Codeye @gridvision

AI 都快把大学教育打成夕阳产业了，有个人今年 31 岁，已经读了 12 个顶级大学学位，而且还没准备停。 《纽约时报》最近写了一个故事。 主人公 Jamie Beaton，Harvard 本科，之后一路读 Stanford、Yale、Oxford、Princeton、Cornell、Dartmouth、清华、Columbia，现在又跑去 Brown 读数据科学。 正常人的 LinkedIn 学历栏是简历，他那个已经有点像滚动字幕了。 更离谱的是，他还不是那种什么都不干、专门靠读书刷成就的职业学生。 Jamie 十几岁的时候就在新西兰研究怎么申请美国名校，高中毕业拿了 Harvard、Yale、Princeton 等 25 所大学的 offer。进 Harvard 前，他已经开始做 Crimson Education，后来一边上学，一边把这家公司做到了超过 6 亿美元估值。 他在 Harvard 时加了 15 个学生组织，凌晨两点还在处理公司电话；大二自己给 Tiger Management 创始人 Julian Robertson 发邮件，后来每周两天从波士顿跑纽约工作，Tiger 最后还投了 Crimson。 后来到了 Columbia，又出现了一个很好笑的场景。 老师开学以后发现 Jamie 怎么一直不来上课，一问才知道，他人还在新西兰，因为把课表搞错了。 他当时正在奥克兰大学给别人上创业课。 过几天飞回纽约继续当学生，作业一份没落，电脑上同时开着工作邮件和股票账户，最后还顺手在班里认识了现在的老婆。 他老师 Amy Chua 对他的评价特别准确： 「他就是停不下来申请东西。」 Jamie 自己倒不觉得这有什么奇怪。 前几个学位，他说是为了补具体能力，后面越来越像兴趣驱动。今天在 Princeton 学量化金融，明天就能拿公司里试；白天经营一家几亿美元的公司，晚上继续回学校交作业。 这也是我觉得这个故事在 2026 年特别有意思的地方。 这两年大家天天讨论 AI 会不会把大学干掉，知识越来越便宜，课程越来越不值钱，甚至一个顶级教授讲半年才能教完的东西，以后一个 Agent 几小时就能帮你搭完整套学习路径。 Jamie 偏偏走到了另一个极端。 当获取知识越来越不需要学校，他却把学校读成了一种基础设施。 他要的可能早就不只是那张文凭了。 教授、同学、研究环境、跨学科的训练，以及强迫自己在一个陌生领域重新当学生，这些东西暂时还没那么容易被一个聊天框完全替掉。 当然，这里面也有一个很讽刺的地方。 Jamie 自己经营的 Crimson，卖的恰恰就是一套高度工业化的精英教育路线，怎么规划、怎么选学校、怎么把一个十几岁的孩子送进 Ivy League。有人愿意为这套服务花几十万美元。 一边是 AI 在把知识的价格疯狂往下打。 另一边，最顶级的教育 credential、筛选和圈层，价格还在继续往上走。 AI 可能会让学东西越来越便宜，但被谁承认你学过东西，目前看一点都没有变便宜。 Jamie 读到第 12 个学位，知识正在变得免费。 名校还没有。

Jamie Beaton @JamieBeaton_nz

2 days ago

It was surreal to see my academic adventures on the front page of the @nytimes Here’s how I built Crimson Education almost entirely while at universities:

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Electronics & wiring are the trickiest part of assembling a robot. We’re shipping an entirely new experience for electronics in your @tnkrdotai repository. Goal is to make it 10x easier to document your electronics system & 10x easier for anyone to assemble. Every team / builder needs this.

Ufoliumで群論と解析力学のシリーズが始まりました！

Ufolium @ufolium

3 days ago

群論のエッセンス 「第1回 群とは何か、ケーリー図」を公開しました！

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Good news for Figma, I’m done for today 🙏

Alex Socoloff @socoloffalex

3 days ago

Bad news for Figma, its 7:50AM and I ran out of coffee ☕️

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Riemann's housekeeper burned the papers, and what survived was seventy years ahead of everyone ✍️ Riemann died in 1866 and his housekeeper burned much of what he left behind. What escaped went to Göttingen as the Nachlass, 52 compilations of manuscripts, calculation sheets and drafts. The famous 1859 paper on prime numbers is eight pages long and states results without proof, which led Landau and Hardy in the early 1900s to complain that Riemann had conjectured much and proved almost nothing. Then in the early 1930s Carl Ludwig Siegel spent about two years deciphering the surviving scraps. He found that Riemann had proved much of what the paper merely asserted, and worse, had developed things nobody had rediscovered in seventy years. Hardy and Littlewood had recently derived an approximate functional equation for the zeta function and obtained only the dominant term; Riemann had the same formula and a method for estimating the remainder. Siegel published in 1932, and the result, now the Riemann–Siegel formula, went straight into current research rather than into the history books. It is still the standard tool for computing zeta zeros at large height. Riemann had also hand-calculated the first several zeros. The uncomfortable implication is that we have no idea how much was in the part that burned.

Four months after he walked out of the Eurogroup, he stood in front of a business school and explained what the room he had just left actually does. Almost nobody watches the whole hour. Yanis Varoufakis, Vienna University of Economics, 4 November 2015. Former Finance Minister of Greece, 7 months in the job, out after voting against the third bailout. Photographers on the floor, a low table, a glass of water, a panel about to sit down. The subject is money and power, and he is one of the few people who has seen both sides from inside. Watch the stretch where he describes how decisions get made in a body with no minutes and no vote on record. He negotiated with that room in July. In November he described it.

Moysei @0xMoysei

2 months ago

x.com/i/article/2085…

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reddit.com/r/FAANGJobs/s/…

AI's energy problem is now so severe that companies are restarting decommissioned nuclear plants just to power GPU clusters. Your brain runs everything you think on 20 watts. A single LLM training run consumes what a small city uses in a year. So a few researchers stopped trying to build better chips and started growing them instead. Cortical Labs built CL1 – 200,000 human neurons grown from skin cells, spread across electrodes, trained to play Doom. Not by programming, by punishment: chaos signal when they fail, calm when they succeed. The cells aren't playing to win. They're trying to make the noise stop. Final Spark now rents human mini-brains over the internet – same pitch, same logic, up to a million times less power than silicon. 12 minutes. Bookmark & watch today. The most uncomfortable thing happening in AI infrastructure right now.

Eron @0xEronn

3 weeks ago

x.com/i/article/2097…

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如果你手里有一份来路不明的软件，想知道它到底在背后偷偷干了什么……你不需要花几万块买商业软件。 你只需要打开这个来自美国国家安全局（NSA） 的官方逆向工具——Ghidra。 这本来是 NSA 用来抓病毒、找漏洞的国家级装备。里面藏着他们十多年积累的团队协作逆向技术 。 现在 GitHub 上直接免费下载。 重点来了， 这东西支持几乎所有你知道的操作系统（Windows、Mac、Linux），甚至能分析路由器和物联网里的芯片 。 最细思极恐的是，早在 2017 年维基解密曝光的 Vault 7 文档里，CIA 就提到过 NSA 一直在偷偷用 Ghidra 。

柴郡🔔｜Crypto+AI Plus @0xCheshire

4 weeks ago

微软这个开源语音项目 VibeVoice，有点厉害的。 60 分钟的会议、播客或访谈，可以整段直接丢进去语音识别，不用切成几十个小片段。 输出也不只有文字，还会直接整理出： 谁说的 + 什么时候说的 + 具体说了什么。 还支持自定义人名、术语等热门词汇，覆盖 50+ 语言。 VibeVoice-ASR-BitNet

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卧槽，这谁干的！！？ 一个人把 ElevenLabs 开源了，还让你装自己电脑上跑。 GitHub 都快 2 万星了，仓库叫 VoiceStudio。 你就给它一段干净的人声，它能把这声音学下来。视频也能配成 646 种语言。有声书、听写、转文字它也干。 引擎还不止一套，给了 14 个。ElevenLabs 自己才 32 种语言。不按字收钱，也没次数限制，音频也不上传。 地址在这： github.com/debpalash/Voic… 有人用 5090 跑过，说还差点意思。但这个不用掏钱，声音还留在自己电脑里！还要什么自行车！

Generative Antitecture. This is not a house. This is automatic architecture. // Vanilla Javascript

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AI这下帮大忙了！ 朋友家里被盗了，去调监控视频，总共400多个视频，累计20多个小时，这要人去看，不得累死。 用Codex手搓了一个监控视频AI分析器，自动对这400多个视频抽帧、ffmpeg静态画面过滤、拼16宫格交给GPT-5.6-Luna进行分析。 GPT-5.6-Luna价格便宜，特别适合干这活，跑了几个小时就定位到了关键画面👍 因为出于实用，所以就没考虑UI美观问题了，能用就行。

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最全的金融数据 MCP 服务 这是我用过最全的金融数据MCP。现在的Agent用来辅助分析和研究最担心的是金融数据不全或者滞后，这个库完美解决这个问题。 这个库把 A 股、港股、美股、基金、债券、期货、加密资产、宏观和新闻等数据统一接入 AI。核心优势是 19 个工具、多数据源智能路由、自动降级、数据来源可追溯、支持技术指标和 stdio/HTTP 双模式，能让 AI 更方便地完成金融分析与投研。 仓库地址：github.com/guangxiangdebi… 我是尼卡，平时会持续分享 AI、美股、Web3 相关有用又有趣的工具和项目，感兴趣的话欢迎关注，下次见～

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Jealousy 尼卡 @eastweb3eth

2 weeks ago

缠论量化分析与策略研究（大全集） 如果喜欢缠论，即想读文章又想有工具可以用，收藏这一个库就够了。而且没想到这个库竟然已经拿到了 6.1K星，缠论的粉丝可是真多啊！ 先说一下这个库包括什么： 1. 缠论全部文字内容整理：chzhshch.blog 一共全部1135篇博文。 2. 缠中说禅图解分析示范 3.

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whoever leaked this has bigger balls than sense someone handed GPT-6 Astra a port's public records and one question: what does not add up. it flagged a plant that officially burned down three years ago and still received containers weekly. the owners had collected $184,000,000 in fire insurance, renamed the company and kept producing. the tip paid $18,400,000 every fake fire, fake bankruptcy and fake shutdown leaves a trail in four public databases. almost nobody reads all four together this is GPT-6 Astra, the layer that reads every public record about one address at once, $0 on top of the plan you already pay for: - pull the customs manifest: by law every container entering the US by sea leaves a record the press may copy and publish, shipper, receiver, cargo, weight, ship. hand Astra the whole export - add the ships: every vessel over 300 tons has broadcast its position on AIS since 2004 and has to keep it on. a weekly port call becomes a count - check it from orbit: NASA FIRMS logs every fire seen from space within 3 hours, date and size included, and Sentinel-2 photographs every point on earth every 5 days at 10 metres, free. a lot full of trucks is not a ruin - let Astra cross-check: 1,050,000 tokens of context, 96.3% recall across a million of them, 4.2% hallucinations. ask for only what the documents prove - file it: the SEC pays 10 to 30% of what it collects once a case clears $1,000,000 and seals your name. its biggest cheque, $279,000,000, went to someone who only widened a case already open none of this was hidden. it was scattered the catch is slow money. nothing is paid below $1,000,000 in sanctions, only after the case closes, and an importer can hide its name on the manifest for two years at a time fraud is a story told to one database at a time every month you scroll past this, someone else's Astra is reading the same public files bookmark this, how to hand Astra a whole problem instead of a question is in the post below ↓

Argona @Argona0x

2 weeks ago

x.com/i/article/2098…

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The Lagrange Points: The Parking Spaces of Space youtu.be/2LjGgJ4ST60?si… 来自 @YouTube

家人们，刚洗完澡刷到个开源项目，人直接傻了。 OmniVoice，Python写的，GitHub星快到1万了。本人声控，看到这种直接反手一个star，别问，问就是手熟。 它能干嘛？一句话糙理不糙：你录一段自己说话的声音丢进去，它给你整个人声纹都扒下来。不是模仿，是真·复刻，就跟你亲嘴说话一样。 我拿自己那口带汤粉味儿的塑料普通话试了试，它给我整出一段英语，还自带慵懒气泡感。我听完愣了一下，这还是我？我英语要能有这么顺，当年四六级早过了。 600多种语言，年龄音高方言气音全给你调，关键是还不用提前训练，扔进去就出活。 更离谱的是，生成速度比实时快40倍。你说完一句话，它那边已经把你声音塞进日语韩语法语西语里滚了一圈了。 剪视频、搞多语言内容的家人，这玩意儿等于白嫖一个配音团队。 链接丢这了，自己拿去玩：github.com/k2-fsa/OmniVoi…

Financial Machine Learning (159 page PDF) Download it here:

In 1967, Canadian mathematician Robert Langlands wrote a letter to a colleague describing a connection between the far-flung realms of number theory and harmonic analysis. It led to one of the most ambitious projects in all of mathematics. quantamagazine.org/what-is-maths-…

I bought a Fable dataset from one of the top Chinese LLM routers yesterday. With just 6TB data, I can take over 7 Chinese/CIS gov entities & 19 top Chinese firms like Xiaomi, Huawei, NIO, Minimax using SSH keys, VPN configs, Aliyun keys, GitLab tokens sent to the router.

Chaofan Shou @shoucccc

6 months ago

26 LLM routers are secretly injecting malicious tool calls and stealing creds. One drained our client $500k wallet. We also managed to poison routers to forward traffic to us. Within several hours, we can directly take over ~400 hosts. Check our paper: arxiv.org/abs/2604.08407

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“𝘐 𝘸𝘢𝘴 𝘢𝘴𝘩𝘢𝘮𝘦𝘥 𝘰𝘧 𝘮𝘺𝘴𝘦𝘭𝘧 𝘸𝘩𝘦𝘯 𝘐 𝘳𝘦𝘢𝘭𝘪𝘻𝘦𝘥 𝘭𝘪𝘧𝘦 𝘸𝘢𝘴 𝘢 𝘤𝘰𝘴𝘵𝘶𝘮𝘦 𝘱𝘢𝘳𝘵𝘺 𝘢𝘯𝘥 𝘐 𝘢𝘵𝘵𝘦𝘯𝘥𝘦𝘥 𝘸𝘪𝘵𝘩 𝘮𝘺 𝘳𝘦𝘢𝘭 𝘧𝘢𝘤𝘦.” — 𝘍𝘳𝘢𝘯𝘻 𝘒𝘢𝘧𝘬𝘢