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逛 HN 的时候，看到了这一篇挺有价值的帖子，作者从 5 万多个书签里，整理出了自己心中的 S 级可视化教程。 在 AI 时代来临以前，大家会花费巨大的精力和时间去手敲写博客和教程 于是才有了下面这些非常优质的教程，AI 时代来临以后，还有人会做同样的事吗？ HN 原帖： 🎮 互动游戏 / 动手学习 从逻辑门开始造一颗 CPU 用游戏学习 Git 分支 用游戏学习 CSS Grid SQL 侦探游戏 另一个 SQL 解谜游戏 从零组装一个神经网络 机器人实时 3D 仿真 🧠 AI / 机器学习 交互式理解 Transformer 可视化理解 K-means 聚类 视觉 Transformer 图解 机器学习可视化入门 线性回归、逻辑回归与神经网络 神经网络的前向传播与反向传播 FAISS 向量检索原理 💻 编程 / 计算机基础 算法可视化 从零实现 React 从零“造”一块 NVIDIA GPU 一次请求如何从浏览器到达服务器 网络七层模型 限流算法 椭圆曲线密码学 🎨 图形学 / 游戏开发 颜色、屏幕、图形、渲染、着色器、编译器与解释器 用 Rust 和 Bevy 搭建 3D 编辑器 Vulkan 图形管线 碰撞检测、着色器、渲染与剔除 📐 数学 / 物理 交互式概率论 线性代数与向量 引力如何工作 ⚙️ 工程 / 硬件 内燃机工作原理 芯片制造流程

Introducing Prime Agent: A self-improving RLM harness for coding and long-running autonomous tasks. Designed to be both token-efficient and expressive through programmatic tool calling, context as a variable, multi-agent messaging, and a self-modifiable harness state.

💫𝙉𝙚𝙬 𝘼𝙧𝙧𝙞𝙫𝙖𝙡💫 メガニケエレグ風ダボダボの黄色フードつなぎ×赤スリングショット水着コスプレが登場💛 大胆なフロントカッティングが腰位置を高く魅せ、メリハリのある美しいボディラインを演出😍🌊 ▶️

Last night Apple briefly removed Telegram from the AppStore because a user had planted illegal porn in a public chat. Telegram was restored within hours. But I want to explain what happened — to warn other app developers and help protect online communities from similar attacks. Because Telegram quickly removes illegal content from public groups using all kinds of moderation tools, the attacker had to resort to a technical trick. He inserted AI-modified illegal content by editing an old message in an active group chat. As a result the content was effectively hidden from the group’s members, preventing them from seeing/reporting it. The attacker was a takedown extortionist: someone who demands ransom from group owners in exchange for not targeting their communities. These extortionists use automated accounts to plant illegal content in public groups and then report it directly to Apple, attempting to trigger the removal of legitimate communities whose owners refused to pay them. From a practical standpoint, illegal pornographic content in Telegram’s public groups is not a systemic problem. Our moderation is effective. The fact that attackers must resort to backdated, effectively invisible content and other technical tricks proves this. ⚠️ However, there are two important lessons here for app developers and online communities: — Extortionists have found a way to manipulate Apple into overreacting. Apple removed Telegram from the App Store before contacting us. This creates a potential systemic risk for every mobile app that hosts user-generated content. If an app used by more than a billion people can be removed from the App Store without prior warning, any app can be. — The tactics used by takedown extortionists are evolving, putting communities across social platforms at risk. Telegram has extensive experience identifying the tricks used by coordinated reporting gangs and protecting legitimate communities (even when doing so risks our own app being temporarily removed from the App Store). Other platforms may not be equally prepared. Stay vigilant! ☝️

ICYMI: our July AI recap ⬇️ 🌦️ Advanced weather forecasting with @NOAA and Google Cloud, using high-performance H4D virtual machines to run its atmospheric models, providing meteorologists with the AI capabilities needed to deliver life-saving early warnings. 💻 Introduced 3 new Gemini models — Gemini 3.6 Flash, 3.5 Flash-Lite, and 3.5 Flash Cyber — to deliver the efficiency, latency, and reliability to build AI agents at scale. 🇺🇸 Launched the Alliance for America’s Skilled Trades With BlackRock, Carhartt, and Ford to build a stronger pipeline for the skilled trades, scale evidence-based training approaches, and expand opportunities nationwide. ☁️ Rolled out AlphaEvolve, our Gemini-powered AI code-optimization agent, to help Cloud customers solve their hardest problems by automatically searching for better solutions and returning human-readable, optimized code. 🎵 Delivered significant advancements in musicality, lyrics, and vocal quality in Google Flow Music with Lyria 3.5, our newest music generation model. 📡 Launched three new FireSat satellites, expanding a global initiative led by the Earth Fire Alliance (EFA) with @GoogleResearch to help detect wildfires before they spread. 🧪 Established over 15 global bioresilience partnerships across governments, research groups, and biosecurity organizations to prevent model misuse, detect outbreaks rapidly, and deliver swift, coordinated responses in partnership with @IsomorphicLabs.

Okay, the @VulcanBench results for Qwen3.8-Max are in, and it is not what I expected. First, for anyone new to VulcanBench, here's a quick TL;DR on the eval suite: 23 frontier-hard software engineering tasks taken from real merged OSS PRs, run in a Docker sandbox, 3 runs per task across all three of its effort levels. No puzzles, no random abstract stuff, all real things engineering teams would do with these models. It looks like Qwen3.8-Max has a major overthinking problem, it uses a LOT of tokens and is very slow, period, no other way to see it. My cost to run this benchmark was $126.25, to run the exact same eval suite with DeepSeek V4-Flash was only $13.60. This makes Qwen3.8-Max an insanely expensive model. The tasks Qwen genuinely can't solve fail at every effort level, extra reasoning didn't help. The regression is almost all in work it already handles: six tasks that low solves every single time account for 83% of the 26-point drop, three of them collapsing to zero. It's not losing the hard problems. It's losing the ones it already knows how to do. Since Qwen3.8-Max hit a lot of wall clock budget caps, I thought I'd share more about this. - VulcanBench caps both steps (50–200) and wall clock (5–60 min), each scaled by repo size. - This is aligned with how comparable harnesses bound agents, DeepSWE caps rollouts at 100 environment steps, sitting right inside my step range; Terminal-Bench enforces a per-task wall clock; SWE-bench Verified scaffolds typically allow 20–60 min per instance with 250–350 step limits. - Every model on my chart gets the identical budget, and Qwen is the slowest model I've tested at 20–25 min/task. Soooo... Alibaba positions Qwen3.8-Max as trailing only Claude Fable 5. But on the kind of real coding work engineering teams would actually throw at it, under a fixed budget, its best setting lands mid-pack and its default lands last, so common. If you want to optimize for accuracy, Grok 4.5 is the move. If you want accuracy per dollar, DeepSeek V4-Flash is hard to beat, heck it's 10× cheaper than Qwen and you get higher accuracy. Qwen just isn't in the game at this point, this is not a model I could see engineering teams using for daily coding work.

🚨 BREAKING: Apple filed for a PRELIMINARY INJUNCTION against OpenAI AND asked a federal judge to put them under forensic supervision "Apple respectfully moves the Court for a preliminary injunction to stop THE THEFT OF ITS TRADE SECRETS" Apple filed NINE sworn declarations, a 28-page memorandum and a concurrent motion for expedited discovery What Apple now says, under oath: Chang Liu: 8 years at Apple, now OpenAI "Member of Technical Staff" exploited an authentication bug to steal Apple trade secrets "on AT LEAST FIVE SEPARATE OCCASIONS" from February to April 2026, WHILE working for OpenAI Liu downloaded "THOUSANDS OF PAGES of Apple's most sensitive trade secrets" The stolen files, NAMED: >DisplayNotes.key — "several hundred pages" on Apple's custom display power development program >Architecture analyses. Fabrication decisions. Testing results >Engineering data for an UNANNOUNCED Apple product: 'touch, display, and power systems" >Final.key + V2.key — compilations of two undisclosed Apple R&D projects >and those are "only four of the dozens of proprietary documents Mr. Liu stole" Liu fed OpenAI "a steady stream of Apple proprietary information that he actively concealed" Liu also "coached Yu-Ting "Alyssa" Peng, then still INSIDE Apple, how to access and copy files from Apple workstations "to avoid trouble with the security team" and directed her to communicate with him on the encrypted LINE app "to avoid detection" Tang Yew Tan: 24-year Apple VP, now OpenAI's Chief Hardware Officer, "used an Apple internal project codename for an unannounced product to elicit still more trade secrets from job candidates." Tan's own messages, quoted in the motion: >"Just like last time, bring some parts you worked on" >"mlb, battery, shields type of stuff is interesting" OpenAI recruiter, quoted: "No, you won't sign anything at the exit interview. If they do ask you to sign anything, let me know asap." APPLE TOLD FEDERAL JUDGE: >"OpenAI knows its misappropriation is wrong and has tried to conceal it." >"This is not a case of 'mere hiring'... it is a case of repeated instances of deliberate theft." Apple says OpenAI went after its SUPPLIERS: >OpenAI "directed a trusted Apple partner [name redacted] to perform [Apple's proprietary metal finishing] process for them, knowing it was proprietary to Apple... because they were involved in this partnership while at Apple." Apple put its own Surface Finishing Manager, Jackie Hughes, under oath to prove it. Apple named ELEVEN MORE former Apple employees at OpenAI — beyond Liu, Tan, and Peng — Fourteen people total. Apple also filed a concurrent motion for EXPEDITED DISCOVERY demanding depositions: - Liu. Tan. Peng. - A fourth unnamed OpenAI employee - Plus OpenAI itself, under oath, through Rule 30(b)(6) Apple has asked a federal judge to put OpenAI under forensic supervision RIGHT NOW: >Forensic inspection of ALL OpenAI devices >ALL cloud storage, Slack, email >Including anything that "previously contained" Apple data — deleted included Demanding the "first available hearing date," citing "imminent threat" to its trade secrets. APPLE: > "The harm is happening now — every day that passes without an injunction allows OpenAI to embed their knowledge of Apple's stolen information into its hardware development efforts." Hearing: October 1, 2026. Judge Edward J. Davila. ITS HAPPENING

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"La Grève" d’Ayn Rand raconte l’effondrement d’un pays dans lequel ceux qui produisent sont progressivement punis pour leur réussite. Les entreprises ferment, les infrastructures se dégradent, les pénuries apparaissent. Mais à chaque crise, l’État répond par davantage de contrôles, de contraintes et de redistribution. Les entreprises inefficaces sont protégées. Les plus performantes sont accusées de nuire à l’intérêt général. Les concurrents incapables d’innover utilisent le pouvoir politique pour ralentir ceux qui réussissent. Dagny Taggart dirige une compagnie ferroviaire. Elle passe son temps à réparer les erreurs de son frère, des bureaucrates et des dirigeants incapables. C’est l’une des idées centrales du livre : un système défaillant peut survivre longtemps grâce à quelques personnes compétentes qui compensent tout en silence. Hank Rearden, lui, invente un métal révolutionnaire. Au lieu d’être récompensé, il devient une cible. On veut limiter sa production, récupérer son invention et lui faire honte de sa réussite. Peu à peu, les meilleurs industriels, ingénieurs et inventeurs disparaissent. Derrière ces disparitions se trouve John Galt. Il a compris que le système ne tient que parce que ceux qu’il exploite continuent malgré tout à le faire fonctionner. Il organise donc une grève particulière : non pas celle des ouvriers, mais celle de l’intelligence, de la compétence et de la responsabilité. Les producteurs ne sabotent rien. Ils cessent simplement de réparer, d’inventer et de porter un monde qui les condamne tout en dépendant entièrement d’eux. Le titre original, « Atlas Shrugged », résume le livre. Atlas porte le monde sur ses épaules. Ayn Rand pose une question : que se passe-t-il si Atlas décide de hausser les épaules et de laisser tomber le monde ? Le pouvoir finit par vouloir tout figer : les entreprises ne peuvent plus fermer, les salariés ne peuvent plus partir, les prix sont bloqués, les brevets saisis. Mais on peut saisir une usine sans savoir la faire fonctionner. On peut confisquer une invention sans être capable d’en créer une nouvelle. On peut imposer l’obéissance. On ne peut pas imposer l’intelligence. C’est ce que raconte "La Grève". Une société peut longtemps mépriser ceux qui la font fonctionner. Mais elle ne peut pas survivre lorsqu’ils décident de ne plus la porter.