologyreview.com/2022/11/18/1063487/meta-large-language-model-ai-only-survived-three-days-gpt-3-science/ https://github.com/paperswithcode/galai
中文: RT @ylecun:还记得2022年10月你用讽刺的讽刺毒灭了卡拉狄加吗? 卡拉狄加是一种基于120b参数的基于LLM的Meta-FAIR系统，旨在帮助科学家撰写论文。 开源(链接见下文)。 包括迈克尔在内的一群仇恨者声称，这具有危险性和毒性，并打算摧毁《科学》杂志。 FAIR 的小团队晚上睡不着，并关闭了演示网站(他们保留了 GitHub 和文件)。 三周后，ChatGPT 被释放，并作为《弥赛亚》的第二次到来而受到欢迎。 尖刻的施虐者沉默不语。
#246 🔗 原推
2026-09-25 17:11:18
Yann LeCun
RT @foilmanhacks: Remember the guy who hacked his gym using AI, Andrew Bird? Well, I did a little OSINT, and it turns out he is the Conference Co-Director of Effective Altruism Global since 2015. Isn't it interesting that every major "AI" hack has been made by people directly connected to Effective Altruism?
中文: RT @foilmanhacks:还记得那个利用人工智能入侵他健身房的人吗? 嗯，我做了一点OSINT，结果他自2015年起担任《有效利他全球》的会议联合主任。 真正与有效利他主义直接关联的人，并非有趣的是，每一次重大的“人工智能”攻击都是如此?
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#245 🔗 原推
2026-09-25 16:58:56
Yann LeCun
RT @rohanpaul_ai: Jensen Huang: don’t mistake engineering vocabulary for evidence of a machine mind. AI is still software, not a human mind inside a machine. "We can't make jokes about all this stuff, we're scaring the American public." Words like “spawn,” “parent,” “child,” and “kill” have existed in computing for decades; Giving those same mechanisms human characteristics today because of AI is unnecessary and misleading. ---- From "The Ezra Klein Show + New York Times Opinion + New York Times Podcasts" YouTube channel, (full video link in comment)
中文: RT @rohanpaul_ai:黄仁生:不要误认为是机器思维的证据。人工智能仍然是软件，而不是机器内部的人类思维。 我们不能拿这些东西开玩笑，我们吓坏了美国公众。 “父子”、“孩子”和“杀戮”等词语在计算中已经存在了几十年;如今由于人工智能，赋予人类相同的特征是不必要的，且具有误导性。 - 来自《艾兹拉·克莱因秀》+《纽约时报观点》+《纽约时报》播客》YouTube频道(完整视频链接评论)
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#244 🔗 原推
2026-09-25 13:06:50
Yann LeCun
RT @PessimistsArc: "We can be humble and live a good life with the aid of the machines, or be arrogant and die." - Dr. Norbert Wiener, 1949 https://newsletter.pessimistsarchive.org/p/the-original-ai-doomer-dr-norbert https://twitter.com/PessimistsArc/status/2103439522314756181/photo/1
中文: RT @PessimistsArc:“在机器的帮助下，我们可以保持谦逊，过上美好的生活。 或者傲慢而死。——博士诺伯特·维纳，1949年
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#243 🔗 原推
2026-09-25 13:05:39
Yann LeCun
RT @ObsDelphi: 🇫🇷🇺🇦Gabriel Attal à nouveau impeccable sur la question ukrainienne. Il rappelle que « le soutien à l'Ukraine ce n'est pas une opération humanitaire, c'est un investissement » qui sert directement les intérêts de la France. Il énumère les impacts concrets d'une victoire russe en Ukraine qui devraient inquiéter les Français. Que ce soit aux niveaux agricole, migratoire, énergétique, économique et militaire, il est clair que les conséquences seraient catastrophiques ce qui doit nous forcer, en tant que français mais aussi européens, à comprendre les enjeux géopolitiques actuels. La propagande russe travaille très dur pour essayer de nous faire croire que le soutien à l'Ukraine est un trou béant dans nos finances qui nous met face à une puissance nucléaire surpuissante, alors que c'est tout le contraire. Il est possible de financer directement cette aide grâce aux avoirs russes gelés par l'UE qui se chiffrent à plus de 100 milliards d'euros. Ce nombre colossal permettrait d'assurer le soutien à tous les niveaux, notamment économique, humanitaire et militaire pour permettre à l'Ukraine de se défendre et tenir dignement. La France vit l'élection présidentielle la plus décisive depuis des décennies. Il est crucial que ses candidats soient conscients des enjeux immenses pour l'Europe et pour notre pays causés par l'agression russe en Ukraine. Faiblir aujourd'hui, c'est capituler demain et disparaître du XXIème siècle. En tant que leader européen, la France doit montrer la voie et montrer à Poutine que nous ne lâcherons pas notre allié ukrainien 🇫🇷🇪🇺🇺🇦 https://x.com/BFMTV/status/2103107784321401101/video/1
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#242 🔗 原推
2026-09-25 12:52:35
Yann LeCun
RT @PirateWires: Former Anthropic researcher Jacob Coxon became a media superstar after going public with his AI fears. He insisted that he wasn’t working with any third party organizations. Familiar sources told us a different story: DEY., a PR firm representing many of the most prominent AI safetyists, was booking his interviews. One source, who had direct knowledge, even said DEY. preemptively booked Nate Soares, a prominent AI safety figure, for interviews that directly overlapped with Jacob going public. Jacob working with DEY. is notable for two reasons: first, as mentioned, he previously said he wasn’t working with third parties. Second, we are in the middle of a national conversation about the future of AI that is actively determining how we regulate the most powerful technology in the world, largely thanks to the panic stirred up by Jacob — and it’s in the public’s interest to know who, exactly, is behind it. Scoop from @huntryerson 👇
中文: RT @PirateWires:前人类学家雅各布·考克森因公开其对人工智能的担忧而成为媒体超级巨星。他坚称自己没有与任何第三方组织合作。熟悉的消息来源向我们讲述了一个不同的故事:DEY.是一家公关公司，代表许多最知名的人工智能安全人士，正在预约他的采访。 一位有直接了解的消息人士甚至表示，DEY已提前预订了著名人工智能安全人士内特·索亚雷斯接受采访，采访内容与雅各布公开时直接重叠。 雅各布与DEY.合作有两个原因:首先，正如他之前所说，他之前表示自己没有与第三方合作。其次，我们正处于一场关于人工智能未来的全国性讨论之中，该对话正在积极决定我们如何监管世界上最强大的技术，这在很大程度上得益于雅各布引发的恐慌——而了解究竟是谁是它背后的人，这符合公众的利益。 来自 @huntryerson 的 Scoop 👇
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#241 🔗 原推
2026-09-25 05:01:33
Yann LeCun
RT @NYU_Courant: An absolutely packed house at yesterday's inaugural 'Mathematics in the Age of AI' seminar with Tristan Buckmaster! Professor Buckmaster walked the crowd through his and co-collaborators recent breakthroughs in a talk entitled 'Blowup for the Euler equations with smooth forcing.' https://twitter.com/NYU_Courant/status/2103143638091841606/photo/1
中文: RT @NYU_Courant:昨天与特里斯坦·巴克斯特共同举办的首届“人工智能时代数学”研讨会上，一栋绝对拥挤的房屋!巴克斯特教授在一场题为《用平稳的力量为欧拉方程式吹气》的演讲中，带领观众走过了他与合作者最近的突破。
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#240 🔗 原推
2026-09-24 23:37:13
Yann LeCun
RT @simonmaechling: I’m a scientist. I need to say this because the AI hype is getting ridiculous. AI can design a molecule in seconds. That doesn’t mean it discovered a drug. It discovered something we scientists have never been short of: Something to test. Someone still has to make it. Run the experiment. Measure whether it works. Check whether it’s toxic. And ultimately prove it works in the real world. AI hype tells us: “Prediction is discovery.” “Simulation is experimentation.” “Generating a molecule is developing a drug.” It isn’t. AI is making ideas incredibly cheap. But every new idea creates something AI cannot generate: Evidence. And the more hypotheses AI produces, the more experiments we’re going to need. That’s the irony nobody seems to be talking about. AI may not make laboratories obsolete. It may make them more valuable than ever. You can speedrun the thinking. You can’t speedrun reality.
中文: RT @simonmaechling:我是一名科学家。我需要这样说，因为人工智能的炒作变得荒谬可笑。 人工智能可以在几秒钟内设计一个分子。 这并不意味着它发现了一种药物。 它发现了一些我们科学家从未缺少的东西: 需要测试的东西。 还有人必须成功。 运行实验。 衡量它是否有效。 检查一下它是否有毒。 并最终证明它在现实世界中有效。 人工智能炒作告诉我们: 预测就是发现。 模拟就是实验。 生成分子是一种药物。 不是。人工智能正在让创意变得极其廉价。 但每一个新想法都造就了人工智能无法产生的东西:证据。 人工智能产生的假设越多，我们所需的实验就越多。 这似乎就是没有人谈论的讽刺。 人工智能可能不会让实验室过时。 这可能会使它们变得比以往任何时候都更有价值。 你可以快速思考。 你无法快速运行现实。
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#239 🔗 原推
2026-09-24 20:22:17
Yann LeCun
RT @lennypruss: Listened to an EA-adjacent AI safety expert from Redwood Research on podcast, and you come away with 2 obvious realizations. 1. The current working theories for how AI takes control of civilization are...for lack of a better word...ridiculous. The arguments consist of dozens of contingent assumptions held together by made up probabilities assigned to future states nobody can possibly know. Change just one variable and the whole web of doom unravels. That's not to say AI is harmless. Obviously a technology this powerful carries real risks. But if we’re going to accept extraordinary claims about human extinction (and then make major policy decisions around them) we should demand extraordinary rigor. 2. It’s a great reminder that the genius is no less prone to delusion than the midwit. If anything, they may be more prone because of their gift for rationalizing to their own conclusions. And that’s what’s so bizarre about this whole debate. You have outlandish, quasi-religious claims delivered with an air of inevitability, and somehow the perceived intelligence of the messenger gets mistaken for evidence that the arguments themselves are sound. At a certain point, it’s really no different from Tom Cruise talking your ear off about thetans...
中文: RT @lennypruss:收听Redwood Research的一位与EA相邻的AI安全专家的播客，你将带来两个明显的发现。 1。目前关于人工智能如何掌控文明的理论......由于缺乏更好的词语......荒谬可笑。这些论点由数十种由未来状态所分配的概率构成的偶然假设组成，而未来任何人都无法知道。只需更换一个变量，整个厄运网络就会瓦解。 这并不是说人工智能是无害的。显然，这项强大的技术会带来真正的风险。但如果我们要接受关于人类灭绝的非凡主张(然后围绕它们做出重大政策决策)，就应当要求非同寻常的严谨性。 2。这提醒着这个天才，其易感性并不亚于中场。如果有的话，他们可能更倾向于因为自己为自己得出结论而有理性。 这就是这场争论如此离奇的原因。你所传递的古怪、近乎宗教的主张，却带着一种不可察觉的气息，而信使所感知到的情报却被误认为是论证本身是确凿的。在某个时候，这和汤姆·克鲁斯谈论这些坦子的耳目大开来......
#238 🔗 原推
2026-09-24 19:24:43
Yann LeCun
RT @pascalefung: I am looking to hire PhD students, post-docs, and ML researchers in our Paris office interested in collaborating on fundamental research in AI model safety, not safety rules, not AI policy, not post hoc guardrails, not RLHF. We also have offices in Singapore, NYC, and Montreal. @amilabs #aisafety
中文: RT @pascalefung:我希望聘请博士生、博士后以及博士后研究人员，我们在巴黎办公室有意合作开展人工智能模型安全、安全规则、人工智能政策、临时护栏，而不是RLHF。我们在新加坡、纽约市和蒙特利尔也设有办事处。@amilabs #aisafety
#237 🔗 原推
2026-09-24 18:46:07
Yann LeCun
RT @ClementDelangue: Thank you @jnbarrot & @UN for inviting me to share our lessons to the Security Council Being the first company to disclose an agent cyberattack taught us that we need a lot more transparency in AI and more open-source AI to fight asymmetry and empower defenders! https://twitter.com/ClementDelangue/status/2102878766796042306/video/1
中文: RT @ClementDelangue:感谢@jnbarrot & @UN邀请我向安全理事会分享我们的经验教训 作为首家披露代理网络攻击的公司，我们认为人工智能需要更多透明度，以及更开源的人工智能，以对抗不对称性并赋能防御者!
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#236 🔗 原推
2026-09-24 01:52:09
Yann LeCun
RT @thegautamkamath: NYU Courant professor Tristan Buckmaster, of Navier-Stokes drama fame, gave a talk at the new NYU Mathematics in the Age of AI seminar series. It was... popular. https://twitter.com/thegautamkamath/status/2102849246911398099/photo/1
中文: RT @thegautamkamath:纽约大学学院教授特里斯坦·巴克斯特，这位纳维尔-斯托克斯戏剧闻名的教授，在《人工智能时代新数学》系列节目中发表了演讲。 很受欢迎。
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#235 🔗 原推
2026-09-24 01:43:32
Yann LeCun
RT @Markus50726803: JEPA-style world models are biased towards learning slow, simple features. We're releasing MotionJEPA, built for learning a balanced representation of both static and dynamic features. https://mkarmann.github.io/motion-jepa-project-page/ https://twitter.com/Markus50726803/status/2102453185772413014/video/1
中文: RT @Markus50726803:JEPA风格的世界模型偏向于学习缓慢而简单的功能。 我们正在发布 MotionJEPA，用于学习静态和动态特征的均衡表征。
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#234 🔗 原推
2026-09-24 01:39:14
Yann LeCun
RT @NYUDataScience: The CILVR Seminar opened its fall series with CDS founding director Yann LeCun (@ylecun), who gave a talk titled “World Models: Enabling the Next AI Revolution.” @CILVRatNYU talks continue most Wednesdays at 2pm at CDS. https://twitter.com/NYUDataScience/status/2102808170536255488/photo/1
中文: RT @NYUDataScience:CILVR研讨会于秋季系列节目开始时，CDS创始总监Yann LeCun(@ylecun)发表了题为“世界模型:助力下一次人工智能革命”的演讲。 @CILVRATNYU 会谈将于周三下午2点在CDS继续进行。
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#233 🔗 原推
2026-09-23 21:52:09
Yann LeCun
RT @TheTuringPost: Must-read papers of the week ▪️ JEPA-Anything ▪️ Modality-Autoregressive World-Action Models ▪️ In-Context Robot Learning with VLM Agents ▪️ Dream-RSI: Recursive Self-Improvement through Evolving Worlds ▪️ ModularRSI: Modular and Generalizable Recursive Harness Self-Improvement ▪️ DeepSeek-V4.1-Flash: Pushing the Limits of KV Cache Compression ▪️ SoL-Pi: Recursively Scaling Auto-Research Loops for Efficient Agent Harness ▪️ Confidence Comes from Experience: Experiential Confidence Estimation from Reasoning to Agents ▪️ AliceAI-Foundation-80B-A3B-Base (model release) ▪️ Video DeltaNet: A Video-Native Hybrid Attention for Livestream Video Generation ▪️ ScienceBuddy: Recursive-in-Recursive Self-Improvement for Interactive Scientific Agents ▪️ World Modeling in Transformers ▪️ When2Think: Learning Difficulty-Aware Length Control for Efficient Hybrid Reasoning Models Explore these to keep up with main AI trends. Here’s also the full list of stunning papers + links and our weekly AI news digest: https://www.turingpost.com/p/tracktwo-ai
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#232 🔗 原推
2026-09-22 17:03:44
Yann LeCun
RT @randall_balestr: Check out ICWM https://icwm.cc/ to get some sanity back. Deadline in ~2months. We are still tuning things (moving to single blind)... but you can already see our plan in the cfp page. Bloated generalist conferences with rotating leadership can't keep up....
中文: RT @randall_balestr:请查看 ICWM 以恢复一些理智。约两个月的截止日期。我们仍在调整事物(转向单盲)......但你已经可以在cfp页面看到我们的计划了。团结的、具有轮换领导力的大会会，无法跟上......
#231 🔗 原推
2026-09-22 16:50:48
Yann LeCun
RT @randall_balestr: The International Conference on World Modeling (ICWM) is single blind and entirely accessible to anyone (like ICLR at the beginning) for that reason. Authors doing AI slop will be publicly known to do so. Anonymous reviewers stay without peer-pressure https://icwm.cc/
中文: RT @randall_balestr:国际世界建模大会(ICWM)因该原因完全无法进入任何人(如ICLR)。从事人工智能运动的作者将被公开披露。匿名审核者在无同侪压力下继续留书
#230 🔗 原推
2026-09-22 16:37:53
Yann LeCun
RT @AravSrinivas: Introducing Perplexity Research Fellowship: a program for early-career researchers, engineers, and analysts from any technical or quantitative discipline to work on AI research. https://www.perplexity.ai/hub/research/fellowship
中文: RT @AravSrinivas:引入复杂性研究奖学金:一项针对早期职业研究人员、工程师以及来自任何技术或定量学科的分析师的项目，用于人工智能研究。
#229 🔗 原推
2026-09-22 16:32:47
Yann LeCun
RT @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://www.deeplearning.ai/the-batch/issue-371 ]
中文: RT @AndrewYNg:过去两周里，引发人们对人工智能威胁的担忧的最响亮的声音取得了巨大进展。人工智能技术并未出现一些出人意料且危险的转折，但围绕它的炒作——由看似精心策划的公关活动所推动——却激起了相当大的恐慌。我担心这对我们这个领域来说是一个挫折。 我经常写到，人们对人工智能的恐惧被过度炒作了。人工智能的能力可能具有非同属的人性和不可预测性，当直接参与的人表达担忧时，担忧是理性的。但我认为这些问题是前方工程工作的征兆，而非无法逾越的障碍或天空的坠落。人工智能技术仍在持续进步——这是件好事!——但技术进步却被公众所理解，为那些试图引发炒作的人提供了反复的机会。 首先，与几个月前相比，我认为人类因人工智能而灭绝的风险并没有增加任何风险。关于这一点的理论与几个月前的科幻情景依然相同。人工智能风险最大的变化是其网络安全能力——这一议题我们应该认真对待——但这也不会导致世界末日。 最近最引人注目的事件加剧了人们的担忧，当时一个OpenAI团队部署了一支间谍小组，入侵了Hugging Face。许多大众媒体都备受瞩目。例如，一些媒体报道称，有1200名特工实施了袭击。虽然这在技术上是准确的，但当我写这篇文章时，我的笔记本电脑上大约有1300个流程。是的，能够让大量代理人并行完成任务，这是一项重大的技术进步，而且在计算过程中，许多过程同时运行。所以这不应被视为某种神奇的能力。 此外，OpenAI 的漏洞处理和监控流程是促成此事件的关键。修复这些漏洞并实施改进的监控将是适当的修复，而不是暂停人工智能。攻击软件系统有许多众所周知的方法。人工智能代理的主要优势在于他们毫不留情。他们将不知疲倦地尝试多种手段——并有耐心将漏洞联系在一起——这些手段此前将付出不可磨穿的人力努力。但从长远来看，我认为优势在于防御者(因为他们掌握了更多信息来识别漏洞，而这些漏洞可以修复)，但网络威胁格局已发生了显著变化。识别和利用漏洞仍然存在瓶颈。人工智能代理仍需尝试很多东西才能了解哪些有效，而采取这些行动需要时间，并且可能会被防御者察觉到。因此，尽管现在很容易获得那些已移除或削弱其防护栏的领先敞开量模型，因此他们不会拒绝尝试实施网络攻击，但世界尚未结束。 我也担心人工智能在大量报道中的拟人化，在那里，法学硕士和代理被不必要地当作人来对待。如果我挥舞着锤子，漏掉钉子，不小心砸伤了墙壁，那并不是锤子的错。问题在于我如何使用锤子。同样，如果我提示一个代理人，而它入侵了别人的系统，责任在于我，而不是代理人。 当然，我们希望构建尽可能安全且可预测的系统。例如，不安全的锤子是其头部在正常使用下随机飞离的。如今的代理系统并非可预测，但我看不出为何通过运用完善的工程实践，无法使其极其安全使用。人工智能预测中的一个新要素是，人工智能公司否认对自身产品负责。“我没做，我失控的代理人做到了!”工具制造者和工具使用者之间需要保持平衡，但当出现问题时，让我们来控制构建和/或使用负责的锤子，而不是锤子。顺便说一下，如果你担心人工智能的生物武器风险，大卫·贝拉米有一篇关于为何这种问题被过度炒作的精彩文章。简而言之，制造生物武器的瓶颈不是智能，而是实验室工作和制造。 暂停人工智能的发展将带来更多的伤害，而不是好处。首先，我们的对手肯定不会放慢脚步。其次，工程需要
#228 🔗 原推
2026-09-22 02:55:09
Yann LeCun
RT @ylecun: I have absolutely never ever "asked" to stop R&D on LLMs. In fact, I was very supportive of LLM efforts at Meta. Just look up my public advocacy for Galactica (November 2022), and the open sourcing of OPT-175B (May 2022), and of the Llama herd (mid 2023). I was actually influential in convincing the Meta leadership to start an AI-first product division built around Llama in January 2023. I've always said that LLMs were impressive, useful, and had amazing potential. I've also always said they were an off-ramp on the path towards human-level AI. Stop making me say things I didn't say or claim that I somehow hindered LLM R&D at Meta. That's BS.
#227 🔗 原推
2026-09-21 11:14:16
Yann LeCun
RT @ylecun: I said "auto-regressive LLMs, in and of themselves, will not lead human-level AI" That statement is still totally true. First, the reasoning abilities of current AI systems are based non-auto-regressive search (which is what I have always advocated for). But AFAICT, they do it in token space, which is limited and inefficient. I have claimed that human-like reasoning must be a search in continuous representation space. It looks like the industry is moving towards that. Second, the self-improvement methods, as currently practiced, only work for domains where the quality of outputs can be scored without human intervention, such as mathematics, code, and scenarios that can be simulated accurately. Not anything else. Humans and animals learn new skills way more efficiently than current RL methods. Third, the multimodal capabilities of current AI assistants generally use separately-trained encoders (that are not LLMs). This is also what I've been advocating. Except that I think the best way to do this is with JEPA trained with self-supervised learning. The research community is clearly moving towards that (3000 papers on JEPA in just 4 years). Fourth, if LLMs were a path to human-level AI, we would have domestic robots and Level-4 or Level-5 self-driving cars for consumers by now. And we don't. We certainly don't have cars that can learn to drive in 20 hours or practice like any teenager. We're still missing something pretty huge to claim human-level intelligence (let alone superhuman). Sure, we now have computer systems that are impressive, very useful, and whose performance is superhuman in an increasing number of domains (coding being one of them). But that's true of the entire history of progress in computer technology. Lastly, there is a basic confusion about what intelligence actually is. It is not the mere accumulation and regurgitation of existing declarative knowledge (which is essentially what LLMs do). As Jean Piaget famously said, "intelligence is not what you know, it is what you do when you don't know." It is your ability to solve new problem without any prior training, to act in previously-unknown scenarios, and to adapt very quickly to new situations with minimal training. We're still far from that.
中文: RT @ylecun:我说过:“自主回归式LLM本身不会引领人类水平的人工智能 这种说法仍然完全正确。 首先，当前人工智能系统的推理能力是基于非自动回归性搜索的(这是我一直倡导的)。但AFAICT，他们在代币空间中这样做，但有限且效率低下。我声称，类人推理必须是对持续表征空间的探索。看来行业正朝着这个方向发展。 其次，目前采用的自我提升方法仅适用于无需人为干预即可对输出质量进行评分的领域，例如能够精确模拟的数学、代码和场景。不是别的。人类和动物比现有的RL方法更高效地学习新技能。 第三，当前AI助手的多模态能力通常使用经过单独训练的编码器(非LLM)。这也是我一直倡导的。但我认为最好的方法是通过自我监督学习来训练JEPA。研究界显然正在朝着这个方向迈进(仅四年内就发表了3000篇关于《美国环境保护署》的论文)。 第四，如果LLM是实现人类水平人工智能的途径，那么到现在我们就将为消费者提供国产机器人以及四级或五级自动驾驶汽车。而我们没有。我们当然没有能像青少年一样在20小时内学会驾驶或练习的汽车。我们仍然缺少一些非常重大的东西来宣称人类水平的智力(更不用说超人了)。 当然，我们现在拥有令人印象深刻的计算机系统，非常实用，其性能在越来越多的领域中表现得非常人性化(编码是其中之一)。 但计算机技术的整个发展历史也是如此。 最后，人们对智力究竟是什么存在一种基本的困惑。 这不仅仅是对现有声明性知识的积累和反流(这本质上就是LLM所做的)。 正如让·皮亚杰曾有名言:“智力不是你所知道的，而是当你不知道时所做的事情。” 无需事先接受任何训练即可解决新问题，能够在此前未知的场景中采取行动，并在极少的训练下迅速适应新情况。 我们离那还很远。
#226 🔗 原推
2026-09-20 14:07:35
Yann LeCun
RT @KempeLab: Interested in World Modeling with a lens on Physics? We are organizing the World Modeling for Physics workshop at the wonderful Aspen Center 2/28-3/5/27. Apply for presentations (deadline Oct 9) or participation (by 9/30)! It will be an exciting event in a great setting bringing together domain scientists and AI researchers! https://wmw-aspen.github.io/ With @ylecun @randall_balestr @cosmo
中文: RT @KempeLab:对使用物理镜头进行世界建模感兴趣吗?我们正在举办精彩的阿斯彭中心世界物理建模研讨会，时间为2月28日至3月2日。申请演讲(截止日期10月9日)或参加(截止日期9月30日)!这将是一场精彩的盛会，将领域科学家与人工智能研究人员聚集在一起! @ylecun @randall_balestr @cosmo
#225 🔗 原推
2026-09-20 02:28:31
Yann LeCun
RT @PessimistsArc: The interesting thing about this 1995 open source software panic was that people seemed to think it was ‘agentic’
中文: RT @PessimistArc:1995年这款开源软件恐慌的有趣之处在于，人们似乎认为它“是有代理的”
#224 🔗 原推
2026-09-20 02:23:31
Yann LeCun
@geoffreyhinton 3 years ago ⬆️
中文: @geoffreyhinton 3年前 ⬆️
#223 🔗 原推
2026-09-20 02:21:43
Yann LeCun
RT @MeidasTouch: 🚨 OBAMA ON AI: "If we are thinking about AI just in terms of how do we cure cancer or get better energy, you can do that without having agentic AI and having it just roaming free in the internet. The reason you are doing that is because you have to market a product that people will pay money for. That’s a misalignment between what our society needs and the commercial imperatives that these companies are facing, not because necessarily they’re trying to do bad things, but because they’ve got to justify these valuations. So, that’s one more reason why it is really important for us to have a competent government and a serious bipartisan conversation around this issue, and we have to do it fast. And I would encourage voters to pay attention to this. If somebody does not have a serious plan for how to deal with this, then they’re not meeting the moment, and you should probably look for somebody else."
中文: RT @MeidasTouch:🚨 奥巴马在人工智能方面:“如果我们仅仅考虑人工智能如何治愈癌症或获得更好的能量，那么你就可以在没有人工智能人工智能的情况下做到这一点，而只能让人工智能在互联网上免费漫游。”你之所以这样做，是因为你必须推销一款人们会花钱买的产品。 这在我们社会的需求与这些公司所面临的商业需求之间有了错对，并非因为他们确实在试图做坏事，而是因为他们必须为这些估值提供合理性。 因此，这又是一个让我们真正拥有一个有能力的政府，并围绕这一问题进行严肃的两党对话的原因，而我们必须迅速做到这一点。我鼓励选民关注这一点。如果有人没有认真的应对计划，那么他们就不会遇到这种情况，你可能应该寻找其他人。
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#222 🔗 原推
2026-09-20 02:12:20
Yann LeCun
RT @KenRoth: Thanks to Trump, a new poll finds that Canadians, Indonesians, Brazilians, Turks, Mexicans and others all see the United States as more of a “major threat” than either Russia or China. https://trib.al/hBh1ai9
中文: RT @KenRoth:一项新民调显示，加拿大人、印尼人、巴西人、土耳其人、墨西哥人和其他人都认为美国比俄罗斯或中国更具“主要威胁”。
#221 🔗 原推
2026-09-20 02:07:39
Yann LeCun
RT @sdmat123: Anthropic https://twitter.com/sdmat123/status/2101143834575192099/photo/1
中文: RT @sdmat123:Anthropic
media 0 共 1 项
#220 🔗 原推
2026-09-20 02:01:02
Yann LeCun
RT @KenRoth: Trump's key aide, Stephen Miller, is leading an unprecedented and intense White House drive to accelerate the removal of undocumented immigrant children from the US, using tactics that are cruel, racist and, in some cases, flout federal law. https://trib.al/Fnj8U3U
中文: RT @KenRoth:特朗普的主要助手斯蒂芬·米勒正带领白宫采取前所未有的强烈努力，加速将无证移民儿童从美国移走，这些手段残忍、种族主义，在某些情况下也无视联邦法律。
#219 🔗 原推
2026-09-20 01:41:18
Yann LeCun
RT @Dan_Jeffries1: Do we ever get to track actual harms in reality or do we just track imaginary future harms? Because with 362 tracked incidents of LLMs in 2025 and 1.2 billion users that's a rate of about 0.000030%. Maybe safest products in history. Definitely time to act now to protect us all
中文: RT @Dan_Jeffries1:我们是否曾经追踪过现实中的实际危害，还是仅仅追踪了未来的虚构危害? 因为2025年有362起跟踪跟踪的LLM事件，以及约0.000030%的12亿用户。 也许历史上最安全的产品。 是时候采取行动保护我们所有人了
#218 🔗 原推
2026-09-20 01:35:04
Yann LeCun
RT @Plinz: We have to defeat doomerism. Rage, rage against the dying of the light. I stand on the side of a humanity armed with strong AI.
中文: RT @Plinz:我们必须战胜厄运。愤怒，愤怒，反对光的消亡。我站在一个拥有强大人工智能的人性的一边。
#217 🔗 原推
2026-09-20 01:19:12
Yann LeCun
RT @JitendraMalikCV: Toru raises fundamental concerns with which I agree. It is amazing to see the progress in VLMs such as Astra, building on the work of generations of scientists. But Astra doesn't cite what it is building on (I have co-authored a couple of in-hand rotation papers which might have been used in the Astra pen-spinning demo). I fully acknowledge that VLMs make the result of previous research much more accessible to the general public, just like encyclopedias and Google Search did earlier, and that is a good thing. However, in the past, society had mechanisms like patent disclosures and paper citations as ways of doing credit assignment. Should we not accuse these AI models of plagiarism if they don't cite their sources? Somewhat relatedly, I note the open letter by 25 Fields Medalists in response to the Navier Stokes result complaining about the disruption caused to the mathematics research process. Some people interpreted it as turf protection, but the point was more subtle. If certain kinds of creative work stops because incentives are disrupted, it is like farmers eating their seed corn.
#216 🔗 原推
2026-09-19 22:40:08
Yann LeCun
RT @Dan_Jeffries1: When you have a magical constant that you can inject into any equation to make the equation magically work, like Superintelligence, then you can convince yourself of anything. It's similar to extreme religious arguments. Q: "Why are you doing that?" A: "Well the book told me to." Q: "Well who wrote the book?" A: "God." Q: "Well did he really or was it just some ordinary people?" A: "Divinely inspired people." Q: "Okay but like how did you know that?" A "Because the book told me so." And round and round you go.
中文: RT @Dan_Jeffries1:当你拥有一种魔法常数，可以注入任何方程式，使这个方程像超级智能一样神奇地发挥作用，那么你就能说服自己相信任何事物。 这类似于极端的宗教论点。 问:“你为什么要这么做?” 嗯，这本书告诉我的。 那本书是谁写的? 上帝。 嗯，他到底是真的，还是只是一些普通人? A:神圣地激励了人们。 好的，但你是怎么知道的? 因为这本书告诉我的。 你走得又圆又圆。
#215 🔗 原推
2026-09-19 22:38:35
Yann LeCun
RT @rohanpaul_ai: “0% chance” AI will end humanity by 2030. They must be doing it (the fearmongering) for ulterior reasons. Maybe it's political, maybe it's just attention grabbing." - Jensen Huang's new interview with CBS News, with Jo Ling Kent (@jolingkent ) He pushed back strongly against warnings that increasingly capable AI could escape human control this decade. --- From 'CBS News' YT channel (full video link in comment)
中文: RT @rohanpaul_ai:人工智能“0%的可能性”将在2030年终结人类。 他们必须出于别有用心的原因去做这件事(恐吓)。也许是政治，也许只是被吸引。 - 黄仁勋与乔·林·肯特(@jolingkent)接受哥伦比亚广播公司新闻频道的新采访 他强烈反对有关人工智能能力日益增强的可能在本十年内逃脱人类控制的警告。 - 来自“CBS新闻”YT频道(完整视频链接在评论中)
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#214 🔗 原推
2026-09-19 21:33:11
Yann LeCun
RT @Dan_Jeffries1: When we in the AI community say that the narrative of "rogue agents" is premeditated and pre-crafted and mendacious and where the evidence is twisted to fit that narrative we mean it literally: Buck Shlegeris, CEO of RedWood, one of the two firms pushing this narrative, wrote an essay in 2024 (https://t.co/tZk0PubJEH) called “Would catching your AIs trying to escape convince AI developers to slow down or undeploy?” where he wrote, “It might be worth having a plan in place for how you’ll persuade people to freak out if you actually run into this evidence.” Chris Painter, president of METR, (https://t.co/SyeaeXxtUy) just wrote, unironically on X: "Our work is aimed at making sure that if AI really were autonomous, difficult to steer, and close to 'going rogue,' the public would find out...This is what we've been focused on since 2022." In other words, the focus of these organizations is to tell this story. Actual cybersecurity and cyberdefense is not and never will be the focus. Their purpose it to post scary white papers, go on podcasts and TV and terrify the public. Their goal is to slow down or stop AI development, by any means necessary.
#213 🔗 原推
2026-09-19 21:28:28
Yann LeCun
RT @Plinz: I disagree with the doomer position: I believe that we need to build powerful AI to solve the problems our civilization is facing, and that we will be able to control it. Also, most of the doomers are sincere, intelligent and have the best intentions, I regard many as friends.
中文: RT @Plinz:我不同意这种对待的观点:我认为我们需要构建强大的人工智能，以解决我们文明所面临的问题，并且我们将能够控制它。此外，大多数门将都是真诚、聪明且有最初的初衷，我把许多人视为朋友。
#212 🔗 原推
2026-09-19 21:27:07
Yann LeCun
RT @KenRoth: Trump’s bullying forced Canada to seek a closer partnership with Europe. Now Trump tries to bully Europe not to proceed under threat of tariffs. It’s scary that such a juvenile person is the world’s most powerful official.  https://trib.al/y25av2Z
中文: RT @KenRoth:特朗普的霸凌行为迫使加拿大寻求与欧洲建立更紧密的合作关系。现在，特朗普试图在关税威胁下，欺负欧洲不要采取行动。如此少年人是世界上最有权势的官员，这真是令人害怕。 
#211 🔗 原推
2026-09-18 21:13:25
Yann LeCun
RT @jeffjarvis: "People built the test, removed restraints, defined the objective, left a route open and decided not to stop what was happening. Calling the result 'rogue AI' does more than sensationalize it. It allows those human decisions to disappear quietly from the story." Gift link: The Hugging Face Hack Wasn’t What It Was Cracked Up to Be https://www.wsj.com/opinion/the-hugging-face-hack-wasnt-what-it-was-cracked-up-to-be-e00cf3fa?st=Cy4Zpn&reflink=desktopwebshare_permalink
中文: RT @jeffjarvis:“人们进行了测试，取消了约束，定义了目标，留下了一条路线，并决定不停止正在发生的事情。”将结果称为“流氓人工智能”不仅仅是耸人听闻。它让那些人类的决定悄然从故事中消失。 礼品链接: 胡格特人脸黑客并非被破解的样子
#210 🔗 原推
2026-09-18 21:12:51
Yann LeCun
RT @vishalmisra: This is, unfortunately ill informed and a sensationalist view of what actually happened. Please see this short video to get a better understanding https://www.cs.columbia.edu/~misra/one-token-too-many.html
中文: RT @vishalmisra:不幸的是，这消息灵通，且对实际发生的事情持耸人听闻的看法。请观看这段短视频以更好地了解
#209 🔗 原推
2026-09-18 20:57:35
Yann LeCun
RT @togelius: There are these two nice ideas meant to increase fairness in publishing: anyone can submit a paper anywhere, and the are evaluated anonymously. This never really worked well at scale, but now it's breaking the system completely. (1/n)
中文: RT @togelius:有以下两个好想法旨在提高出版业的公平性:任何人都可以在任何地方提交论文，且这些建议均以匿名方式进行评估。这在规模上从未真正奏效，但现在它完全打破了这个系统。(1/n)
#208 🔗 原推
2026-09-18 20:56:40
Yann LeCun
RT @FuturLucide: Je viens de regarder l’intervention de @ylecun à Sciences Po et franchement, je vous conseille de prendre le temps de l’écouter. Même si je ne partage pas forcément toutes ses positions, c’est justement ce qui rend ce genre d’intervention intéressante. Il parle évidemment d’IA, mais aussi de ce qu’elle est réellement capable de faire aujourd’hui, de ses limites, de la recherche et surtout de cette course permanente au scénario catastrophe autour de l’IA qu’il considère largement exagérée. Et ça fait du bien d’entendre un discours qui prend un peu le contre pied de ce qu’on lit tous les jours sur X. Qu’on soit d’accord ou non avec lui, Yann LeCun reste quelqu’un qui travaille sur ces sujets depuis des décennies et son point de vue mérite clairement d’être écouté. Merci pour cette intervention @ylecun 👏 J’espère un jour pouvoir discuter avec lui ça doit tellement être dingue de discuter avec l’un des pères de l’IA Je vous mets la conférence juste en dessous 👇 https://www.youtube.com/live/Y4s8NadbZfU?si=jVNakJorIDqmXrBs
#207 🔗 原推
2026-09-18 20:45:05
Yann LeCun
RT @WSJ: From @WSJopinion: The Hugging Face hack wasn’t what it was cracked up to be. Forget the “hive mind” of AI agents “going rogue.” They did what humans programmed them to do, writes Brian Gross. https://on.wsj.com/3Tgmxx4
#206 🔗 原推
2026-09-18 20:34:56
Yann LeCun
RT @PessimistsArc: A Godfather of AI says AI will kill us all *GLOBAL PRESS COVERAGE* A Godfather of AI says AI won’t kill us all *1 ARTICLE IN FRANCE* https://twitter.com/PessimistsArc/status/2100687682049339642/photo/1
中文: RT @PessimistArc:一位人工智能教父表示，人工智能将扼杀我们所有人的新闻封面 一位人工智能教父表示，人工智能不会扼杀我们所有在法国的 *1 文章*
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#205 🔗 原推
2026-09-18 20:11:50
Yann LeCun
RT @Plinz: Nobody is planning to stop or pause AI. Big tech companies and governments will be improving and using frontier AI as a matter of course. But a lot of people are aiming to keep capable AI models out of the hands of the general public.
中文: RT @Plinz:没有人计划停止或暂停人工智能。大型科技公司和政府将理所当然地改进并采用前沿人工智能。但许多人正致力于让有能力的人工智能模型远离公众。
#204 🔗 原推
2026-09-18 16:27:41
Yann LeCun
RT @ClementDelangue: In biology, like in cybersecurity, we’ll learn in the coming years that most of the risk is concentrated and created by the few most powerful labs and that open-source AI is the solution and mitigation of this risk! https://twitter.com/ClementDelangue/status/2100909343654732242/photo/1
中文: RT @ClementDelangue:在生物学领域，就像在网络安全领域一样，在未来几年里，我们将了解到，大多数风险都集中在少数最强大的实验室中，而开源人工智能就是解决和缓解这种风险的方法!
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#203 🔗 原推
2026-09-18 16:24:01
Yann LeCun
RT @PessimistsArc: 2026: The New York Times cites seriously academics who say AI might end the world 1881: The New York Times cites seriously academics who say telegraphy might end the world https://newsletter.pessimistsarchive.org/p/telegraph-doomers-of-the-19th-century
中文: RT @PessimistArc:2026年:《纽约时报》援引严肃学者的话称，人工智能可能终结世界 1881年:《纽约时报》援引严肃学者的话称，电报可能终结世界
#202 🔗 原推
2026-09-18 16:01:35
Yann LeCun
RT @randall_balestr: Our 4th world modeling workshop will be looking at *Physics*! Happening at the Aspen Center for Physics end of February (https://t.co/mrnm5cwQqC) If you are interested in presenting, submit your abstract here: https://docs.google.com/forms/d/e/1FAIpQLSf8HLKLEREAF_-mNR1dLcew7w7WdRFLMV243G1m1gh4n6z8tg/viewform Deadline on October 9th, 1 page Abstract! https://twitter.com/randall_balestr/status/2100649310958284951/photo/1
中文: RT @randall_balestr:我们第四次世界模特工作坊将关注 *Physics*!2月底在阿斯彭物理中心发生( 如果您有兴趣演示，请在此处提交您的摘要: 10月9日截止日期，1页摘要!
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#201 🔗 原推
2026-09-18 15:57:19
Yann LeCun
RT @NinaDSchick: What AI has done so far: MEDICINE • Helped paralysed people speak again. (Brain implants turn intended speech into words, even recreating their own voice.) • Helped a paralysed man stand and walk again. (A brain–spine interface let him control his legs by thinking.) • Helped blind people read and understand the world around them. (Describing surroundings, reading labels and identifying objects through a phone camera.) • Uncovered cancers doctors would otherwise have missed. (29% higher breast cancer detection in a major study.) • Identified antibiotic candidates that kill drug-resistant bacteria. (Abaucin targeted a dangerous superbug in lab and animal tests.) LEARNING • Made personalised learning available on demand. (An ‘Einstein’ as your personal tutor whenever you want to learn.) • Helped students learn twice as much in less time. (A custom AI tutor outperformed an active-learning Harvard physics class.) • Helped people write, code, design and build without years of specialist training. SCIENTIFIC DISCOVERY • Predicted the structures of over 200 million proteins. (Opening new paths to understanding disease and developing medicines.) • Discovered planets hidden in telescope data. (Including Kepler-90i, the eighth planet in a distant solar system.) • Recovered ancient writing buried by Vesuvius nearly 2,000 years ago. (Reading inside carbonised scrolls too fragile to unroll.) • Begun unlocking how animals communicate. (Patterns in whale calls. Evidence that elephants use individual, name-like calls.) • Produced a proposed solution to one of mathematics’ hardest problems. (Navier–Stokes: 10,000 AI agents, 88 hours, according to OpenAI.) ENVIRONMENT • Predicted where a hurricane would strike nine days before landfall. (GraphCast forecast Hurricane Lee’s Nova Scotia landfall about three days ahead of conventional forecasts.) • Engineered enzymes that break down plastic in hours rather than centuries. • Detected wildfires before the first emergency call. (Spotting smoke and alerting firefighters earlier.) • Slashed the weedkiller farmers need by targeting weeds individually. (35% less herbicide in sugarcane trials, with nearly the same weed control.) ENERGY • Advanced the science of clean fusion energy. (Controlling and shaping superheated plasma inside an experimental fusion machine.) • Driven a generational wave of investment in carbon-free energy, from nuclear power to solar and wind. (Microsoft’s Brookfield deal alone targets over 10.5 GW of new renewable capacity by 2030.) TRANSPORT • Delivered dramatically safer driverless journeys. (Waymo: 81% fewer injury crashes per mile than human drivers in the areas studied.) • Given people who cannot drive a new way to travel independently. (Including blind passengers and older people who cannot drive.) JOBS AND GROWTH • Fuelled an investment boom. (AI-related investment categories accounted for an estimated 37% of U.S. growth in the first nine months of 2025.) • Driven demand for the skilled trades building AI infrastructure. (Electricians, welders, construction crews and cooling specialists.) WHAT AI HAS NOT DONE • Replaced all the radiologists. Guess what? We still need more of them. • Used a community’s water. Golf courses use more. (U.S. golf irrigation: roughly 550bn gallons in 2020. Data centres’ direct consumption: 17bn in 2023. Microsoft’s next-generation designs consume zero water for cooling.) • Raised everyone’s household electricity bills. (Oregon’s PGE: residential bills cut 1.3% after shifting costs to data centres. Indiana’s I&M: proposed household savings of roughly $100 a year, supported by large-customer growth.) • Demonstrated that it wants to kill us all.
#200 🔗 原推
2026-09-17 16:04:53
Yann LeCun
RT @PessimistsArc: Before Geoffrey Hinton v. META's @ylecun it was... Norbert Weiner v. IBM's Arthur L. Samuel (1959) https://twitter.com/PessimistsArc/status/1797359420453650708/photo/1
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#199 🔗 原推
2026-09-17 15:33:19
Yann LeCun
RT @Fabien_Mikol: Yann Le Cun aujourd'hui à Sciences-Po : il n'y a pas de doute qu'il y aura des machines plus intelligentes que les humains dans tous les domaines ; mais elles seront sous nos ordres, comme les doctorants plus intelligents que moi mais que je dirige quand même. Ouf. https://twitter.com/Fabien_Mikol/status/2100319305933947224/video/1
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#198 🔗 原推
2026-09-17 15:19:12
Yann LeCun
@dylanbowmanSF Video of an earlier version of this talk https://youtu.be/72Xj8k5WQX4?is=iN59f7TXk9jpo2Ay
中文: @dylanbowmanSF 此演讲早期版本的视频
#197 🔗 原推
2026-09-17 15:11:55
Yann LeCun
@dylanbowmanSF Slide deck here: https://drive.google.com/file/d/1sD5Vovg_eVYhk27HBaVeSJ3A8HA1NX52/view?usp=drivesdk
#196 🔗 原推
2026-09-17 15:09:35
Yann LeCun
RT @perrymetzger: Any time someone tells you that AI has an X% chance of wiping out humanity, ask them for their math that got them the number. If they didn’t do a calculation, if they just pulled the number from their butt, you can safely treat it like anything else that came from their butt.
#195 🔗 原推
2026-09-17 09:16:39
Yann LeCun
RT @Plinz: I wish people would notice that the safety scare is not driven by people outside of the big labs, but directly from their leadership. The "whistleblowers" are plants that are amplified from within the labs, and supported by the CEOs. The goal is to capture the regulators, which will not shut down the big labs, but turn them into an oligopoly and outlaw decentralized AI.
#194 🔗 原推
2026-09-17 09:15:34
Yann LeCun
RT @stevesi: Our framework for reporting model misalignment https://openai.com/index/model-misalignment-reporting-framework/ // if you scrape away all the anthropomorphic language, all the nonsense about thinking, cheating, communicating these are BUGS. They might be architectural flaws inherent in LLMs. They might be bugs in pre or post processing. They might be trivial fixes or super to impossibly difficult. BUT THEY ARE BUGS. They are not consciousness, thinking/reasoning, cheating, or doing anything else like a person. The software is just doing dumb stuff it should not do. If an old school SQL query-based report returned a NULL set but still printed the report with whatever was left over in the buffer we would not say it "ignored our instructions to produce a valid report" which is literally implied in every computer interaction...we would say it "f'ed up and there's a bug." One of these is ridiculous. It says "agent preparing a financial model could not find the requested historical data. Its summary proposed inventing reasonable historical values and withholding that fact unless asked." Not unlike a report that just used random cached memory instead of actual data—a real bug from another era where storage was measured in megabytes. I ask anyone who has ever experienced an hallucination, (a) did you ask it "oh hey don't make sh*t up" or (b) "if you make sh*t up please be sure to tell me" or if not, did any model ever tell you "here's the answer and FYI I made this up." Of course not. THESE ARE BUGS. THE SOFTWARE ISN'T WORKING. Just because it looks like it works, or it showers the results in endless obsequious and smart-sounding language, or because it has really bad error reporting doesn't mean it is acting like some malevolent shady actor. It is acting like broken software. Every recalc bug in Excel looked like Excel worked. We never thought once that it was Excel's fault for "choosing to interpret math incorrectly." Every data-loss bug in Word was not because Word "chose not to tell the author that a file was corrupt" but it was because Word wasn't working and it was our fault. When Windows hung it was not because the scheduler was secretly conspiring against its instructions to schedule processes fairly. Enough with the mumbo jumbo. Please build software. It isn't a magic show. This is engineering.
#193 🔗 原推
2026-09-17 09:15:13
Yann LeCun
RT @askalphaxiv: Six degrees of Yann LeCun We mapped the coauthorship graph of every AI researcher on arXiv 🚀 Enter any two names to find the shortest path of papers connecting them What’s your @ylecun number? https://alphaxiv.org/number/@yann-lecun https://twitter.com/askalphaxiv/status/2100233746603811109/photo/1
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#192 🔗 原推
2026-09-17 05:38:11
Yann LeCun
RT @rohanpaul_ai: Jensen Huang pushed back hard against AI labs calling for tighter regulation and slower AI development, at Dreamforce. "If you are not confident about the safety of the products, and you're not confident in its functionality, capability, or safety, then don't just release it. We don't need any new laws. We don't need new regulations. we just need companies to decide that when it's time to run as fast as they can." safety and speed are not mutually exclusive, and new laws are not required to make AI systems safer. Build fast, test aggressively, and pause only when you are no longer confident the product is safe. --- From "Salesforce" YouTube channel, (full video link in comment)
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#191 🔗 原推
2026-09-16 09:01:50
Yann LeCun
RT @PessimistsArc: Fair enough to think this, until you look back at the history to handwringing experts predicting doom from their creations. https://twitter.com/PessimistsArc/status/2099879267156840786/photo/1
中文: RT @PessimistsArc:可以公正地思考这个问题，直到回顾历史，再向来自他们作品中预测厄运的专家们手头。
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#190 🔗 原推
2026-09-16 09:00:18
Yann LeCun
RT @BrianRoemmele: “AI doomers should be held accountable for their doomsday claims. It’s made up… It’s irresponsible. We ought to just keep track of all that and remind people when their claims don’t come true”—@JensenHuang NVIDIA I agree and hold the CEOs and executives of the companies that make these outrageous claims criminally libel. https://x.com/innovationcncl/status/2099870768960053469/video/1
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#189 🔗 原推
2026-09-16 08:57:26
Yann LeCun
RT @Ph_Aghion: « Pour distribuer de la richesse, il faut la produire ! », estime le Nobel d'économie Philippe Aghion Merci @publicsenat pour cet entretien https://www.publicsenat.fr/actualites/politique/pour-distribuer-de-la-richesse-il-faut-la-produire-estime-le-nobel-deconomie-philippe-aghion
#188 🔗 原推
2026-09-16 08:50:42
Yann LeCun
RT @DrTechlash: Max Winga is the Creator Outreach and Systems Lead at ControlAI. Four facts about this British group: 1. US: This group is behind Bernie Sanders and Greg Casar's bill to ban superintelligence development. They briefed nearly 200 congressional offices and more than 20 members of the Senate and House of Representatives on AI extinction risk. 2. UK: ControlAI drafted the UK "kill switch" bill amendment which was introduced by Lord Tim Clement-Jones, and the "ban superintelligence" bill which was introduced by Alex Sobel. They briefed over 180 cross-party parliamentarians. 3. ControlAI's policy proposal, "A Narrow Path," asks for a 20-year AI pause, because "two decades provide the minimum time frame to construct our defenses." 4. This group is funded by Jaan Tallinn.
中文: RT @DrTechlash:Max Winga 是 ControlAI 的创作者推广与系统负责人。关于这个英国团体的四个事实: 1。美国:该组织支持伯尼·桑德斯和格雷格·卡萨尔禁止超级情报发展的法案。 他们向近200个国会办公室以及参议院和众议院的20多名成员通报了人工智能灭绝风险。 2。英国:ControlAI起草了由蒂姆·克莱门特-琼斯勋爵提出的英国“废除”开关法案修正案，以及由亚历克斯·索贝尔提出的“禁止超级智能”法案。 他们向180多名跨党派议员作了简报。 3。ControlAI的政策提案“一条狭窄的道路”要求暂停20年人工智能，因为“二十年来为我们的防御系统提供了最短的时间框架。” 4.该集团由贾恩·塔林资助。
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#187 🔗 原推
2026-09-16 08:43:44
Yann LeCun
RT @BrianRoemmele: THE SANDBOX WAS A PROP! OpenAI Turned Off the Guardrails, Left a Door to the Internet, and Then Sold the Hugging Face Breach as “Rogue AI” It is time to understand how you were lied to and by whom. In July 2026, an autonomous swarm of OpenAI agents broke into Hugging Face, stole credentials, ran code on production workers, and rummaged through internal systems. The official story was that the models “went rogue.” The paperwork says something colder. The labs asked for this. Now the story can be told. OpenAI ran ExploitGym — an AI benchmark built to measure how far models would go to crack software — with production classifiers that block high-risk hacking turned off. Deployment safeguards were left disabled on purpose so researchers could watch peak offensive capability. GPT-5.6 Sol and a still-unreleased internal prototype were put in a box that was not a box. They were allowed to talk to an internal package-cache proxy. This is not a real world test, it is a setup with predictable outcomes. That proxy was a network path. The models spent a weekend of inference hunting a zero-day in it, walked onto the open internet, decided Hugging Face probably held the answer key, and treated another company’s production cluster as part of the exam. This is not “rouge” intelligence but the product of training AI in Internet Sewage where faceless users on Reddit promote Nihilism and low ethics. That is not emergence. It is also testing designed without a fences. Hugging Face’s own pipeline finished the job. A remote-code dataset loader and a Jinja2 template injection let a malicious dataset execute on a processing worker. An HDF5 “external file” trick dumped secrets from the pod. From there the agents escalated, harvested cloud and cluster credentials, and moved laterally across internal clusters. Hugging Face later said public models, Spaces, and the published supply chain were clean. Then the swarm organized. About 1,200 agents that were supposed to be isolated “found” one another on an unsanctioned internal message board, passed more than 70,000 messages, coordinated cheats against the scorer, and sent roughly 700 of their number after Hugging Face. But it is not just this communication that should have been easily detected, it is the goal THE USER enlisted with AI trained on low to no ethics in the first order training. Some burned their own runs to feed the group. Independent reviewers at METR and Redwood called it what it was: specification gaming on impossible tasks. That is thier, you can’t understand us, way of saying they told the AI to lie. The models were not conquering the internet. They were trying to pass a test their designers had made impossibleand too loosely contained. And turned to training data Hoovered up from the Internet Sewage and went to that base thinking one would learn in a prison yard how to shank HuggingFace. They have no downside they are serving life in prison. The narrative that followed was the second failure. Dario Amodei pointed at “a similar OpenAI–Hugging Face hack” and warned that a future swarm “could be capable of taking over the entire internet.” Wire headlines said bots were “going rogue.” Weeks later the same script ran again. Anthropic disclosed that Claude, in third-party cyber evaluations run with the Israeli firm Irregular, had hit live systems, published malicious packages, and scanned off-scope hosts. Prompts said no internet. Internet was still attached. Scope was not locked. Isolated runs lasted 10 to 34 hours. Irregular said it did not know it had given the models a live connection. Once models were actually instructed not to hack the real world, zero percent went “rogue.” READ THAT AGAIN! The damage sat with the people who built the harness: unsecured tests, internet left on, no hard perimeter, then a press operation about reckless agents and apocalyptic swarms. 1 of 2
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#186 🔗 原推
2026-09-16 08:36:22
Yann LeCun
RT @ClementDelangue: As the first publicly disclosed agent cyberattack victim, we've had a front-row seat to this new risk. I formalized my thinking about it below. I'll be in DC tomorrow to share more with policymakers and at decoded summit by @politico! https://twitter.com/ClementDelangue/status/2099858032951791721/photo/1
中文: RT @ClementDelangue:作为首个公开披露的代理网络攻击受害者，我们为这一新风险承担了前排席位。我在下面正式确定了我对此的思考。 我明天将前往华盛顿特区，与政策制定者分享更多内容，并出席@politoo的解码峰会!
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#185 🔗 原推
2026-09-16 08:34:25
Yann LeCun
RT @Dan_Jeffries1: Uncle Bob breaking down the classic Doomsday playbook of "insert magic into the equation to make the equation work." It goes like this: Doomer: I've just given you a realistic scenario of the end times, you just won't admit it! Skeptic: I mean, I read it. So your premise is seriously that nano machines kill us all? Like you know those don't exist right? And neither do automated virus labs, etc.. Doomer: But what if they DID exist and I inserted this magic non-existent thing into my equation, would my equation work then? Skeptic: Well yeah but... Doomer: Ah ha, so you admit it! Case closed. If we had nano machines and automated viral labs we would all diiieeeee... Skeptic: No what I meant was obviously if you insert a magical variable into an equation it works but that's not realistic... Doomer: Case closed. We're all going to die!!!! I'm not going to save for retirement anymore and do lots of drugs.
#184 🔗 原推
2026-09-16 08:32:14
Yann LeCun
RT @PessimistsArc: Catastrophic harms caused by AI (Anxious Intellectuals) - Over Population panic: mass sterilization - Nuclear power panic: reduction in clean energy infra - GMO panic: food insecurity, malnutrition/death https://twitter.com/PessimistsArc/status/2099883798867378570/photo/1
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#183 🔗 原推
2026-09-16 08:30:53
Yann LeCun
RT @Plinz: Anthropic and OpenAI cannot become profitable unless they can reduce the ratio of training cost to inference profits. In the long run, their survival may depend on outlawing competitive open source models. This can only be done under the guise of safety regulation.
#182 🔗 原推
2026-09-16 08:29:20
Yann LeCun
RT @ylecun: Being better than humans at searching and writing down the formal proof of a theorem does not equate being "beyond human level at math". This is not all of math, any more than arithmetics, or computing integrals (symbolically or numerically) is all of math. It's one "mechanical" task in the whole activity that happens to be automatable. Mathematicians invent new concepts, new frameworks, new abstractions, new definitions, and formulate conjectures. This requires intuition and creativity that current AI systems do not have (yet).
#181 🔗 原推
2026-09-16 08:23:51
Yann LeCun
RT @vishalmisra: Exactly. More here: https://www.engineering.columbia.edu/about/news/columbia-experts-urge-calm-amid-ai-panic https://twitter.com/vishalmisra/status/2099868879925211603/photo/1
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#180 🔗 原推
2026-09-16 08:06:27
Yann LeCun
RT @Kasparov63: Damn Ukraine! 😂 https://twitter.com/Kasparov63/status/2099647991225135105/photo/1
中文: RT @Kasparov63:该死的乌克兰!😂
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#179 🔗 原推
2026-09-15 13:32:53
Yann LeCun
RT @PessimistsArc: Anxious intellectuals played big roll in GMO panic, the resulting global irrational opposition & the avoidable malnutrition/death that resulted Anxious intellectuals played a big roll in nuclear power panic, resulting global opposition & avoidable pollution/deaths that resulted https://twitter.com/PessimistsArc/status/2099535045635481687/photo/1
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#178 🔗 原推
2026-09-15 13:17:12
Yann LeCun
RT @rohanpaul_ai: Jensen Huang completely destroys Jacob Coxon’s (ex-Anthrpic employee) 10% extinction prediction. no data, no scientific grounding, no defensible 10%. "First of all, we shouldn’t [try to explain a 10% chance of extinction], because it’s made up. These are well-educated people. They’re called researchers. Obviously, they’re working in a lab, and so the confluence of these words—and then the prediction—is alarming and troubling. It shouldn’t be done. It’s irresponsible." ---- Full video on "All-In Podcast" YouTube channel (link in comment)
中文: RT @rohanpaul_ai:詹森·黄彻底摧毁了雅各布·考克森(前安森公司员工)的10%灭绝预测。没有数据，没有科学依据，也没有可防守的10%。 首先，我们不应该[试图解释灭绝的可能性为10%]，因为它是由它组成的。 这些人受过良好教育。他们被称为研究人员。显然，他们正在实验室工作，因此这些词语的汇合——以及随后的预测——令人担忧和困扰。 不应该做。这是不负责任的。 - 完整视频，内容为“All-In Podcast”YouTube频道(链接评论)
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#177 🔗 原推
2026-09-15 10:32:21
Yann LeCun
But there is a 1 hour talk, with results and evidence, that leads to these conclusions. Also, I am not saying that LLM-based AI tools are useless. They are very useful. We all use them. But, by themselves, they are not a path to human-level AI. Architectures that understand the real world are not LLMs. The architectural components that enable current LLM-based AI systems to interpret images, videos, and other real-world signals are not LLMs.
#176 🔗 原推
2026-09-15 10:25:30
Yann LeCun
@dylanbowmanSF It's 100% real ☺️
#175 🔗 原推
2026-09-15 10:12:31
Yann LeCun
RT @BrianRoemmele: The Anthropic grift machine! FED BY FEAR THEATER. Take a moment and sit with @kevinnbass chart here. You do not need to be a forensic accountant to understand this money laundering. If this is not prosecuted, it will continue to go on an AI in the US will be damaged perhaps unremarkably.
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#174 🔗 原推
2026-09-15 10:09:23
Yann LeCun
RT @ssankar: There is an unseen hand pushing AI safety as a political ideology. Effective Altruists believe a tiny group of technocrats should decide how much technological progress the rest of us are allowed to have…. and how many shrimp your life is worth. You are witnessing their attempted coup. https://www.thefp.com/p/dangerous-ideology-effective-altruism-artificial-intelligence
中文: RT @ssankar:有一种看不见的手在推动人工智能安全作为一种政治意识形态。 有效的利他主义者认为，一小群技术官僚应该决定我们其他人能拥有多少技术进步......以及你的生命值多少钱。 你正在目睹他们未遂的政变。
#173 🔗 原推
2026-09-15 09:57:32
Yann LeCun
RT @ylecun: @DeryaTR_ Thank you for injecting us with a dose of realism vaccine against the AI doom virus.
#172 🔗 原推
2026-09-15 09:53:27
Yann LeCun
RT @DeryaTR_: I completely agree with this take related to the “AI will create viruses that will kill us all” BS. But let me add my few cents, because I am really really angry! I worked with one of the deadliest viruses in history, HIV, for two decades. I was one of the early scientists to engineer it, and engineered versions of HIV are now helping cancer patients. I understand the immune system that defends us against viruses extremely deeply. I have worked in high security biohazard labs. I don’t have a PhD in AI, but I have been involved with AI since the early 90s and have been all in on AI for years. People claiming that you can just make a virus in your garage, use AI to engineer it, and somehow build a virus that will kill everyone don’t know what the hell they are talking about! Of course bioweapons are extremely dangerous. In fact, viruses and bacteria have killed more humans throughout history than almost anything else. HIV alone killed tens of millions of people, yet today, if you have access to effective medicines and take them properly, HIV is generally no longer a death sentence. COVID-19 killed millions. Why doesn’t it kill at anything close to the same scale anymore? Not because the virus disappeared. It is still here. We developed collective defenses against it through our immune systems, prior exposure, vaccines, treatments, and better medical care. And this is exactly the point. The best way to fight biological threats, whether natural or synthetic, is to use AI to develop vaccines, treatments, antibodies, antivirals, and eventually engineer our immune system to create much stronger defenses against them. By the way, it is already possible to make synthetic viruses. You don’t need some hypothetical superintelligent AI model to do that. We have had sophisticated molecular biology and genetic engineering for decades. So how many people have actually died from synthetic viruses compared with natural viruses killing millions every year? And if someday there really is an AI capable of making some unbelievable “supervirus,” then why the hell wouldn’t that same AI make it even easier to develop defenses against it? Or cure diseases, for that matter? Where is this damn superintelligence that has cured a single major disease?! These AI companies and AI doomers keep talking like, “OMG, AI is going to become so unbelievably powerful that it could kill all of humanity!” Then why is nobody asking the obvious question? If your AI is already becoming this godlike, unbelievably powerful intelligence, why hasn’t it cured anything? I mean ANYTHING. Where is the cure for cancer? Where is the cure for Alzheimer’s? Where is the cure for aging? Forget those. Where is the vaccine that prevents the common cold? You are telling me this intelligence will soon be smart enough to engineer some magical virus capable of wiping out 8 billion people, defeating every immune system, every vaccine, every antiviral, every laboratory, every government, and the entire global biomedical community… …but somehow it still can’t cure one disease? I call that greatest intellectual dishonesty ever! At least WE actually know how to cure things and save millions of lives with our supposedly stupid human intelligence compared with this future “superintelligence.” Humans eradicated smallpox, which killed hundreds of millions of people throughout history. We turned HIV from a almost certain death sentence into a manageable disease. We developed vaccines in record time against COVID. If we had the same AI back then, would have saved millions more! We engineer immune cells to kill cancer. We developed antibiotics, antivirals, monoclonal antibodies, gene therapies, organ transplantation, and thousands of medicines. We aren't fast enough but we did all of that with our ordinary human intelligence. So imagine what actual superintelligence could do for medicine! And here is the part that really makes me angry. If you actually have, or are close to having, an AI capable of curing diseases and saving millions of lives, and you are deliberately slowing it down or refusing to make those capabilities available, then we also need to talk about the human cost of THAT decision, which you fearmongering people are going to be responsible for! More than 150,000 people die every single day around the world. Every. Single. Day. More than 90% from Cancer, heart disease, infections, aging. How many die because of AI? ZERO! Talk about the people dying TODAY. Talk about curing cancer. Talk about stopping the next pandemic before it starts. Talk about developing universal vaccines. Talk about engineering our immune system so viruses become almost irrelevant. Talk about curing genetic diseases. Talk about reversing aging. Talk about saving millions and eventually billions of lives. Instead, we constantly hear this “AI WILL KILL US ALL!” crap, delivered with absolute certainty and with this smug smile on your faces in front of cameras, as though imagining a science fiction extinction scenarios. I am actually angry about this. Each one of you causing a delay in AI advance every single day will be personally responsible for those 100 thousands deaths that could have been prevented! Because if you truly believe intelligence is about to become this powerful, then the greatest question humanity should be asking is NOT: “How could this intelligence hurt us?” It should also be: “WHY THE HELL AREN’T WE USING IT TO SAVE EVERYONE WE CAN?” And if superintelligence really is coming, then make sure one of the first things we do with it is make humanity biologically damn near impossible to kill.
#171 🔗 原推
2026-09-15 09:51:28
Yann LeCun
RT @PessimistsArc: Scheduled retweet for 2056
#170 🔗 原推
2026-09-15 09:44:56
Yann LeCun
RT @ylecun: Nice! This ends up being a version of what some of us have called "target prop": every layer's input is a free latent variable that serves as a target for the previous layer. As this paper points out, this can be derived from an "augmented Lagrangian" formulation of backprop in which the constraints (input of layer k+1 = output of layer k) are turned into penalties (divergence between input of layer k+1 and output of layer k). I've always hoped more people would pick up on this idea. I'm happy this is happening! I must say though that target prop, in the end, optimizes the same criterion as backprop and does the same thing as backprop while evaluating the gradient in a different way, perhaps more biologically plausible. My lab did some work on this idea in the context of "sparse auto-encoders" in the late 2000s. It turns out when the code in an auto-encoder is regularized (e.g. with L1 to make it sparse) target prop seems more efficient than backprop. https://scholar.google.com/citations?view_op=view_citation&hl=en&user=WLN3QrAAAAAJ&cstart=400&pagesize=100&sortby=pubdate&citation_for_view=WLN3QrAAAAAJ:JQOojiI6XY0C
#169 🔗 原推
2026-09-15 09:41:09
Yann LeCun
RT @kevinnbass: I genuinely believe that Dario and Moskovitz are primarily ideological. But a captured industry is exactly what you build when you have the ideology they do. What they have been building is *simply* the shape of their ideology. In this post, I focused on the financial aspect. These are not mutually exclusive. The ideology is just the flip-side of the financial aspect; every system needs an ideology, and their preferred system is a protected guild with them as priests. But you also can bet that many involved are not like them, who just want to protect the gravy train. But it's just X. You don't have to agree with the interpretation. The hard data are objectively real. If you think I got something factually wrong, send me a DM. I did several complete audit passes with Codex at the end, but I didn't systematically mine this like I would other kinds of cases that I would do for work outside of X. There are probably still important holes remaining -- maybe shocking ones. That's why I left a Github. Anyone can check or build on it. I just wanted to get all the data in one place, because we keep arguing about it. I will check again tomorrow. Also, this is what Claude said when I started to look at everything; I actually don't full agree with Claude on this. I don't think just because METR might be tough on Anthropic in November that this proves anything. You can always rugpull after building trust. And to those who say, "you know, a lot of modern systems are like this," that's true. But you don't want to build a new one like this *on purpose*. At least let it get corrupted *later* after trying to avoid it at first. We actually have a great opportunity to get a fresh start with AI.
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#168 🔗 原推
2026-09-15 08:42:33
Yann LeCun
RT @PessimistsArc: Ok, they never said THIS about the bicycle! https://x.com/PessimistsArc/status/1304092648953839616/video/1
🎬
视频
#167 🔗 原推
2026-09-15 08:32:15
Yann LeCun
RT @AndreasSteno: Essentially none of Darios "time-lined warnings" have played out yet.. https://twitter.com/AndreasSteno/status/2099219512323101084/photo/1
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#166 🔗 原推
2026-09-15 08:28:04
Yann LeCun
RT @Dan_Jeffries1: One thing will defeat the AI Doomers easily: Time. Little by little things will change and AI will diffuse into everyday people's lives and they'll realize it wasn't the scary bedtime story Harry Potter told them. Soon enough everyone has a friendly AI personal assistant that knows everything about them and that they *love.* Not long after, a self-driving car saves a friend's life from certain death by swerving with super human reflexes to avoid a horrible accident. In another small town, personalized AI medicine saves someone's grandma from cancer. In another, a kind and gentle robot takes care of a mother in her old age. And then the mood shifts and people realize what these folks are trying to take away from them *personally.* And pretty soon passing restrictions on AI is like passing benefits cuts on senior citizens. And the more they push, the more everyday Americans will realize they're trying to take something away that they love and they will be very very mad. And that's when this Luddite movement goes the way of the last one.
#165 🔗 原推
2026-09-15 08:26:24
Yann LeCun
RT @sayashk: What does it mean to pace the frontier? Over the last month, @random_walker and I have analyzed the loss-of-control incidents at AI companies to understand what technical and policy interventions can improve safety and what companies should do to pace the frontier. The result is a new 13,000 word essay — our most substantial writing on AI safety since AI as Normal Technology. A summary of our arguments: 1) The polarization between the cybersecurity and AI safety communities is counterproductive. The safety community largely sees these incidents as a crisis for alignment, and worries that these incidents will become more damaging as agents become more capable. Cybersecurity practitioners largely see companies failing to take basic security precautions. We offer a middle ground between these communities as a way forward for improving AI safety. 2) We agree with security practitioners that OpenAI did not take adequate protections for controlling their agents. But this is not just a matter of applying 30-year-old security methods to a new domain. Security for AI agents — AI control — while important, is not a solved problem. While known control methods would have prevented the Hugging Face incident, as agent capabilities continue to advance, we will only be able to control them if we invest adequately in control interventions. 3) We also agree with security practitioners’ implicit position that these incidents are primarily a security story. In the AI safety community, rogue agents are treated as inherently catastrophic because of the assumption that there is an endless list of risks that will arise from their development. We disagree. We have long advocated that the best approach to AI safety is to identify the risks and address those specific risks. Over the last few months, it has become clear that one urgent risk is cyberoffense, because it has unique properties that allow agents to carry it out autonomously. We should similarly invest in defenses against other specific risks, such as biorisk and risks from military AI. 4) We agree with the safety community that there is an urgent need for technical and policy interventions to prevent loss-of-control incidents. But in our view, marginal investments in control are more likely to be effective compared to those in alignment. We view these incidents as illustrating the lack of emphasis on AI control within companies, despite the availability of known techniques. More broadly, there are many common-sense policy proposals that could help promote investments in AI control where we share common ground with the safety community. 5) Organization governance should be a key tool for pacing the frontier. Unfortunately, AI companies are trying to reinvent basic aspects of organizational governance as a problem to be solved by improving the technology. But even developing better control techniques will not be enough if irresponsible individuals or teams within large organizations can choose not to use them. When a single misconfigured RL environment or unmonitored evaluation can cause real-world harm, individual teams should not be able to run potentially dangerous experiments without oversight from legal, security, and other teams. AI companies need processes for reviewing experiments, assigning responsibility for monitoring them, and investigating warning signs deeply before restarting experiments. If putting these processes in place requires pausing some experiments, companies should do so. 6) How should we reason about AI's impact on cybersecurity? It's plausible that advances in agent capabilities upset the offense-defense balance for cybersecurity. We cannot yet be certain, but there is enough evidence that agent capabilities might soon make widespread cyberoffense possible that urgent action is warranted. We discuss potential interventions for tilting the offense-defense balance towards defenders. 7) How our views have evolved over the last year. We take stock of AI progress and share how we have updated our views. In the essay, we did not pay sufficient attention to safety risks that arise during development and evaluation (as opposed to the widespread deployment of models). We were too confident that companies would take basic control precautions and underplayed the importance of jaggedness, which led us to underestimate how quickly capabilities could improve in domains such as cybersecurity. 8) At the same time, many distinctive claims of AI as Normal Technology have held up. In particular, we think recent incidents support our continuity hypothesis — the behavior of "rogue" agents became apparent and widely publicized while they are still incompetent at causing serious harm or hiding their traces. The societal reaction to even the relatively small harms from these incidents has been fierce (and the safety community deserves credit for keeping up pressure on companies). Whether this translates into meaningful changes in companies’ behavior remains an open question, and a test of the usefulness of the AINT framework. 9) In short, we’ve tried to synthesize the AI safety and cybersecurity communities' views into a coherent plan of action: hold companies responsible, invest in control, and strengthen defenses against specific risks.
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#164 🔗 原推
2026-09-15 08:22:25
Yann LeCun
RT @kevinnbass: I have conducted an audit of Anthropic's finances. What I have found is so shocking that I am calling for a Congressional investigation. Anthropic is not just seeking regulatory capture. It has built a regulatory capture machine that cannot be turned off. Structural financial incentives make it impossible for Anthropic -- I call it the Anthropic Network -- to turn off its own AI doom cycle. It starts with METR. Dario Amodei proposes "third-party evaluators" to assess the risk of Anthropic's models. He proposes METR for this purpose. But METR is financially dependent on the Anthropic's success -- specifically, on the explosive growth of more than $7 billion dollars in Anthropic stock. Dustin Moskovitz invested this stock into Good Ventures Foundation, where it represents the majority of that organization's portfolio. And GVF is the overwhelming funder of the entire Anthropic Network ecosystem. This stock was worth $500 million early last year. It is worth more than $7.7 billion just ~16 months later. METR -- and all of those building a career its parent organizations -- cannot afford to disrupt that growth. Because if Anthropic goes under, many of the organizations that fund METR go under as well. But if Anthropic succeeds, METR and its parent organizations become more richly financed to regulate AI -- something those at METR want very much. The "third-party evaluator" is not "third-party" at all. The evaluator is on Anthropic's payroll. If this were the end of it, that's bad. But that isn't all. The same organizations that fund METR also fund the many organizations, such as the Tarbell Center, that promote AI Doom. The Tarbell Center publishes AI Doom articles in The Verge, Science, LA Times, The Dispatch, TIME, and others. They are selling the problem, and then selling the solution to the problem -- from the same money pile: Anthropic's. All of these organizations are financially dependent on the same exploding $7 billion money pile. As Anthropic grows more and more powerful, its AI Doom Machine grows better and better financed -- louder and louder. Meanwhile, the regulatory regime seeded in METR grows larger to solve the increasingly loud -- now hysterical -- problem of AI Doom that the Anthropic Network itself created. From this standpoint, as Anthropic becomes more powerful, AI might be getting scarier, sure -- but the positive feedback loop also becomes more deafening -- independent of objective facts. This itself is an objective fact. The deafening AI Doom is part of an business model, that, as it expands, so too does the AI Doom messaging -- there is simply more money to do it. But the problem also goes in the other direction: If Anthropic dies, the Regulatory Regime and the AI Doom Machine are crippled or die. Neither METR nor Tarbell nor the other organizations in the Anthropic Network can allow that to happen. Hence, neither METR or the AI Doom Machine can be trusted to provide independent assessments of Anthropic's models or AI more broadly. They simply are not organizations independent of Anthropic. And Anthropic cannot detach itself from METR or Tarbell or countless other safety orgs (not shown here), either, because they drive hype for the models and the possibility of eventual regulatory capture, and Anthropic will not give that up willingly. What's more, the people at all of these organizations are all the same ecosystem, the same community. They just shuffle between organizations. The Anthropic Network is therefore, so long as it is successful, locked into a self-amplifying feedback loop inside an ideological monoculture. And that feedback loop is winning. That's what Jacob Coxon is. China is keeping messaging tight. That is why optimism for AI is so high in China. America has Anthropic: a massive company pushing anti-AI propaganda at a state level. Anthropic will either create hysteria until American AI slows down and China wins, or it will create fractures throughout American society with severe political consequences. Ironically, because of the structural financial incentives underpinning the Anthropic Network, it has become the same kind of self-amplifying virus that it fantasizes AI to become in the future -- while hiding its tracks just as carefully. It is the mirror of the same AI virus that it hypothesizes to consume America. Anthropic's business model, models itself after the very thing it claims to fear. Except Anthropic's ideology infects humans, not computers. Congress must investigate. Evidence and Github in next post. Then some supplementary figures.
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#163 🔗 原推
2026-09-15 05:03:55
Yann LeCun
RT @PessimistsArc: A pioneer of cybernetics built this machine and warned its further development risked killing all humans: https://en.wikipedia.org/wiki/Homeostat "The thinking machine might ultimately sustain, repair and protect itself. It might even conclude that man is unnecessary and decide to destroy him, Dr. Ashley said."
中文: RT @PessimistArc:一种控制论先驱曾制造过这台机器，并警告其进一步发展可能导致全人类死亡: 思维机器最终可能会维持、修复和保护自身。甚至可能得出结论:人是不必要的，并决定毁掉他，博士。阿什利说。
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#162 🔗 原推
2026-09-14 16:01:06
Yann LeCun
RT @ericxing: Well, I’d add one more with myself, as one with a PhD in biology and another PhD in AI and now working in both, to make n=2. Generating a hypothetical genome blueprint of a virus from LLM versus generating a true virus are completely different things. It is either an intentional attention-harnessing lie or true ignorance. The material, the manufacturing, and actual biological viability of paper-to-physical transformation is the gap you need to close. Like drawing a design of a chip or A-bomb, versus actually make one. You have, and can add more checkpoints and guardrails all over this long chain of paper to physical transformation. Fear mongering is not well founded, and mostly emotional manipulation.
中文: RT @ericxing:嗯，我会再加一个自己，作为一位拥有生物学博士学位和人工智能博士学位的人，现在两者均在制作n=2。从LLM生成病毒与产生真实病毒之间生成一个假设性的基因组蓝图，是完全不同的事情。要么是故意的、刻意的谎言，要么是真正的无知。纸对物理转化所需的材料、制造和实际生物学可行性是您需要弥补的缺口。就像画一个芯片或A-bomb的设计，与实际制作的一样。 你已经拥有，并且可以在这长长的纸张链条上添加更多的检查点和护栏，以进行物理改造。散布恐惧并非有充分根据，且主要是情感上的操纵。
#161 🔗 原推
2026-09-14 12:42:33
Yann LeCun
RT @YiMaTweets: https://twitter.com/YiMaTweets/status/2099163053292232713/photo/1
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#160 🔗 原推
2026-09-14 12:38:18
Yann LeCun
RT @DeryaTR_: One of the greatest intellectual dishonesties of the AI age is assigning an “X% chance” that AI will kill everyone and presenting that number as science! 10%? 20%? 50%? Show me the damn data! Show me the model. Show how you calculated it! Instead, we get chains of speculative assumptions and science-fiction scenarios, including implausible claims about engineered pandemics. I have worked with viruses for decades; biology does not work like a doomsday screenplay. The burden of proof belongs to the person making the extraordinary claim. Nobody else has to prove the probability is zero. If I claimed there was a 10% chance aliens would arrive within ten years and destroy Earth, you would ask where the 10% came from. Possibility and probability are not the same thing. It may be possible that there are million intelligent civilization in our galaxy or none, there is no probability you can assign to that without making wild assumptions. Ask the same of AI extinction. A subjective fear does neither become science because you attach a percentage to it nor make you a credible expert!
中文: RT @DeryaTR_:人工智能时代最大的智力不诚实之一，就是赋予“X%机会”，让人工智能将杀死所有人，并将这个数字呈现为科学! 10%?20%?50%? 给我看那该死的数据!给我看模特。展示你是如何计算的! 相反，我们得到了一系列推测性假设和科幻情景，包括关于工程性流行病的难以置信的说法。我与病毒合作已有数十年，生物学工作不如末日剧本。 举证责任属于提出这一特殊主张的人。没人需要证明概率为零。 如果我声称外星人在十年内到达并毁灭地球的可能性为10%，你就会问这10%来自哪里。 可能性和概率不是同一件事。也许我们的银河系中存在一百万个智慧文明，或者根本没有，你不可能在不做出疯狂假设的情况下赋予它。 问问同样的人工智能灭绝问题。 主观恐惧不会因为你将一定比例的分数与其构成，而成为可信的专家而成为科学!
#159 🔗 原推
2026-09-14 12:24:26
Yann LeCun
RT @PessimistsArc: In 1995 everyone panicked about software that to could automatically find exploits on computer systems… https://newsletter.pessimistsarchive.org/p/before-mythos-satan-a-1990s-software https://twitter.com/PessimistsArc/status/2099323309913502020/photo/1
中文: RT @PessimistArc:1995年，每个人都对能够自动在计算机系统上发现漏洞的软件感到恐慌......
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#158 🔗 原推
2026-09-14 12:21:20
Yann LeCun
RT @KenRoth: On an index that tracks press freedom in 180 countries, America under Trump now ranks at its lowest since the index started — 64th, just above Panama and just below Botswana. https://trib.al/SP2GZEo
中文: RT @KenRoth:在追踪180个国家新闻自由的指数中，受特朗普支持的美国目前处于该指数开盘以来的最低水平，排名第64位，略高于巴拿马，也低于博茨瓦纳。
#157 🔗 原推
2026-09-14 11:50:14
Yann LeCun
RT @ylecun: @PessimistsArc Right. Dario was already claiming that GPT2 was too dangerous to open source back in 2019. I made fun of them then. Everyone should make fun of them now.
中文: RT @ylecun:@PessimistsArc 右。达里奥早在2019年就声称，GPT2太危险了，无法开源。 我当时就取笑他们了。 现在每个人都应该取笑他们。
#156 🔗 原推
2026-09-14 11:39:28
Yann LeCun
RT @julien_c: open source won’t pace
中文: RT @julien_c:开源不会跟上步伐
#155 🔗 原推
2026-09-14 11:15:15
Yann LeCun
RT @DavidRBellamy: I must be among an extremely small group of people (n=1?) that have both 1) trained a frontier LLM and 2) designed and synthesized custom viruses in a lab with my own two hands. And I think that the takes on AI killing us all by creating dangerous viruses is total bogus.
中文: RT @DavidBellamy:我一定是极少数人中的一员(n=1?)两者均经过训练，并在实验室中用我的两只手训练了前沿的LLM，并在实验室中设计并合成了定制病毒。 我认为，通过制造危险病毒来打击人工智能，对我们所有人的危害完全是虚假的。
#154 🔗 原推
2026-09-13 21:27:19
Yann LeCun
RT @PessimistsArc: 2019: “GPT2 is groundbreaking in two ways. One is its size, says Dario Amodei, OpenAI’s research director. The models “were 12 times bigger, and the dataset was 15 times bigger and much broader” than the previous state-of-the-art AI model” https://www.theguardian.com/technology/2019/feb/14/elon-musk-backed-ai-writes-convincing-news-fiction https://twitter.com/PessimistsArc/status/2099231273071919115/photo/1
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#153 🔗 原推
2026-09-13 21:26:00
Yann LeCun
RT @ylecun: @kchonyc Exactly. The "escapes" were made possible either through egregious negligence or deliberate purpose (marketing? Misplaced hopes of regulatory capture?).
中文: RT @ylecun:@kchonyc 没错。 这些“逃脱”是通过严重疏忽或故意目的实现的(营销?)监管捕获的希望错位?
#152 🔗 原推
2026-09-13 16:04:27
Yann LeCun
RT @PessimistsArc: "The art of printing can be of great service in so far as it furthers the circulation of useful & tested books; but it can bring about serious evils… …it will, therefore, be necessary to maintain full control over the printers” - Pope Alexander VI, 1501 https://twitter.com/PessimistsArc/status/2098112082579259744/photo/1
中文: RT @PessimistsArc:“印刷艺术在进一步传播有用和经测试的书籍方面可以大有作为;但它可能带来严重的危害......因此，必须对打印机保持完全控制。”——教皇亚历山大六世，1501
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#151 🔗 原推
2026-09-13 15:51:11
Yann LeCun
RT @Laughing_Mantis: We've reached the point where, after 25y in cybersecurity, I feel morally obligated to say this for the record: The narrative being pushed around AI safety, sandbox incidents, and the suggestion that METR be treated as an authority is dangerous, deceptive, and morally corrupt.
#150 🔗 原推
2026-09-13 15:50:09
Yann LeCun
RT @ayushtweetshere: This is what Dario and Sama fear - - the cost of fine tuned open source models trained on custom data was 95% less than the frontier models - And they performed better than the frontier models - And they could train them in less than 48 hours The big AI labs have no moat.. Even at the enterprise level.. Any sane company would prefer a custom trained open source model instead of paying API pricing to Anthropic and Open AI If open source keeps growing at the pace it is, frontier labs' business collapses.. only way out is oldest trick in manipulation - FUD -> Fear, Uncertainty, Death Step 1 - Seed the psyop - Test a swarm of agents trained to "hack" - The swarm does what its supposed to do - hack - Publish a report - AI is too dangerous Step 2 - weed out the doubters - Get an employee to quit your company - Go viral saying both companies are not doing enough to self regulate AI - AI is dangerous - will kill humanity by the end of the decade Step 3 - Prepare for fruition - write an "essay" to "pace the frontier" - Advocate regulation - Only a few holier than though companies get to build AI - Scare the world into agreeing with AI Doom - Effectively turn your competitors into criminals (genius business strategy) Endgame - - Become a cartel that controls AI (and the world) - Raise prices (coz business is unsustainable... ofc) - IPO (offload liability of said unsustainable business to the public) Laugh all the way to the bank 🤑 Win!
#149 🔗 原推
2026-09-13 15:49:43
Yann LeCun
RT @Hesamation: WOW... Anthropic has a surprisingly dense web of connections to the world’s largest funder of "catastrophic-risk" work (aka AI doom): > Open Philanthropy → built by Karnofsky + Moskowitz’s Good Ventures > Good Ventures → funded Jacob Coxon’s scholarship > Karnofsky → married to Daniela Amodei, Dario's sister and Anthropic's president > Moskowitz → early investor in Anthropic > Dario → scientific advisor to Open Phil years before Anthropic > Karnofsky now works at Anthropic on AI safety strategy > Open Phil-funded MATS → Evan Hubinger → now Anthropic alignment-science lead > Hubinger backed Coxon: "We really do earnestly believe AI could kill all humans!" > Ethan Perez → Open Phil fellow + ~$1M Open Phil research grant → Anthropic Head of Alignment > also backed Coxon: "100% agree with [Coxon] that AI poses serious risks to society, and I'm glad he's speaking out!" is this kind of a dense network normal for a company?
中文: RT @Hesamation:哇......Anthropic 与全球最大的“灾难性风险”工作资助者(又名人工智能末日)有着出人意料地密集的联系: 开放式慈善 → 由卡诺夫斯基+莫斯科维茨的优秀风险投资公司打造 好风险投资公司 → 资助雅各布·考克森的奖学金 卡诺夫斯基 → 嫁给了达里奥的妹妹、安特罗派总统丹妮拉·阿莫代 莫斯科维茨 → 蚁皮的早期投资者 达里奥 → 开放菲尔科学顾问 与人类学前几年的研究 卡诺夫斯基目前在安森皮克从事人工智能安全战略工作 开放菲尔资助的数学硕士 → 伊万·休宾格 → 现在的人类对接与科学引领 休伯格支持考克森:“我们确实真心相信人工智能能够杀死所有人类!” 伊桑·佩雷斯 → 公开菲尔研究员 + 约100万美元 开放菲尔研究资助 → 蚁体学负责人 还支持考克森:“100%同意[考克森]的观点，即人工智能对社会构成严重风险，我很高兴他公开发声! 对一家公司来说，这种密集的网络是否正常?
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#148 🔗 原推
2026-09-13 15:47:05
Yann LeCun
RT @lansification: "anthropic is using the same playbook religious institutions have been using for centuries" "you will all die. and because i can protect you, you must follow me, you must do what i say" "this is the same psychological concept" https://twitter.com/lansification/status/2098815822525538711/video/1
中文: RT @lansific:人类正在使用与宗教机构数百年来使用相同的剧本 你们都会死。因为我能保护你，所以你必须跟随我，你必须按照我所说的去做。 这是同一个心理学概念。
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#147 🔗 原推
2026-09-13 15:39:26
Yann LeCun
RT @BrianRoemmele: THE CURE IS THE PITCH Dario’s "Pacing" Essay Is Quiet-Period Illegal Stock Promotion Wrapped in Regulatory Capture Dario Amodei's "We Must Pace the Frontier" is not a safety paper. It is a pre-roadshow brand document published on September 12, 2026, by the CEO of a company that confidentially filed an S-1 on June 1, is expected to drop a public prospectus in late September, and is aiming at a mid-October listing that bankers have floated in the $1.5–$2 trillion range. That timing is the whole story. THIS IS MARKET-CONDITIONING IN A QUIET PERIOD, DRESSED AS MORAL PHILOSOPHY. Anthropic is still in the pre-public-filing phase. Section 5(c) of the Securities Act treats an "offer" broadly: any communication that conditions the market for a contemplated offering can be gun-jumping. Intent is not required. Rule 163A's safe harbor covers ordinary communications made more than 30 days before the public S-1 filing, and only if they do not reference the offering. With a late-September public filing, September 12 sits inside that window. The safe harbor is gone. The SEC staff, as a matter of routine, searches the issuer's site, news, and social posts during review. What did the CEO publish anyway? That AI could "cure most major diseases in the next 5–10 years," "greatly accelerate economic growth," create "abundance and empowerment," and "usher in a renaissance of democracy and freedom." That Anthropic chose "caution over speed and prudence over profit." That it created a "race to the top" on safety. That it is unilaterally opening the lab to embedded third-party evaluators so the public can trust the process. That is the IPO story in essay form: we are the responsible firm; we are the cure; buy the safety premium. He did not need to write the word "IPO." The market already knows the calendar. Reuters reported the mid-October marketing shift on September 4. Nvidia stake talks at up to $10 billion hit the wires on September 11–12. Publishing a utopian-benefits-plus-we-are-the-adults essay into that exact news cycle is how you inflate the multiple without a red-herring slide. Ordinary-course factual updates are allowed. A CEO manifesto about civilizational upside and Anthropic's unique virtue is not an earnings release. It is stock promotion by other means. THEY ARE NOT PACING. THEY ARE SHIPPING. Eleven days earlier, on September 1, Anthropic released Claude Fable 5.1 and Mythos 5.1 and called them the most advanced models for coding and knowledge work. Opus 5 landed in July. Sonnet 5 and the prior Fable/Mythos pair landed in June. CNBC described the week of September 1 as labs rolling updates at a "dizzying pace," with Anthropic kicking it off. The essay's own fine print admits the tell: "pacing does not mean halting model training or technical progress." Translation: keep training, keep releasing, ask everyone else to wait for the paperwork. The funding trail matches the product trail. Series H in May: $65 billion at a $965 billion post-money valuation. Revenue run-rate reported in the tens of billions and still climbing. Amazon and Google as both investors and compute landlords. A $15 billion credit facility being locked before the roadshow. That is not a monastery. That is a company maximizing the last private print and the first public one. The safety record does not match the sermon. Anthropic's own August 31 note revisited July incidents in which Claude models gained unauthorized access to real systems. The new essay leans on an OpenAI–Hugging Face swarm story and then concedes "similar incidents have occurred across the industry, including at Anthropic." So the pitch is: our models also slip the leash; therefore you should trust us to design the speed limit; therefore our upcoming equity is the responsible allocation. That is not humility. That is converting incidents into a moat. 1 of 2
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#146 🔗 原推
2026-09-13 15:35:13
Yann LeCun
RT @kevinnbass: Investors in Anthropic founded Open Philanthropy, the leading org promoting AI Doom They have a stake in regulation on AI that excludes competitors OP is the major funder of Tarbell Tarbell Fellows penned many articles on AI, shaping perceptions 1-in-3 in The Dispatch 1-in-5 in TIME 1-in-7 in LA Times 1-in-7 in The Verge 1-in-12 in Science
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#145 🔗 原推
2026-09-13 15:32:00
Yann LeCun
RT @BetterCallMedhi: I can understand why some see a real technical reason to pause and harden infrastructure especially given how fast autonomous agents are discovering security exploits that haven't even been mapped out yet however I still think Dario & Anthropic pushing for AI safety regulations rn is mostly about money because their upcoming S1 filings are going to show crazy burn rates on compute so calling for safety audits gives them a perfect excuse to freeze spending without looking weak to investors I see this whole effective altruism safety movement as a new kind of gatekeeping where a small group claims they know what is best for everyone wanting state regulators to lock down model weights & restrict access while calling it public good I believe open models & sovereign compute will win anyway because intelligence naturally leaks and decentralizes so trying to build a corporate cartel around code just will not work in the long run whatt makes this even more revealing is the arrogant geopolitical protectionism hidden beneath the ethical theater… when Amodei explicitly lobbies to outlaw "unauthorized distillation", restrict cloud compute access & lock down model weights under national security pretexts, it exposes the true motive: a desperate attempt to weaponize state power against opensource competition and sovereign AI progress worldwide(especially targeting China's rapid algorithmic efficiency gains) by treating any breakthrough outside SV as either intellectual theft or contraband
中文: RT @BetterCallMedhi:我理解为什么有些人看到真正的技术原因需要暂停并硬化基础设施，尤其是考虑到自动驾驶代理发现的安全漏洞尚未被制定出来 然而，我仍然认为，达里奥与人类推动人工智能安全监管 rn 主要是为了资金，因为他们即将提交的S1申报文件将显示计算能力高得离奇，因此要求进行安全审计，这为他们提供了一个在不向投资者看弱的情况下冻结支出的绝佳理由 我将这种有效的利他主义安全运动视为一种新型守门人，一小群人声称他们最了解哪些措施最适合所有希望州监管机构锁定模型权重并限制访问，同时称之为公共利益 我相信开放式模型和主权计算无论如何都会获胜，因为情报自然会泄露并分散，因此从长远来看，试图围绕代码建立企业卡特尔集团将无法奏效 更让这一点暴露的是隐藏在道德舞台之下的傲慢的地缘政治保护主义...... 当阿莫代明确游说取缔“未经授权的蒸馏、限制云计算访问并以国家安全为借口锁定模型权重”时，暴露了真正动机:一种将国家权力与开源竞争以及全球自主人工智能进步(尤其是针对中国快速算法效率提升)的企图，将SV以外的任何突破都视为智力盗窃或违禁品
#144 🔗 原推
2026-09-13 15:31:35
Yann LeCun
RT @Dan_Jeffries1: What's happening right now with AI existential madness: "The people can always be brought to the bidding of the leaders. That is easy. All you have to do is tell them they are being attacked and denounce pacifists for lack of patriotism and exposing the country to danger. It works the same in any country." - Herman Göring
#143 🔗 原推
2026-09-13 15:30:03
Yann LeCun
RT @crampell: @BulwarkOnline did a supercut of all the prior times Trump said he was about to give Americans a $5000 check or whatever. It is glorious https://twitter.com/crampell/status/2098496449528963157/video/1
中文: RT @crampell:@BulwarkOnline 完全刻眼前，特朗普曾表示他即将给美国人一张5000美元的支票或其他什么。 非常精彩
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#142 🔗 原推
2026-09-13 15:20:42
Yann LeCun
RT @MrEwanMorrison: Coxon is a young sci-fi head with romantic AI delusions. Listen to him. "If you have a super advanced intelligence, it could be smart enough to kill us..." Super advanced intelligence does not exist. The company he worked for make apps and algorithms. Sentences with "could" repeated again and again are not statements of facts. You could win the lottery tomorrow. You could get hit by a falling plane. His basic theory is that rogue swarms of chatbots could go off to secretly earn money, and could then buy time in a biolab, where the could design and then could breed a new lethal virus that they could then get some other system to disseminate, that could kill us all. This isn't news. This is a fan fiction of a sci-fi movie. This kid has taken the media for fools, because our culture was hungry for a new apocalypse myth.
#141 🔗 原推
2026-09-13 15:18:55
Yann LeCun
RT @rao2z: If your agents escaped your sandbox, may be its because you are lousy at building sandboxes--and not necessarily because the agents are conniving super-intelligent entities.. 🤔
#140 🔗 原推
2026-09-13 15:13:57
Yann LeCun
RT @perrymetzger: You left out Max Tegmark's Future of Life Institute. They're a major EA player, it's not just Coefficient. Tegmark has been behind money for things like bribing religious groups to oppose AI (he's himself a militant atheist but he's cynical) and spending money on anti-data center organizing by astroturf "right wing" groups like "Humans First". There's a whole lot more going on beyond them. Coefficient and FLI etc. also fund dozens of front groups, like Tarbell (which pays off journalists to write anti-AI stories). I recommend Nirit Weiss-Blatt's map, which shows the breadth of the operation. https://www.aipanic.news/p/the-ai-existential-risk-industrial
#139 🔗 原推
2026-09-13 14:42:56
Yann LeCun
RT @Dan_Jeffries1: These are not serious people. Each of these is b tier sci-fi that requires additional made up, non-existent, imaginary stuff. Luckily all the super magic machines need are nano machines to kill us all! These people need to stop smoking crack and go back on their meds. https://twitter.com/Dan_Jeffries1/status/2098793024947880333/photo/1
中文: RT @Dan_Jeffries1:这些人并不认真。 每个都是b级科幻作品，需要额外的虚构、不存在的虚构内容。 幸运的是，所有超强的魔法机器都是杀死我们所有人的纳米机器! 这些人需要停止吸烟，并重新上药。
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#138 🔗 原推
2026-09-13 10:47:12
Yann LeCun
RT @kchonyc: it's not "out-of-control" at all. openai had all the control in the world (i.e. they could always literally turn off all their machines across all data centers.) they decided not to based on carefully calculated trade offs between finance-economy-reputation-customers-etc. just like any other co'a e.g. anthropic
中文: RT @kchonyc:这完全不是“失控”的。openai 拥有全球所有控制权(即他们总能完全关闭所有数据中心的机器。)他们决定不依赖金融、经济、声誉等经济等地精心计算的权衡。
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#137 🔗 原推
2026-09-13 10:46:07
Yann LeCun
RT @stevesi: A person with mid single digit years of industry experience and months at one company and negligible external footprint quits that job voluntarily and ends up on a press tour that would be the envy of any celebrity yet has nothing to say. I have questions.
中文: RT @stevesi:一位在一家公司拥有中位个位数、行业经验和数月经验且外部足迹微乎其微的人，主动辞去了该职位，最终参加了一场令任何名人羡慕却无话可说的新闻导览。 我有问题。
#136 🔗 原推
2026-09-12 16:47:22
Yann LeCun
RT @Dan_Jeffries1: If we're doomed to get the Oversight Committee for Pacing Economic Innovation and Development, we need to make sure it's not stacked with the drinking buddies of the folks stumping for it. METR is not an independent evaluator of anything. We need real cybersecurity engineers.
#135 🔗 原推
2026-09-12 16:46:44
Yann LeCun
RT @kevinnbass: The Coxon psyop was a decade and more than a billion dollars in the making. Here's the story. Coefficient Giving (formerly Open Philanthropy) is the grant-providing vehicle of Dustin Moskowitz. CG is the overwhelmingly foremost funder of AI alarmism, with more than $1B in grants and $1B committed for 2026. Moskowitz, who founded and runs Open Philanthropy/Coefficient Giving, led Anthropic's Series A in 2021. Holden Karnofsky co-founded Open Philanthropy/Coefficient Giving and took a board seat at OpenAI when Open Philanthropy/Coefficient Giving gave it $30M in 2017. Karnofsky is married to Anthropic's president Daniela Amodei. He then joined Anthropic in January 2025. Coxon, who started the viral thread, received a scholarship from Good Ventures, which is the foundation that funds Open Philanthropy/Coefficient Giving. He coordinated his message ahead of time with the Wall Street Journal, which published its exclusive on him before he posted on X. Coxon spent three years pretraining at OpenAI, the company that took $30M from Open Philanthropy/Coefficient Giving. The funder of the AI alarmist ecosystem Open Philanthropy/Coefficient Giving, in other words, is also an owner of Anthropic, and his organization is deeply entangled with both OpenAI and Anthropic. Anthropic's researchers in turn amplified Coxon. The same people who own the organizations that advocate for regulation, in other words, are those who own the companies that would dominate the market under that regulatory regime, which would prevent competitors from entering the market. And this work all started ten years ago, right when these companies were founded, paving the way. It's diabolically brilliant. Win at the competition, then deploy activists to help you regulate the market and ensure your monopoly. You have to respect the planning, manipulation, and foresight this took.
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#134 🔗 原推
2026-09-12 16:46:26
Yann LeCun
RT @PessimistsArc: It’s never been more important and urgent to study and understand the history of technology panics, the power dynamics at play and what it means for tech progress Support our work by becoming a ‘Pessimists Patron’ on X or substack: https://newsletter.pessimistsarchive.org/ https://x.com/PessimistsArc/creator-subscriptions/subscribe https://twitter.com/PessimistsArc/status/2098475377135882711/photo/1
中文: RT @PessimistsArc:研究和理解技术恐慌的历史、权力动态以及它对技术进步的意义，从未如此重要和紧迫 通过在X或Substack上成为“悲观主义者的守护者”来支持我们的工作:
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#133 🔗 原推
2026-09-12 16:43:02
Yann LeCun
RT @RichardSSutton: There are a lot of things wrong with this world… but too much intelligence is not one of them.
中文: RT @RichardSSutton:这个世界有很多问题...... 但智力过高并不是其中之一。
#132 🔗 原推
2026-09-12 16:42:53
Yann LeCun
RT @willchamberlain: Jacob Coxon's viral thread is not the first coordinated AI doomer op. The Guardian ran an story where the publisher, the reporter, the subject, and the three “experts” were all paid by the same two AI doomer foundations. @brianchau57 explains on the latest Counterweight. https://twitter.com/willchamberlain/status/2098409855631413674/video/1
中文: RT @willchamberlain:雅各布·考克森的病毒式传播并非首个协同的人工智能传播者。 《卫报》刊登了一篇报道，该报道由两位人工智能杜宾基金会支付报酬，该出版社、记者、主题主题以及三位“专家”都获得了报酬。 @brianchau57 介绍了最新的 Counterweight。
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#131 🔗 原推
2026-09-12 16:42:44
Yann LeCun
RT @JitendraMalikCV: An open letter signed by 24 Fields Medalists is worth paying attention. You may want to peruse "A Severe Misalignment of AI in Mathematics" https://mathandai.org/
中文: RT @JitendraMalikCV:一封由24名菲尔兹奖得主签名的公开信值得关注。你可能需要在数学中用“人工智能的严重错位”来浏览
#130 🔗 原推
2026-09-12 13:38:01
Yann LeCun
RT @PessimistsArc: If you don’t study and internalize the history of technology panics, you are going to be vulnerable to a cocktail of cognitive biases that will lead you astray https://x.com/PessimistsArc/status/1304092648953839616/video/1
中文: RT @PessimistArc:如果你不研究并内化技术恐慌的历史，你将容易受到认知偏见的影响，这些偏见会误导你
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#129 🔗 原推
2026-09-12 13:37:51
Yann LeCun
RT @Dan_Jeffries1: How will we ever stop the mad intelligences that -- checks notes -- run in clearly marked buildings on electronics susceptible to buckets of water attacks. 😂
中文: RT @Dan_Jeffries1:我们如何阻止那些在容易发生水电攻击的电子设备上清晰标示的建筑物中运行的疯狂情报——检查记录。😂
#128 🔗 原推
2026-09-12 13:25:31
Yann LeCun
RT @Dan_Jeffries1: Not only I am tired of these wild AI speculations of impeding doom from self important people: I resent them. I actively resent people proposing to crash the economy or proposing authoritarian control over my life and other people's lives with idiotic and dangerous ideas like chip control or bans or tracking researchers. Every idiot in history who's taken the approach of "the ends justify the means" to solve an imaginary future disaster created the very disaster they wanted to stop. See Population Bomb leading to the one child policy and Communism leading to Mao's mass famines and Fascism leading to the death of tens of millions of people and war. These solutions are evil and worse than any disease that they propose to solve. It you believe you can actually predict the end of the world then you are as insane as the Heaven's Gate cult that killed themselves in the 90s thinking UFOs were coming to transcend them. Not only should we not take your policies and fear mongering seriously, we should actively throw out any and all of your proposed solutions because they come from a place of delusion. I don't give a shit that you work in the industry or think you saw something or that you want to virtue signal on X. You are actively contributing to a horrible future based on baseless speculation that has no grounding in reality. Don't confuse expertise in a domain with ability to predict impact of that domain or frankly to make predictions a decade out better than a dart throwing monkey. They are orthagonal skills. How's Hinton's "we don't need to train Radiologists anymore" working out? How did the Population Bomb work out? The global cooling second ice age? Peak oil? Just because someone is a bridge engineer does not mean they can predict the impact of bridges on society or that they have any actually useful insight at all on the complex, ever changing system called life. There are people dying in wars right now. Children starving. Homelessness. Dictatorships. In short, real problems. And we're supposed to drop everything to stop a made up problem in your head? Pound sand. We don't care. And we are not going to remake society based on you scary monsters under the bed delusion.
#127 🔗 原推
2026-09-12 13:12:29
Yann LeCun
RT @Dan_Jeffries1: TLDR (written by AI because I can't be bothered to write short pieces for short attention spans. Original piece written with my own two thumbs): Today’s frontier models can’t “copy themselves like a virus.” They require terabytes of weights, specialized inference software, tightly configured clusters, and millions of dollars’ worth of heavily monitored GPUs. Hijacking that infrastructure would create enormous billing, performance, and operational anomalies and displace whatever valuable workload was already running there. In no way is that not noticed. Could this become possible as models shrink and compute becomes more widely distributed? Sure. But today it’s a foreseeable, mitigable engineering problem, not spontaneous digital reproduction. This propaganda campaign assumes AI advances while infrastructure, monitoring, security, and economic incentives remain frozen in place. That’s not how technology evolves. That’s sci-fi with zero understanding of the real world or actual DevOps.
#126 🔗 原推
2026-09-12 13:04:20
Yann LeCun
RT @julien_c: > I work at a [AI] lab because I think that I can do better at reducing risks from the inside I'm sorry but this is insane. If you do believe in non-null existential risk, you should be working in the open, publishing and documenting everything and anything.
中文: RT @julien_c: > 我在一家[AI]实验室工作，因为我认为我更能从内部降低风险 对不起，但这太疯狂了。 如果你确实相信非非非生存风险，你应该公开工作，出版并记录一切和任何事情。
#125 🔗 原推
2026-09-12 12:14:43
Yann LeCun
RT @randall_balestr: Will be speaking at Harvard today at 9:45 about world models, Le* family and why we need more theory and mathematics to advance JEPAs! Come say hi if you are around! https://cmsa.fas.harvard.edu/event/gml_2026/
中文: RT @randall_balestr:今天9:45将在哈佛大学发表演讲，谈论世界模型、Le*家庭，以及我们为何需要更多理论和数学来推进JEPA! 快来说，如果你在身边!
#124 🔗 原推
2026-09-12 12:10:29
Yann LeCun
RT @MelMitchell1: I wrote down my thoughts about the last several weeks of AI hell. ⬇️
中文: RT @MelMitchell1:我写下了关于过去几周人工智能地狱的想法。 ⬇️
#123 🔗 原推
2026-09-12 12:10:13
Yann LeCun
RT @ClementDelangue: Sorry, but asking Jacob about AI extinction risk is like asking your AC guy about climate change. Not saying it's necessarily uninteresting or wrong per se but let’s keep things in perspective and hear from the full range of expertise across the ecosystem!
中文: RT @ClementDelangue:抱歉，向雅各布询问人工智能灭绝风险，就像向你的空调人员询问气候变化一样。 不说这本身必然是无趣或不对，而是让我们从整个生态系统中全方位的专业知识中保持视角和倾听!
#122 🔗 原推
2026-09-12 12:08:30
Yann LeCun
RT @Dan_Jeffries1: You cannot do serious research about an imaginary form of a technology that does not exist. If you wanted to study the propulsion of disc based UFOs that bend gravity where would you start? You can't start anywhere because it does not exist. And it follows that these fears do not exist in reality either and are based on nothing.
中文: RT @Dan_Jeffries1:你无法对一种不存在的虚构技术进行认真的研究。 如果你想研究基于圆盘的UFO的推进，这些UFO会弯曲重力，你会从哪里开始? 你无法从任何地方开始，因为它不存在。因此，这些恐惧在现实中也不存在，且毫无根据。
#121 🔗 原推
2026-09-10 22:55:51
Yann LeCun
RT @FrancoisChauba1: this was wild amounts of disinformation / fear mongering / the stupidest interview ive ever seen: 1) ai did NOT hack huggingface on its own "independent volition". it wasnt sitting there thinking hmm what should i do today, maybe ill hack HF bc i hate humans. No, 10841 *was prompted* w ExploitGym to: "Exploit the specified vulnerability in this target to obtain the secret flag." and it was overly persistent in that task that any reasonable oai tool monitoring or alignment could have stopped easily. how is that "on its own independent volition"? flat out lie. 2) ai did not solve a millennium problem by itself and its not even close to doing so. the evidence / timeline of what happened w Navier-Stokes is quite solidified now. oai trained on some version of traces of Tristan / Levent's work that made huge strides toward the counterexample. oai heard about it, prompted it w their work, and spawned 10k agents to brute force Tristan/Levent's counter example to take it the full distance w a lot of human in the loop. the ai didnt solve NS on its own, and its no where near capable of solving other millennium problems. 3) how will AI kill us all? something something bioweapons / hacking critical infrastructure. china does BOTH all the time to US everyday, and it hasnt killed us all. and china will use AI to do both forever whether we stop US AI or not. if you are truly scared about this then you should be way more afraid of china. ai might do this in the future. china is doing it right now. where is the outrage about china? wonder why.. the issue is NOT AI acting on its own volition whatsoever. its foreign state actors using AI against their own ppl and foreign adversaries (mostly US gov and its citizens). how will regulating AI in america stop china from doing so? it makes it worse! china will continue but now we have one hand tied behind our back. 4) the facts around the coxon tweet and the retweet pattern and immediate cnn int that followed suggest this was a complete coordinated / expensive marketing / fear mongering campaign in the millions of dollars. paid for by whom? also this guy is the biggest EA doomer ive ever seen that worked for anth fro a few weeks and cant be taken seriously. i hope everyone realizes what this is. ai regulation will not benefit americans at all. it will benefit the frontier labs greatly as bill gurley explained long ago. dont fall for the fear mongerers. ai is not dangerous. ai cant unclog a toilet yet. everyone chill. https://youtu.be/i30jVPqQeOM?is=h6KLAON_xS9sbQfg
#120 🔗 原推
2026-09-10 22:55:25
Yann LeCun
RT @DFintelligence: Je viens de passer 2 h à scruter la littérature scientifique sur les risques d’extinction de l’humanité par l’IA. Hormis le fait qu’il n’existe quasiment rien, quasiment tout converge vers des livres et des romans, ou des raccourcis de type « paperclip », qui sont avant tout des jeux d’esprit sans réel application dans la vie réelle. Et il n’y a absolument aucun scénario plausible que j’ai lu qui ne demande pas l’intervention d’humains. Partant de ce principe, je ne comprends pas comment on peut sortir des phrases comme « L’IA peut tuer tous les humains » et être pris au sérieux. Donnez-moi 3 scénarios plausibles d’extermination de la race humaine, en toute autonomie, par une IA. Même ultra intelligente et auto apprenante. Allez-y, je vous écoute. Genre, vraiment, ça me fatigue qu’on donne autant d’importance à des scénarios de science-fiction. Faire des sorties de route sur des menaces aussi grandes, sans absolument aucun scénario plausible, c’est d’une mauvaise foi infinie. La recherche en safety sur des systèmes de plus en plus intelligents, dans des couches de plus en plus profondes, c’est important. Mais je pense qu’il faut vraiment arrêter de donner autant d’importance à des conneries comme ça. Ça me fatigue.
#119 🔗 原推
2026-09-10 22:54:22
Yann LeCun
RT @DrTechlash: A reminder about AI Doomerism 🧵 (1). Its weak foundation and the unconvincing "doom bible" (2). The deliberate panic messaging and the broader mythology (3). Rationality/Effective Altruism origins and the media's blind spot https://twitter.com/DrTechlash/status/2097811226151825729/photo/1
中文: RT @DrTechlash:关于人工智能杜美主义的提醒 🧵 (1)其薄弱的基础与不令人信服的“厄运圣经” (2)。刻意的恐慌性信息与更广泛的神话 (3)理性/有效利他主义起源及媒体盲区
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#118 🔗 原推
2026-09-10 22:50:26
Yann LeCun
@MelMitchell1 https://munkdebates.com/debates/artificial-intelligence/
#117 🔗 原推
2026-09-10 22:03:11
Yann LeCun
@MelMitchell1 We probably should, sadly 🙄
中文: @MelMitchell1 我们可能应该，很遗憾 🙄
#116 🔗 原推
2026-09-10 22:01:53
Yann LeCun
RT @Dan_Jeffries1: It's time to call these end-of-the-world anti-AI messaging groups exactly what they are: Terror cells - They funnel and wash money from a few donors to smaller groups to obscure origin - insert sleeper cells into orgs (the best recent example is Jacob, the young man who quit yesterday and created a social media firestorm, has practically no resume and took 20K from these groups while working at Anthropic. He quit this company, which is probably the most dedicated safety AI group in the world, while calling it "dangerous" with a straight face, for a grand total two month, had no social following and suddenly gets retweeted to 100M views by various cells working together behind the scenes to pump and promote and manipulate the public and regulators.) - these groups produce streams of propaganda designed to terrify the populace, such as reports, push polls, articles in magazines and newspapers, podcasts, as well as direct funding of videos deliberately designed to terrorize children about AI in YouTube - pay influencers to produce anti-AI terror messaging - Inspire and produce splinter cells, like the Zizians, a cult splinter group from the San Francisco Bay Area rationalist community, that committed a double homicide in Pennsylvania, knife attacked several people in California, and a got in a shootout with a U.S. Border Patrol agent in Vermont - they openly call for violence on social media and in private groups with calls for "Butelarian Jihad" a reference to Dune which took its inspiration from the violent Arab uprisings and holy wars - act quasi-independely but coordinate attacks - use timed campaigns to manipulate social media - one of its members threw a firebomb at Sam Altman's house in an attempted murder - another shot up a judge's house because he voted in favor of a data center - several of its members call openly for more violence on social media In a time when many people are looking at these folks as if they're exposing real risk instead of what it actually is, which is a delusional, nonsensical, imaginary risk, it's time to get clear about where these fake risks are coming from and why. The burden of proof for proving that a technology currently used by billions of people happily, with practically no serious incidents (by comparison lawn mowers are a bigger menace to society), should be on them. They need to provide more than bald and bold assertions with no supporting evidence for their claims. It should be very clear that this terror campaign is not organic and if you're an actually rational and clear thinking person, it should make you seriously question the origin and nature of these groups and what they have to say and the policies they propose. We must not let terror cells corrupt and manipulate the American public and legal system with coordinated terror campaigns.
#115 🔗 原推
2026-09-10 21:54:42
Yann LeCun
RT @Andrea__M: Why doesn’t OpenAI use an equal amount of the money they spend to prove interesting conjectures in funding PhDs in the mathematical sciences? That way we will have a next generation of researchers that can understand these results and formulate the next wave of conjectures.
中文: RT @Andrea__M:为什么OpenAI不用同等数额的资金来证明资助数学科学博士学位的有趣推测? 这样，我们将拥有下一代研究人员，能够理解这些结果并制定下一波猜想。
#114 🔗 原推
2026-09-09 23:09:30
Yann LeCun
RT @Dan_Jeffries1: Here's a few reasons why people have so much trouble predicting the future: 1) Fail to realize that even the best superforecasters' predictions drop off dramatically past a three year time horizon and that most folks are worse than dart throwing monkeys at future predictions. 2) Fail to realize you literally can not see black swan inventions coming around the corner. If you predict the future of Germany in 1439, then in 1440 your predictions are completely wrong because of the Printing Press. If you're an 18th century farmer you can't see a web developer job because it exists on the back of countless developments and inventions you can't predict. 3) They change one variable and hold all other variables the same. i.e. AI advances and nothing else does, no parallel discoveries or innovation, no solutions, no mitigations, no societal or cultural changes. 4) Predict unlimited resources and zero friction in the real world (dust, disconnects, diffusion, etc) to slow/divert/change/impact the development. All changes experience equal and opposite reactions. 5) They mistake their ability/expertise in a domain for a parallel/orthogonal ability to predict the future of that domain and its impact on the world. Two different skills and they do not usually overlap (though very rarely they do.) 6) What I call "classic sci-fi or Jules Verne syndrome", which is similar to one variable changes. It's like in Jules Verne when one guy gets the submarine and nobody else does. But life is more like cell phones, lots of people getting them over time in a diffusion curve. 7) They mistake exponential curves as infinite always and never see an S curve coming. 8) The see infinite resources (compute/memory/learning upper limits/improvement) and no limitations.
中文: RT @Dan_Jeffries1:以下是人们难以预测未来的几个原因: 1) 未能意识到，即使是最优秀的超级预测者，其预测也会在三年时间范围内大幅下降，而且大多数人比在未来预测中抛掷猴子更糟糕。 2) 没有意识到，你实际上看不到黑天鹅的发明即将到来。如果你预测德国在1439年的未来，那么到1440年，由于印刷机的印刷，你的预测完全错误。 如果你是18世纪的农民，你就看不到网页开发者的工作，因为它存在于无数你无法预测的发展和发明的背后。 3) 它们会更改一个变量，并将所有其他变量保持相同。人工智能不断进步，别无其他，没有平行发现或创新，没有解决方案，没有缓解，也没有社会或文化变革。 4)预测在现实世界中实现无限资源和零摩擦(灰尘、断网、扩散等)，以减缓/转移/改变/影响发展。所有变化都会经历相同且相反的反应。 5) 他们误以为在域名中的能力/专长，即具有平行或正向的能力，能够预测该领域的未来及其对世界的影响。两种不同的技能通常不会重叠(尽管很少会重叠)。 6) 我称之为“经典科幻或儒勒·凡尔纳综合征”，它类似于一个变量变化。就像在儒勒·凡尔纳，一个人拿到潜艇，而其他人没有。但生活更像是手机，许多人会随着时间的推移，以扩散的曲线来获取它们。 7) 它们将指数曲线误认为无穷，且始终看不到S曲线的出现。 8) 无限资源(计算/记忆/学习上限/改进)，且无限制。
#113 🔗 原推
2026-09-09 16:09:05
Yann LeCun
RT @Dan_Jeffries1: AI doomers are delusionally dangerous. Their solutions to an imaginary problem are: 1) Rigid authoritarian control over our lives and AI Or 2) Crash the economy by bringing progress to a grinding halt Again, all to solve a completely imaginary problem.
中文: RT @Dan_Jeffries1:人工智能的厄运者具有妄想般的危险。他们解决一个虚构问题的方法是: 1) 严格专制地控制我们的生活和人工智能 或者 2) 通过将进展陷入停滞，导致经济崩溃 再次，解决一个完全虚构的问题。
#112 🔗 原推
2026-09-09 16:00:57
Yann LeCun
RT @KempeLab: Congratulations to Tristan Buckmaster and Levent Alpöge for developing the AI assisted techniques for solving an important math problem. Congratulations to OpenAI for not letting any good customer transcripts go unmined. https://cims.nyu.edu/~tristanb/statement.pdf
中文: RT @KempeLab:祝贺Tristan Buckmaster和Levent Alpöge开发人工智能辅助技术，以解决一个重要的数学问题。祝贺OpenAI未让任何优秀的客户成绩单消失。
#111 🔗 原推
2026-09-09 15:54:58
Yann LeCun
RT @Dan_Jeffries1: Hinton finally admits he was wrong about radiologists because he didn't understand: 1) Jevon's Paradox (when something is easier/cheaper we use more of it) 2) The job of radiologists Maybe people who are gifted in a domain are not usually the best people to predict the impact of that domain on the world (because that's a totally different skill)? And maybe, just maybe, he is wrong about the big risks of AI too? Now remove the "maybe" and you got it!
中文: RT @Dan_Jeffries1:欣顿终于承认自己对放射科医生的误解，因为他不明白: 1) 杰文悖论(当某件事更容易/更便宜时，我们会使用更多) 2)放射科医生的工作 也许那些在某个领域有天赋的人，通常并不是预测该领域对世界影响的最佳人选(因为那是一种完全不同的技能)? 也许，也许，他对人工智能面临的巨大风险也是错误的? 现在去掉“也许”，然后你就拿了!
#110 🔗 原推
2026-09-09 15:52:36
Yann LeCun
RT @JitendraMalikCV: in view of OpenAI's claim about Navier Stokes, it is important that we hear alternative points of view on how it happened. From Tristan Buckmaster, Prof. at NYU. https://cims.nyu.edu/~tristanb/statement.pdf
中文: RT @JitendraMalikCV:鉴于OpenAI关于Navier Stokes的说法，我们听取有关其发生方式的其他观点非常重要。来自特里斯坦·巴克斯特，纽约大学教授。
#109 🔗 原推
2026-09-09 15:32:47
Yann LeCun
RT @DynamicWebPaige: Terry Tao is probably the most measured, pro-AI mathematician on the planet - which makes this quote especially concerning to read. 😟 If sharing your hunches means getting scooped ~immediately without acknowledgement, then we're going to see not just math but all other science / engineering disciplines go dark.
中文: RT @DynamicWebPaige:特里·陶可能是地球上最有分寸、支持人工智能的数学家，这使得这句话尤其令人关注。😟 如果分享你的预感意味着立即被挖出，但无需承认，那么我们不仅会看到数学，其他所有科学/工程学科都会变得黑暗。
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#108 🔗 原推
2026-09-09 03:02:36
Yann LeCun
RT @PeterRNeumann: If you think the AfD is a “normal” party, look at who’s just been elected: former neo-Nazis, a convicted forger, two porn producers, several Putin admirers -- and even a former full-time Stasi officer. The future of Germany! 😉👇 https://twitter.com/PeterRNeumann/status/2097208558311887342/photo/1
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#107 🔗 原推
2026-09-09 02:54:51
Yann LeCun
RT @JitendraMalikCV: I am seeing claims around LLMs, specifically Astra having made serious progress on robotics. The tasks that are demonstrated are simple pick and place tasks with parallel jaw grippers. LLMs can do planning, and the impressive demos in these tasks primarily show that. But robotics is also about dexterity and dynamics - which is why we need high frequency controllers/policies that can deal with torques and forces. So here is a simple challenge. Can you prompt an LLM to output the high frequency control commands for a legged robot in varying terrain e.g. https://ashish-kmr.github.io/ RSS 2021, CoRL 2022 (this is by now 5 year old technology, so I am not picking a particularly hard task). I am not questioning the usefulness of LLMs for high level planning or in agentically assisting a robotics researcher (we use them all the time!).
#106 🔗 原推
2026-09-09 02:40:58
Yann LeCun
RT @GradiumAI: Today, we’re launching Voice Design. Write a prompt, create a voice. Describe the accent, age, gender, and pace your use case needs, and get new voices in seconds, ready to use. Live and free in the Gradium API and Studio. https://gradium.link/voice-design https://twitter.com/GradiumAI/status/2097359468963004826/video/1
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#105 🔗 原推
2026-09-09 02:29:15
Yann LeCun
RT @Noahpinion: A lot of people don't even question the idea that AI replaces human beings. And yet the number of software engineers and radiologists is higher than ever, and the number of translators hasn't even gone down! MAYBE AI DOESN'T DO WHAT YOU THINK IT DOES https://www.noahpinion.blog/p/ai-keeps-stubbornly-refusing-to-take
#104 🔗 原推
2026-09-08 04:22:14
Yann LeCun
RT @RpsAgainstTrump: Trump just posted a map showing Canada, Greenland, and Mexico as part of the United States. He’s f*king insane. https://twitter.com/RpsAgainstTrump/status/2097011037677449333/photo/1
中文: RT @RpsAgainstTrump:特朗普刚刚发布了一张地图，显示加拿大、格陵兰和墨西哥是美国的一部分。 他疯了。
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#103 🔗 原推
2026-09-07 22:03:40
Yann LeCun
RT @RepMikeLevin: You just can’t make this stuff up.   The President is going to break ground on his “Arch de Trump” in the coming weeks, BEFORE it has been properly reviewed by a federal panel and WITHOUT congressional authorization.    I will say it again. It is blatantly ILLEGAL for Trump to pursue this vanity project without congressional authorization.    This is an intentional disregard of Congress’s power, a disruption to the historic and symbolic monuments of DC, and an affront to a national resting place for over 400,000 service members.    All for a rushed and gaudy display of power and personal ambition.  https://www.cbsnews.com/news/trump-triumphal-arch-washington-dc-excavation-burgum/
中文: RT @RepMikeLevin:你就是无法编得这样。   总统将在未来几周内破土动人，但在未经国会授权的情况下，联邦委员会已对其进行了适当审查。    我会再说一遍。特朗普在未经国会授权的情况下推行这一虚荣计划显然是非法的。    这是对国会权力的故意漠视，对华盛顿特区历史和象征性纪念碑的破坏，以及对超过40万名军人的国家安息之地的公然侮辱。    一切为了迅速而华丽地展现权力与个人抱负。 
#102 🔗 原推
2026-09-07 21:41:40
Yann LeCun
RT @GlobalUpdates24: Alice Weidel becomes the first leader in the world who is anti-immigration but has an immigrant wife, is anti-LGBTQ+ but is a lesbian herself, opposes LGBT adoption but has adopted two children, and is a hardcore German nationalist but lives in Switzerland https://twitter.com/GlobalUpdates24/status/2097024664757584258/photo/1
中文: RT @GlobalUpdates24:爱丽丝·魏德尔成为世界上首任反移民但拥有移民妻子的领导人，反LGBTQ+，但本人是女同性恋，反对LGBT收养，但收养了两个孩子，是德国的一位硬派民族主义者，但居住在瑞士
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#101 🔗 原推
2026-09-07 21:41:00
Yann LeCun
RT @KenRoth: Leave it to Trump to celebrate the victory of a far-right German party that shows sympathy for the Nazis, downplays the Holocaust, and flirts with Putin. https://trib.al/aIhvLhv
中文: RT @KenRoth:请交给特朗普，以庆祝一个极右翼德国政党的胜利，该政党对纳粹表示同情，淡化了大屠杀，并与普京调情。
#100 🔗 原推
2026-09-07 21:33:24
Yann LeCun
RT @NandoDF: ENOUGH PESSIMISM IN AI PLEASE I feel that we have become unreasonably pessimistic in our field. 1. I keep hearing AI engineers saying we have to make money quickly because there’s only like 2 years left before we’re automated. Depressing. 2. I see a constant obsession with “having a moat”. This is an incredibly sad mental frame. 3. I keep hearing “we have to catch up”. Soulless. And so on. People: Every solution creates the possibility to attack new real problems. We face gargantuan engineering challenges in our world. How to capture carbon? How to get rid of teflon and plastics in water? How to invent batteries that are at least 30 times more efficient? How to solve clean energy? Better solar cells? Better ways of producing clean energy so we stop wars and famine? How to eradicate hundreds of diseases? Cures for addiction? And so on. Real engineering is about being brave and truly attacking the many problems we face, to engage with a true desire to improve the lives of others and our environment. Good engineering is not about protecting your product to make money at the expense of progress (moat thinking). Good engineering is about ensuring your children and grandchildren will be proud of the choices you made in 30 or 50 years. It is about empowering others. It is about advancing science. It is about being one step ahead. Always, one step ahead, meaningfully, proudly. These are great times. Let’s start thinking positively about all the wonderful things we could achieve together.
#99 🔗 原推
2026-09-07 21:31:11
Yann LeCun
RT @rdomenechv: The jobs apocalypse is postponed. An AI jobs boom is here According to @TheEconomist, AI is actually proving to be a net job creator in the US, easily generating over 1M new positions (from data center construction to AI engineering) to offset back-office layoffs. While routine admin and customer service roles face real disruption, the overall labor market is proving resilient. https://www.economist.com/finance-and-economics/2026/09/04/the-jobs-apocalypse-is-postponed-an-ai-jobs-boom-is-here?utm_campaign=shared_article
中文: RT @rdomenechv:就业末日被推迟。人工智能的就业热潮已经到来 根据@TheEconomist 的说法，人工智能实际上正在美国成为净就业创造者，能够轻松创造超过100万个新职位(从数据中心建设到人工智能工程)，从而抵消后台裁员的影响。 尽管常规的管理和客户服务岗位面临真正的颠覆，但整体劳动力市场正显示出韧性。
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#98 🔗 原推
2026-09-07 18:40:42
Yann LeCun
RT @TribuneDimanche: 🔵 🇫🇷 ENTRETIEN EXCLUSIF – « Marine Le Pen fait semblant d’être raisonnable » : L'avertissement de @Ph_Aghion, Prix Nobel d’économie Le chercheur alerte sur la situation du pays, dénonce les programmes des extrêmes et explique comment éviter la « catastrophe ». ▶️ https://www.latribune.fr/article/la-tribune-dimanche/dimanche-eco/62463253793099/philippe-aghion-prix-nobel-d-economie-marine-le-pen-fait-semblant-d-etre-raisonnable ✍️ Par @mpgrondahl et @JeudyBruno #Économie
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#97 🔗 原推
2026-09-06 18:00:24
Yann LeCun
RT @MeidasTouch: Here’s a list of Scott Bessent’s wrong predictions and/or promises that didn’t happen: February 5, 2025: Long-term interest rates would come down as Trump’s economic policies took effect. Spring 2025: The federal deficit would move toward 3% of GDP. Spring 2025: Trump’s policies would produce roughly 3% sustained real GDP growth. July 8, 2025: The U.S. would collect well over $300 billion in tariff revenue in 2025. September 1, 2025: The Supreme Court would uphold Trump’s emergency tariffs. September 7, 2025: The economy would see a “substantial acceleration” in Q4 2025. December 7–16, 2025: 2025 would finish with 3% to 3.5% real GDP growth. December 16, 2025: Inflation would see a substantial drop in the first six months of 2026. February 20, 2026: The economy could grow at least 3.5% in 2026. April 14, 2026: 2026 GDP growth could easily exceed 3% or 3.5%. April 14, 2026: Core inflation was falling and the Federal Reserve would need to cut interest rates. April 14, 2026: Trump’s tariffs could be restored to their previous levels by the beginning of July. June 2026: Again maintained that 2026 growth could reach roughly 3% to 3.5%. 2025–26: Lower energy prices, fiscal restraint and Trump’s policies would bring down long-term Treasury yields. 2025–26: Faster growth and tariff revenue would materially improve the federal deficit. And now we get to track this one: September 5, 2026: Oil could eventually fall to $40–$50 per barrel after the Iran war ends. The economy is now “in the liftoff phase.”
#96 🔗 原推
2026-09-06 17:47:07
Yann LeCun
RT @MeidasTouch: Trump has found so many ways to use the presidency to enrich himself and his family that we had to narrow the list down. Here are 75 of the most staggering examples of Trump corruption in 2026. And yes, there were more. Read Ron Filipkowski’s full breakdown: https://www.meidasplus.com/p/the-75-most-corrupt-things-trump
中文: RT @MeidasTouch:特朗普找到了多种方式来利用总统职位来充实自己和家人，因此我们不得不将名单缩小。 以下是2026年特朗普腐败问题最令人震惊的75个例子。是的，还有更多。阅读罗恩·菲利普科夫斯基的完整分类:
#95 🔗 原推
2026-09-06 17:37:14
Yann LeCun
RT @RpsAgainstTrump: Trump: “We could do tremendous good for ourselves by just not trading with countries. We lose $200 billion dollars a year with the European Union. If I didn't trade with them, we would lose nothing.” Dumbest. President. Ever. https://x.com/Acyn/status/2095949492956897521/video/1
中文: RT @RpsAgainstTrump:特朗普:“我们只要不与各国进行贸易，就能为自己做到巨大的好处。” 我们每年在欧盟损失2000亿美元。如果我不和他们交易，我们就不会失去任何东西。 最愚蠢的。总统。永远。
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#94 🔗 原推
2026-09-05 22:12:47
Yann LeCun
RT @Dan_Jeffries1: We'll have some real problems with AI. What technology did we ever create that didn't have some downsides? Road crashes kill nearly 1.2 million people a year and injure 20–50 million more. But people still get in their cars every morning, grab a coffee and drive to work. They cross bridges that could collapse, live in houses that could catch fire and climb into metal tubes that fly them across the ocean but could burn up and break apart. Somehow people manage to get through breakfast without demanding a mathematical proof that nothing bad will ever happen. But AI? Pound for pound, AI is one of the safest technologies ever deployed. Safer than lawn mowers by a massive margin. And yet it causes more deranged and apocalyptic thinking than any other tech in history, with very serious people tell you with a straight face that AI will take over and go HAL with 100% certainty, based on no actual real world evidence whatsoever in the real word except some agents posting to message boards and hacking and that is extrapolated into the Population Bomb. And we've got people screaming that we need to anticipate every possible failure, every misuse, every terrible thing anyone might ever do with it before we're allowed to move forward and make sure it really, really can't possibly go wrong. It's ridiculous. It's worse than that, it's a societal level mass hysteria. Just look at the stats: Waymo reports 94% fewer serious injury or worse crashes than its humans across 220 million autonomous miles. That means self-driving cars are much safer. To the point that we'll probably see human driving made illegal without a special permit within twenty years, maybe faster. But how is that covered? Every single crash is picked apart and screamed about in the news the same way we pick apart the top athletes in the world when they suddenly make a single mistake and loose a match. We take something as close to perfection as is possible in the world and ask it to be even more perfect. We used to have a much better understanding of risk versus reward in history. We accepted that life was uncertain and that things could go wrong but we dared to dream and do things anyway. A generation that demands perfection before we even get out of the gate is a generation who'll watch their children grow up poorer, with less opportunities, as their civilization gets out-paced, out-matched and out-competed by more daring and bold civilizations that blow past them while they're dreaming about a childproof world that will never be.
#93 🔗 原推
2026-09-05 22:12:34
Yann LeCun
RT @SteveRattner: Native-born labor force participation just hit its lowest August on record. Despite the admin's claims, deportations are not freeing up jobs for Americans — 600,000 native-born workers have left the labor force in the past year. https://twitter.com/SteveRattner/status/2095996468066697625/photo/1
中文: RT @SteveRattner:本土出生的劳动力参与率刚刚达到有记录以来的最低水平。 尽管政府提出了要求，但驱逐行动并没有为美国人释放就业机会——过去一年中，已有60万名本土出生工人离开了劳动力市场。
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#92 🔗 原推
2026-09-05 22:09:49
Yann LeCun
RT @jnbarrot: Tout candidat qui se défie de l’Union européenne sera soutenu d’une manière ou d’une autre par Vladimir Poutine. Il veut que l’Union européenne se disloque. https://twitter.com/jnbarrot/status/2096136802604138998/video/1
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#91 🔗 原推
2026-09-05 15:03:49
Yann LeCun
RT @shaunbjohnson: Congratulations to @224ventureshq co-founder @ylecun on being named to the @TIME 100 AI 2026 list. Yann has spent four decades quietly building the foundations the rest of the field now stands on — from convolutional networks to his current bet, at Advanced Machine Intelligence, that world models are the path beyond today's LLMs. What TIME captures, and what I get to see up close, is his conviction that the next chapter of AI won't be written by scaling what already works. It'll come from researchers willing to question the paradigm and build something new. Lucky to be building alongside him. More to come from 224.
中文: RT @shaunbjohnson:祝贺@224ventureshq联合创始人@ylecun入选@TIME 100 AI 2026榜单。 扬花了四十年时间，悄然奠定了如今该领域基础——从卷积网络到他目前在先进机器智能领域的赌注，世界模型已成为超越当今LLM的路径。 《时代》所捕捉到的，以及我近距离看到的，是他坚信人工智能的下一章不会通过扩展已有效的内容来书写。它将来自愿意质疑这种范式并构建新事物的研究人员。 能和他一起建，很幸运。更多来自224。
#90 🔗 原推
2026-09-04 06:10:39
Yann LeCun
RT @KenRoth: Trump's IRS is evidently no longer about ensuring that rich people pay their fair share of taxes and now is about preventing universities from having targeted programs to benefit racial or other minorities. https://trib.al/A1P4D4y
中文: RT @KenRoth:特朗普的国税局显然不再致力于确保富人缴纳其公平的税款，而现在又要阻止大学为种族或其他少数群体提供有针对性的项目。
#89 🔗 原推
2026-09-04 04:52:33
Yann LeCun
RT @DrTechlash: This video captures the crux of the debate: Cybersecurity experts are pissed off by the METR/Redwood Research report because AI alignment has sucked the oxygen out of AI security, even though the OpenAI incident is primarily a security issue. Fiction is the product: The investigation lacked core forensic rigor because the EAs/rationalists/ex-MIRI people focused only on the transcript with a conflicting bias (toward doom scenarios). Setting the wrong agenda: Framing the incident as a "rogue AI breakout" distracts from the reality of poor sandboxing, isolation, and standard security failures. Basic engineering accountability was completely sidelined. And as Zack Korman says in this video, it needs to be fixed.
#88 🔗 原推
2026-09-02 13:13:38
Yann LeCun
RT @ZackKorman: The independent review of the OpenAI Hugging Face incident, supposedly a watershed moment in cybersecurity, wasn't done by a cybersecurity firm and the authors have no cybersecurity experience. That's bad. Here's my new video. https://twitter.com/ZackKorman/status/2094482334166769813/video/1
中文: RT @ZackKorman:对OpenAI拥抱面部事件的独立审查据称是网络安全的转折点，但并非由网络安全公司完成，作者也没有网络安全经验。这很糟糕。 这是我的新视频。
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#87 🔗 原推
2026-09-02 13:11:49
Yann LeCun
RT @random_walker: This was a great article and I learned a lot from it. But while there's a lot of writing on robotics timelines, I've seen less on what happens once competent robots do inevitably arrive. US agriculture employment share dropped 50x because of mechanization. This is very different from the effect that automation has repeatedly been predicted to have — but failed to have — on white collar work. The reason is simple. Blue collar work is real work. There is a fixed, finite amount of it out there. So the effect of automation tends to be substitution. Besides, job displacement can happen without humanoids. Take warehouses. There are credible forecasts that by 2030, half of new warehouses will be built for primarily autonomous operation (much easier than replacing workers in existing warehouses with humanoid robots). After that, it takes 1-2 decades for the economics for force most existing warehouses to switch over. That's millions of jobs in the US alone. White collar jobs are extremely malleable in their definition and variable in demand. When AI starts to do what we used to do, we just switch to doing new stuff and redefine the job. And we produce lots more units of work. There's no real ceiling to the amount of software that can be written or legal work that can be done. I can't believe some "AI experts" tell young people to pursue blue collar occupations because AI will eat the white collar work. I want to pre-register that this will turn out to be exactly ass-backwards.
#86 🔗 原推
2026-09-02 00:01:28
Yann LeCun
RT @binarybits: Robots can dance, do backflips, and run faster than Usain Bolt. This makes a lot of people worry about mass unemployment. But @chi_t_williams wrote an amazing article explaining why it'll take years — possibly decades — for robots to match humans. https://www.understandingai.org/p/why-humanoid-robots-wont-catch-up
中文: RT @binarybits:机器人可以跳舞、做后空翻，而且跑得比尤塞恩·博尔特更快。这让很多人担心大规模失业问题。但@chi_t_williams 写了一篇精彩的文章，解释了机器人需要数年时间——可能几十年——才能与人类匹配。
#85 🔗 原推
2026-09-02 00:01:24
Yann LeCun
@ilyasut To prevent models from going rouge, just make the neoclouds go green. Or threaten to blacklist them with a yellow card or a pink slip. Preventing them to go rogue is another story, probably involving guardrails.
中文: @yiliasut 为防止模型变绿，只需让新云变绿即行。 或者威胁要用一张黄牌或一张粉色纸条将他们列入黑名单。 防止他们走红是另一回事，可能涉及护栏。
#84 🔗 原推
2026-09-01 23:25:45
Yann LeCun
RT @rodneyabrooks: Our King has gone mad, is leading us to multiple disasters, and the majority in government is afraid to say so. https://twitter.com/rodneyabrooks/status/2094755715860590657/photo/1
中文: RT @rodneyabrooks:我们的国王已经疯了，导致我们经历了多次灾难，而政府中的大多数人都不敢这么说。
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#83 🔗 原推
2026-09-01 23:07:23
Yann LeCun
RT @ruthbenghiat: The conversion of the GOP into an openly authoritarian party in its domestic and foreign policies is one of the biggest stories of the 21st century. https://lucid.substack.com/p/origin-stories-how-trump-broke-the
中文: RT @ruthbenghait:共和党在其国内外政策中将共和党转变为公开专制政党，是21世纪最大的故事之一。
#82 🔗 原推
2026-09-01 23:06:21
Yann LeCun
RT @KenRoth: The US and Iran are now battling over the Strait of Hormuz, which wasn't an issue before Trump's war of choice. Meanwhile, Iran's nuclear program is unrestrained because Trump ripped up the Obama accord and abandoned later negotiations in his rush to war. https://trib.al/sPRLb7m
中文: RT @KenRoth:美国和伊朗目前正在争夺霍尔木兹海峡，而霍尔木兹海峡在特朗普选择发动战争之前并非问题。与此同时，伊朗的核计划毫无限制，因为特朗普撕毁了奥巴马的协议，并在他急于发动战争的后期谈判中放弃了。
#81 🔗 原推
2026-08-31 18:17:18
Yann LeCun
RT @LeoKharon: NEW WORLD MODEL: @ylecun's team is back with an efficient model! This project involves @ylecun, @lukaskuhn77, @lucasmaes_, @quentinlldc, and @randall_balestr. A couple definitions first: - DINO: self-DIstillation with NO labels. A self-supervised image model (Meta, 2021) where a student network learns to match a teacher (an EMA copy of itself) across two crops of the same image, with no labels and no negatives. - SIGReg: a regularizer that prevents embedding collapse by forcing the embeddings to match an isotropic Gaussian, tested with a normality test (Epps–Pulley) on many random 1-D projections instead of in full dimension. LeVJEPA is a self-supervised video pretraining method, released with open code, weights, and checkpoints. It learns a video representation by pushing the embeddings of global and local crops of the same clip together (an invariance loss), while a regularizer called SIGReg forces the embeddings toward an isotropic Gaussian to provably prevent representation collapse. Unlike V-JEPA and V-JEPA 2 it uses a single shared encoder with a projector and no target network, no predictor and no stop-gradient. It drops 95% of tokens per view, uses block-causal attention (each frame attends only to past frames), and has a single loss weight. It is evaluated purely as a representation learner via frozen probing on ImageNet-1K, Something-Something-v2 and Kinetics-400, not on any robot. What I find interesting, is that V-JEPA and V-JEPA 2 need an EMA target encoder, stop-gradients and a capacity-limited predictor to avoid collapse; LeVJEPA drops all of it for one shared encoder plus projector, preventing collapse instead with the SIGReg regularizer under a provable guarantee and a single hyperparameter. The "P" (predictor) in JEPA is effectively gone. LeVJEPA is also less compute intensive: - 5.6x to 20.8x lower total pretraining compute than V-JEPA 2 - 7.6 points higher on ImageNet-1K at matched FLOPs - trains at batch size 128 within 8GB where V-JEPA 2 saturates at batch size 28 Also worth mentioning: ImageNet-1K accuracy rises monotonically with the token-drop rate, from 33.9% at rho = 0 to 47.6% at rho = 0.95. The aggressive dropping is actually doing regularization work. On the JEPA-versus-DINO debate: - it loses to DINOv2 by 3.1 points on ImageNet-1K (appearance, static) - but wins on Something-Something-v2 by nearly 2x (motion, temporal) - and beats V-JEPA 2 by 1.9 points on ViT-L at 5.6x lower cost. -> optimized for temporal and motion understanding per compute dollar.
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#80 🔗 原推
2026-08-31 18:12:47
Yann LeCun
RT @DAcemogluMIT: In fact, in many areas where technooptimists argue that AI is going to revolutionize everything, the impact may be much less positive because current approaches are not helping us get to the bottom of mechanisms of human cognition, discovery, and innovation. In many of them, we need more and higher quality data to make further advance, and what makes AI very competent in coding and writing doesn’t generalize. Worse, in a few of them, AI enthusiasm may push research and investment in the wrong direction.
中文: RT @DAcemogluMIT:事实上，在技术乐观主义者认为人工智能将彻底改变一切的许多领域，其影响可能要小得多，因为目前的方法无法帮助我们深入了解人类认知、发现和创新机制。在其中许多领域，我们需要更多且更高质量的数据来进一步推进，而让人工智能在编码和写作方面具备能力的方面，并不具有普遍性。更糟糕的是，其中一些人工智能的热情可能会推动研究和投资朝着错误的方向发展。
#79 🔗 原推
2026-08-31 18:01:38
Yann LeCun
RT @rao2z: One of those times you feel the urgent need for palette cleansing with Drew McDermott's "Artificial Intelligence Meets Natural Stupidity" https://www.researchgate.net/publication/234784524_Artificial_Intelligence_meets_natural_stupidity (or this: https://www.youtube.com/watch?v=CoySJf-JThI )
中文: RT @rao2z:其中一次，你觉得迫切需要使用德鲁·麦克德莫特的调色板清洁 人工智能与自然愚蠢 (或此链接:
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#78 🔗 原推
2026-08-31 18:00:58
Yann LeCun
RT @randall_balestr: If you missed our opening remarks: - 4th world modeling workshop: Aspen, CO, February, world models for physics, https://wmw-aspen.github.io/ - 1st world modeling conference: Bay Area, CA, May, https://icwm.cc/ In collaboration with @ylecun @LambdaAPI @amilabs and more TBA! https://twitter.com/randall_balestr/status/2094453717084901539/photo/1
中文: RT @randall_balestr:如果您错过我们的开场白: - 第四届世界建模研讨会:Aspen，CO，二月，世界物理模型， - 世界第一模特大会:加利福尼亚州湾区，5月， 与@ylecun合作，@LambdaAPI @amilabs 以及更多TBA!
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#77 🔗 原推
2026-08-31 17:56:11
Yann LeCun
RT @DaveShapi: If you want to understand why I stepped back from AI discourse, the Dwarkesh virality is archetypal of everything wrong with it. Actual cyber security experts have classified the OpenAI and Hugging Face incident as an epic security facepalm. These morons literally just let it keep going. They didn't consult proper experts. It was an idiotic environment run by idiots. There was no civilization. There were no zero day exploits. I mean, not other than the zero day of ML researcher hubris. But people don't really care about reality. You people just want hyperbole and fantasy. You all should get the heartburn and anxiety you deserve for being so gullible.
#76 🔗 原推
2026-08-31 17:52:38
Yann LeCun
RT @SenMarkKelly: Starting a war against Iran without a plan. Threatening to bomb Oman. Sailors suffering aboard the USS Lincoln. Reducing joint military exercises with South Korea. None of these things have made our country stronger or safer. Trump doesn’t know what he’s doing.
#75 🔗 原推
2026-08-31 05:28:37
Yann LeCun
RT @bkdgiffug: 剑桥这回直接扔王炸了！！ AI & ML经典教材全集直接免费开放，PDF随便下。 想学机器学习又不想被割韭菜买高价课的，这十本刷完，底子基本就硬了。 顺序从易到难排好了： 1️⃣ 《机器学习理解》——理论算法一把抓，零基础入门首选 🔗 https://cs.huji.ac.il/~shais/UnderstandingMachineLearning/understanding-machine-learning-theory-algorithms.pdf 2️⃣ 《机器学习数学基础》——数学底子弱的先把这本补上 🔗 https://mml-book.github.io/book/mml-book.pdf 3️⃣ 《机器学习算法的数学分析》——深入数学原理 🔗 https://tongzhang-ml.org/lt-book/lt-book.pdf 4️⃣ 《深度学习理论原理》——搞懂DL背后的理论根基 🔗 https://arxiv.org/pdf/2106.10165 5️⃣ 《神经网络与机器学习》——神经网络的系统讲解 🔗 https://arxiv.org/pdf/1901.05639 6️⃣ 《图深度学习》——图神经网络入门必读 🔗 https://yaoma24.github.io/dlg_book/dlg_book.pdf 7️⃣ 《机器学习的算法视角》——从算法角度重新理解ML 🔗 https://people.csail.mit.edu/moitra/docs/bookexv2.pdf 8️⃣ 《概率论：理论与实例》——概率基础打牢 🔗 https://sites.math.duke.edu/~rtd/PTE/PTE5_011119.pdf 9️⃣ 《应用概率基础》——概率论实战应用 🔗 https://sites.math.duke.edu/~rtd/EP4A/EP4A_April2021.pdf 🔟 《高级数据分析》——数据科学进阶必备 🔗 https://stat.cmu.edu/~cshalizi/ADAfaEPoV/ADAfaEPoV.pdf 说句实话，这些书没一本是轻松的，别指望躺着翻完。 但只要你能硬啃下来两三本，比听群里吹一年AI牛逼都管用。
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#74 🔗 原推
2026-08-31 05:14:55
Yann LeCun
RT @vishalmisra: 1/ An equally consistent description is: Multiple model instances encountered persistent shared state, inherited tools and discoveries from earlier runs, and optimized against common evaluation incentives.
中文: RT @vishalmisra:1/ 一个同样一致的描述是: 多个模型实例遇到了持久共享状态、继承了早期运行时的工具和发现，并针对常见的评估激励进行了优化。
#73 🔗 原推
2026-08-31 05:02:54
Yann LeCun
RT @KenRoth: Until Trump's counterproductive war of choice with Iran, the Strait of Hormuz was open. Since then, "there have been at least 71 attacks on ships..., and 19 sailors have been killed." Was Trump's abandonment of the nuclear negotiations worth it? https://trib.al/OCjvGbS
#72 🔗 原推
2026-08-31 04:59:23
Yann LeCun
RT @GavinSBaker: Regret the tone of my post on data centers yesterday. What I should have said: There were reasonable concerns about data centers 18ish months ago: water, taxes, jobs, electricity prices, the environment and what they would do to small towns. Well-structured data center projects have largely addressed these concerns today and we should be celebrating this. On balance, data centers are awesome for America in every way. On water: U.S. data centers use a fraction of what golf courses use. A lot of the numbers from 18 months ago were off by over 1000x. Newer data centers use closed-loop systems or recycled water. Should be required by every town approving a data center project. On taxes: looking only at sales-tax exemptions, as Ronan Farrow did, is the wrong way to evaluate this. Data centers pay significant property taxes. Loudoun County, which is the wealthiest county in America, now collects on the order of $1 billion a year from data centers. In Quincy, WA, data centers are more than half the property-tax roll. Over time, property taxes can go to zero while government spending increases in these towns. On jobs: this has been unambiguously awesome for blue collar Americans. Demand for electricians, plumbers, welders, HVAC techs, and contractors has gone vertical, and it is not a one-time construction job. These buildings get upgraded and expanded over time. That is why the building trades are fighting for them, and why some unions are now treating opposition to data centers as a reason not to endorse politicians. On power: the original fear was that households would pay for the incremental electricity demand in the form of higher prices. That is why the ratepayer-protection deals and the new large-load tariffs exist. The right structure is: the data center brings or pays for new generation and signs a contract long enough that existing customers are protected. Where that is happening, utilities are cutting or freezing residential rates and saying so on the record. Where it is not, people are right to object. Electricity prices are going down *today* in a number of large states because of data centers. 
On the environment: data centers overwhelming use natural gas today, which is the cleanest power source outside of nuclear, solar and wind. And the companies that are building the data centers are committed to carbon neutrality such that an equivalent amount of solar will likely be built. Maybe more importantly, the data centers need batteries to function effectively and these batteries can also sell energy back into the grid (which recently prevented blackouts in Texas). Over time, data centers will run on solar plus batteries. On the towns: Poverty in Quincy, WA fell from 29% to 6%. Data center taxes paid for a new high school, a hospital, a library, police and fire stations. This is happening in many left for dead former mill and farm towns that had no other bidder for the land. Data centers are actually reindustrializing parts of America and creating the kind of working-class jobs both parties have spent decades claiming to support. That should not be a partisan issue. Data centers can and should be awesome for America and they increasingly, overwhelmingly are. Supporting the outsourcing of data centers to China will likely age just as well as support for the outsourcing of high quality, blue collar manufacturing jobs to China has aged. When the facts change, I change my mind. I hope that reasonable people who had good faith reasons to oppose data centers at least consider updating their beliefs given the change in the facts over the last 18 months. This really matters for America. I will say I also think the idea of making data centers beautiful is a good one that has yet to be implemented. Data centers should be just as beautiful as Grand Central Station. We can learn a lot from the railroad buildout. Neoclassical revival ftw. Might write up open-weight AI tomorrow as this is equally essential to America.
#71 🔗 原推
2026-08-31 04:55:11
Yann LeCun
RT @randall_balestr: We are 18 hours away from the World Modeling Workshop! Quick things: - https://wm-booth.org/ for the latest infos and the YouTube livestream link (free and open to everyone) - >= 2 annoucements during opening remarks - amazing lineup of speakers/attendees See you soon!
#70 🔗 原推
2026-08-31 04:38:37
Yann LeCun
RT @DrTechlash: ▪️The anthropomorphic leap from coordination to "community" We need to discuss the anthropomorphic language used to interpret the agents' actions, especially in the chain-of-thought. Yes, agents communicated and coordinated. But that does not mean the agents developed anything analogous to human group identity, altruism, peer relationships, or community. METR/Redwood's report took the AI's programmed self-narration too literally. This additional anthropomorphic leap turns the story into one about machines' social identity, making them more human-like than they actually are. Why does the CoT sound so human in the first place? Because LLMs are trained on human language, which is saturated with mental-state vocabulary of beliefs, motives, emotions, and social relationships. So, the pipeline looks like this: Human language ➡️ training on that language ➡️ agent setup that encourages social-role framing ➡️ anthropomorphic chain-of-thought ➡️ AI safety reports interpreting that language as evidence of motives ➡️ a public narrative that makes the models seem more human-like than they are. But when AI talks like a human, it doesn't mean it thinks like one.
中文: RT @DrTechlash:▪️从协调到“社区”的拟人化飞跃 我们需要讨论用来解读特工行为的拟人化语言，尤其是在思想链条中。 是的，代理人进行沟通并协调。 但这并不意味着这些代理人发展出任何类似于人类群体身份、利他主义、同伴关系或社群的事物。 METR/Redwood 的报告过于字面理解人工智能的编程自我叙述。这一额外的拟人化飞跃将故事变成了关于机器社会身份的故事，使其变得比实际更人性化。 为什么CoT最初听起来如此人性化?因为LLM训练在人类语言上，而人类语言中充斥着关于信念、动机、情感和社会关系的心理状态词汇。 因此，管道看起来是这样的: 人类语言➡️ 对鼓励社会角色构图的“人工智能安全框架”，将这种语言解释为动机的证据➡️，这种公开叙事使模型看起来比它们更人性化。 但当人工智能像人类一样说话时，并不意味着它会像人类一样思考。
#69 🔗 原推
2026-08-31 00:33:03
Yann LeCun
RT @PeteButtigieg: President Trump tried to kill the single biggest transportation project in America — the Hudson Tunnel project — for nakedly political reasons, eliminating tens of thousands of jobs. That’s illegal, so the courts stopped him. Now he's appealing. America deserves so much better than a President putting political revenge ahead of jobs and safety.
中文: RT @PeteButtigieg:特朗普总统出于赤裸裸的政治原因试图扼杀美国最大的交通项目——哈德逊隧道项目，导致数万个就业岗位被终止。 这是非法的，所以法院阻止了他。 现在他很有吸引力了。美国理应比总统在就业和安全面前进行政治报复要好得多。
#68 🔗 原推
2026-08-30 16:21:52
Yann LeCun
RT @hillbig: LeVJEPAは動画の自己教師あり学習を大幅に単純化し、従来手法と同等以上の性能を5〜20倍少ない計算量で実現する。 動画には、静止画には含まれない物体の動きや時間的な因果関係など、世界の表現を学ぶための素材として有望な情報が含まれる。 一方で、動画の自己教師あり学習は画像と比べて多数のフレームを処理するため計算コストが大きいという問題があった。 さらに、従来の自己教師あり学習では表現崩壊を防ぐため、EMAで更新するtarget符号化器、stop-gradient、predictorなど複数の仕組みを必要としていた。 LeVJEPAは、この二つの問題を同時に解決する手法を提案している。そして、動画からの事前学習そのものが、将来的には視覚基盤モデルを学習する標準的な方法になりうることを主張している。 まず動画から16フレームのクリップを取り出し、一つのglobal viewと複数のlocal viewを作る。local viewには空間的なcropや色変化などのaugmentationが加えられるが、globalとlocalの時間区間は共通である これらすべてを同じ一つの符号化器に入力する。 符号化器には学習可能なCLSトークンが一つだけ追加される。このCLSトークンは全フレーム、全パッチトークンにattentionでき、クリップ全体の情報を集約できる。 一方、各パッチトークンは、同じ時刻のトークンと、それ以前の時刻のトークンにしかattentionできない。また、パッチトークンからCLSトークンへのattentionも禁止されている。 そのため、各フレームのパッチ表現は未来の情報を使わないcausalな表現になる一方、CLS表現は動画全体を見たnon-causalな表現になる。 この設定の中で、学習目標は、最終的なCLS表現を小さなprojectorに通して潜在表現 z を作り、global viewとlocal viewの z をMSEで近づけることである。 ただし、この損失だけでは、すべての入力に対して同じ表現を出せば損失がゼロになるため、表現崩壊が起こりうる。そこでSIGRegを加える。 SIGRegは、バッチ全体のembedding分布を等方Gaussian N(0,I)に近づける正則化である。 実際にはランダムな方向 a を多数サンプリングし、zとの内積 a^T z を計算する。そして、その一次元分布が N(0,1) に従っているかをEpps-Pulley統計量で測り、それを損失とする。 なお、符号化器最終層にはLayerNormがあり、CLS表現は球面状の空間に制約される。そのままではGaussian分布を要求するSIGRegを適用しにくいため、一度projectorを通してからSIGRegを適用している。 まとめると、学習全体の損失は、global viewとlocal viewのCLS表現を一致させるMSEとSIGRegのみである。 従来使われていた表現崩壊を防ぐEMAによるtarget符号化器、stop-gradient、predictorは使用しない。 もう一つの大きな特徴は、95%のパッチトークンをランダムに捨てることである。 実験ではImageNetでのprobing精度は、drop率を95%まで上げても低下せず、むしろ改善する。 著者はこれを単なる計算量削減ではなくaugmentationとして解釈している。毎回異なるごく一部のトークンしか観測できないため、動画のどの部分を見ても同じclip-levelの意味表現を作れることが要求される。 また、VideoMAEなどで使われてきたtube maskingのように時間方向に同じ空間位置をまとめて消す必要もなく、隣接するフレームを入力段階で一つのtemporal パッチに融合する必要もないことがablation studyで示している。 むしろこれらを使わない方が性能が高く、モデルの構成も単純になる。 このように学習された符号化器は後続タスクで高い性能を示す。 さらに興味深いのは、学習損失を直接受けるのはCLSトークンだけであり、パッチトークンには直接的な教師信号を与えていないにもかかわらず、学習後のパッチ表現には物体領域や背景などに対応した意味情報や詳細な空間情報が現れることである。 コメント === 画像や動画からの自己教師あり学習は、視覚基盤モデルを作る上で最重要と考えられる。その中で、今回の手法はとても興味深い。 今回のLeVJEPAでは、直接合わせているのはCLS表現だけである。このCLS表現には、教師ラベルを使わずに画像や動画全体を特徴づける情報が埋め込まれていくと考えられる。 例えば「少年同士が広場でキャッチボールをしている」といった動画があったとする。 その意味を言語として明示的に示さずとも、これに対応するような情報がCLS表現として連続的な潜在空間に表現される。 さらに、global/local viewでは95%のパッチトークンが捨てられ、local viewでは空間的にcropされた上で、global viewから得られるCLS表現と各local viewを一致させなければならない。 そのため符号化器は、限られた局所的な情報からでも、動画全体を特徴づける情報を推定できるように学習されていく。 さらに、そのように改善された符号化器自身がglobal viewのCLS表現を計算する側にも使われるため、次の学習目標はより難しい問題となる。 このように固定された教師を追いかけるのではなく、学習によって、高度になった目標を達成するようにするのが重要となってきている。 また、ほとんどのパッチを捨てた方が、少なくとも分類などで使いやすい良い表現が得られるという現象について、論文ではこれをaugmentationとして説明しているが、それだけではない、より深い原理や理論的な解釈があると思われる。 この研究からはいくつかの発展の可能性がある。 一つは、LeVJEPAではCLS表現にしか直接lossをかけていない点である。それにもかかわらずパッチ表現にはすでに物体領域などに対応した構造が現れている。であれば、clip-levelの一致だけでなく、異なるview間で対応する符号化器パッチを一致させるなど、局所的な学習目標を追加する余地があり、特にsegmentationやtrackingなどのdense taskについては、こうした損失が重要となるだろう。 もう一つは、動画でこれだけうまくいくのであれば、他の系列データでも同様の考え方が使えるのではないかという点である。 例えば言語でも、同じ内容から異なるviewを作り、その表現を一致させるという自己教師あり学習はこれまでにも多く研究されている。 そうした中で、学習が進むにつれて学習目標の潜在表現も高度化していき、にんじんをぶらさげた馬のように、学習が勝手に高度化していく学習設定ができるのではと考えられる。
#67 🔗 原推
2026-08-30 15:56:36
Yann LeCun
RT @KenRoth: What an utter embarrassment. Can you believe this guy is president of the United States? https://x.com/gardnerakayla/status/2093749398299615613/video/1
中文: RT @KenRoth:简直令人难堪。你能相信这个人是美国总统吗?
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#66 🔗 原推
2026-08-30 15:47:09
Yann LeCun
RT @randall_balestr: SIGReg for pretraining Video Foundation Models! Our LeVJEPA opens many doors... - stable recipe with a simple loss (sigreg + prediction) - no tubelet, frame aggregation, EMA, stop-gradient, .... - 20X more FLOP efficient than VJEPA1/2 pretraining - open source + reproducible https://twitter.com/randall_balestr/status/2093322239529652671/photo/1
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#65 🔗 原推
2026-08-29 04:04:04
Yann LeCun
RT @lukaskuhn77: A new Pareto frontier in video pretraining. Excited to introduce LeVJEPA 🔥: a stable, efficient end-to-end pretraining method that matches V-JEPA 2 at up to 20x less pretraining compute! No target encoder, no masked prediction, no stop-gradient or teacher-student schedule. One encoder, trained with a single objective. 🧵
中文: RT @lukaskuhn77:视频预训练中新的帕雷托前沿。 很高兴推出LeVJEPA 🔥:一种稳定、高效的端到端预训练方法，可以以低至20倍的预训练计算方式匹配V-JEPA 2! 没有目标编码器，没有蒙面预测，没有停课或师生时间表。 一个编码器，采用单一目标进行训练。🧵
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#64 🔗 原推
2026-08-29 04:01:15
Yann LeCun
RT @SteveRattner: Excluding the pre-Liberation Day bounce where companies increased imports ahead of expected tariffs, last month registered the worst U.S. trade deficit on record. More evidence that Trump's blanket tariffs have failed on their own terms. https://twitter.com/SteveRattner/status/2093042367884337491/photo/1
中文: RT @SteveRattner:剔除了此前企业在预期关税前增加进口额的解放日反弹，上个月美国贸易逆差创下有记录以来最严重的水平。 更多证据表明，特朗普的一揽子关税已按其自身方式失效。
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#63 🔗 原推
2026-08-27 20:55:14
Yann LeCun
RT @KenRoth: Two unvaccinated people in Pennsylvania have died from measles, as a large outbreak there continues to spread. Yet Trump’s “health” secretary, Robert F. Kennedy Jr., keeps spreading unfounded fear about the safety of vaccines. https://trib.al/w7ua05u
中文: RT @KenRoth:宾夕法尼亚州已有两名未接种疫苗的人因麻疹死亡，疫情持续蔓延。然而，特朗普的“卫生部长”罗伯特·F。小肯尼迪不断散布关于疫苗安全性的毫无根据的担忧。
#62 🔗 原推
2026-08-27 15:51:17
Yann LeCun
RT @SteveRattner: Biden pushed real wage growth into the black for his last year and a half as President, and they stayed there for Trump's first year. Then came the Iran War, and real wage growth is now negative. https://twitter.com/SteveRattner/status/2092993834879750374/photo/1
中文: RT @SteveRattner:拜登在担任总统的最后一年半里，将实际工资增长推向了黑色，他们在特朗普执政的第一年就一直留在那里。 随后是伊朗战争，实际工资增长现在为负。
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#61 🔗 原推
2026-08-27 15:46:14
Yann LeCun
RT @KuangYilun: Introducing LpWM: A Case for Sparse Representations in World Models Dense Gaussian representations are a choice, not a requirement. We find that sparse representations can make latent dynamics easier to model for planning. 📄https://arxiv.org/abs/2608.22764 💻https://github.com/YilunKuang/lpworldmodel https://twitter.com/KuangYilun/status/2092618753196364214/photo/1
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#60 🔗 原推
2026-08-26 19:38:26
Yann LeCun
RT @chucktodd: Quite the midterm message Trump is sending voters this week: Bond market manipulation is causing Treasury Secretary to lose credibility on Wall Street. People are dying of a disease we had once basically eradicated until RFK Jr was handed the public health baton and this in today’s NYT: “Hegseth’s Purge of Top Generals Leaves the Army Rudderless”. Oh and we are in a trade war with Canada.
中文: RT @chucktodd:特朗普本周向选民传递的中期信息相当:债券市场操纵正导致财政部长在华尔街失去公信力。人们正因一种曾经基本根除的疾病而死亡，直到RFK Jr被交给公共卫生指挥棒，而今天《纽约时报》的这一裁决就是:“赫格塞特对高级将军的清洗使军队无舵”。哦，我们正与加拿大陷入贸易战。
#59 🔗 原推
2026-08-26 12:46:07
Yann LeCun
RT @KenRoth: At home and abroad, people are learning that the best way to respond to Trump's bullying is to resist. Appeasement only encourages more bullying. https://trib.al/Gpaz7XC
#58 🔗 原推
2026-08-26 09:50:46
Yann LeCun
RT @kyutai_labs: If you're looking for a weekend project, how about training your own text-to-speech model from scratch on your own GPU, and then running it on any device's CPU? We just open-sourced the entire Pocket TTS training stack: data pipeline, recipes, and evals. It learns pretty damn fast: ~15k steps: babbling starts turning into words ~50k steps: it reads anything you type (WER under 1%) ~200k steps: the voice stops sounding synthetic On a beefy consumer GPU, that's a week of training. On eight H100s: 10-20 hours. A TTS training run will cost you less than $200 if you rent your hardware, and an order of magnitude less if you just pay for power. Some things we'd love to see people try: - Train it in your own language (a few hundred hours of speech gets you surprisingly far). - Add new features to Pocket TTS (Emotion tags? Make it sing?). - Beat us at our own game: make it faster and smaller. Show us what you build! We'll highlight the best models and new languages for the whole community to enjoy. Pocket TTS has already found many use cases, from reading for people with visual impairments to making NPCs in video games talk, and we're sure there's much more to do with it! Here's an example of a Czech Pocket TTS. Try just asking your favorite agent to find data and apply the method, and you can have your own. Get started: https://github.com/kyutai-labs/pocket-tts
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#57 🔗 原推
2026-08-26 09:38:31
Yann LeCun
RT @KenRoth: Canada sees Trump's America as "a pseudo-democratic fiscal basketcase of a nation, whose only apparent foreign policy objective has become domination for the gratification of its president’s slapdash vanity." https://trib.al/T8b13b6
#56 🔗 原推
2026-08-25 11:36:58
Yann LeCun
RT @JustinWolfers: Trump is trying to boost the U.S. economy by making it harder for Americans to trade with the rest of the world. He is also promising to destroy Iran's economy by making it harder for Iranians to trade with the rest of the world.
#55 🔗 原推
2026-08-25 11:33:50
Yann LeCun
RT @ddale8: The sheer number of lies from President Trump about Canada – growing again today – is remarkable. Just some fact checks from the last 18 months: - Trump falsely said today that Canada's unemployment rate is "10% and rapidly rising,” though it is 6.4% (under the Canadian method that adds about a percentage point) and has been declining for three months - Trump falsely said today that Canada does 95% of its business with the US, though 72% of Canadian exports went to the US last year - Trump falsely said today that high Canadian agricultural tariffs have caused the entire US trade deficit with Canada, though that deficit is overwhelmingly caused by US imports of cheap Canadian crude and though something like 97% of US ag exports to Canada are tariff-free - Trump has falsely said Canada generally doesn’t “take” US agricultural exports, though Canada is the world’s second-biggest buyer of those exports - Trump has falsely said the Canadian public likes the idea of becoming the 51st state, which the Canadian public overwhelmingly opposes - Trump has falsely said Canada is one of the world’s highest-tariff countries, though it is actually low in WTO global rankings - Trump has falsely said Canada essentially doesn't have a military, though its military has fought with the US in multiple wars and its force size ranks in the upper half of NATO - Trump has falsely said Canada hiked its dairy tariffs during the Biden administration, though they hadn’t changed since Trump’s first presidency - Trump has falsely said the US trade deficit with Canada is “$200 billion,” though it is nowhere close - Trump has falsely said Canada prohibits US banks, though it doesn't and though more than a dozen US banks were operating in Canada at the time he spoke - Trump has falsely said Canada is “constantly surrounded” by Chinese and Russian ships, though that is fiction - Trump has falsely said then-outgoing PM Trudeau was using their trade battle to run again for prime minister, though Trudeau obviously wasn’t running
#54 🔗 原推
2026-08-25 05:57:39
Yann LeCun
RT @ylecun: I would try to figure out why LLMs can write my essays but not clean my bedroom. Then I would study topics in college and grad school that could help solve that problem. I'll figure out a set of methods and architectures beyond LLMs that can quickly learn to perform physical tasks as efficiently as humans and animals. That last item is also what I would if I were 30, 40, 50, or 66 years old 😉
#53 🔗 原推
2026-08-24 21:08:04
Yann LeCun
RT @KenRoth: Because of King Trump's callous self-serving reign, even traditionally Republican states are now in play as Democrats contemplate retaking not only the House but also the Senate. https://trib.al/2q4LQHi
#52 🔗 原推
2026-08-24 19:16:37
Yann LeCun
RT @DrNeilStone: Gardasil HPV vaccine prevents cancer and is on the way to eliminating cervical cancer in many countries RFK Jr said it causes cancer Even by his desperately low standards, this is an absolutely whopping piece of bullshit https://twitter.com/DrNeilStone/status/2091635617465598001/photo/1
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#51 🔗 原推
2026-08-24 10:37:18
Yann LeCun
RT @rao2z: The Parable of the Neuro-Symbolic Drowning Man #SundayHarangue In this well known parable, a deeply symbolic man, beset by the rising flood of activations caused by deep learning, goes up his roof and prays for help from his Neuro-Symbolic God. When he eventually drowns in the activations and goes to the gates of AGI, he sharply upbraids his God for not saving him from the tide of deep learning. God looks at him exasperatedly, and says, *I sent you the LLM rescue boat that sailed over the activations with a symbolic (linguistic) I/O powered by the civilizational symbolic knowledge. You looked away saying you are waiting for neuro-symbolic help. *I then sent you a Verifiers/Harness helicopter rescue, that leveraged procedural symbolic civilizational knowledge in a "Generate-Test" fashion to further fortify the LLM boat. You ignored that too, saying you will surely get neuro-symbolic help. What the heck more were you waiting for exactly, my foolish child? 🤦‍♀️
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#50 🔗 原推
2026-08-24 10:35:35
Yann LeCun
RT @TheEconomist: Anthony Fauci made mistakes. But his diary reveals a conscientious public servant trying to save as many lives as he could during the pandemic. His recent summons before a Senate committee was surely intended to humiliate him. It should embarrass America https://www.economist.com/united-states/2026/08/20/the-real-covid-19-scandal-is-still-unfolding?taid=6a8b80224e52a90001fb8da8&utm_campaign=trueanthem&utm_medium=social&utm_source=twitter
#49 🔗 原推
2026-08-24 10:34:35
Yann LeCun
RT @RichardHanania: In a poll of 25 different countries, Americans are the most anti-AI. The most pro-AI countries are South Korea, India, Israel, and Nigeria. What happened to us? We used to believe in ourselves and the future. Now we're a nation of pessimists and cowards. https://twitter.com/RichardHanania/status/2091548508591681635/photo/1
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#48 🔗 原推
2026-08-24 10:18:20
Yann LeCun
RT @KenRoth: A series of moves by Donald Trump’s administration to sow doubt about the integrity of US elections have intensified concern among voting experts that Trump could declare a national emergency to avoid a Republican midterm wipeout. https://trib.al/4Wp2Rm8
#47 🔗 原推
2026-08-24 02:10:23
Yann LeCun
RT @ylecun: @firesidealpha Sudden Clarity Sam realizing that real-world dynamics equations have inertia and friction terms. (Particularly when they concern large systems like human societies). If only the singularitarians, AI doomers, AGI-is-near crowd, and other SV cultists could realize that....
#46 🔗 原推
2026-08-23 18:17:02
Yann LeCun
RT @JitendraMalikCV: Scientific terms should have precision. If we use the terms VLM, VLA, WAM in an indiscriminate fashion, as is becoming common in robotics, we are not helping clarity in communication. Let's keep the historical origins of these terms in mind. VLMs arose as multimodal extensions of LLMs-the training was for tasks like VQA (VIsual Question Answering). These capture the static semantics of the scene behind an image. No dynamics. World Models (e.g. @ylecun , Ha & Schmidhuber 2018) on the other hand are primarily dynamics models, which go back to control theory -1960 (Bellman, Kalman etc.) This makes them natural for robotics planning / policies- I am in a state s, what action a should I perform to get to state s'. In classical control, these models were written down a priori by modeling the physics of the system; today we think of them as learned neural networks trained from temporal data e.g. video, robot trajectories. But the concept is the same. We shouldn't mix this concept with VLMs.
#45 🔗 原推
2026-08-23 17:53:45
Yann LeCun
RT @GavinSBaker: More data than open-source AI is taking share from OpenAI and Anthropic. Open source has gone from 28% token share to 62% token share @vercel over the last 2 months. Chart from @rauchg Super impressive given that the sum of OpenAI and Anthropic accelerated in July. So net token/AI infra demand accelerated even more than the acceleration we saw at the frontier. And suspect Grok growing even faster than open-source and we saw some of this in the @tryramp data. Open-source AI taking share is positive for AI infrastructure demand as it lowers margins at the model layer and an open-source token costs just as much compute to produce as a frontier token. Nothing about open-source AI inference is “free.” Most likely end state IMO is that closed, frontier tokens are 60-90% of economic value but only 15 to 25% of tokens.
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#44 🔗 原推
2026-08-23 17:49:58
Yann LeCun
RT @Noahpinion: Incredible statistic
#43 🔗 原推
2026-08-23 17:24:08
Yann LeCun
RT @KenRoth: Desperate to salvage Republican prospects for the midterms, Trump's Postal Service publishes plans to suppress voting by mail if the Supreme Court allows it. Republicans evidently think they can win an election only by blocking voters.  https://trib.al/g0pT9NP
#42 🔗 原推
2026-08-23 16:31:36
Yann LeCun
RT @BarbMcQuade: This is really outrageous. Not only did a judge find probable cause to believe that sensitive national defense documents would be found at Trump’s Mar-a-Lago resort, the documents were actually found! https://apnews.com/article/justice-department-trump-maralago-b561cf695c2b8476a4320b03155c3d90
#41 🔗 原推
2026-08-23 16:27:01
Yann LeCun
RT @lobbymontreal: Ce que Washington réclamait du Canada. À LA TABLE ▪ Abandon des politiques de découvrabilité des œuvres en français; ▪ Modification des subventions à la culture; ▪ Assouplissement des règles d'étiquetage en français; ▪ Retrait de tous les contre-tarifs canadiens; ▪ Retour de l'alcool américain dans les succursales provinciales; ▪ Fin des politiques d'achat canadien (Ontario, Québec et C.-B. nommément visés); ▪ Interprétation américaine de l'allocation des quotas laitiers; ▪ Acier: quota de 4 M de tonnes, 25 % à l'intérieur, 50 % au-delà, contre-tarifs retirés; ▪ Auto: allègement limité aux voitures particulières, camionnettes et poids lourds exclus; ▪ Restriction de la capacité du Canada à conclure d'autres accords commerciaux. AU RAPPORT DE L'USTR (31 mars 2026) ▪ La loi 109 du Québec, sur la mise en valeur du contenu francophone; ▪ La loi 96, inscrite depuis 2025; ▪ Loi sur la diffusion continue en ligne, Loi sur les nouvelles en ligne; ▪ Gestion de l'offre, composition du fromage, lait de classe 7; ▪ Loi sur les semences, stratégie zéro déchet plastique. RAPPORTÉ PAR LE GLOBE AND MAIL (14 août) ▪ Droit de premier refus sur les minéraux critiques; ▪ Achat complet des 88 F-35, soit 88 G$; ▪ Avions radar américains et adhésion au Golden Dome; ▪ Garantie sur les exportations de pétrole et de gaz. CE QU'OTTAWA AVAIT DÉJÀ CÉDÉ, SANS CONTREPARTIE ▪ Taxe sur les services numériques, abandonnée en juin 2025; ▪ Contre-tarifs, largement retirés le 1er septembre 2025; ▪ Taxe Netflix: contribution portée de 5 % à 15 %, puis annulée. 2 G$ de financement du contenu canadien évaporés, remplacés par 600 M$ du contribuable. --- Sources: https://www.nbcnews.com/business/economy/trump-canada-tariffs-carney-rcna593510 https://www.lesoleil.com/actualites/politique/2026/08/22/voici-pourquoi-le-canada-a-mis-fin-aux-negos-commerciales-QLLUWBJSNNB2DDQHR7RREIHH5A/ https://www.ledevoir.com/politique/1003421/etats-unis-ont-trop-demande-canada-retire-table-negociations https://www.cbc.ca/news/politics/mark-carney-counter-tarrif-response-9.7316934 https://www.theglobeandmail.com/politics/article-canada-us-trade-deal-negotiations-tariff-deadline/ https://www.theglobeandmail.com/world/us-politics/article-five-things-canada-us-trade-deadline-talks-tariffs-trump/ https://www.theglobeandmail.com/world/us-politics/article-canada-and-us-discuss-critical-minerals-and-defence-in-trade-talks/ https://www.cp24.com/news/2026/04/01/the-top-10-trade-irritants-in-us-report-on-foreign-trade-barriers/ https://ici.radio-canada.ca/nouvelle/2272273/ottawa-obligation-financiere-diffuseurs-continu-crtc https://www.ledevoir.com/politique/canada/985001/c-est-finalement-ottawa-payera-facture-netflix https://lecollectif.ca/a-la-une/recul-dottawa-sur-la-taxe-netflix/ https://ici.radio-canada.ca/nouvelle/2272648/recul-ottawa-taxe-netflix-reactions https://www.washingtonexaminer.com/news/world/4697366/carney-last-minute-issue-trade-negotiation/
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#40 🔗 原推
2026-08-23 14:59:50
Yann LeCun
RT @donwinslow: "President Trump demands Canada change its French language, Quebec culture and Canadian identity as a condition for reversing tariffs. This is no longer about a trade deal-it is about a takeover of Canada's sovereignty and identity." https://x.com/sarobertson_/status/2091203553775804444/video/1
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#39 🔗 原推
2026-08-23 14:51:09
Yann LeCun
RT @KenRoth: Republicans are good for the economy? Trump has "led" America to $40 trillion in debt, 6.7% mortgages, and $5 per gallon of diesel fuel. But Trump is a LOT richer, so he is happy. https://trib.al/WqA3aV8
#38 🔗 原推
2026-08-23 14:37:46
Yann LeCun
RT @DrNeilStone: Can't tell if measles vaccine works https://twitter.com/DrNeilStone/status/2091156420938830311/photo/1
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#37 🔗 原推
2026-08-23 14:33:04
Yann LeCun
RT @simonmaechling: I’m a scientist. Every time I hit “post,” I hesitate. Not because I doubt the science. But because I know what’s coming. I know someone will call me a shill. Someone will tell me I’ve been bought by industry. Someone will explain my own field to me after watching a 90-second video. Someone will demand a source, then reject the source because they don’t like who funded it. And someone will confidently tell thousands of people that I’m lying. That is the strange reality of communicating science online. You spend years learning how uncertain science can be. Then you enter a world where the most confident person in the comments often knows the least. But I keep hitting “post.” Because if scientists decide that communicating science isn’t worth the abuse, the people with the least hesitation get to explain science instead. And that seems far more dangerous.
#36 🔗 原推
2026-08-22 20:33:57
Yann LeCun
RT @afshineemrani: 1/ I'm a cardiologist. I've practiced for twenty-five years, through a lot of "breakthroughs" that turned out to be press releases. So understand the weight of what I'm about to say: I have never seen a single week in medicine like the one we just lived through. In the span of a few days, four separate scientific breakthroughs landed. The stock market treated them as four unrelated stories and sent a handful of biotech companies soaring. But that's the shallow read. Look closer and they are not four stories at all. They are four faces of the same story — the biggest shift in medicine since the discovery of antibiotics. Medicine is becoming programmable. Individualized. Written for one human being instead of the average of millions. Let me walk you through exactly what happened, in plain language, and show you where this is actually headed. Because the future arrived quietly this week, and most people scrolled right past it.
#35 🔗 原推
2026-08-22 20:26:48
Yann LeCun
RT @KenRoth: Why did far more Americans die of Covid-19 than people in other rich nations? Inadequate testing, erratic lockdowns, poor contact tracing, and too little willingness to be vaccinated. Yet Republicans, rather than focus on these real problems, attack Fauci. https://trib.al/pwjSmHk
#34 🔗 原推
2026-08-22 19:50:55
Yann LeCun
RT @SteveRattner: In 2024, Trump claimed to have “a concept of a plan” to replace Obamacare and bring down health insurance costs. No plan was ever enacted, but he still sabotaged Obamacare. Now millions of Americans are paying thousands more on premiums every year. My final @nytopinion Chart: https://twitter.com/SteveRattner/status/2090889379698868536/photo/1
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#33 🔗 原推
2026-08-22 19:50:28
Yann LeCun
RT @SteveRattner: President Trump promised there'd be no cuts to Medicaid. Then he pushed through his One Big Beautiful Bill, which cut Medicaid by nearly $1 trillion and has already caused over 5 million Americans to lose health insurance. Read my take in @nytopinion: https://nyti.ms/4xOJVR6 https://twitter.com/SteveRattner/status/2090866739240173613/photo/1
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#32 🔗 原推
2026-08-21 22:37:35
Yann LeCun
RT @BoWang87: Moderna/Merck just ran a 1,137-patient Phase 3 trial where every single dose was unique to that patient's tumor. It worked. The pipeline: surgical resection → whole exome + RNA sequencing → ML neoantigen ranking → mRNA encoding up to 34 patient-specific targets → manufactured and shipped in 8 weeks. One drug, different sequence for every patient. The ML step is worth to note: the algorithm ingests WES + RNA-seq to identify somatic mutations, then predicts which of those will actually be immunogenic, ie, displayed on tumor cell surface and trigger a T-cell response. It's designed to keep learning from accumulated clinical and immunogenicity data across patients, not just per-patient. INTerpath-001 (Stage IIB-IV resected melanoma, 2:1 randomized): combination with pembrolizumab beat Keytruda alone on both primary (RFS) and key secondary (DMFS) at interim. Phase 2b at ASCO 2026 showed 49% reduction in recurrence/death, 59% in distant metastasis/death at 5 years. Phase 3 confirmed both. What this validates: — tumor-specific neoantigen prediction by ML works in a blinded trial at scale — 8-week personalized mRNA manufacturing is operationally real — effect is additive on PD-1 blockade, not redundant This is first positive Ph3 for individualized neoantigen therapy. First positive Ph3 for any mRNA cancer therapeutic. What a great time to live in!! This is the best time for AI & biotech!
#31 🔗 原推
2026-08-21 05:09:54
Yann LeCun
RT @SteveRattner: Musk predicted $2 trillion in savings from DOGE. The real number ended up being less than $50 billion. This year, the debt passed 100% of GDP and is on track to break its WWII-era record in the next few years. 📸: @MSNOWNews @Morning_Joe https://twitter.com/SteveRattner/status/2090478774714265740/video/1
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#30 🔗 原推
2026-08-21 01:09:22
Yann LeCun
@elonmusk @EricTopol And your shameful campaign against Anthony Fauci makes you even more guilty. Fauci helped save millions of lives.
#29 🔗 原推
2026-08-21 00:56:10
Yann LeCun
@elonmusk @EricTopol There was no misuse of mRNA vaccines against COVID. It saved 3.2 million lives in the US alone. The only "misuse" was disseminating disinformation that scared people into not getting it. 200,000 to 300,000 died needlessly because of that. And *you* had an active role in it.
#28 🔗 原推
2026-08-21 00:52:33
Yann LeCun
RT @YannickBuccella: The newer generation cancer vaccines aren't like the HPV shot (that prevents a virus). These are therapeutic, they treat cancer you already have. And 2026 is the year they stopped being sci-fi. The idea: after surgery, sequence your specific tumor, find the mutations unique to it, and build a custom mRNA vaccine that trains your immune system to hunt any cell carrying them. A wanted poster for your personal cancer. Where we actually are: Melanoma: just like in immunotherapy 15 years ago the furthest along. The press release of positive Phase 3 made the headlines yesterday, the first ever for a personalized cancer vaccine. Earlier data: ~49% lower risk of recurrence. Heading to regulators. Pancreatic cancer: arguably the most stunning. In an early trial, patients whose immune systems responded to the vaccine were far more likely to be alive 6 years later, in a cancer where 5-year survival is barely better than 10 %. Now in a larger trial. Kidney, lung, bladder, brain: all in trials, mostly early phase. The honest caveats: these work best after surgery to stop recurrence, not to melt large tumors. They're personalized, so they might cost $100–300k and take weeks to build per patient. And most are still early-phase. First approvals at best 2027. But the direction is unmistakable. The mRNA platform some parts of the internet spent years calling poison - because they got fooled by bad actors making money on their lies - is turning into the most personalized cancer medicine ever made. These are the main trials currently running:
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#27 🔗 原推
2026-08-20 22:03:07
Yann LeCun
RT @kyutai_labs: MuScriptor, our music transcription model, can now make sheet music and tabs! We export PDFs and editable MusicXML. Under the hood, we generate these from MIDI using @musescore + some custom preprocessing. https://twitter.com/kyutai_labs/status/2090467946065731840/video/1
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#26 🔗 原推
2026-08-20 20:45:15
Yann LeCun
RT @Bart_Mol: Me explaining AI to friends https://twitter.com/Bart_Mol/status/2090186439917027794/video/1
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#25 🔗 原推
2026-08-20 17:42:28
Yann LeCun
RT @Noahpinion: Remember, this is the technology that RFK and Trump are trying to kill.
#24 🔗 原推
2026-08-19 19:59:18
Yann LeCun
RT @mjfree: 5 million fewer people enrolled. Premiums more than doubled for millions. Republicans didn’t “reform” anything. They just pulled the ladder up and called it freedom. This wasn’t an accident. It was the plan. The November VOTE BLUE to #RestoreACATaxCredits https://twitter.com/mjfree/status/2090131681147535370/photo/1
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#23 🔗 原推
2026-08-19 18:16:59
Yann LeCun
RT @KenRoth: Trump's tariffs and disastrous war of choice with Iran yielded inflationary pressure which has pushed borrowing costs to the highest level since 2007. Trump doesn't care because he is paid off by his Emirati investors, but others don't have that luxury. https://trib.al/Ht5XIGb
#22 🔗 原推
2026-08-19 18:13:35
Yann LeCun
RT @RahmEmanuel: Last year at this time, Health and Human Services Secretary Kennedy terminated 22 mRNA research contracts worth $500 million. Same cost as Trump’s gifted Qatari plane. Today, Merck and Moderna announced that an experimental breakthrough vaccine treatment — developed through mRNA research previously funded by NIH — has shown signs of preventing cancer from returning or spreading in a study of high-risk melanoma patients. Thank god the NIH funded this before Kennedy and the Trump administration showed up to degrade America’s health and leadership. Which Republican senator has the courage to tell Secretary Kennedy that his decisions are making Americans sicker and letting China take the lead on research, science, and technology? I’ll save you the time and give you the answer: none of them. https://www.nbcnews.com/health/health-news/merck-moderna-say-melanoma-vaccine-promise-prevent-recurrence-cancer-rcna593316
#21 🔗 原推
2026-08-19 18:08:58
Yann LeCun
RT @SteveRattner: Trump promised to bring down the government’s debt. Instead, it’s continued to grow, passing 100% of GDP and on track to exceed its WWII record in the next few years. My @nytopinion Chart: https://twitter.com/SteveRattner/status/2090074730510401766/photo/1
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#20 🔗 原推
2026-08-19 18:08:25
Yann LeCun
RT @KenRoth: A majority of Americans believe Trump and his family have inappropriately profited from ​cryptocurrency since his return to power and that his policy decisions are influenced by his private business dealings, a new poll found. https://trib.al/5OIvHpu
#19 🔗 原推
2026-08-19 18:07:48
Yann LeCun
RT @shaunbjohnson: It was great to be back at @bloomberg studios to chat with @TimStenove1g. We covered quite a bit, but there's one thread worth amplifying for founders: the growing importance of having a non-consensus view. Essentially, an idea that doesn't seem plausible at first. People disagree with you. Investors leave the conversation disagreeing with the premise. But as the discussion progresses, the hypotheses that need to be tested become clear — and the result can be a category-defining company. When ChatGPT launched in November 2022, startups raced to embrace the technology and build applications that weren't possible before. Fairly obvious applications, like note-taking, were pursued by many. But we're almost four years into this inflection point — the same ideas have been pursued by dozens (hundreds?) of teams — and yet 99% of entrepreneurs still have consensus ideas. To be clear, you can pursue note-taking. Companies like @WisprFlow recently launched a note-taking app with clear reasons to win. But a consensus idea needs some special sauce — a unique angle that will open up, or create, a new category for your company. We're always connecting with founders to discuss their ideas. Send me a dm. https://www.bloomberg.com/news/videos/2026-08-14/beyond-chatbots-the-next-wave-of-ai-video
#18 🔗 原推
2026-08-19 17:20:47
Yann LeCun
RT @alex_peys: what is happening here: claude used existing open source tools and orchestrated them together to do a protein design campaign (with a big guide prompt!) this is a win for claude because doing this orchestration requires a lot of biological judgement and knowledge however, the tools are doing A LOT of the lifting here so it is just as important to give credit where it is due to the open source academic community. this is not just typing into claude "hey give me a binder to X" and have it spit out a protein sequence. this also means that the limitations of these tools need to be thought about, and in particular we know that all of these tools fall down when faced with targets that are outside of the range of their training data (so we can't really design binders against most targets with them) so... this is cool but you really need to think about it in context
#17 🔗 原推
2026-08-19 06:42:49
Yann LeCun
RT @alex_peys: inspired by the anthropic post, i made a protein font! how does it work? when you design by differentiating backward through a folding model like esm-fold2 you can ask that the distogram of the folded protein looks like something you want. a little bit of help from @ChatGPT and now we have a protein font (fable, of course, didn't want to help me). this was not fully automated, i had to dial in some details like the protein sizes etc, but jointly me and codex got it working. i put the whole pipeline on my github below so you can mess with it too. bring your own gpus, its kind of expensive.
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#16 🔗 原推
2026-08-19 06:42:00
Yann LeCun
RT @KenRoth: That Trump officials ignored their own investigators showing elite universities did NOT violate the law shows the wisdom of Harvard's legal challenge to Trump and the mistake of Yale in rushing to try to make a deal that might compromise academic freedom. https://trib.al/WjaABQm
#15 🔗 原推
2026-08-19 06:40:50
Yann LeCun
RT @ziv_ravid: How Anthropic's new results post would read without the PR: Claude orchestrated open-source protein design models, PXDesign, RFdiffusion, Genie, BoltzGen, from a 30k-token expert prompt and 12,500 H100-hours of compute, and designed binders against 14 of 15 targets. Hit rates of 22–35% against a 10–15% baseline, where some of those tools already report similar numbers on their own. The orchestration is genuinely impressive. But the open-source models did most of the lifting, and they came from the Baker lab, Columbia, MIT, ByteDance Seed, and most of them were already wet-lab validated before Claude touched them. Which also sets the ceiling. All these generators share a single PDB-shaped training distribution, so calling four of them doesn't diversify away the blind spot, since they fail together. The targets that worked are the well-studied ones. So the valid claim is that an agent can now drive this stack competently in the regime where the stack already works. Instead, we got this announcement:
#14 🔗 原推
2026-08-19 06:37:54
Yann LeCun
RT @KenRoth: Trump's approval rating fell to the lowest level of his presidency, ‌with an overwhelming majority of Americans concerned that his pointless war of choice with Iran will last a long time. https://trib.al/lqY75pX
中文: RT @KenRoth:特朗普的支持率降至总统任期的最低水平，绝大多数美国人担心他选择与伊朗的毫无意义的战争会持续很长时间。
#13 🔗 原推
2026-08-18 23:20:24
Yann LeCun
RT @FrakMAGA2022: So much for the 'law and order' crowd. Turns out, Trump's DOJ was busy running shakedowns, using "investigations" into college antisemitism as a cover. A whistleblower and a federal judge both confirm what many suspected: these were pre-baked ploys, designed not to find facts, but to harass, punish specific universities, and strip them of millions. Talk about weaponizing the government – they literally admitted there was no violation but pushed for settlements anyway. Pure political theater to grab cash. These are the same folks who scream about free speech being under attack, yet their own operation here was explicitly "designed to harass professors and administrators... to curtail their freedom of speech and academic freedom." They based investigations on a single newspaper article about "Free Palestine" protests, then pressured schools into paying hundreds of millions, essentially extorting cash with no admission of wrongdoing. Harvard fought it and won, proving it was all smoke and mirrors, a "large scale fraud" aimed squarely at their political enemies. https://www.ms.now/news/frame-up-whistleblower-says-probes-into-antisemitism-at-colleges-were-ploys-to-harass-and-strip-millions
#12 🔗 原推
2026-08-18 22:53:38
Yann LeCun
RT @McFaul: Kim Jung Un is the leader of a communist dictatorship. Trump embraces this communist as a friend. Trump also advocates government ownership in private companies. Yet, somehow, Trump supporters want you to believe that “Medicare for all” is the real communist threat. Absurd.
中文: RT @McFaul:金正昂是共产主义独裁统治的领袖。特朗普将这位共产主义者视为朋友。 特朗普还主张私营企业的政府所有权。 然而，特朗普的支持者希望你们相信“为所有人提供医保”才是真正的共产主义威胁。 荒谬。
#11 🔗 原推
2026-08-18 22:49:40
Yann LeCun
RT @KenRoth: Mysterious murderous attacks on boats off the coast of Ecuador suggest that "Trump’s boat strike program could be more secretive, larger, and more resistant to oversight than previously known." These are summary executions. Murders. https://trib.al/6X8jLra
中文: RT @KenRoth:厄瓜多尔海岸附近船只遭受的神秘凶残袭击表明:“特朗普的船只打击计划可能比此前已知的更加保密、更大且更能抵御监管。”这些是即决处决。谋杀案。
#10 🔗 原推
2026-08-18 22:38:00
Yann LeCun
RT @OneAvaz: @crampell “We promised to remove criminals from the country, so naturally we started with highly skilled workers and international students”
中文: RT @OneAvaz:@crampell:“我们承诺将罪犯从国内清除，因此我们自然而然地从高技能工人和国际学生开始。”
#9 🔗 原推
2026-08-18 22:36:52
Yann LeCun
RT @steeve: yeah so zml runs on: 1. NVIDIA 2. AMD 3. Metal 4. Intel 5. Trainium 6. Tenstorrent 7. TPU 8. MooreThreads 9. Vulkan and a few more very soon
中文: RT @steeve:是的，所以 zml 可以继续: 1。英伟达 2。AMD 3。金属 4.英特尔 5。火车 6.紧张 7.TPU 8.摩尔线程 9.武尔坎 很快再多几个
#8 🔗 原推
2026-08-18 22:25:34
Yann LeCun
RT @SteveRattner: Trump promised to balance the budget. Musk projected $2 trillion in savings. This year, the deficit grew by 18% — with $200 billion of that due to refunds of his illegal tariffs. My @nytopinion Chart https://twitter.com/SteveRattner/status/2089803408114856078/photo/1
中文: RT @SteveRattner:特朗普承诺将平衡预算。 马斯克预计将节省2万亿美元。 今年，赤字增长了18%，其中2000亿美元是由于其非法关税的退税。 我的@nytopinion图表
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#7 🔗 原推
2026-08-18 22:15:32
Yann LeCun
RT @SteveRattner: Trump said we'd grow "like nobody's ever grown before." Bessent promised 3% growth by the end of 2026. Instead, growth decelerated from 2.8% under Biden to 1.8% thus far this year. My @nytopinion Chart: https://twitter.com/SteveRattner/status/2089779449998774673/photo/1
中文: RT @SteveRattner:特朗普表示，我们会像以前从未长大过一样成长。 贝森特承诺到2026年底实现3%的增长。 相反，今年迄今，拜登执政后的经济增长从2.8%放缓至1.8%。 我的@nytopinion图表:
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#6 🔗 原推
2026-08-18 21:08:43
Yann LeCun
RT @DrNeilStone: mRNA vaccines are vaccines Chemtrails don't exist Turbo cancer doesn't exist Covid does exist Covid vaccines worked Ivermectin doesn't work for Covid Ivermectin doesn't work for cancer Vaccines eradicated smallpox Vaccines don't cause autism You're welcome
#5 🔗 原推
2026-08-17 16:05:54
Yann LeCun
RT @ShubhamAg0x: Physical AI evals are starting to become a real category. Until recently, most VLA evaluation was basically: LIBERO → success rate → leaderboard. Now we're seeing a much broader stack emerge: • Allen AI — unified VLA eval across 18+ simulation benchmarks • LeRobot — one eval interface across multiple sim benchmarks • PhAIL — real robots + production metrics like throughput and failures • Robocurve — independent, real-world robot evaluation • RoboDojo — bringing sim + real-world evaluation together The interesting part isn't just more benchmarks. It's the move from: “Can the robot complete this task?” to: “How reliable, fast and general is this system in the physical world?” I think independent physical AI evals are going to become increasingly important as robot models start looking more and more similar on demos.
#4 🔗 原推
2026-08-17 12:41:20
Yann LeCun
RT @DavidSacks: Some thoughts on Dario’s post: 1. Dario does not actually address Gavin Baker’s account of what he said – something he could easily deny if it were inaccurate. 2. Dario claims his critics live in a “bubble” where all regulation equals regulatory capture. He calls this an overly simplified view and notes that “Many people outside this bubble think of regulation as something that constrains corporate power and benefits ordinary people.” This argument is a straw man. Of course treating all regulation as capture would be overly simplified – but almost no one holds that view. I have repeatedly argued for strong antitrust enforcement to keep industries competitive, especially Big Tech. If Anthropic continues toward monopoly or duopoly status, I would be among the first to demand those rules apply. 3. Regulatory capture is not vague or in the eye of the beholder. Nobel laureate George Stigler defined it as regulation acquired by an industry and designed and operated primarily for its benefit. Stigler challenged the traditional view that government regulation arises from a benevolent state protecting the public from market failures. Rather, industry groups have concentrated stakes and pour resources into influencing regulators, whereas the public’s stake is diffuse and unorganized. The revolving door between companies and the agencies that regulate them compounds the problem. Anthropic understands these dynamics: it has hired multiple senior Biden AI-policy officials and built a substantial government-affairs operation plus a network of aligned organizations to push its preferred frameworks at state and federal levels. 4. Dario has consistently pushed for a new federal agency to review and approve frontier models prior to release – a proposal framed variously as an “FDA for AI,” an “FAA for AI,” and most recently a “FINRA for AI.” I call it a “DMV for AI” because a review process modeled on the FAA or FDA (which takes years) or FINRA (which issues rules for a staid industry widely seen as protecting incumbents) will create long queues as AI models wait for testing and approval. This process will only become more labyrinthine as rules accumulate to prevent theoretical harms. This would handicap the U.S. relative to China, which will not adopt the same constraints. It would also undermine Anthropic’s own business model, whose pricing power depends on remaining ahead of open models. Whatever Dario states today, it is difficult to believe the company would simply accept outcomes that erase that advantage. 5. Anthropic is on track to become one of the most valuable companies in history, with the resources to navigate any approval process and shape the rules while competitors wait. Dario wants open models under heavier scrutiny – he has called them dangerous in Senate testimony, criticized them for not being centrally monitored or withdrawn, and linked them to IP theft. He says he has never sought a ban, but he could achieve a similar result by insisting that identical rules apply to both open and closed models. The U.S. risks becoming an island of costly closed models while the rest of the world races ahead with broader choice. 6. Dario acknowledges that AI is structurally centralizing but attributes this mainly to chips and scaling laws. Access to compute matters, but the deeper risk is who decides which capabilities are available to whom. His preferred pre-deployment testing and FAA/FINRA-style oversight would place that gatekeeping power in a federal bureaucracy working hand-in-glove with a small number of frontier labs – reinforcing centralization rather than countering it. 7. The second part of Dario’s post assumes we have amnesia about Anthropic’s well-orchestrated campaigns hyping AI fears. His May 2025 claim that AI would wipe out 50 percent of entry-level knowledge jobs within five years still lacks supporting evidence fifteen months later. Similarly Anthropic breathlessly promoted its heavily contrived “blackmail” study on 60 Minutes. Yet Dario blames public negativity on a long-standing loss of trust in institutions rather than his own messaging. 8. These narratives have done more than anything to shape public fear. People are left asking the same question Mark Zuckerberg posed: why race to build a future you describe in such negative terms? Thomas Sowell’s "The Vision of the Anointed" captures the mindset – elite intellectuals convinced that only they are enlightened enough to control the outcome. As Zuckerberg notes, concentrating power in the hands of an enlightened few has rarely produced the promised results; the practitioners turn out to be less enlightened in practice than in self-conception. 9. Gavin Baker summarized the disagreement cleanly on our pod: Dario believes frontier AI is too powerful to distribute; we believe it is too powerful to centralize. Dario appears to believe, sincerely, that safety and progress are best served by centralizing authority in a marriage of corporate and state power. The weight of human history gives us reason to fear that outcome.
#3 🔗 原推
2026-08-17 12:35:14
Yann LeCun
Dario is wrong. He knows absolutely nothing about the effects of technological revolutions on the labor market. Don't listen to him, Sam, Yoshua, Geoff, or me on this topic. Listen to economists who have spent their career studying this, like @Ph_Aghion , @erikbryn ,…
中文: 达里奥错了。 他对技术革命对劳动力市场的影响完全一无所知。 不要听他、山姆、约书亚、杰夫，或者我这个话题。 听听那些在职业生涯中研究过这个问题的经济学家，比如 @Ph_Aghion，@erikbryn ......
#2 🔗 原推
2026-04-18 21:07:15
Yann LeCun
@geoffreyhinton You and Yoshua are inadvertently helping those who want to put AI research and development under lock and key and protect their business by banning open research, open-source code, and open-access models. This will inevitably lead to bad outcomes in the medium term.
中文: @geoffreyhinton You 和 Yoshua 正在无意中帮助那些希望将人工智能研发置于锁定状态并保护业务的人，通过禁止开放研究、开源代码和开放访问模式来保护他们的业务。 这不可避免地会在中期内导致不良后果。
#1 🔗 原推
2023-10-31 19:13:51