Rest at the edge of chaos. .... . .-.. .--. -....- -- . God plays dice. Maybe that's a feature, not a bug. 一切都会好起来。

崩溃边缘 Edge of Chaos
Joined December 2009
如果用“权力”理论解释的话。 越接近权力的中心越禁忌。 当权力来源于某个群体,那这个群体就不能被贬低,比如有投票权的人。 当权力来源于某个偶像,那这个偶像就不能被贬低,比如安拉。 当权力来源于某个阶级,那这个阶级就不能被贬低,比如天龙人。 要清楚你是拥有权力的一方还是被权力奴役的一方。
这边大部分人对于言论自由的概念是种族歧视,常见句式是:“每个地方都有每个地方的禁忌,你们欧美也不可以开黑人,LGBTQ,犹太人玩笑”等等…………
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谎言不会伤人,真相才是快刀。 你说Trump 是独裁者,他不但不会急眼,还会四处发自己是King 的meme。 但是你说Trump 是傻逼,他是真的着急,四处找证据证明自己是Stable genius.
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如果他真的只是有查资料的需求的话🤔 我自己当他的中转站,他把需求发给我的bot,让bot自己去查不就好了
我们健身房的医生问我该怎么翻墙😂他想用ChatGPT... 他跟我说他只是想查手术和医学资料。。。 如果他的需求只是这些的话🤔我是不是该介绍给他个中转站呢?
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阿橡 retweeted
Everyday is zero-day these days
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2023: GPT-4 almost solved grade-school math 2024: IMO silver 2025: IMO gold 2026 May: Erdős unit-distance conjecture 2026 Sep: Navier–Stokes Millennium Prize Problem solved 2026 Oct: 722 AI-written math manuscripts Today: OpenAI proves ETH is false Tomorrow: P = NP?
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我不知道大家怎么理解ETH这件事。 我还认识一些TCS领域的人。有些老教授的此刻正在经历精神世界乃至大半生心血被时代巨浪瞬间重塑的极限冲击,这样说也毫不为过。自从数十年前,这一假设被提出以来,ETH 就一直是理论计算机科学中,用来证明某个问题到底有多难、算法下限在哪的最核心的基座之一。 插一句,其实还有SETH,强指数时间假设。如果ETH完蛋了,那SETH也完蛋了。ETH和SETH就是算法复杂度理论的“牛顿三定律”级别的基座。如果这些都是错误的,那很多技术护城河,就是纯废铁。 在学术界,有多少篇的论文都是建立在假设 ETH 为真的前提下展开推导的? 答案是,很多很多。推特已经有人做了论文的总结。ETH彻底证明错误将失去任何价值的论文。ETH这个大前提被 AI 证伪了,意味着成千上万篇基于它的复杂度分析、衍生证明、理论模型,在逻辑的源头上瞬间失效,彻底失去意义。 你现在和ChatGPT、Claude聊,它可能会假惺惺地安慰你,说这是科学的必由之路,是人到机器火炬的传递。是的,我承认它们说的在某种意义上没错,但是这是科学本身的递进本质。我从来不否定对于整体人类和科学进步来说,ETH错误确实是一场伟大的纠错,但对于被大厦崩塌砸中的每一个活生生的个体来说,那些数十年的通宵不眠、熬干的心血、甚至为此放弃的无数个人生活,在一夜之间沦为废纸,其代价就是成为AI时代的炮灰。 在科学的漫长进程中,这种大厦一夜倾覆的个体悲剧曾无数次上演。当爱因斯坦证明绝对时空观错误时,无数研究了一辈子经典力学的物理学家在一夜之间失去了方向;当以太假设被证伪时,那些为之付出大半生心血的科学家也曾陷入同样的虚无与绝望。现在,我们仿佛就在那个节点上。
不想传播焦虑,但这次我无话可说。 今年科学界最大的新闻,没有之一。OpenAI 的内部 AI 模型自己做出了三个科学难题的成果。我用我自己的理解说一下。 第一,Kakeya 猜想。这个问题研究波聚焦时会怎样。原来的猜想我记得是说最极端的聚焦只会持续很短时间。人类以前只在低维度证明过,OpenAI 说它的模型证明了所有维度的情况,因此顺带解决了 Kakeya 猜想和 Stein 限制猜想。纯逆天。 第二,指数时间假说 ETH 被推翻。这个太难以置信了。ETH 好像是说有一类逻辑难题不可能被比暴力穷举快很多地解决。而之前学界普遍相信它成立,几百篇论文都以它为前提,现在 AI 却证明它是错的。 这个太他喵逆天了,因为我之前是研究过一段时间理论计算机的。这几十年ETH几乎被当成公理在用。很多论文的结论都写成假设 ETH 成立,那么某某问题不可能在多少时间内解决。现在地基没了,这些不可能,全都要打问号。 最让我感觉匪夷所思的是 AI 证明的方式。据 Lean 证明的说明文档,它给出的是一个确定性算法,应该是对固定宽度的 k-CNF 公式,它能在亚指数时间、多项式空间内精确数出所有满足的赋值。但是,懂行的人应该都知道“数出有多少个解”通常比“判断有没有解”难得多,它连更难的那个都做到了,所以 ETH 只是顺带被推翻。 第三,杨-米尔斯、量子色动力学。AI 应该是给出了一套严格的数学证明,证明描述强核力的理论在数学上确实成立,其中包括纯杨-米尔斯理论的存在性,这是千禧年七大难题之一的一部分。我不太了解,但是只是知道一些浅层的理论,就不评论了。 最让我恐惧和惊骇的是第二个。今天晚上我看了又看,感觉这是地震级别。如果最终确认无误,这会是 AI 第一次独立推翻一个被广泛相信的核心猜想。说它是一个时代的分界点,也毫不夸张。 如果这三个都核查通过,这代表 AI 第一次在多个顶尖领域独立解决了几十年没人能解决的难题,影响史无前例。
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Probably.
p still probably doesn't equal np
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天真塌了😭
Announcing three major scientific discoveries, one each in mathematics (harmonic analysis), computer science (complexity theory), and physics (quantum field theory). AI starting to help us improve our understanding of the universe! openai.com/index/building-sc…
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最近翻墙这么不稳定,原来是因为开大会嘛?
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我们健身房的医生问我该怎么翻墙😂他想用ChatGPT... 他跟我说他只是想查手术和医学资料。。。 如果他的需求只是这些的话🤔我是不是该介绍给他个中转站呢?
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完了,我有点嗑你俩了。 “有哪些优秀的百合同人作品?”
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又到了一年中最想死的时间了。。。
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Workbuddy 的日活已经1300万了嘛! 腾讯强到过分了。。。
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AI房产经纪人,第一单成交了 来吧,大裁员时代,谁都逃不过 36kr.com/p/4037778327720835
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我刚刚了解了一下,才知道胡塞武装跟ISIS不是同一个派别,甚至是不同的极端。 他们的共同点只有都会屠杀平民。
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今年的万圣节,会不会有人cos豆包,Deepseek ? 我已经看到有人Cos娘化马尔福了😂
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平台对用户的影响真的太大了。 我认识一个小学老师,去年她说她喜欢看的内容和今年她喜欢看的内容是完全不同的。 比如去年她喜欢看的都是产生瞬间多巴胺的内容,今年她喜欢看的都是点收藏想要之后再回来看的内容。 而我刚好知道这是抖音对于创作者内容激励的改变方向。 她自己可能没意识到自己的改变
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我认为我获取信息的方式有问题。 这么好的tweet,我居然是先在墙内看到有人提,然后才跑到推上来看原文的…… 比tweet发布的时间晚了整整十天。 我需要减少低价值信息在我时间线上的暴露程度。 也许我需要一个agent 专门帮我做这个事情。
Assorted things I've been mulling over regarding agents in the economy: • Companies are in some sense the original superintelligence. It's often the case that they can use their amortized cognitive surplus to advance their interests against those of certain consumers: relative to the optimization capacity of companies, consumers can be inattentive, underinformed, irrational, etc. (Think, say, of some of the classic insurance upsells at the end of a booking process, which is typically priced substantially above what a regular policy would cost.) Herbert Simon introduced the idea of bounded rationality, and firms often end up benefiting from it. Thanks to personal agents, we will probably get somewhat more rational in how we engage with companies. • How exactly will outcomes change? Well, certain kinds of price discrimination will work less well (how do coupons work if every agent hunts fastidiously for them?), and certain kinds of customer cross-subsidy will change (today, people who forget to cancel subscriptions subsidize those who don't). Taken across the economy as a whole, I'm not sure what the incidence of all of this will be. • In corporate strategy, people have long debated the relative importance of distribution and product quality. Perhaps you've made something better, but does anyone know about it? Won't people just continue to buy the ACME Corp Mousetraps? Personal agents will, I think, act as a kind of structural subsidy for product quality. How would markets look different if individuals always spent at least 10 hours researching their purchases? On the margin, focusing on making a product better is, I think, going to become a more effective strategy for companies. This is good! • It true, a corollary is that information about product quality will become more important and impactful. Today, most people have very limited ability to aggregate and integrate such data, but agents will have insatiable thirst for such signals. (It's often said that data is becoming more valuable because it helps in the training of models. That's obviously true, but I think there's a secondary way in which it's more valuable simply as a complement to cheaper intelligence.) • A big question is whether agents will increase superstar effects (rational agents all settle on the same product) or increase dispersion (because everyone has slightly different tastes and preferences, which agents are good at eliciting, finally overcoming the artificial clustering we've been subjected to). • Many internet companies have monetized demand routing, which is in turn often predicated on short attention spans. "I'll click on the first thing I see." This has led to some amount of inefficiency, as companies try to propitiate capricious ranking algorithms and incur various placement fees. It's not all deadweight loss (willingness to pay is itself a kind of signal, which is valuable to buyers), but it's not great. How will the nature and value of this routing change in a world of personal agents? I don't know the answer, but I think that the effects might be pretty big. • Much of what I'm writing hinges on the assumption that personal agents will be on the consumer's side. I suspect that that will be the winning strategy, but whether it's true, and what it means to be true, involves a lot of other questions. Taken as a whole, the market is a massively parallelized, decentralized, and highly imperfect value attribution machine, and, taking stock of all of the effects, it seems to me that the quality point may well be the biggest: that agents will change the nature of the backpropagation such that the rewards for better products increase. Maybe this is too optimistic, but I suspect (and hope) that companies that make things that they're proud of will feel that the universe is a little more partisan in their favor.
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