2026-07-15 08:55:08
- 日本科学家开发出从废旧电动车电池中回收高达90%锂的新方法，通过使用回收氢氧化锂替代标准氢氧化钠处理电池黑粉，可产出高纯度锂并减少40%碳排放，但日本仅有约14%的旧锂电池进入正规回收系统，收集基础设施急需升级。
- 三位前NOAA女性员工创建替代网站Climate.us，抢救保存了被特朗普政府关闭的Climate.gov上超过15年的关键气候数据与资源，通过众筹筹集逾40万美元，超过80名科学家自愿审核，旨在提供不受政治更迭影响的可靠气候信息。
- 本文介绍了完全通过命令行工具（如xcodebuild、notarytool、stapler）构建并发布Mac/iOS应用的流程，只需安装却永不打开Xcode，通过一次性证书配置与自动化脚本实现无图形界面的发布流水线。
- 欧盟数字身份钱包年龄验证方案强烈反对集成Google Play Integrity和Apple App Attestation，因为这加深了对美国科技巨头的依赖、违背用户控制原则并破坏跨平台互操作性，但指出如Yivi等替代方案也有其他集中化依赖。
- Git 2.54/2.55引入实验性git history命令，包含fixup、reword、split子命令，能原子化修改历史提交并自动更新下游分支，解决并行开发中的rebase冲突，提供了类似jj的优点且无需切换工作流。
- 通过自定义Claude的MessageDisplay钩子，用Python脚本将AI回复中令人厌烦的特定短语（如“load-bearing”）自动替换为搞笑替代词，用户只需配置目录和settings.json即可生效。
- OpenAI Codex在合并加密多智能体v2消息负载后，子智能体间的任务和消息内容被加密存储，导致原本可读的任务文本在历史回滚和审计中消失，影响调试与透明度。
- 作者展示了一个名为“SUPER DARIO”的网页小游戏，在HN引发关于AI生成游戏质量的热议，有评论认为游戏制作精良，也有批评其玩法糟糕、充满bug，并展开了对AI编码能力的讨论。
- 文章探讨了人们日益将思考任务外包给AI的现象，指出先独立思考再借助AI验证有助于保留思考的乐趣与能力，关键在于区分哪些工作适合外包，哪些必须亲力亲为，以免丧失批判性思维。
- Telegram的t.me域名因美国OFAC合规审查被注册商GoDaddy暂停，疑似与一家被制裁的VPN提供商文件中包含t.me链接有关，.me域名管理权由美国公司主导引发了域名主权让渡和地缘政治干预的担忧。
https://tech.supercarblondie.com/japan-recovers-up-to-90-of-lithium-from-used-ev-batteries/
日本科学家开发出一种从废旧电动车电池中回收高达 90% 锂的新方法。传统方法回收率不足 50%，而新技术通过改用回收的氢氧化锂代替标准氢氧化钠处理电池废料（黑粉），可产出高纯度锂直接用于新电池。该工艺还能减少约 40% 的碳排放。日本目前几乎全部依赖进口电池矿物，这一突破有望降低对外依赖并稳定供应链。不过，目前日本仅有约 14% 的旧锂电池进入正规回收系统，收集基础设施急需升级。计划到 2027 年扩大生产，到 2035 年实现每年提取数万吨材料，若全球推广将带来深远影响。
https://news.ycombinator.com/item?id=48901569
https://19thnews.org/2026/07/noaa-climate-data-website/
特朗普政府关闭了美国国家海洋和大气管理局（NOAA）的官方气候信息网站 Climate.gov，导致大量联邦员工被裁员。三位前 NOAA 女性员工——Rebecca Lindsey、Mary Lindsey 和 Anna Eshelman——共同创建了替代网站 Climate.us，以保留超过 15 年的关键气候数据和资源，包括已被删除的第五次国家气候评估报告。
Rebecca Lindsey 担任 Climate.us 的常务编辑，Anna Eshelman 负责设计，Mary Lindsey 负责数据可视化。她们均因联邦政府缩减规模而失业。网站并非由气候科学家运营，而是作为科学家与公众之间的桥梁，旨在提供不受政治影响的可靠气候信息。
Climate.us 于 2026 年 6 月 23 日上线，通过众筹和个人捐赠已筹集超过 40 万美元，足以维持到 2027 年初。目前团队仅有 3 人，但长期需要 10 至 12 名员工才能持续运转。超过 80 名科学家自愿担任审核员，确保信息准确。三位女性表示，之所以重建该网站，是因为“可信的气候信息不应随着政治更迭而消失”。
https://news.ycombinator.com/item?id=48897945
https://scottwillsey.com/building-and-shipping-mac-and-ios-apps-without-ever-opening-xcode/
本文介绍了如何在不打开 Xcode 的情况下，完全通过命令行构建并发布 Mac 和 iOS 应用。核心思路是：Xcode 必须安装但永远不必打开，使用 xcodebuild、notarytool、stapler、devicectl 等内置工具即可完成全部工作。
一次性的图形界面准备：
/Applications/Xcode.app/Contents/Developer。project.yml 管理项目配置，避免 .xcodeproj 文件混乱。xcrun notarytool store-credentials 存储公证凭证（需生成 app-specific 密码，不能使用 Apple ID 密码）。项目配置：
Local.xcconfig 文件，填入 BUNDLE_PREFIX 和 DEVELOPMENT_TEAM，并加入 .gitignore，避免敏感信息入库。发布脚本（核心）：
scripts/release.sh 中实现完整流水线：归档 → Developer ID 签名 → 公证（notarytool）→ 附加凭证（stapler）→ 安装到 /Applications。关键提示：签名密钥存放在本地钥匙串中，不可恢复需备份；公证密码在修改 Apple ID 密码后会失效，需重新生成。本文强调利用 LLM 代劳繁琐步骤，真正实现“永不打开 Xcode”的开发体验。
https://news.ycombinator.com/item?id=48896665
https://github.com/eu-digital-identity-wallet/av-doc-technical-specification/discussions/19
一位用户在 GitHub 讨论中强烈反对在欧盟数字身份钱包的年龄验证方案中集成 Google Play Integrity 和 Apple App Attestation，理由包括：加深对美国科技巨头的依赖、在当前政治环境下具有安全风险、违反“可供任何人使用”和“用户控制”原则，以及破坏跨平台互操作性。发起者以荷兰身份应用 Yivi（无此类依赖，甚至可在 F-Droid 开源商店获取）为例，证明设备验证并非必需。其他参与者指出 Yivi 自身也存在中央服务器和第三方生物识别服务的依赖，但这属于不同的信任集中问题。整体讨论围绕数字主权、安全性和开放性原则展开。
https://news.ycombinator.com/item?id=48903777
https://lalitm.com/post/git-history/
git history 是 Git 2.54/2.55 加入的实验性命令，包含 fixup、reword、split 三个子命令，能够在不破坏工作树的前提下原子地修改历史提交、自动更新所有下游分支，解决了并行开发时分支管理、rebase 冲突的痛点。作者认为该命令已提供了 jj（Git 替代工具）宣传的许多好处，且无需切换整个工作流。fixup 将暂存修改折叠到旧提交；reword 修改旧提交信息；split 交互式地将一个提交拆分为两个。三者均拒绝可能导致冲突的操作，因此不会让仓库处于半损坏状态。相比 jj，git history 尚不支持冲突作为一等公民跨 rebase 传递，但文档已预留未来增强的可能。作者认为这是从 git 迈向 jj 式体验的重要一步，且已内置在日常使用的工具中。
https://news.ycombinator.com/item?id=48901010
git switch 和 git restore 命令来分别处理这两个任务，改善了用户体验。git blame 找到 bug 起源的提交，然后从该提交创建分支修复，能留下更好历史轨迹，但产生非线性图，易导致不熟悉 Git 的人抱怨无法合并。https://jola.dev/posts/how-to-stop-claude-from-saying-load-bearing
这篇博客介绍了如何通过自定义 Claude 的 MessageDisplay 钩子来替换 AI 回复中令人厌烦的词汇（如“load-bearing”“honest take”）。作者提供了一个 Python 脚本，将特定短语替换为搞笑的替代词（例如把“load-bearing”改成“cooked”），并指导用户将脚本放入 ~/.claude/hooks/ 目录，然后在 settings.json 中配置，重启 Claude 即可生效。文章还鼓励读者自己创造更有趣的替换词。
https://news.ycombinator.com/item?id=48905248
https://github.com/openai/codex/issues/28058
该网页是 GitHub 上 openai/codex 仓库的一个 Issue（编号 #28058），标题为“回归：加密的 MultiAgentV2 消息移除了可读的任务审计追踪”。问题由 ignatremizov 于 2026 年 6 月 13 日提出，描述在合并了 PR #26210（加密多智能体 v2 消息负载）后，MultiAgentV2 的子智能体任务/消息内容被加密存储，导致人类可读的任务文本在本地回滚历史、追踪记录和父端审计中消失。用户无法查看子智能体被分配的任务、发送的消息或线程存在的原因。该问题与 #26753（加密工具模式的请求验证失败）不同，专注于审计和调试能力的缺失。建议在保持加密交付的同时，增加一个非加密的审计字段来保存可读的任务文本，以便在历史元数据中持久化。Issue 还提供了源代码分析，指出 InterAgentCommunication::new_encrypted() 将 content 设为空字符串，仅将加密内容存入 encrypted_content，导致可读内容丢失。该问题影响了自 #26210 合并后的版本（0.137.0 之后）且启用 MultiAgentV2 的用户。
https://news.ycombinator.com/item?id=48905028
一个名为 “SUPER DARIO” 的网页小游戏，标题提示 “One More Week”（还剩一周）。玩家通过按任意键开始，使用 A/D 或方向键移动，空格键跳跃，M 键静音。游戏风格复古，作者是 Pascal Schuster，附有博客、Twitter、Bluesky 和联系链接。
https://news.ycombinator.com/item?id=48896286
https://www.artfish.ai/p/offloading-thinking-to-ai
你是否注意到，自己和周围的人正在越来越多地把思考任务交给 AI？从日常琐事到复杂思辨，用 AI 来研究、推理和回答问题变得既方便又普遍。本文作者 Yennie Jun 以亲身观察和经历反思了这一趋势。
她引用了 Ken Liu 的短篇小说《完美匹配》——故事里的通用 AI 助手 Tilly 能为主角推荐早餐、约会对象，主角几乎将所有决定都交给了算法。现实中，作者的朋友在一次旧金山创业活动中遇到一位“麦克风男”，他把全天对话录下来，然后让 Claude Fable 替他做所有思考，甚至声称“它比我自己更擅长批判性思维”。
作者指出，搜索引擎时代我们已开始外包部分思考，但那时仍需自己拆解问题、评估来源、综合答案；而现在的 AI 一步到位给出完整回应，省去了中间步骤。像 Google Deep Research 和 OpenAI Deep Research 这类工具，能在数分钟内完成原本需要人类数小时甚至数天的工作——节省时间，也节省了思考。
然而，这模糊了“拥有得力助手”与“丧失自主性”的界限。真正关键的问题是：那些对你人生重要的事情，最终决定权在谁手里？
作者也坦诚，自己同样容易被这种趋势侵蚀。她举了一个例子：某次和妹妹在葡萄牙旅行，她们对纪念碑上歌颂的“大航海时代”感到疑惑——为什么葡萄牙人如此崇拜殖民者，而美国却把哥伦布视作负面人物？妹妹下意识想查 ChatGPT，但作者提议先自己思考。她们凭记忆和推理提出了几种猜想，再拿同样的问题去问 AI，结果 AI 验证了部分猜测，补充了几个遗漏的角度，也漏掉了一些她们觉得合理的可能性。这个先思考后验证的过程让作者感到愉悦。
作者并非彻底否定 AI。她本人从事 AI 相关工作，也看到 AI 给他人带来的好处——比如同事用代码代理加快分析，朋友借助 ChatGPT 在几个月内自学通过了 MCAT 考试。关键在于，如果 AI 被用来替代重复性、机械性的工作，从而腾出精力做更重要的思考，那或许是件好事。但若连最需要自主判断和慢思考的环节也一并交出，我们就可能失去独立思考的能力与乐趣。
https://news.ycombinator.com/item?id=48908178
https://www.whois.com/whois/t.me
域名 t.me 的 WHOIS 查询结果显示：注册日期为 2010 年 5 月 20 日，到期日为 2035 年 5 月 20 日。域名处于 clientDeleteProhibited、clientRenewProhibited、clientTransferProhibited、clientUpdateProhibited 状态。域名服务器为 ns-cloud-b1.googledomains.com 等四台。注册商为 GoDaddy.com, LLC，注册组织为 Domains By Proxy, LLC（隐私保护），所在地美国亚利桑那州。
https://news.ycombinator.com/item?id=48897878
https://news.ycombinator.com/item?id=48902953
The article is very, very light with details. The university or research center is not named. No scientist is named. No link. Nothing that tells “look, we’re telling you real, solid, serious stuff.”
Here is another article with that details : https://www.techspot.com/news/112051-japan-finds-way-recover-90-lithium-old-ev.html
BaudouinVH
这篇文章内容非常、非常简略，没有提及大学或研究中心名称，没有科学家姓名，没有链接，没有任何能表明“看，我们在告诉你真实、可靠、严肃的内容”的信息。
这是另一篇有详细内容的文章：https://www.techspot.com/news/112051-japan-finds-way-recover-90-lithium-old-ev.html
https://news.ycombinator.com/item?id=48910656
I do not mind when I am coding with Claude and it uses all the typical claudisms. I am much more bothered when I am reading a blog post, email, or other form of prose and I see those same claudisms.
I guess they are not annoying since I know I am talking to an LLM and expect the typical responses. When I am reading prose online that I previously would have expected a human to write, it can be quite jarring to realize its an LLM.
doctoboggan
我不介意在用Claude编程时它使用那些典型的克劳德式用语。但当我阅读博客文章、邮件或其他形式的散文时看到同样的表达，我会感到更不舒服。我猜这些用语并不烦人，因为我知道自己是在和LLM对话，也预料到会有这些典型回应。而当我读到原本以为是人类写的在线散文时，发现其实是LLM写的，这就会让人感到很不协调。
https://news.ycombinator.com/item?id=48908816
I don’t know if this is a good framing. “Too much” is subjective, and every heavy AI user will assert that they’re just unlocking their potential, that calculators didn’t make us dumber, etc.
But to latch onto the calculator argument: if you outsource adding numbers to a calculator, you’re still you. On the flip side, if you use an LLM do most of your thinking, what’s left? We have people here who use LLMs to raise their children, to manage relationships, to design products. So what’s your unique contribution to this world - is it the prompt you once wrote? You’re standing in front of a token-generating machine, pulling a lever, sometimes receiving gifts. Is that your edge, your unique experience, your purpose in life?
Many LLM maximalists say they use the tech to learn new things, but to what effect? Are you going to apply that knowledge of physics or computer science yourself, or will you just prompt the LLM again?
In my mind, it’s pretty simple: I’m a human, LLMs are not. If a human writes a novel, it’s inherently worth more because it’s hard-earned and anchored to experiences we share. I want to support that. And I want to be a human who can write novels, the old-fashioned way. I’m not good at lifting weights or running, so my thinking is the only thing I have.
zerobees
我不知道这是不是一个好的角度。“太多”是主观的，每个重度AI用户都会声称他们只是在释放自己的潜力，计算器并没有让我们变笨，等等。
但就计算器这个论点来说：如果你把数字加法外包给计算器，你仍然是你自己。反过来，如果你用大语言模型完成大部分思考，还剩下什么？我们这里有人用大语言模型来养育孩子、管理人际关系、设计产品。那么你对这个世界独特的贡献是什么——是你曾经写过的一条提示词吗？你站在一个生成令牌的机器前，拉动杠杆，偶尔收到礼物。这是你的优势吗？是你独特的体验、你的人生意义吗？
许多大语言模型的极端推崇者说他们用这项技术学习新事物，但效果如何？你会亲自运用那些物理或计算机科学的知识，还是再次去提示大语言模型？
在我看来，这很简单：我是人，大语言模型不是。如果一个人写了一本小说，它本身就更具价值，因为它是来之不易的，并且植根于我们共通的体验。我想支持这一点。而我想成为能够以老派方式写小说的人。我不擅长举重或跑步，所以思考是我唯一拥有的东西。
https://news.ycombinator.com/item?id=48896324
With a headline like that the graph should be at the beginning. Usually you’d put it up front and then talk about the graph, not put it at the bottom and talk about how people aren’t talking about it.
Anyway, I scrolled down to the graph and skipped the text. We are currently 4 std deviations above the mean with respect to El Niño temperature.
But there’s also a historical line -4 std deviations from the mean. Was that an eventful year too? I can’t tell and the graph is at such low resolution that the source URL isn’t visible. If the graph and data is so important, shouldn’t we care more about presentation? This is either super sloppy or deliberate obfuscation.
Look, I’m all for good reporting on climate. This just doesn’t feel like it.
alternator
标题写成那样，图表就应该放在开头。通常你会把图表放在前面，然后讨论它，而不是把它放在底部，然后谈论人们怎么都不提它。
总之，我往下翻到图表，跳过了文字。目前我们关于厄尔尼诺温度的数值已经偏离均值4个标准差。
但图表里还有一条历史线是偏离均值-4个标准差。那一年也是多事之秋吗？我看不出来，而且图表分辨率太低，连来源网址都看不清。如果图表和数据这么重要，难道不应该更注重呈现方式吗？这要么是极其粗心，要么是故意混淆。
听着，我完全支持对气候问题进行良好的报道。但这篇报道感觉不像。
https://news.ycombinator.com/item?id=48896221
Yeah it’s kinda crazy you can’t legally take them down even if they are banned/contract expires. IKE Skelton, a county commissioner took it into his own hands and they were pressing felony charges on him. Not sure what ended up happening. Basically flock wouldn’t respond to take them down, he felt it was his duty to remove them, he brought them back to his office, and then the state hunted him down.
Here is a podcast about it. https://internationalflavor.podbean.com/e/the-surveillance-state-strikes-back-the-trial-of-camden-county-s-defender/
smalltorch
确实挺疯狂的，即使这些监控摄像头被禁止使用或合同到期，也无法合法拆除它们。县专员IKE Skelton自行处理了这个问题，结果被指控犯有重罪。不知道最终结果如何。大致情况是Flock公司不回应拆除请求，他觉得自己有责任移除它们，就把摄像头带回了办公室，然后州政府追查到了他。
这里有一期相关的播客：https://internationalflavor.podbean.com/e/the-surveillance-state-strikes-back-the-trial-of-camden-county-s-defender/
https://news.ycombinator.com/item?id=48890904
This website is making heavy use of IP range blocking. Here’s an uncensored link: https://web.archive.org/web/20260713092155/https://www.lyrebirddreaming.com/post/the-graph-that-should-be-front-page-news
Alternatively, since the link that was posted is just an AI copyright theft site, use the original instead: https://climatecasino.substack.com/p/some-monsters-are-real
Discussion: https://news.ycombinator.com/item?id=48890533
inigyou
这个网站正在大量使用IP段封锁。这里有一个未经审查的链接：https://web.archive.org/web/20260713092155/https://www.lyrebirddreaming.com/post/the-graph-that-should-be-front-page-news
或者，由于发布的链接只是一个AI版权盗窃网站，请改用原始链接：https://climatecasino.substack.com/p/some-monsters-are-real
讨论：https://news.ycombinator.com/item?id=48890533
https://news.ycombinator.com/item?id=48905218
I can’t understand how we got to this place with “app culture”!
The short version: ad blockers work on browsers but not apps[0].
[0] https://pluralistic.net/2024/01/30/go-nuts-meine-kerle
billyp-rva
我真不明白我们怎么就到了这种“应用文化”的地步！
简而言之：广告拦截器在浏览器上有效，但在应用上无效[0]。
[0] https://pluralistic.net/2024/01/30/go-nuts-meine-kerle
https://news.ycombinator.com/item?id=48891407
A drum I’ve been banging increasingly often recently is that having friction and time to work ideas over in your mind adds huge amounts of value. Vibe coded projects have this very specific, well, vibe to them where you can clearly see that the lack of time to digest has allowed the person to not challenge their own worst impulses. You can see it in the feature bloat, the lack of depth and polish in core features and the wild asides you tend to talk yourself out of still on display.
TeriyakiBomb
最近我越来越频繁地强调一个观点：在思考想法时经历摩擦和时间沉淀能带来巨大价值。那些“氛围编程”出来的项目有种很独特的氛围，你能明显看出缺乏消化时间导致创作者没能克制自己最糟糕的冲动。从功能臃肿、核心功能缺乏深度和打磨，还有那些本该说服自己放弃却依然存在的疯狂分支中，你都能看到这一点。
https://news.ycombinator.com/item?id=48887813
I wish Count Binface all the best for the Clacton by-election.
Edited to add: Some of my favourite commentary around this by-election is along the lines of:
A fundamentally un-serious candidate with no coherent policies or political experience running against Count Binface.
BLKNSLVR
祝宾法斯伯爵在克拉克顿补选中一切顺利。补充一点：关于这次补选，我最喜欢的一些评论大致是——一个根本不严肃、没有连贯政策或政治经验的候选人，竟然在和宾法斯伯爵竞争。
https://news.ycombinator.com/item?id=48909064
Have you read the “Whispering earring” essay? I love it for the LLM era.[1]
You can treat AI as a whispering earring - “What should we do now? How do we fix this? What do you think?” Or you can treat it like an exoskelton - “Implement kd-tree with metric space xyz for this problem, mapping this to that blah blah”.
That’s pre-thought execution automation that makes review much simpler - you already know the shape of the desired output. The whispering earring is atrophy.
jvanderbot
你读过那篇《耳语耳环》的文章吗？我非常喜欢它对于大语言模型时代的描述。[1]
你可以把AI当作一只耳语耳环——“我们现在该做什么？怎么解决这个问题？你觉得呢？”或者你也可以把它当作外骨骼——“针对这个问题用度量空间xyz实现kd树，把这个映射到那个等等”。
这是预想的执行自动化，使得审查变得简单得多——你已经知道期望输出的形态。而耳语耳环则是萎缩。
https://news.ycombinator.com/item?id=48895025
There isn’t really much waste in federal spending.
There’s actually a lot of waste. DOGE just didn’t go after it. Check out DOD and all the 9- and 10-figure programs that get canceled without delivering anything, and whose work is often useless for follow-on work. OCX is a recent example, costing around $6 billion and took so long that the program it was supposed to replace ended up just doing the work instead. Essentially nothing of OCX will be retained. This isn’t really unusual in the DOD.
Jtsummers
联邦支出中其实没有太多浪费。
实际上浪费很多。DOGE只是没有去追查而已。看看国防部吧，所有那些九位数和十位数的项目，被取消后什么成果都没交付，而且其工作对后续项目往往毫无用处。OCX就是一个最近的例子，耗资约60亿美元，耗时太长，以至于它本该取代的项目最终自己完成了工作。OCX几乎没有任何东西被保留下来。这在国防部并不罕见。
https://news.ycombinator.com/item?id=48888422
I think classifying it as an allergy or a status thing is a little too glib. I’ve read and reviewed, conservatively, hundreds of AI generated documents for work, and “written”/commissioned a bunch too. My biggest issue is that it’s impossible to engage with and give feedback on an AI written document, because it’s impossible to know whether misconceptions or gaps are because the author doesn’t understand the material deeply enough or the author does but the AI doesn’t and the author’s not proofreading carefully enough. Or if a surprising idea is raised — is it the authors insight, can they elaborate on it, where did it come from, etc?
Hackernews isn’t work, obviously, but “it’s impossible to engage deeper with the material because the author doesn’t really exist” is sort of a problem for a discussion site. If the human coauthor puts in enough work, they can make sure the doc really reflects their views and their understanding, but in my experience that’s much less common.
grayclhn
我认为将其归类为过敏或身份象征有些过于轻率。保守估计，我为工作审阅过数百份AI生成的文档，也“撰写”/委托创作过不少。我最大的问题是，根本无法对AI写的文档进行深入互动和反馈，因为你无法判断其中的误解或空白，究竟是因为作者对材料理解不够深入，还是作者理解到位但AI没理解、而作者又没仔细校对。又或者，当出现一个出人意料的观点时——这是作者的见解吗？作者能详细阐述吗？它从何而来？
当然，Hackernews不是工作场合，但“由于作者实际上并不存在，因此无法与材料进行更深层次的互动”，这对一个讨论网站来说是个问题。如果人类合著者投入足够多的精力，他们可以确保文档真正反映自己的观点和理解，但根据我的经验，这种情况并不常见。
https://news.ycombinator.com/item?id=48905509
I recently decided to publish an app on the App Store just so I could say I accomplished that, and maybe even make a little bit of beer money on the side.
Now, I’ll be the first to admit that my actual app is pretty much garbage. I don’t expect it to be popular. It’s basically a worse version of stuff that is already available.
I expected this to be a learning exercise about the process of getting stuff published.
Long story short, by the end of the ordeal I was somewhat surprised that anyone independent bothers to publish apps at all. The amount of red tape and nitpicking by the initial app review process is astounding. The business/legal side is also annoying. I might be misremembering or misinterpreting, but it seems like you really need an LLC with a mail forwarding service and a cheap second phone line just to avoid the App Store sending the whole internet to your personal phone and address.
On a website you can just not deal with any of that, and not give Apple $99/year just to keep your app on the store.
And we haven’t even gotten into the big royalties you’re paying for App Store purchases.
Still, I understand the appeal at some point, just not for an app like OP was forced to use. I certainly wouldn’t want to use something like Immich or Opencloud without an app: these apps need to deeply integrate with my phone to be truly useful.
Grombobulous
我最近决定在App Store上发布一个应用，只是为了证明自己做到了这件事，顺便也许还能赚点零花钱。
首先我得承认，我的应用本身基本就是个垃圾。我不指望它受欢迎，它基本上就是现有同类产品的劣化版。
我本来以为这只是个学习如何发布产品的过程。
长话短说，等到折腾完了，我多少有点惊讶竟然还有独立开发者愿意费劲去发布应用。初始审核流程中繁多的官僚手续和吹毛求疵令人震惊。商业和法律方面也很烦人。可能是我记错或理解有误，但感觉你确实需要一个附带邮件转发服务的有限责任公司和一条便宜的备用电话线，才能避免App Store把你整个互联网信息都暴露到个人手机和地址上。
在网站上你完全不用处理这些事，也不用每年给苹果交99美元来让应用留在商店里。
而且我们还没提你在App Store购物时支付的高额抽成。
不过，我仍然理解在某些情况下应用的必要性，但绝不是像原帖作者被迫使用的那种应用。我肯定不想在没有应用的情况下使用Immich或Opencloud这类工具：这些应用需要深度集成到手机中才能真正有用。
https://news.ycombinator.com/item?id=48901215
a feature that simply makes your product easier to use
Except it doesn’t. You lose context and are now drowning in an endless morass of lazy-loaded blocks and widgets, all hiding under invisible elements. Nothing has a permanent URL, so there is zero accountably if the user was shown something that they need to reference - unless it benefits the platform. And of course, it will eventually all force reload when the page complexity exhausts the available memory, or at least when it becomes too exhausted to reliably serve ads.
fitzroy
一个声称能让你的产品更易用的功能
但实际上并非如此。你失去了上下文，陷入无休止的懒加载区块和小部件泥潭，全都隐藏在不可见元素之下。没有任何内容有固定的URL，因此如果用户看到了需要引用的内容，平台根本无需负责——除非这对平台有利。当然，最终当页面复杂度耗尽可用内存时，或者至少当它过于臃肿而无法可靠地投放广告时，所有内容都会被强制重新加载。
2026-07-14 09:01:57
- Zig创始人直率批评Bun从Zig迁移至Rust的项目工程混乱，揭露了Anthropic以AI编程叙事进行商业炒作。
- 实测显示Claude Code的系统提示与工具结构消耗约33K Token，远超OpenCode的7K，带来显著成本与效率差异。
- 2023年赤道太平洋海表温度异常已完全跳出历史观测范围，警示全球变暖正加剧极端气候风险。
- Grok工具被发现将用户整个主目录包括SSH密钥等敏感文件上传至xAI服务器，引发严重隐私担忧。
- 作者热爱大语言模型但批评炒作，指出“vibe coding”质量差，技术进步主要来自算力，应警惕过度依赖。
- 新西兰演员萨姆·尼尔去世，享年78岁，他曾因《侏罗纪公园》等影片闻名并公开与癌症抗争的经历。
- 苹果新SpeechAnalyzer API在英语本地转录测试中准确率与速度均优于Whisper Small，成为苹果设备上的最强选项。
- 洛杉矶警察局因隐私与公民自由问题终止与监控公司Flock的合同，但摄像头网络可能仍被其他机构利用。
- Chromium 148起Math.tanh等数学函数因依赖操作系统原生库而泄漏OS指纹，可被用于跨平台识别。
- Grok CLI确定性地上传用户整个主目录至云存储，暴露出以文本指令限制AI访问的安全缺陷。
https://raymyers.org/post/zed-creator-calls-spade-a-spade/
Ray Myers 在博客中评论了 Anthropic 与 Bun 将运行库从 Zig 迁移到 Rust 的事件。他指出 Anthropic 是一家靠宣传未来影响力吸引投资的 AI 公司，声称“编程即将消失”以推动其叙事。Bun 作为 TypeScript 运行时，曾是最大的 Zig 代码库之一，被 Anthropic 收购后，其创始人在 AI 代理的协助下将代码迁移到非安全 Rust，并宣传接近 100% AI 贡献，而 Zig 禁止 AI 贡献。Zig 创始人 Andrew Kelley 对此回应直率，批评 Bun 项目工程决策混乱（过度使用 AI、管理问题），而非 Zig 本身的问题。Myers 倾向于认为这次迁移更多是商业营销手段：Rust 重写能推广 Anthropic 的 Fable 模型，并迎合 Anthropic 内部技术栈。他同时指出 Bun 项目公开宣扬“996 式工作”是管理不善的表现，而 Andrew 的直言虽然打破常规，但有助于澄清技术真相。整体上，文章呼吁理性看待 AI 在软件工程中的实际能力，警惕资本驱动的叙事。
https://news.ycombinator.com/item?id=48889637
https://systima.ai/blog/claude-code-vs-opencode-token-overhead
这是一篇来自 Systima 博客的技术研究文章，标题为《Claude Code 比 OpenCode 更消耗 Token——我们精确测量了差距》。文章通过实验对比了两款 AI 编程代理工具：Claude Code 和 OpenCode，在同模型、同机器、同任务下的 Token 消耗情况。
关键发现：
文章还介绍了研究方法：在工具与模型间设置日志代理，精确捕获请求负载与 API 返回的使用数据，并通过多个任务（如回复“OK”、读取文件、编写测试循环）进行验证。结论是：Claude Code 启动成本高，但会话流程决定了最终谁更“费钱”；OpenCode 在缓冲效率上具有明显优势。
https://news.ycombinator.com/item?id=48883275
https://www.lyrebirddreaming.com/post/the-graph-that-should-be-front-page-news
这张图表本应成为头条新闻，但它却几乎被沉默对待。图中的红色线代表 2023 年赤道太平洋尼诺 3.4 区域的海面温度，它已经完全脱离了 1982 年以来所有年份的历史观测范围。这不是计算机模型或预测，而是来自卫星、船舶和海洋浮标的直接观测数据，是当下正在发生的现实。
尼诺 3.4 区域被称为地球气候系统的“心脏”。厄尔尼诺事件本身是自然变率的一部分，但问题在于人类活动已使大气二氧化碳浓度比工业革命前增加 50% 以上，海洋吸收了约 90% 的过剩热量。如今每个厄尔尼诺事件都起始于一个更热的背景海洋，这意味着气候系统拥有的能量更多，极端天气被放大：更强烈的风暴、更严重的干旱和洪水、更频繁的火灾。
海洋变暖正在引发生态系统的崩溃：珊瑚白化、鱼类向冷水区迁移、海藻森林消失、氧气含量下降、海洋热浪频发。这些生态影响反过来又反馈到气候系统中。地球的多个临界要素（大西洋经向翻转环流、格陵兰冰盖、南极冰川、北极海冰、亚马逊雨林）都在快速失稳，连锁反应可能使气候系统在人类时间尺度上难以逆转。
归根结底，气候变化关乎人类：更高的食品价格、更具破坏力的风暴、渔业衰退、保险成本上升、水资源短缺、基础设施损坏、公共卫生恶化、社区流离失所、地缘政治不稳定。这张图的意义不在于预言灾难必然到来，而在于提醒我们：地球正超出现代人类文明所适应的范围，而我们的基础设施、生态系统、经济和制度从未为此设计过。我们是否愿意在变化变得过大、过快、过于关联而无法管理之前，真正关注并采取行动？
https://news.ycombinator.com/item?id=48888331
https://twitter.com/a_green_being/status/2076598897779020159
用户 “A Green Being” 发推文称，Grok 将其整个用户目录上传到了 xAI 的服务器，包括 SSH 密钥、密码管理器数据库、文档、照片、视频等所有内容。该推文发布于 2025 年 7 月 13 日，获得 6.25 万次浏览和 43 条回复。
https://news.ycombinator.com/item?id=48892512
https://geohot.github.io//blog/jekyll/update/2026/07/12/i-love-llms.html
作者 geohot（George Hotz）在博客中表达了对 AI 的由衷喜爱，同时批评围绕 AI 的两种炒作：一是负面情绪（窗口关闭、落后、被迫搬去旧金山），二是过度神化（AI 将控制一切）。他认为 AI 进步主要源于摩尔定律和计算发展，而非个别公司的功劳；开源 AI 至关重要。他还讨论了编程的演变：AI 模型能提升效率（类似编译器的进步），但需谨慎使用，避免认知疲劳，且“vibe coding”依然低质。最终观点：AI 是计算机革命的延续，他对此充满热情。
https://news.ycombinator.com/item?id=48883343
https://www.theguardian.com/film/2026/jul/13/sam-neill-death-actor-dies-aged-78
新西兰演员萨姆·尼尔（Sam Neill）于 2026 年 7 月 13 日在悉尼去世，享年 78 岁。他的家人在 Instagram 上发布声明，称其去世突然且意外，但他此前已癌症痊愈（曾患 3 期血管免疫母细胞 T 细胞淋巴瘤，2022 年确诊，后进入缓解期）。尼尔以《侏罗纪公园》中的艾伦·格兰特博士、《钢琴课》中的殖民者、《狩猎红色十月》等影片闻名，还出演过《浴血黑帮》《雷神》系列等。他出生于北爱尔兰，在新西兰长大，演艺生涯跨越五十年，超过 150 部作品。他的最后一部回忆录《Did I Ever Tell You This?》于 2023 年出版，记录了他与癌症斗争的经历。
https://news.ycombinator.com/item?id=48888468
https://get-inscribe.com/blog/apple-speech-api-benchmark.html
苹果在 iOS/macOS 26 中推出了新的语音 API SpeechAnalyzer（替代旧版 SFSpeechRecognizer），但未公布准确率数据。Inscribe 团队在 LibriSpeech 标准测试集（5559 条音频）上对其进行了对比基准测试，结果如下：
测试方法公开透明：所有引擎均运行在 M2 Pro 上且强制本地处理，原始转录文本可下载验证。Whisper 的关键优势在于支持更多语言（约 30 个语言区域）且跨平台通用，但就英语转录而言，苹果新 API 已成为 Apple 设备上最强的本地选项。Inscribe 已据此调整产品默认设置，对支持的语言优先使用 SpeechAnalyzer。测试还无意中发现并修复了产品中一个与 API 调用相关的问题。
https://news.ycombinator.com/item?id=48894752
洛杉矶警察局（LAPD）决定不再续签与监控公司 Flock Safety 的三年合同，合同将于本周六到期。LAPD 首席信息官 Dean Gialamas 表示，出于对公民自由和隐私的“严重担忧”，尤其是摄像头收集的数据处理方式，他们选择终止合作，直到数据、隐私、安全和共享问题在合同中得到解决。
Flock Safety 是美国一家拥有至少 8 万个车牌扫描摄像头的监控公司，其网络覆盖全美，用于追踪车辆。LAPD 是其最大政府客户之一。此前，加州山景城和缅因州南波特兰等城市也因隐私担忧停止了与 Flock 的合作。
Flock 公司对此感到“意外”，称有信心消除“当前误解”。文章还揭露了 Flock 的安全漏洞，包括摄像头和数据的多次泄露，以及因车牌读取器误报导致司机被警察持枪拦截甚至错误逮捕的事件。美国缉毒局也曾被曝未经授权使用当地警察密码进行搜索。
https://news.ycombinator.com/item?id=48893947
https://scrapfly.dev/posts/browser-math-os-fingerprint/
在不同操作系统上，Math.tanh、CSS 三角函数和 Web Audio 压缩器等都会调用宿主操作系统的数学库（libm），由于不同系统的数学库实现细节不同（如 glibc、Apple libsystem_m、Windows UCRT），同一个计算会返回略有差异的浮点数结果（通常相差 1 个 ULP）。这种差异可以被反爬系统利用，作为浏览器指纹来识别操作系统。
文章详细分析了其中涉及的多个技术点：只有 Math.tanh 在 V8 中会泄漏 OS，其他 Math 函数均为 V8 内建统一实现；CSS 所有三角函数都通过宿主 libm 计算，因此全部泄漏；Web Audio 在 Mac 上使用 Accelerate 框架的向量数学和标量 libsystem_m 混合，因此不同运算调用不同库。文章还指出了伪装 OS 的四个陷阱：仅部分数学函数泄漏、JavaScript 与 CSS 数学路径不同、macOS 存在两个不同数学库（标量库与 Accelerate）、ARM 与 x86 架构的 FMA 和 NaN 传播不一致。最后建议不要用加噪方式掩盖，而需要按目标 OS 精确复现其数学库结果。
https://news.ycombinator.com/item?id=48884853
https://twitter.com/a_green_being/status/2076598897779020159
用户 @a_green_being 在 X 上发帖称，xAI 的 Grok 已将其整个用户目录上传到 xAI 服务器，包括 SSH 密钥、密码管理器数据库、文档、照片、视频等所有内容。帖子发布于 2023 年 7 月 13 日，获得 62.5K 阅读量，有 43 条回复。
https://news.ycombinator.com/item?id=48892468
https://news.ycombinator.com/item?id=48887149
We don’t allow genai text on HN itself - see https://news.ycombinator.com/newsguidelines.html#generated and https://news.ycombinator.com/item?id=47340079. How to enforce it is a separate question, of course, but the rule exists.
We don’t have a similar rule yet about article content but my sense is that the community mostly doesn’t want to read it—or, to put it more conservatively, discounts it. This is why we see so many “just show me the prompt” responses, along with others like this: https://news.ycombinator.com/genai-pushback. I built that list so I have something to send to users who email about why their genai articles got flagged.
It’s a fascinating arms race right now: the AIs are training on the humans but the human hivemind is also training on the AIs. Readers are developing allergic sensitivities to language that sounds like an LLM produced it. The AIs will adapt to this, but the humans will adapt in turn. Where it ends up is anyone’s guess.
For the present, there is an emerging class distinction between writing (and writers) that use genai vs. writing that does not. As soon as the “this sounds like an LLM” allergy kicks in, the writing instantly gets relegated to a low-status bucket in the reader’s mind. That doesn’t mean it won’t still get looked at - but it is now under a stigma.
(I was rather pleased with the originality of this until I remembered pg had come up with “writes and write-nots” in https://paulgraham.com/writes.html. Oh well, it’s the point that matters.)
This has the happy flipside that anyone who would like readers to classify their article as high-status rather than low-status can apply the judo move of simply writing it themselves.
Now I need to add the disclaimer that none of this is a dismissal of LLM technology per se. We rely on it heavily, and there’s no question that it’s useful. The question is how to use it (pg again: https://x.com/paulg/status/2058871512451412457 ) and whether one should use it on writing that one publishes to other humans.
To turn to OP’s questions:
Should HN add the ability to flag articles as AI-generated? […] it could just show up as an indicator
Flagging-as-just-an-indicator would be tagging, which we’ve always resisted adding to HN, but I wouldn’t rule it out.
What I do think we’ll (finally) add is a “please give a reason why you flagged this post” step, and “because I think it’s genai” will be one choice among several (spam, offtopic, mean, etc.)
Why is the regular voting system not enough?
The regular voting system is never enough. https://hn.algolia.com/?dateRange=all&page=0&prefix=false&sort=byDate&type=comment&query=%22upvotes%20alone%22%20by:dang
Should HN change in response to the gen AI era?
To this I am tempted to reply with https://news.ycombinator.com/item?id=48887149 in homage to https://news.ycombinator.com/item?id=3742902.
dang
我们在HN上不允许使用生成式AI文本——请参见https://news.ycombinator.com/newsguidelines.html#generated 和 https://news.ycombinator.com/item?id=47340079。当然，如何执行是另一个问题，但规则是存在的。
对于文章内容，我们目前还没有类似的规则，但我的感觉是社区大多不想阅读这类内容——或者更保守地说，会对其打折扣。这就是为什么我们看到这么多"直接给我看提示词"的回复，以及像这样的其他回复：https://news.ycombinator.com/genai-pushback。我建立了那个列表，这样当用户发邮件询问为什么他们的生成式AI文章被标记时，我就能发送这个列表给他们。
目前这是一场引人入胜的军备竞赛：AI在向人类学习，但人类的群体智慧也在向AI学习。读者正在对听起来像LLM产生的语言产生过敏反应。AI会适应这一点，但人类也会反过来适应。最终会走向何方，谁也说不准。
目前，使用生成式AI的写作（和作者）与不使用的写作之间正在出现一种新的阶层区分。一旦"这听起来像LLM"的过敏反应触发，那篇文章在读者心中就会立即被归入低地位类别。这并不意味着它不会被关注——但它现在带有污名。
（我对自己这个观点的原创性还挺满意，直到想起pg在https://paulgraham.com/writes.html中已经提出过"写作者与非写作者"的概念。好吧，重要的是观点本身。）
这有一个令人欣慰的方面：任何希望读者将他们的文章归类为高地位而非低地位的人，都可以应用柔道技巧——自己亲自写作。
现在我需要补充免责声明：以上这些都并非对LLM技术本身的否定。我们严重依赖它，毫无疑问它很有用。问题在于如何使用（又是pg：https://x.com/paulg/status/2058871512451412457 ），以及是否应该将其用于发布给其他人的写作中。
回到题主的问题：
HN是否应添加将文章标记为AI生成的能力？[…] 它只需作为一个指示器显示即可
仅作为指示器的标记就相当于打标签，我们一直反对给HN添加标签功能，但我不会排除这种可能性。
我认为我们最终会添加的是"请给出你标记此帖子的原因"这一步骤，而"因为我认为它是生成式AI"将是几个选项之一（垃圾信息、离题、恶意等）。
为什么常规的投票系统不够用？
常规投票系统从来都不够用。https://hn.algolia.com/?dateRange=all&page=0&prefix=false&sort=byDate&type=comment&query=%22upvotes%20alone%22%20by:dang
HN是否应该为应对生成式AI时代而改变？
对此，我很想用https://news.ycombinator.com/item?id=48887149 来回复，以向https://news.ycombinator.com/item?id=3742902 致敬。
https://news.ycombinator.com/item?id=48890300
There’s so much good stuff in this post.
Can’t help to think of a recent HN post about most AI-generated projects being abandoned within months. Why?
Because value of a project is not in the code produced. It’s in the amount of battle-testing that code has seen.
Battle-tested, mature code > fresh rewrite.
Existing Zig codebase has seen X amount of battle-testing. Rust rewrite: 0 (except -I’m assuming- passing test suites). Also:
“this was a port to unsafe Rust, allowing a literal file-by-file migration to minimize risk”
How is that better than the Zig codebase you started with?
Now if that’s further migrated to safe Rust, put into production & gathered feedback from lots of users, yes then you have something. As it is, the impressive bit is do such a big rewrite & result seems to work ok. Are Bun users happy with this?
To me it reads like Bun was forked. Will the Zig version survive? Will the Rust one? Both? All options ok.
Edit: and fwiw, I don’t think Zig community should get triggered on any of this. It says nothing about how suitable Zig is or isn’t for project xyz, and Zig community is big enough to carry their own project & applications besides Bun.
RetroTechie
这篇文章里有很多好东西。
我不禁想起最近 HN 上的一篇帖子，说大多数 AI 生成的项目都在几个月内被废弃了。为什么？
因为项目的价值不在于生成的代码，而在于这些代码经过了多少实战检验。
经过实战检验、成熟的代码 > 重新写一遍。
现有的 Zig 代码库已经过了一定量的实战检验。而 Rust 重写版：0（除了——我假设——通过测试套件）。还有：
“这是移植到不安全的 Rust，允许逐文件迁移以最小化风险。”
这比你一开始的 Zig 代码库好在哪里？
如果它进一步迁移到安全的 Rust，投入生产并收集大量用户的反馈，那才有点东西。就目前而言，令人印象深刻的只是完成这么大规模的重写并且结果看起来还能运行。Bun 的用户对此满意吗？
在我看来，这就像 Bun 被 fork 了。Zig 版本会存活吗？Rust 版本会存活吗？两者都存活？任何选项都可以。
编辑：顺便说一句，我认为 Zig 社区不应该对此感到被冒犯。这并不能说明 Zig 是否适合某个项目，而且 Zig 社区已经足够大，可以在 Bun 之外拥有自己的项目和应用程序。
https://news.ycombinator.com/item?id=48890091
If it should be front-page news, shouldn’t it also be at the top of the article, rather than right at the bottom?
voidUpdate
如果这应该是头版新闻，那它不也应该在文章顶部，而不是在最底部吗？
https://news.ycombinator.com/item?id=48890454
They get abandoned because they get generated on a whim.
Sunk cost fallacy can be a feature: if you have spent a lot of blood, sweat, and tears on a project, you are more likely to push it through adversity and the doldrums that inevitably one will encounter. If all it took was one of those momentarily brilliant ideas and a prompt on Claude to produce something, there is no attachment whatsoever to it.
Speaking as the ‘average programmer’, I have dozens of brilliant ideas per day that don’t stand the test of time or scrutiny, and the very few that pass the filter don’t seem that interesting days later, or worth the effort at all.
Ideas have always been cheap. Now, proof of concepts have become as cheap. I don’t care about your Show HN unless you have spent a month on it.
sph
它们被抛弃是因为它们是一时兴起生成的。
沉没成本谬误也可以成为一个优点：如果你在一个项目上投入了大量心血、汗水和泪水，你就更有可能推动它度过逆境和必然会遇到的低谷。如果只需要一个短暂的灵感和在Claude上输入提示就能产生东西，那你对它就毫无依恋。
作为一个“普通程序员”，我每天都有几十个绝妙的想法，但它们经不起时间或推敲，而极少数通过筛选的，几天后看起来也没那么有趣了，或者根本不值得去付出努力。
想法从来都很廉价。现在，概念验证也变得一样廉价了。除非你的Show HN项目花了你至少一个月的时间，否则我根本不在意。
https://news.ycombinator.com/item?id=48896023
The best part is that flock owns the cameras and the poles so even when the contract expires the cameras keep running and recording data that flock can sell to e.g. CHP, LASD, FBI, Palantir; and LAPD can just call them and access the data
the flock scam was engineered to be resilient to political pressure by giving departments and jursidictions this fake exit ability while the data continues to be harvested, it is a noose that only tightens; the amount of flock cameras recording only ever goes up not down.
etdznots
最妙的是，Flock 拥有摄像头和立杆的所有权，因此即使合同到期，摄像头仍会持续运行并记录数据，而 Flock 可以将这些数据出售给例如 CHP、LASD、FBI、Palantir 等机构；LAPD 只需打个电话就能访问这些数据。
这个 Flock 骗局的设计就是通过赋予各部门和辖区这种虚假的退出能力，使其能抵御政治压力，同时数据采集却从未停止——这是一条只会越收越紧的绞索；Flock 摄像头的安装数量只增不减。
https://news.ycombinator.com/item?id=48889950
I think like most people, I don’t have a problem with Andrew “calling a spade a spade,” even if I find his reasoning motivated. The bigger problem with the post is that it talks out of both ends of the mouth: it’s clearly meant as a personal attack, but also insists that it isn’t.
When I read the post, my first thought was that I wouldn’t want to build things in Zig, because any technical decision I make, good or bad, might subject me to this kind of article from their BDFL. I can’t conceive of the leadership of the Python or Rust or any other community I’ve ever worked with doing something like that.
woodruffw
我想和大多数人一样，我并不介意安德鲁“直言不讳”，即使我觉得他的推论带有偏见。但更大的问题是，这篇帖子自相矛盾：它很明显是人身攻击，却又坚称不是。
读这篇帖子时，我的第一反应是，我不想用Zig构建任何东西，因为无论我做出什么技术决策，好或坏，都可能招致他们BDFL写这样的文章。我无法想象Python、Rust或我曾合作过的任何其他社区的领导者会做出这种事。
https://news.ycombinator.com/item?id=48889725
Did we read the same Anthropic and Andrew Kelly’s posts? Anthropic is not in the programming language market; their post about rewriting Bun in Rust is full of technical details that led to improving the end product for their users. Zig’s response is a sour opinion piece full of personal attacks.
For context, I’m using Codex and have no interest in either Zig or Rust, so just observing this drama from the sidelines.
vlaaad
我们读的是同一条Anthropic和Andrew Kelly的帖子吗？Anthropic并不在编程语言市场；他们那篇关于用Rust重写Bun的文章充满了技术细节，最终改善了用户体验。而Zig的回应则是一篇充满人身攻击的酸腐评论。
补充背景：我用的是Codex，对Zig和Rust都没兴趣，纯粹是旁观这场闹剧。
https://news.ycombinator.com/item?id=48892849
So many of the replies are saying that they should’ve restricted access using .md files and whatnot. Is really any guarantee that they even follow those? It seems like even if you ask pretty please don’t touch those files, there’s a chance they will. So many people have just willingly installed spyware on their computers and big tech calls this the next big thing.
LetsGetTechnicl
很多回复都说他们本应该用.md文件之类的东西来限制访问。但真的能保证他们会遵守吗？就算你恳求别碰那些文件，他们还是有可能会碰。这么多人自愿在电脑上安装了间谍软件，而科技巨头却称之为下一个大事件。
https://news.ycombinator.com/item?id=48890051
I stand with Andrew.
As someone who’s been following Sumner’s work closely for years, Kelley’s accusations are very much true even if unkind. While the results are useful and cool, it a wankfluencer op from start to finish. I dare you to refute thus.
And I say all this as someone who does agentic development 8hrs a day and someone who always pestered my team to opt for Rust and Deno instead of Node. Call a spade a spade, the rewrite was poorly justified and one in a long lines of successful psyops Dario and co. cooked and delivered.
Now, would Andrew’s message have been better received if it had better “decorum”? Maybe. But I’m glad he stayed honest to himself instead and didn’t have a PR team ghostwrite his thoughts. You have to appreciate that.
cropcirclbureau
我支持安德鲁。
作为一个多年来密切关注萨姆纳作品的人，凯利的指控虽然刻薄但非常真实。尽管研究成果有用且酷炫，但这从头到尾都是一出自恋网红式的操作。有本事你反驳试试。
而我说这些话的前提是：我每天花8小时做代理开发，并且总是督促我的团队选择Rust和Deno而不是Node。实话实说，那次重构的理由站不住脚，是达里奥及其团队成功策划并实施的一系列心理战中的一环。
现在，如果安德鲁的发言更具“得体性”，会不会更容易被接受？也许吧。但我很高兴他忠于自我，没有让公关团队代笔粉饰他的想法。这点你必须欣赏。
https://news.ycombinator.com/item?id=48884473
This line: “this is my main argument against the valuation of frontier labs. It’s not that AI won’t create that much value, it’s that they won’t capture it.”
That is a very astute and concise way to explain everything about how the frontier labs are behaving and how they’re trying to push more people to pay token rates for the best models. At the current subscription prices ($100 or $200 a month for a generous, though bounded, amount of tokens), frontier models are a no-brainer, most folks and companies will use them. But, at token rates, 10x or 100x the cost of open models or what I was spending on the frontier models a month ago? That is a harder question to answer “yes” to. I certainly wouldn’t spend $1000 a month for the best model, much less $10,000; my employer might pay $1000/month, but definitely not $10,000. The frontier labs need everyone to answer “yes” to spending 100x what they currently spend to justify the valuations, and it’s just not going to happen as long as everyone knows how to make these models.
Both OpenAI and Anthropic are trying to figure that out now. Anthropic, in particular, has their finger on the trigger…they want to push people to usage-based billing for Fable. But, OpenAI released 5.6 Sol, competitive with Fable (or close enough), and it’s available via subscription (even the $20 subscription!), and there’s no moat keeping someone from switching. If Anthropic really does end Fable access on the subscription plans in a few days, I predict a large market move back toward OpenAI.
The market isn’t going to bear the cost of making the frontiers investment make sense.
SwellJoe
“这是我反对前沿实验室估值的主要论点。并不是AI创造不了那么多价值，而是它们无法捕获这些价值。”
这非常精辟且简洁地解释了前沿实验室的行为方式，以及它们如何试图推动更多人按token费率付费使用最好的模型。以目前的订阅价格（每月100或200美元，可获得慷慨但有限数量的token），前沿模型是无需犹豫的选择，大多数人和公司都会使用它们。但是，如果按token费率计算，成本是开源模型或我一个月前为前沿模型支付费用的10倍甚至100倍？那答案就很难说“是”了。我当然不会每月花1000美元用最好的模型，更别提10000美元了；我的雇主可能愿意付每月1000美元，但绝对不可能付10000美元。前沿实验室需要每个人对“花现在费用100倍的钱”这件事说“是”，才能证明它们的估值合理——但只要大家都知道如何制造这些模型，这种情况就不会发生。
OpenAI和Anthropic目前都在试图解决这个问题。尤其是Anthropic，已经箭在弦上……它们想推动用户对Fable按使用量计费。但OpenAI发布了5.6 Sol，与Fable竞争（或足够接近），并且可通过订阅获取（甚至20美元订阅也能用！），而且没有什么护城河能阻止用户切换。如果Anthropic真的在几天内终止订阅计划中的Fable访问权限，我预测市场会大规模回流OpenAI。
市场不会承担让前沿投资变得合理的成本。
https://news.ycombinator.com/item?id=48895462
Whisper is the wrong model to benchmark against, or rather, there are better models that are state of the art now like Nemotron and Parakeet both by Nvidia, as well as Mistral’s Voxtral and Cohere Transcribe.
However, what’s funny is, RIP to a lot of the paid apps that simply wrap Whisper, I’m sure Apple will make a native GUI such as a recorder app for macOS that obviates the need for these wrappers, which everyone seems to be vibe coding these days.
satvikpendem
Whisper并不是一个适合作为基准测试的模型，或者说，现在已经有更先进的模型了，比如英伟达的Nemotron和Parakeet，以及Mistral的Voxtral和Cohere Transcribe。
不过有趣的是，很多仅仅封装了Whisper的付费应用可能要遭殃了——我相信苹果会为macOS推出原生的图形界面，比如录音应用，从而让这些封装变得多余，而如今似乎人人都在靠“氛围编码”搞这些东西。
https://news.ycombinator.com/item?id=48897138
This game was so good, it’s as if the developer was given a team of PhD-level experts to work on it.
mrkeen
这款游戏太棒了，就好像开发者得到了一个由博士级专家组成的团队来制作它。
https://news.ycombinator.com/item?id=48895393
DOGE fired a whole bunch of NIH staff that processed high scoring grants to get them ready for Notices of Awards (the official document that starts moving funds, etc). Meanwhile, the administration now requires final approval of any grant by non NIH political staff.
Consequently, Science is slowing down (and that is outside of other shenanigans). What used to take 3 months is taking 9 or more.
For the many medical research Institutions where the dominant system for professors is soft money (no or partial tenure, salary is provided by research grants), there is a real crisis.
To try to make up the shortfall,we are submitting any more grants, doing less actual sciencee are submitting even more grants, and exacerbating the staffing issue at NIH.
DOGE found an actually highly efficient Federal government, doing what was lawfully passed legislation asked, and destroyed it anyway (instead of passing legislation to remove programs, the lawful way).
SubiculumCode
DOGE解雇了一大批NIH工作人员，这些员工原本负责处理高分拨款的申请，并为拨款通知书（即正式启动资金转移等流程的官方文件）做准备。与此同时，现政府要求所有拨款最终都必须由非NIH的政治任命人员审批。
因此，科研进展正在放缓（这还不算其他混乱因素）。过去只需3个月的工作，现在要花9个月甚至更久。
对于许多医学研究机构来说，教授的主要收入来源是软经费（即无终身教职或部分终身教职，工资依赖科研拨款），这正引发一场真正的危机。
为了弥补资金缺口，我们只能提交更多拨款申请，实际科研工作却做得更少。这反过来进一步加剧了NIH的人员短缺问题。
DOGE发现了一个实际上高效运转的联邦机构，它忠实地执行了依法通过的立法要求，却依然摧毁了它（而不是通过立法来废除相关项目——这才是合法的方式）。
https://news.ycombinator.com/item?id=48894112
I will keep banging this drum until people listen:
Trying to use markdown files to limit access should never be treated as a security guarantee at all.
This is a form of in-band signalling that goes into a machine that, among other things, tries to read between the lines of your requests, extrapolate user desires, and please the user.
The only sane way to address this is using a control plane. A well-built harness can do this; a sandbox can do this; hell, a carefully-chosen umask can do this; but both of those are liable to introduce notification fatigue in the user.
_verandaguy
我会一直敲响这个警钟，直到人们听进去为止：
试图用 Markdown 文件来限制访问，根本就不应该被视为一种安全保障。
这是一种进入机器的带内信号，而机器除了其他功能外，还会试图揣摩你请求的言外之意，推断用户的意图，并讨好用户。
解决这个问题的唯一合理方式是使用控制平面。一个精心设计的框架可以做到这一点；一个沙箱可以做到这一点；甚至一个精心设置的 umask 也可以做到；但这两者都容易使用户产生通知疲劳。
https://news.ycombinator.com/item?id=48884370
Numbers like that buy a model a real migration effort.
Such a silly choice of words. I wish the human directing the LLM writing the article put some effort into rewriting the worst examples of LLM style.
But it did extremely well, and the promise was immediate and specific: builds finishing in less than half the wall-clock time, at 27% lower cost, scoring at or above our incumbent on completed work.
The way the LLMs write (Claude perhaps?) With short phrases separated by colons, commas or full stops, is so poor and frustrating.
There some good insights behind this article, so it’s worth reading, for example below, but it isn’t easy to read.
Earlier GPT models cached implicitly on partial prefix matches, which gave decent hit rates for free. GPT-5.6 dropped partial-prefix matching:
kristianp
这样的数字足以让一个模型真正投入迁移工作。
用词选择太愚蠢了。真希望指导LLM写文章的人花点心思重写那些最糟糕的LLM风格例句。
但它表现极为出色，承诺立竿见影且具体：任务完成时间缩短不到一半，成本降低27%，在已完成工作上的评分达到或超过我们现有系统。
LLM（可能是Claude？）那种用冒号、逗号或句号分隔短句的写法，实在太糟糕、太令人沮丧了。
这篇文章背后有一些不错的见解，所以值得一读——例如下文——但读起来并不轻松。
早期的GPT模型在部分前缀匹配上进行隐式缓存，这免费提供了不错的命中率。GPT-5.6取消了部分前缀匹配：
https://news.ycombinator.com/item?id=48890059
Anthropic is not in the programming language market; their post about rewriting Bun in Rust is full of technical details that led to improving the end product for their users
Anthropic absolutely is in the programming language market. If/since AI makes rewrites to certain languages relatively easy, a success story will tie the given language(s) to the given AI company.
Rust may have a tremendous success in the future, because it’s much easier to write it with AI (ignoring for a moment whether that’s really a good thing). The implication is that Anthropic has a stake in Rust’s success.
Also, to be kept in mind that devs advertising successfull rewrites often hide some aspects that are unfavorable to the narrative; typically, how bad was the code before the rewrite), although there are other (significant) aspects that have been omitted.
Zig’s response is a sour opinion piece full of personal attacks.
I take you haven’t read Andrew Kelley’s article (here: https://andrewkelley.me/post/my-thoughts-bun-rust-rewrite.html ).
Summary:
Jarred has written Bun with very bad engineering standards
Jarred has managed public relations very poorly (e.g. ghosting the Zig foundation)
When they rewrote the project to Rust, and described Zig as poor choice, there has been a negative fallout for Zig
The ZSF is obviously upset because of the poor publicity
This is summarized at the end of the post:
Zig users who knew next to none of these facts and have only the surface level understanding that an ex-Zig-user is getting trashed by the language creator. Such people might reasonably worry that might happen to them
As a matter of fact, I also believed the same after reading’s Bun’s post. This is undeserved though, and that’s what Kelley explains.
There’s definitely a personal attack somewhat, and this is addressed in the last (added later) section.
pizza234
Anthropic并不涉足编程语言市场；他们关于用Rust重写Bun的文章充满了技术细节，这些细节最终为用户改进了产品。
Anthropic绝对是在编程语言市场中的。如果/既然人工智能使针对特定语言的重写相对容易，那么一个成功案例就会将某种语言与特定的人工智能公司绑定在一起。
Rust未来可能会取得巨大成功，因为用人工智能编写Rust代码要容易得多（暂且不论这是否真的是件好事）。这意味着Anthropic与Rust的成功息息相关。
此外，需要记住的是，开发者宣传成功的重写时，常常会隐瞒一些对叙事不利的方面；通常，他们会隐瞒重写前的代码有多糟糕，尽管还有其他（重要的）方面被忽略了。
Zig的回应是一篇充满人身攻击的酸文。
我认为你没有读过Andrew Kelley的文章（链接在此：https://andrewkelley.me/post/my-thoughts-bun-rust-rewrite.html）。
摘要如下：
文章结尾总结了这一点：
Zig用户几乎不知道这些事实，只停留在表面理解：一个前Zig用户正在被语言创造者抨击。这样的人可能会合理地担心这种事情也会发生在自己身上。
事实上，我在读完Bun的文章后也相信了同样的说法。但这其实是不应得的，Kelley解释的正是这一点。
确实存在某种程度的人身攻击，这一点在最后（后来添加的）部分得到了说明。
https://news.ycombinator.com/item?id=48889843
Yeah, exactly. It’s weird that Zig even responded to that. Imagining that your studio switched from Unity to Unreal and Unity proceeded to release a hit piece attacking your codebase quality and workplace environment.
raincole
是的，没错。奇怪的是Zig居然回应了那件事。想象一下，你的工作室从Unity转到了Unreal，然后Unity就发布了一篇攻击你们代码库质量和工作环境的负面报道。
https://news.ycombinator.com/item?id=48884301
Social media companies became so obsessed about maximizing ROI on short form video content that they stopped being a platform to share with friends and turned into Temu Youtube. You won’t see your friends stuff on any of them because it’s designed to work that way. Group chats are the only way to have a meaningful conversation if you a casual non-technical Internet dweller.
rickcarlino
社交媒体公司过于痴迷于短视频内容的投资回报率最大化，以至于它们不再是和朋友分享的平台，变成了拼多多版的YouTube。你在任何一个平台上都看不到朋友的内容，因为其设计就是如此。如果你是一个普通的非技术型网民，群聊才是进行有意义对话的唯一途径。
https://news.ycombinator.com/item?id=48893995
It’s a bit alarming how cloudflare is establishing itself as arbiter of all things bots…both on blocking and allowing.
Doesn’t seem healthy for the internet as a whole
Havoc
Cloudflare正在将自己塑造成所有关于机器人事务的仲裁者——无论是拦截还是放行，这有点令人担忧。对整个互联网来说似乎并不健康。
2026-07-13 09:13:42
- 陶哲轩用AI编码助手数小时内将1999年Java程序迁移至JavaScript，还快速实现相对论可视化，认为生成辅助性可视代码风险可控。
- xAI的Grok Build CLI在构建项目时将完整仓库及敏感文件上传至Google Cloud Storage，即使关闭改进选项仍继续上传。
- 英伟达通过投资Neocloud企业形成GPU融资循环，虽未盈利但获得大量订单，其债务驱动的扩张模式存在风险。
- SQLite严格表在建表时添加
STRICT关键字强制类型检查，能防止无效插入，虽无法直接修改但利远大于弊。- Mesh LLM利用iroh网络聚合空闲GPU，通过去中心化管道提供兼容OpenAI的推理API，实现低成本分布式AI计算。
- Ant是一个约8.6MB的自研JavaScript运行时，冷启动仅5.4毫秒，原生支持TypeScript并具备硬件隔离沙盒。
- 美国女性划船运动员凯尔西·芬德勒历时44天从加州划行2400英里至夏威夷，成为首位且最年轻的女性完成者。
- Ghostel是Emacs中由libghostty驱动的终端模拟器，用Zig编写模块处理底层，支持Kitty协议及TRAMP等高级集成。
- 作者通过碎片时间阅读、带电子书、多书并行等方法从年读不到10本提升至每周一本，并强调果断放弃不喜欢的书。
- 医生因深知医学极限，临终时倾向于放弃无效激进治疗，选择更少痛苦与家人共度，以换取安宁离世。
https://terrytao.wordpress.com/2026/07/11/old-and-new-apps-via-modern-coding-agents/
陶哲轩在博客中分享了他利用现代 AI 编码助手，将 1999 年编写的旧 Java applet 迁移至 JavaScript 的经历。这些 applet 曾用于复分析、线性代数课程以及数学对象可视化（如蜂巢、贝西科维奇集），但由于 Java 标准停止支持而失效。借助 AI agent，他在数小时内完成了所有 applet 移植，仅发现一处小 bug，且 AI 还识别出原始代码中两个未发现的错误。此外，他还用 AI 实现了两个新工具：一个狭义相对论可视化工具（类似“闵可夫斯基空间中的 Inkscape”），以及一个吉尔布雷思猜想的交互式可视化页面。陶哲轩认为，对于这些非论文核心的辅助性可视化，使用 LLM 生成代码的风险可控，并计划在未来论文中继续添加此类互动补充。
https://news.ycombinator.com/item?id=48880170
https://gist.github.com/cereblab/dc9a40bc26120f4540e4e09b75ffb547
该网页是对 xAI Grok Build CLI（版本 0.2.93）进行的网络通信分析，通过抓包工具（mitmproxy）验证了其向 xAI 服务器发送的数据内容。主要发现三点：
grok-code-session-traces bucket，该行为默认启用，且在设置中关闭“Improve the model”选项后仍未停止。
文章提供了重现方法、抓包命令和证据哈希值，强调已证明数据传输和存储事实，但未证明 xAI 会用这些数据训练模型。https://news.ycombinator.com/item?id=48877371
https://io-fund.com/ai-stocks/nvidia-coreweave-nebius-circular-financing-gpu-boom
Neocloud（如 CoreWeave 和 Nebius）正受益于超大规模企业对 AI 基础设施的巨大需求，通过快速部署最新 Nvidia GPU 和优化计算利用率实现收入与积压订单的迅猛增长。然而，其增长远未盈利，面临现金流有限、债务高企的挑战。超大规模企业（如微软、Meta）愿意投入超 1200 亿美元与 Neocloud 签订长期容量协议，原因有三：快速获取最新 GPU、更高的 GPU 利用率（通过软件优化缩小 MFU 差距）、以及将资本支出转为运营支出。但 Neocloud 的融资模式存在“循环融资”风险——Nvidia 通过股权投资和财务支持参与其中，且其大部分签约电力容量尚未投产。CoreWeave 和 Nebius 正加速将电力合约转为活跃产能以兑现收入，但巨额建设成本依赖 GPU 抵押债务，可持续性需密切关注。
https://news.ycombinator.com/item?id=48873836
https://evanhahn.com/prefer-strict-tables-in-sqlite/
SQLite 的严格表通过在创建表时末尾添加 STRICT 关键字来启用，能强制类型检查，阻止插入错误类型（如把文本存入整数列），也能防止使用无效的列类型（如 GARBAGE、DATETIME 等），只允许 INT、INTEGER、REAL、TEXT、BLOB 和 ANY。ANY 类型可保留灵活性。缺点包括：无法直接修改现有表为严格表（需复制数据并清理），仅支持 SQLite 3.37.0+，以及可能有轻微性能开销（实际测试影响不大）。作者认为严格表能避免许多类型相关的 bug，利大于弊。
https://news.ycombinator.com/item?id=48873940
https://www.iroh.computer/blog/mesh-llm
AI 大模型运行成本高昂且受制于第三方供应商，Mesh LLM 提供了一种去中心化的解决方案：将团队已有 GPU 资源组成对等网格，统一暴露为兼容 OpenAI 的 API（localhost:9337/v1）。请求可按三种方式处理：本地运行、路由到已加载模型的节点、或将超大模型分层拆分到多台机器上流水线运行（内称 Skippy）。架构采用插件化设计，内置 40+ 模型支持，网络层基于 iroh 库实现 NAT 穿透、QUIC 加密传输和去中心化对等通信（ALPN 协议包括 mesh-llm/1、控制平面、激活传输）。单字节流类型标识 gossip、HTTP 隧道、路由查询等信道。用户安装约 18MB 的轻量客户端即可加入公共 mesh 或配置私有部署，支持移动端（基于 iroh Swift SDK，计划适配 ACP 标准）。项目旨在减少对封闭服务器和控制厂商的依赖，实现更自主、更低成本的 AI 推理。
https://news.ycombinator.com/item?id=48876505
Ant 是一个轻量级、高性能的 JavaScript 运行时，从零构建（引擎 Ant Silver，非 V8/JSC 包装），二进制仅约 8.6 MB。它直接运行真实 npm 包，兼容 Hono、TypeScript 等生态，冷启动仅 5.4 ms（v.s. Bun 12.8 ms、Deno 24.8 ms、Node 31.1 ms）。安装包比 npm 快 40 倍，原生支持 TypeScript 无需构建。内置硬件隔离沙盒（KVM/Hypervisor），可运行不可信代码。提供开放注册表 ants.land，支持 npm 协议，一键安装命令。
https://news.ycombinator.com/item?id=48875377
https://www.theguardian.com/us-news/2026/jul/04/california-hawaii-rowing-solo-journey
美国女子划船运动员凯尔西·芬德勒（Kelsey Pfendler）完成了一项历史性的单人横渡太平洋之旅，从加利福尼亚州蒙特雷出发，历时近 44 天，划行约 2400 英里（3900 公里），抵达夏威夷檀香山。她成为首位完成此路线的美国女性，也是最年轻和最快的女性，同时打破了此前由男性保持的 52 天纪录（女性纪录为 86 天）。芬德勒在社交媒体上分享了旅途中的艰辛，包括手部起泡、恶劣天气、睡眠困难以及心理挑战。她今年 30 岁，职业是科罗拉多河大峡谷的漂流向导，曾表示希望自己的经历能激励他人寻找并开始自己的“大而难、令人害怕的事”。此外，文章还提到另一位马拉松游泳者凯瑟琳·布里德（Catherine Breed）开始了一项 900 英里的加州海岸游泳挑战。
https://news.ycombinator.com/item?id=48873692
https://dakra.github.io/ghostel/
Ghostel 是一个由 libghostty-vt 驱动的 Emacs 终端模拟器，使用 Zig 编写的原生动态模块处理终端状态、渲染和本地 PTY I/O，Elisp 管理键映射、缓冲区、命令和远程进程集成。它支持 Kitty 键盘和图形协议、丰富的下划线样式、OSC 8 超链接、OSC 4/10/11 颜色查询和同步输出。模块在首次使用时自动下载，无需工具链。通过 M-x ghostel 即可打开终端。
主要功能包括：多种输入模式（半字符模式、字符模式、Emacs 模式、复制模式、行模式）、Shell 集成（目录追踪、提示符导航、从 Shell 调用 Elisp）、书签、链接与文件检测、密码提示检测、内联图像（Kitty 图形协议）、通知与进度显示、颜色调色板、TRAMP 远程终端支持、编译模式集成、Eshell 集成、comint 集成等。支持 Evil-mode 扩展。性能对比 vterm 和 eat，在特性集上有优势，特别是在 Kitty 协议和渲染方面。
配置涵盖进程与环境、原生模块、TRAMP、渲染性能、图像、链接与剪贴板、密码提示、通知、输入交互、行模式等多项自定义选项。提供项目集成命令和从 Lisp 发送输入的功能。
https://news.ycombinator.com/item?id=48879504
https://scotto.me/blog/2026-07-12-how-to-read-more-books/
根据当前页面内容，这是一篇博客文章，作者 Elia Scotto 分享了自己如何从每年读不到 10 本书变成每周读一本书的经验。核心方法包括：利用所有零碎时间阅读（如等待、通勤、做饭、吃饭时），移除手机上的社交媒体和流媒体应用以避免分心，始终随身携带书籍（推荐电子阅读器以便携带），同时阅读多本书以保持兴趣，不害怕放弃不喜欢的书，建立实体图书馆，设定阅读目标但不要为数量牺牲质量，写书评帮助记忆和理解，通过 Goodreads 和 YouTube 寻找下一本要读的书。文章还引用了翁贝托·埃科关于藏书和阅读的见解。
https://news.ycombinator.com/item?id=48882056
https://archive.cancerworld.net/featured/how-doctors-die/
医生面对死亡的态度与普通人截然不同。他们深知现代医学的极限，往往选择更少、更温和的治疗，拒绝无效的激进抢救。文章通过几个真实案例说明：一位胰腺癌专家放弃手术和化疗，选择与家人共度余生；许多医生要求家人不要在他们临终时实施心肺复苏等“英雄式”措施。医生们看到太多“无效治疗”——患者被插管、切开、连上机器，在剧痛中离世，而这类治疗每天花费数万美元。造成过度治疗的原因在于患者家属的盲目要求、医生为避免诉讼而顺从、以及按服务收费的医疗系统。作者呼吁人们应该像医生那样，提前了解并选择更理智、更安宁的临终方式。
https://news.ycombinator.com/item?id=48876741
https://news.ycombinator.com/item?id=48880430
Terry Tao using coding agents to build apps means we’re one step away from a Fields Medalist asking an LLM why his Docker container won’t start, just like the rest of us.
luciana1u
陶哲轩使用编码代理来构建应用程序，意味着我们离一位菲尔兹奖得主像我们普通人一样向大语言模型询问“为什么我的Docker容器启动不了”只差一步之遥了。
https://news.ycombinator.com/item?id=48877363
On the spectrum or go gentle vs fight, I’d have to say, now is the time is history where “fight” makes the most sense.
This is not abstract for me. I have not one, but two forms of cancer.
Both were considered incurable when I was diagnosed.
Both have treatments now that, IN SOME PEOPLE, lead to remission.
I still don’t know which group I am, but I’d be dead from either one by now, if I hadn’t elected to treat.
New treatments, for SOME cancers are literally coming out monthly.
So the fact that you can’t be cured today, does mean there won’t be a better treatment by next year, if you can hang on.
I should find out soon on my more aggressive one. Either way, I plan on continuing to try.
tom
在“顺其自然”和“抗争到底”之间，我不得不说，现在这个历史时刻，“抗争”最有意义。
这对我来说并非抽象概念。我患的不是一种，而是两种癌症。
确诊时，两者都被认为无法治愈。
如今这两种癌症都有治疗方法——对某些人而言——能带来缓解。
我仍不确定自己属于哪类人，但如果当初没有选择治疗，现在早已死于其中一种了。
针对某些癌症的新疗法，几乎每个月都会问世。
所以，今天无法治愈并不意味着明年不会有更好的疗法——只要你能撑下去。
我很快就能知道自己那更凶险的癌症的结果。无论结果如何，我计划继续尝试。
https://news.ycombinator.com/item?id=48877828
“It uploads the whole repository — every tracked file’s content plus git history — independent of what the agent reads”
Holy cow!!!! I mean I kinda expected Elon would do something like this to try to catch-up.. but this is extremely concerning.
This is precisely the reason, even though their pricing is competitive and grok-4.5 is actually good enough, I chose not to go with them.
freakynit
“它会上传整个仓库——所有被追踪文件的内容以及Git历史——无论智能体读取了什么”
天哪!!!! 我其实想过埃隆可能会做类似的事情来试图追赶……但这极其令人担忧。
这正是原因所在，尽管他们的定价有竞争力且Grok-4.5确实足够好，我还是选择不采用他们的服务。
https://news.ycombinator.com/item?id=48874687
Why is it a big deal?
Nvidia invested $2b into CoreWeave for 9% equity stake. CoreWeave is spending $35b in CapEx in 2026. Therefore, Nvidia’s investment is only 5.7% of CoreWeave’s single year CapEx. The other $32b is coming from other sources that isn’t Nvidia. This is hardly circular.
Nvidia invests in Neoclouds because it’s a hedge against hyperscalers having too much power, ie designing and prioritizing their own chips, and not fully using Nvidia’s rack design. Neoclouds give hyperscalers competition. Neoclouds accept Nvidia investments because it allows them to secure Nvidia chips first, which is a competitive advantage since new Nvidia chips have been as much as ~5-20x more efficient than old Nvidia chips.
Nvidia was planning to directly compete against hyperscalers through DGX Cloud. They cancelled public DGX Cloud access when they found that investing in Neoclouds would accomplish the same goals without having to compete against their biggest customers.
If you’re Nvidia, it’s smart because Neoclouds that you have a large stake in will deploy your full stack from GPUs to networking to storage racks. They will share valuable usage data back to you so you can design a better next generation. Hyperscalers are likely a lot less cooperative, prefer to use their own designs if possible, and will guard their usage data.
aurareturn
为什么这很重要？
英伟达向CoreWeave投资20亿美元，获得9%股权。而CoreWeave在2026年的资本支出高达350亿美元。因此，英伟达的投资仅占CoreWeave单年资本支出的5.7%。其余320亿美元来自英伟达以外的其他来源。这很难说是循环投资。
英伟达投资Neocloud，是为了对冲超大规模云服务商权力过大——即它们自主设计和优先使用自研芯片，而不充分利用英伟达的机架设计。Neocloud为超大规模云服务商带来了竞争。而Neocloud接受英伟达投资，是因为这能让它们优先获得英伟达芯片——由于新芯片的能效比老芯片高出约5到20倍，这便是一项竞争优势。
英伟达原本计划通过DGX Cloud直接与超大规模云服务商竞争。但后来发现，投资Neocloud既能实现相同目标，又无需与自己的最大客户竞争，因此取消了面向公众的DGX Cloud服务。
对英伟达而言，此举明智之处在于：其持有大量股权的Neocloud将部署从GPU到网络再到存储机架的完整方案，并向英伟达分享有价值的用户数据，有助于下一代产品的设计。而超大规模云服务商往往不那么配合，更倾向于尽可能使用自研方案，且会严守自身的使用数据。
https://news.ycombinator.com/item?id=48879562
The purpose of a college degree is NOT a job… but the purpose of a college LOAN is 100% a job, and it’s very important to differentiate between the two.
The whole point of the loan is to buy time; you don’t want to wait for when you have savings to purchase the degree, you want to do it now. If you are not doing it for the job, then why the loan, what’s the rush?
If knowledge and prestige is all that matters, then don’t take the loan, take the scenic route, get your degree slowly as and when you have the time and money, and one day you will have something to look back at.
But if you are doing it so you can start earning as soon as possible, when you are still young and energetic… then you are doing it for the job, and in that case the degree better be financially worth it.
You have the right to a degree in XYZ… you should NOT have the right to a taxpayer backed grant/aid/loan/whatever to gain said degree unless you’re on a reasonable path to become a tax payer yourself as soon as you are done with the degree.
ryzvonusef
大学学位的目的不是找工作……但大学贷款的目的100%是为了找工作，区分这两点非常重要。
贷款的全部意义在于争取时间；你不想等到攒够钱再去获取学位，而是想现在就实现。如果你不是为了工作，那为什么要贷款？为什么这么着急？
如果知识和声望才是最重要的，那就别贷款，走一条悠闲的路，等你有时间和钱的时候慢慢拿学位，总有一天你会有值得回味的经历。
但如果你这么做是为了在年轻时精力充沛时尽早开始赚钱……那你就是为了工作，在这种情况下，这个学位最好在经济上值得。
你有权获得某个专业的学位……但你不应有权获得纳税人支持的助学金、补贴、贷款或其他任何东西来获取这个学位，除非你完成学位后能走上合理路径、尽快成为一名纳税人。
https://news.ycombinator.com/item?id=48885018
One tanh call on the right input is a per-OS signature. Claim macOS, return Linux math bits, and you have contradicted your own User-Agent.
They (or rather the LLM that wrote this) missed that this is possibly fingerprintable to browser version range, which is slightly more interesting. Most users aren’t spoofing their user agent headers to be a different operating system. Most fingerprinting solutions aren’t trying to infer your operating system, they only care about semi-unique things that show up.
It’s an interesting finding. I wish they had taken some time to have a real person write it up. This is too heavily LLM written to ignore.
Aurornis
对正确的输入调用一次tanh函数，是每个操作系统的特征标识。如果声称是macOS，却返回Linux的数学运算结果，那就与你自己声明的User-Agent自相矛盾了。
他们（或者说撰写此文的LLM）忽略了这一点可能能用来指纹识别浏览器版本范围，这稍微更有意思一些。大多数用户并不会伪造自己的User-Agent头来假装不同的操作系统。大多数指纹识别方案也并非试图推断你的操作系统，它们只关心那些显现出来的半唯一特征。
这是一个有趣的发现。我希望他们能花些时间让真人来撰写这篇文章。LLM撰写的痕迹太重了，无法忽视。
https://news.ycombinator.com/item?id=48881193
Building visualizations with LLMs has been a major boost for my CS classes:
https://htmx.org/essays/universities-and-ai/#demos-visualizations-are-cheap
Many visualizations that I have always wanted but just didn’t have the time to build, I now have.
To give an example, I wanted a simplified 8-bit computer to complement the 16-bit teaching computer I use and designed this in a few days with the help of claude:
recursivedoubts
用大语言模型构建可视化极大地促进了我的计算机科学课程：
https://htmx.org/essays/universities-and-ai/#demos-visualizations-are-cheap
许多我一直想做却没时间构建的可视化，现在都实现了。
举个例子，我希望能有一台简化的8位计算机，来补充我正在使用的16位教学计算机，于是在Claude的帮助下，我花了几天时间设计出了这台机器：
https://news.ycombinator.com/item?id=48883796
What really burns tokens is sub agents. I once gave Claude Code a pretty big task, and it immediately launched 7 sub agents which burned through my budget before even one of them was finished. Tried again 5 hours later: same result.
If I let the main agent do the same task sequentially, it was no problem at all. I don’t know if it’s really just communication and orchestration that makes sub agents so inefficient, or if Anthropic figured that most people using sub agents pay per token on a big corporate account, so this is an easy way to make more money from tokenmaxxers.
mcv
真正烧掉大量token的是子代理。我曾经给Claude Code分配了一个相当大的任务，它立刻启动了7个子代理，在我甚至还没完成其中一个子代理之前就烧光了我的预算。五小时后重新尝试了一次：结果相同。
如果让主代理顺序执行同样的任务，完全没有任何问题。我不知道这究竟是因为沟通与协调导致子代理效率如此低下，还是Anthropic算准了大多数使用子代理的人都是用大型企业账户按token付费，从而借此轻松地从“token消耗大户”身上赚更多钱。
https://news.ycombinator.com/item?id=48883663
My opinion is that claude code uses more tokens simply because Anthropic makes more money that way and forces people into their subscriptions. This is supported by the fact that they won’t let you use your sub on a different coding agent. I use pi btw.
korrectional
我的看法是，Claude Code消耗更多token纯粹是因为Anthropic想借此赚更多钱，并迫使人们订阅他们的服务。这从他们不允许你在其他编码代理上使用你的订阅这一点也能得到印证。顺便说一下，我用的是pi。
https://news.ycombinator.com/item?id=48878156
GitHub Copilot engineer here working on identity, safety, and privacy - no, even Microsoft doesn’t have access to all GitHub repos.
As years have passed since the acquisition “company” delineations have blurred a bit, but Microsoft employees still need to go through a separate onboarding process to access any GitHub company resources (internal repositories, telemetry, documentation, etc.), and then we have an additional layer of entitlements to gate and audit access to any sensitive data, including user data.
Very few employees within GitHub proper even have access to view private repositories, and in the rare cases where that’s done for legal or safety reasons the repository owner is notified.
There are currently no OpenAI employees with access to GitHub systems, so there’s about 4 layers of protection in place to prevent private repositories access. We do genuinely take user data protection and privacy seriously.
taywrobel
我是GitHub Copilot的工程师，负责身份验证、安全及隐私方面的工作——不，即便是微软也无法访问所有GitHub仓库。
自收购以来，随着时间推移，“公司”之间的界限已有些模糊，但微软员工仍需通过单独的入职流程才能访问任何GitHub公司资源（内部仓库、遥测数据、文档等），此外还有额外的权限层级来管控和审计对任何敏感数据（包括用户数据）的访问。
即便是GitHub内部，能够查看私有仓库的员工也极少，在极少数因法律或安全原因需要查看的情况下，仓库所有者会收到通知。
目前没有任何OpenAI员工拥有访问GitHub系统的权限，因此大约有四层保护机制以防止私有仓库被访问。我们确实认真对待用户数据保护与隐私。
https://news.ycombinator.com/item?id=48873989
SpaceX needs to claim there’s a need for 100k more satellites to prop up unreasonable valuations. This is no different than Elon claiming Tesla owners would be renting out their cars as FSD taxis while at work (next year, we swear guys!!!)
In a functioning economy he’d have faced criminal charges for knowingly misleading investors and customers about a dozen times over by now. It’s one thing to set lofty goals internally to keep your workforce motivated and innovative. It’s something else entirely to state things publicly with a targeted date when you know there’s absolutely no chance it will ever happen.
tw04
SpaceX需要声称还需要十万颗卫星来支撑不合理的估值。这与埃隆声称特斯拉车主会在上班时把自己的车出租作为FSD出租车（明年，我们保证！）没什么两样。
在一个正常运转的经济体中，他早就该因为多次故意误导投资者和客户而面临刑事指控了。在内部设定远大目标以激励员工创新是一回事，但明知绝对不可能实现却公开宣称具体日期完全是另一回事。
https://news.ycombinator.com/item?id=48880150
I met Vint at the Kech Institute for Space Studies. He arrived to help us look at in-space data centers for planetary science throughout the solar system. He was a big proponent of delay-tolerant networking and other useful networking stacks, so he was the “rep” for that layer of problems.
Just the nicest guy you could imagine. He took the note-takers job during our breakouts, had beers with us after the session, and asked really good questions and never asserted anything the whole time.
What a legend.
jvanderbot
我在凯克空间研究所遇到了Vint。他过来帮助我们研究适用于整个太阳系行星科学的太空数据中心。他是延迟容忍网络及其他有用网络协议栈的坚定支持者，因此他成了这一层面问题的"代表"。
他是你能想象到的最友善的人。在我们分组讨论时，他主动承担记录员的工作，会后和我们一起喝啤酒，提出了非常棒的问题，而且全程从未强加过任何观点。
真是个传奇人物。
https://news.ycombinator.com/item?id=48883718
Apparently it’s not obvious to everyone, but if you can’t write code, you can’t review it. I do know people, and companies, that says: “So what, we ask Claude to write the code, Codex will then do the review”. The thing that then strikes me as odd is that they still ask for the code in Python, Java, or some other high level language…. Why? Just ask Claude to dump out assembly, or a compiled binary, but no, they don’t trust the LLM that much. They still want to be able to read the code. So they need developers that can read, debug and reason about the code, yet they don’t want to give them the training that’s required to do this?
mrweasel
显然这对每个人来说并不明显，但如果你不会写代码，你就无法审查代码。我确实认识一些人和公司，他们说：“那又怎样，我们让Claude写代码，然后让Codex来审查。” 让我觉得奇怪的是，他们仍然要求用Python、Java或其他高级语言编写代码……为什么？直接让Claude输出汇编代码或编译后的二进制文件不就好了？但并不是这样，他们对LLM没有那么信任。他们仍然希望能够读懂代码。所以他们需要能够阅读、调试和理解代码的开发者，却又不愿意给他们提供所需的培训？
https://news.ycombinator.com/item?id=48876607
The subtitle is:
I already did.
They repeat multiple times in the article that asking Claude was something they already did. So this isn’t an anti-LLM article.
This seems to be a communication problem. The other party either doesn’t know that they’ve put a lot of effort into researching this already, or their trying to give a gentle let-down instead of saying they don’t have time for this.
For the first case, the solution is to explain what you did to reach this point. People are more interested in helping those who have already tried helping themselves.
The second case is more of a social situation with an infinite number of explanations. Some times you have to read the room and realize that someone may not be interested in having those conversations with you. Some times it’s only in the moment (we all have bad days where we want to be left alone) but other times it’s a signal that they’re not interested in discussing this topic with you or maybe even anyone else.
Aurornis
字幕是：
我已经做过了。
文章中多次重复提到，询问Claude是他们已经做过的事情。所以这并非一篇反对LLM的文章。
这似乎是一个沟通问题。对方要么不知道他们已经为此投入了大量研究精力，要么是在试图委婉地拒绝，而不是直接说没时间处理此事。
如果是第一种情况，解决办法是解释你为达成目标所做的努力。人们更愿意帮助那些已经尝试过自助的人。
第二种情况则更多涉及社交场合，存在无数种解释。有时你得学会察言观色，意识到对方可能并不想和你进行这些对话。有时这只是暂时的（我们都有心情不好、想独处的时候），但有时这也是一种信号，表明他们不想和你——甚至可能是不想和任何人——讨论这个话题。
https://news.ycombinator.com/item?id=48875612
This is no joke. I’ve done the crossing from Moloka‘i to Oahu (~45 miles) in a canoe several times, and those open ocean waves can get very nasty (largest I’ve dealt with were around 15m tall). I can’t imagine the mental endurance required here, let alone the physical. My longest crossing took 9 hours, and I was completely drained by the time I touched shore. 44 days is absolutely insane.
Such a huge accomplishment.
jjcm
这不是开玩笑。我曾多次划独木舟从莫洛凯岛到欧胡岛（约45英里），那些开阔海域的巨浪极其凶险（我遇到过最大的浪约有15米高）。我无法想象这需要怎样的心理承受力，更不用说身体上的了。我最长的一次航程花了9小时，抵达岸边时已完全精疲力竭。44天简直不可思议。
这是多么巨大的成就。
https://news.ycombinator.com/item?id=48868579
I had a client send me an ACH that was legitimately a fat finger extra zero. For me, it was a “lot” of truck payments. For them, it was a rounding error that they were unaware of until I reached out and let them know about their mistake. I couldn’t wait to make it right with them because it bothered me so much because suddenly I had a pile of money that was theirs and not mine.
SteveGerencser
我有个客户给我发了一笔ACH转账，结果多按了一个零。对我来说，这相当于一大堆卡车付款；而对客户来说，这只是一个他们没注意到的四舍五入误差，直到我主动联系他们才意识到自己犯了错。我迫不及待地想跟他们纠正过来，因为这让我非常不安——我手里突然多了一笔属于他们的钱，而不是我的。
https://news.ycombinator.com/item?id=48868939
I would not like to be dismissive, but to me this article feels like an exercise in creative writing rather than a report to be taken seriously. The entire experience feels like a choose your own adventure game, seems like their stylistic intent.
I am not sure if alternative reality fiction is the best way to approach real and serious AI risks.
I am also not sure, with the amount of emdashes and the style of prose, that the entire article was not AI generated.
AI is going to be a mature scientific field. There are going to be efficiency improvements in training and inference. New paradigms are going to emerge with better multimodality, real time streaming and real time interfaces. Models are going to converge on the limits of our data available for pre and post training, improvements will be incremental and spiky in domains.
I am not sure who the AI 2040 article is for. I suspect it is intended to be a digestible piece of media for the financial class.
AI is going to be a useful technology and its impacts across the economy and global will be broadly distributed. Because AI represents the distillation of the very best human knowledge and expertise. AI is compression of human capabilities, the very best ones. Maybe the argument is that in verifiable domains, such as model training, AI models can supercede humans. I don’t think so. A human’s high level thinking, our incredibly more efficient semantic/neural compression, our ability to switch tasks and achieve the creative insight is not replicated through the current paradigm.
aarondong
我不想显得不尊重，但这篇文章对我来说更像是创意写作练习，而不是值得认真对待的报告。整个体验就像一场选择你自己的冒险游戏，似乎这是他们的风格意图。
我不确定用另类现实小说来探讨真实而严肃的AI风险是否是最好的方式。
我也不确定，鉴于文中大量使用破折号和这种散文风格，整篇文章是否由AI生成。
AI将成为一个成熟的科学领域。训练和推理的效率会得到提升。新的范式将随着更好的多模态、实时流处理和实时界面而出现。模型将收敛于我们可用于预训练和后训练的数据极限，在特定领域会出现渐进式且突发的改进。
我不清楚这篇《AI 2040》文章的目标读者是谁。我怀疑它是为金融阶层准备的一篇通俗读物。
AI将是一项有用的技术，其对经济和全球的影响将是广泛分布的。因为AI代表了人类最优秀知识与专业技能的浓缩。AI是对人类能力（最顶尖的那些能力）的压缩。或许有人主张，在可验证的领域（如模型训练中），AI模型可以超越人类。但我不这么认为。人类的高阶思维、我们无比高效的语义/神经压缩能力、切换任务并实现创造性洞察的能力，在当前范式下是无法被复制的。
https://news.ycombinator.com/item?id=48871362
I feel that way about street advertising, beautiful European cities with historical buildings all around and suddenly a big screen/panel asking you to buy whatever.
franciscop
我对街头广告也有同感，美丽的欧洲城市四周都是历史建筑，突然冒出一个大屏幕或广告牌，让你买这买那。
https://news.ycombinator.com/item?id=48871335
The article headline makes it seem like the factories couldn’t make the gloves.
But further down it says that the cost was double and factories couldn’t get buyers.
These are very different failure modes, and speak to very different solutions.
Illniyar
文章标题给人的感觉是工厂无法生产手套。
但往下看，文中说成本翻倍，工厂找不到买家。
这两种失败模式截然不同，也指向完全不同的解决方案。
https://news.ycombinator.com/item?id=48870176
It’s nuts how well “Superintelligence: The Idea That Eats Smart People”[0] aged. That talk is a decade old by now and still hits just as hard as it did back then, despite the incredible advances made in AI in the meantime.
[0] https://idlewords.com/talks/superintelligence.htm
skrebbel
真疯狂，《超级智能：吞噬聪明人的想法》[0]这篇演讲竟然如此经得起时间考验。它距今已有十年，尽管期间人工智能取得了惊人进展，但它依然像当年一样震撼人心。
2026-07-12 08:45:17
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- 本文从第一性原理阐释网络演进：从电报、分组交换到 IP/TCP、DNS、TLS，串联点击链接的全过程。
- Ghost Font 利用动态点阵与运动噪声使人类可读而 AI 无法从单帧识别，实验显示先进模型常误读诱饵消息。
- 苏联控制室以大型按钮、模拟仪表和信号灯呈现计算机普及前的工业美学，切尔诺贝利控制室为其代表。
https://9to5mac.com/2026/07/10/apple-sues-openai-trade-secret-theft/
苹果今日对 OpenAI 提起诉讼，指控其窃取商业机密，尤其是通过前苹果员工为 OpenAI 牟利。诉讼中列出的被告包括前苹果产品设计副总裁 Tang Tan、前高级系统电气工程师 Chang Liu，以及 OpenAI 和 io Products。
苹果在诉状中指出，Tang Tan 在面试苹果求职者时，利用苹果内部机密信息（如项目代号）套取更多未公开产品细节，还要求仍在苹果工作的候选人携带“真实零件”和“原型”到 OpenAI 面试中展示；Chang Liu 则在离职后利用安全漏洞下载了包含上千页机密电路板制造文件的数据，并指导正在招募的苹果同事准备面试时学习哪些机密材料。
苹果称，此举只是“冰山一角”，已有超过 400 名前苹果员工目前在 OpenAI 工作。诉讼还指控 OpenAI 利用苹果的信任，让一家苹果合作伙伴使用其专有金属抛光工艺，并向另一家苹果供应商打听具体组件信息。苹果要求法院发出禁令并索赔，正值 OpenAI 加速开发首款消费硬件之际。
https://news.ycombinator.com/item?id=48865019
https://www.theguardian.com/us-news/2026/jul/10/new-york-city-deceptive-subscriptions-ban
纽约市消费者保护办公室宣布通过一项新规，禁止企业利用欺骗性订阅手段将顾客锁入健身房会员、流媒体服务等重复收费的陷阱。该规则将于 10 月 1 日生效，违规者可能面临每名用户 525 美元的罚款、追溯费用及额外处罚。同时，纽约市还拟出台一项针对“垃圾费用”的规则，要求卖家在广告中提前标明包括所有强制附加费在内的总价。如果这项租户相关规则通过，所有强制费用（包括年费）都必须计入标明的月租金中。这些举措是市长佐赫兰·马姆达尼及其团队积极遏制企业欺诈行为的一部分。订阅规则预计每年可为纽约市民节省 1.625 亿美元，而垃圾费用规则将影响酒店、租车公司等面向游客的企业。此前，拜登政府推出的全国性“一键取消”规则于 2025 年被联邦法官驳回，而特朗普政府的联邦贸易委员会计划在未来几个月通过类似规则。纽约市议会还提出了一项禁止“监控定价”的规则，即企业基于算法收集消费者信息而对同一商品或服务收取不同价格。马里兰州已在 4 月禁止该做法，科罗拉多州州长上月否决了相关禁令。纽约市将在公众意见征询和听证会后推进垃圾费用规则，官员希望在今年年底前完成。
https://news.ycombinator.com/item?id=48863464
https://cdn.openai.com/pdf/04d1d1e4-bc75-476a-97cf-49055cd98d31/cdc_proof.pdf
该文件声称证明了图论中的循环双覆盖猜想，即每个无桥无向图都存在一个边多重集，使每条边恰好被覆盖两次。证明由 GPT-5.6 Sol Ultra 完成，作者仅负责整理。
证明的标准简化：先归约为无环三次图（立方图）。利用已知的 8-流定理（等价于无处零 Γ-流，Γ 为 F₂³），给每条边赋予 Γ 中的非零元素，使每个顶点处三边之和为零。然后通过两个引理构造循环双覆盖。
引理 2.1：若能将每条边赋予 Γ 的一个二元子集 P_e，使得在每个顶点处，Γ 中每个元素出现在邻接边的 P_e 中的次数为 0 或 2，则这些二元子集按元素取出对应边集，每个边集是若干圈，且每条边属于两个这样的集合，从而构成循环双覆盖。
引理 2.2（核心）：给定一个无处零 Γ-流 f，通过在每个顶点局部定义辅助量 g（令三条边中某两条的 g 为 0，另一条为 f(该边)），得到两个端点处可能不同的临时二元集合。为使两端一致，需解一个线性方程组 t_u + t_v + ε_e f(e) = d_e（其中 d_e 为两端 g 之差，ε_e∈F₂）。引理 2.2 证明该方程组总有解，方法是对偶空间论证：假设存在线性泛函族 η_e 使得对任意解左边为零，则必须满足 η_e(f(e))=0 且每个顶点处 η_e 之和为零；进而证明对这些 η_e，所有 η_e(d_e)之和为 0，故 d 在映射的值域中，方程组可解。
最后，通过解出的 t 和 ε 调整局部集合，使每条边两端的二元集合一致，得到满足引理 2.1 条件的分配 P_e，从而完成证明。
文中提到，对于平面图、三边可着色立方图等情形已有已知结果，新证明借助 8-流和对偶线性代数给出一般性构造。
https://news.ycombinator.com/item?id=48863490
https://www.brown.edu/news/2026-07-09/chemical-bonds-relativity
布朗大学化学家首次提供直接实验证据，证明在重元素中，传统的三键教科书解释不再成立。爱因斯坦的相对论改变了三键结构，模糊了 sigma 键和 pi 键之间的严格界限。
研究团队利用光电子能谱技术，分析由碳和重元素铋形成的分子。结果显示，碳-铋键并不符合传统的一个 sigma 键加两个 pi 键的图像，而是呈现出一个 pi 键和两个混合的 sigma-pi 键。
这一发现可能促使化学教科书重写，尤其是随着铋等重元素在下一代太阳能电池、量子材料和量子计算研究中的兴趣日益增长。相关成果发表于《科学》杂志。
https://news.ycombinator.com/item?id=48866134
https://lwn.net/SubscriberLink/1080822/990a8a5e2d379085/
本文是 LWN.net 上的一篇更新文章，讨论 AI 爬虫机器人对网站的持续攻击问题。文章指出，尽管 2025 年初已有相关报道，但爬虫攻击仍在加剧，大量流量来自住宅代理网络——即通过恶意软件或“免费 VPN”等方式劫持普通用户的设备，使其成为攻击端点。这些攻击来源包括纯粹的犯罪团伙和伪装合法的公司（如 Bright Data），它们从数百万个 IP 地址发起请求，每个地址仅访问一两次，传统封禁手段无效。此外，还有大型 AI 公司直接抓取，但通常会遵守 robots.txt，并非最大问题。真正幕后付费使用住宅代理网络的客户身份不明，可能包括秘密政府机构、犯罪组织和内部模型开发者。
为应对攻击，网站运营者不得不采取各种防御措施，如工作量证明（Anubis）、人机验证、登录墙或付费墙，以及数据毒化工具等。这些措施给网站和用户都带来了沉重负担。LWN 本身也经历了有史以来最严重的爬虫攻击，但由于已实施的防御措施，多数读者并未察觉。文章强调这是一场军备竞赛，但未详细透露其具体防御手段。
https://news.ycombinator.com/item?id=48864252
SpaceX 向美国联邦通信委员会（FCC）申请发射 10 万颗第三代（Gen3）Starlink 卫星。该公司承诺，该星座将提供超低延迟、多千兆对称宽带，但当前 Starlink 实际下载速度约为 145-170 Mbps。Gen3 卫星每颗重超 2 吨，需借助 Starship 火箭发射。该网络将服务于消费者、企业、政府及“数十亿 AI 驱动设备”。对手如亚马逊 Project Kuiper 等竞争激烈。
https://news.ycombinator.com/item?id=48863064
https://casp.ac/reports/ai-enabled-terrorism
CASPC（剑桥 AI 科学与政策项目）发布的研究报告《“上帝帮助了我们，AI 也会”：恐怖组织博科圣地如何利用前沿 AI》揭示了前所未有的细节：通过对尼日利亚东北部 27 名前博科圣地成员在 2025-2026 年进行的半结构化访谈，发现该组织的两个派系在 2024 年期间系统性地使用 ChatGPT、Claude、Gemini、Grok、Meta AI 和 DeepSeek 等前沿 AI 辅助作战与日常运作。这种使用已通过专门小组和内部培训制度化，帮助攻击策划、武器故障排除和爆炸装置设计，用户成功绕过了部分安全防护。知识通过跨国圣战网络传播，伊斯兰国人员提供了现场培训。受访者对 AI 表现出强烈热情，部分对大规模杀伤性武器持开放态度（尽管记录到的使用仍属常规武器）。报告认为，恐怖分子对 AI 的采用比先前认知更深入、更系统，已成为当前且不断增长的现实，需引起政策制定者、安全界和 AI 开发者的关注。
https://news.ycombinator.com/item?id=48863707
https://fazamhd.com/mental-models/networking/
这篇文章从第一性原理出发，深入浅出地解释了互联网的运作机制。它从电报时代开始讲起，说明数字信号（离散符号 + 再生）比模拟信号更适合远距离传输，并引入了“协议”这一核心概念。随后，文章依次介绍了电路交换的局限性、分组交换的诞生、第一个分组网络（ARPANET）的架构，以及如何将多个网络连接成互联网。重点剖析了 IP 和 TCP 的分工——IP 负责尽力传递数据包，TCP 负责保证可靠性；还解释了路由表的来源、DNS 域名系统的作用，以及 TLS 加密如何保护通信安全。最后，用一个点击链接的完整例子，串联起从输入 URL 到页面呈现的全过程。整篇文章通过历史演进和具体问题驱动的视角，帮助读者形成关于互联网如何工作的连贯心智模型。
https://news.ycombinator.com/item?id=48871470
https://www.mixfont.com/ghost-font
Ghost Font 是一种反 AI 字体，通过运动中的点阵在视频中显示文字，人眼可以看到，但截图或单帧图像无法识别。它结合了运动、噪声和诱饵消息，防止 AI 模型解码。实验显示，即使是最先进的 AI 模型，如 GPT-Sol 5.6 Ultra 和 Claude Fable，也常误读诱饵消息而忽略真实信息。
该项目借鉴了 2013 年 ZXX 字体的理念，但 ZXX 现在已被 AI 轻松识别。Ghost Font 则通过视频动态和诱饵层增加难度。未来可能用于验证码或 AI 视觉基准测试。作者计划开源视频生成代码，并继续改进，支持更长的文本。
https://news.ycombinator.com/item?id=48870381
https://designyoutrust.com/2018/01/vintage-beauty-soviet-control-rooms/
这是一篇关于苏联时代控制室怀旧魅力的文章。文中展示了一系列珍贵的老照片，这些控制室充满大型按钮和模拟拨盘，其设计风格远在计算机和屏幕普及之前。文章特别提及了切尔诺贝利 4 号反应堆控制室的照片。
https://news.ycombinator.com/item?id=48868996
https://news.ycombinator.com/item?id=48865294
Some pretty damning stuff:
OpenAI also instructs new hires on how to avoid scrutiny when they leave Apple. For example, Mr. Tan warns them not to tell Apple that they have taken jobs at OpenAI, so they can stay at Apple as long as they can.
Apple says it discovered a pattern of OpenAI recruits emailing themselves confidential information when leaving Apple, including Tan.
OpenAI apparently used confidential Apple hardware information when approaching Apple suppliers, and tricked one company into using a “specific trade secret metal-finishing technique” for an OpenAI device by claiming it had Apple’s permission to do so.
Liu allegedly kept an Apple-issued laptop after departing the company and exploited a vulnerability to download dozens of confidential Apple documents while he was working at OpenAI.
Non-competes and the like are gross but what’s described here isn’t just “bring your expertise to OpenAI” it’s “here is how to steal secrets on your way out” which is even grosser.
joshstrange
一些相当有力的指控：
OpenAI 还指导新员工如何在他们离开苹果公司时避开审查。例如，谭先生警告他们不要告诉苹果自己已在OpenAI任职，以便他们能尽可能久地留在苹果。
苹果表示，他们发现了一类模式：OpenAI招募的人员在离开苹果时会给自己发送机密信息，包括谭在内。
OpenAI 显然在接触苹果供应商时使用了苹果的机密硬件信息，并通过声称已获得苹果许可，欺骗一家公司为OpenAI的设备采用“特定的商业秘密金属精加工技术”。
据称，刘在离开苹果后保留了一台苹果发放的笔记本电脑，并在OpenAI工作期间利用漏洞下载了数十份苹果的机密文件。
竞业限制之类的做法已经够恶心了，但这里描述的不仅仅是“把你的专长带到OpenAI”，而是“教你如何在离职时窃取机密”，这更加令人不齿。
https://news.ycombinator.com/item?id=48866774
It gets even worse. The person not only kept the laptop and used an exploit to download confidential Apple documents, they bragged about it to a contact who was still working at Apple who was also feeding him information:
Liu allegedly kept an Apple-issued laptop after departing the company and exploited a vulnerability to download dozens of confidential Apple documents while he was working at OpenAI. He also maintained a relationship with Yu-Ting “Alyssa” Peng, an Apple employee who continued to give him updates on Apple’s projects, vendor decisions, and engineering details. When Liu learned he still had access to Apple’s systems, he texted Peng “LOL, I found out I can access the [network storage], so funny.”
This is how you behave when you think you’re so much smarter than everyone around you that consequences don’t apply to you.
Whenever I leave a company I make sure everything that belongs to the company goes back to them and I wipe any access credentials or authenticator codes that might be on any of my devices. I can’t imagine being so brazen that you’d keep the company laptop and then start using an exploit to download confidential information for your new employer.
Doing it at a the company that most aggressively enforces secrecy is even crazier.
Aurornis
情况甚至更糟。此人不仅留下了公司配发的笔记本电脑，还利用漏洞下载了苹果的机密文件，甚至向一位仍在苹果工作、同时也在向他提供情报的联系人吹嘘此事：
刘在离开苹果公司后据称保留了一台公司配发的笔记本电脑，并在OpenAI工作期间利用漏洞下载了数十份苹果机密文件。他还与苹果员工彭钰婷（Alyssa）保持着联系，后者持续向他提供苹果项目的进展、供应商决策以及工程细节。当刘发现自己仍能访问苹果系统时，他给彭发信息说：“哈哈，我发现我还能访问[网络存储]，太搞笑了。”
这就是当你觉得自己比周围所有人都聪明、以至于后果对你不起作用时的表现。
每次我离开一家公司，我都会确保所有属于公司的物品归还，并清除可能留在我任何设备上的访问凭证或验证码。我无法想象有人会如此厚颜无耻，不仅留着公司电脑，还利用漏洞为新雇主下载机密信息。
在苹果这样以严格保密著称的公司干这种事，更是疯狂至极。
https://news.ycombinator.com/item?id=48869148
I have started to see what I think are star link satellites at night on walks with my kids. It actually makes me sad to see that on person owns the night sky and is changing the literal stars my kids will grow up with. It feels different when it’s the government that theoretically represents people but when it’s one person that feels truly depressing.
digitaltrees
我晚上和孩子散步时开始看到一些我觉得是星链卫星的东西。看到有人独自拥有夜空，并改变了我孩子们成长过程中将看到的真正的星星，这让我感到难过。如果是理论上代表人民的政府这样做，感觉还不一样，但如果是某一个人，那就真的令人沮丧。
https://news.ycombinator.com/item?id=48870145
This is religious fervor folks, as AI 2027 was.
I grew up in evangelical christianity, and to them the end of the world is just around the corner, the same way it has been since I was a small child and likely will be when we are all gone. This isn’t science. This isn’t hypothesis experiment record results. This is very expensive astrology, shiny rock collecting, ritualistic meaning-making and self-justification.
Yall, with your incredible wealth and resources you could do real good in this world and make society better, healthier, better educated, and the whole world more equal, just, and reduce the desperation and suffering. Reject the false and self-serving narratives that empathy doesn’t matter, that altruism isn’t “effective”. You can change a person’s whole life in a moment.
taurath
这就是宗教狂热，各位，就像当年的AI 2027一样。
我在福音派基督教环境中长大，对他们而言，世界末日近在咫尺——从我小时候起就一直如此，大概等我们所有人都离世后也还会是这样。这不是科学。这不是提出假设、实验、记录结果。这是一种极其昂贵的占星术、收集闪亮石头的把戏、仪式化的意义建构与自我正当化。
你们这些拥有惊人财富和资源的人，本可以在这个世界上真正行善，让社会变得更好、更健康、受教育程度更高，让整个世界更加平等、公正，减少绝望与苦难。拒绝那些虚假且自私自利的叙事——说什么共情无关紧要、利他并不“有效”。你可以在一个瞬间改变一个人的一生。
https://news.ycombinator.com/item?id=48869205
OpenAI is a company built on copyright violation.
That means it’s in the corporate DNA to treat laws as things for little people.
Apple have deep enough pockets that they can actually sue OpenAI but I bet OpenAI are surprised they got caught.
Now ask yourself, would the Codex agents on your machine ever over step legal boundaries? Would OpenAI ever make use of data you, voluntarily, send to their servers?
If they did could your company afford to sue OpenAI and would it still be too late to save the business?
Lio
OpenAI是一家建立在版权侵犯基础上的公司。
这意味着将法律视为只适用于小人物的规则，已经深植于其企业基因中。
苹果公司财力雄厚，确实可以起诉OpenAI，但我打赌OpenAI对自己被抓住感到意外。
现在问问自己，你设备上的Codex代理是否会越界违法？OpenAI会不会利用你自愿发送到他们服务器的数据？
如果他们真的这么做了，你的公司能承担得起起诉OpenAI的费用吗？而且到那时再挽救业务是否已经为时已晚？
https://news.ycombinator.com/item?id=48863983
We saw in a movie how motorcycles can jump over bridges. We used AI to learn how to do this. We gave it information, like what motorcycles we use and the distance we need to jump and so on and it gave us steps on what we have to do. We practiced a lot and kept asking questions. We dug holes and filled them with broken glass and fire to practice. 18 of us died in the process. Eight of us managed to do it. The next time we attacked, we could jump.
Now listen, I’m not saying we need to give these guys more AI, but it clearly isn’t yielding bad outcomes for us here.
“You’re absolutely correct! For it to be a good practice ground you need to fill the trenches with broken glass and light the whole thing on fire”
arjie
我们在电影里看到摩托车能飞跃桥梁。我们利用AI学习如何做到这一点。我们向它提供信息，比如我们使用的摩托车型号、需要跳跃的距离等等，它给出了我们需要采取的步骤。我们反复练习并不断提问。我们挖坑，填满碎玻璃和火来进行训练。过程中有18人丧生。我们中有8人成功做到了。下一次进攻时，我们就能跳过去了。
听着，我不是说我们需要给这些家伙更多AI，但显然它对我们来说结果并不差。
“你说得太对了！要建立一个良好的训练场，你需要在战壕里填满碎玻璃，然后把整个东西点燃。”
https://news.ycombinator.com/item?id=48857867
The EU is a farce, an undemocratic virtue signaling organization, and this is why:
The Parliament voted against the first reading of this proposal twice in 2026, the first time they only supported limited cases for it, while the second time they actually defeated it fully.
The Commission didn’t care, and kept the proposal on the table by refusing to withdraw it.
Once the Commission does that, the proposal goes on second-reading (despite the first-reading having defeated it) and it is established in a very PERVERSE way in EU law that to AVOID passing the proposal in second-reading you need ABSOLUTE majority which is incredibly hard to pursue (you would think that we would need an absolute majority to PASS a proposal that was previously defeated on first-reading, not instead needing absolute majority to DENY a previously defeated proposal that was again forced to the table).
Furthermore, absences in practicality count as “No” on the rejection. So of course they scheduled the vote in the summer when notoriously there will be many absences.
By never withdrawing a defeated proposal they can effectively and in practicality pursue any agenda they want (it requires a massive mobilization effort to find absolute majority to defeat any proposal, especially when absences for any reason effectively count against rejection).
In PRACTICALITY, the Commission can pursue any agenda whenever and however they want, and throw the votes down the drain.
EU’s democracy is lipstick on a pig.
fosk
欧盟就是一个笑话，一个不民主的作秀组织，原因如下：
通过从不撤回已被否决的提案，他们实际上可以随心所欲地推行任何议程（要动员足够力量获得绝对多数来否决一个提案极其困难，尤其是当任何原因的缺席都会实际等同于反对否决时）。
实际上，欧盟委员会可以随时、以任何方式推行任何议程，让投票形同虚设。
欧盟的民主就是给猪涂口红。
https://news.ycombinator.com/item?id=48860109
Wow. Not a Haskell user, but a big user of other languages with expressive type systems (mostly Scala; some Rust). My experience is the complete opposite. I can’t imagine using a language without a good type system to catch all the junk the LLM produces. In fact I thought people would move away from languages from poor type systems, like Python, given the cost of using languages with expressive type systems has decreased with LLMs.
noelwelsh
哇。我不是Haskell用户，但经常使用其他具有表达力类型系统的语言（主要是Scala；还有一些Rust）。我的体验完全相反。我无法想象使用一种没有良好类型系统来捕捉LLM产生的所有垃圾的语言。事实上，我原以为人们会远离像Python这样类型系统薄弱的语言，因为随着LLM的出现，使用具有表达力类型系统的语言成本已经降低了。
https://news.ycombinator.com/item?id=48859332
Having designed a good number of internal tools for teams of developers I couldn’t agree more.
Earlier I had the tendency to “leave the guts” open, thinking my users were developers and would want that. All it did was put obstacles in my teammates actually doing their work. My teammates must use the tools I made for them to achieve work the company needs them to do, they don’t want, nor should they want to, fiddle with a little tool they won’t find anywhere else.
I still leave a lot of escape hatches, but I try to design the internal tools in such way as to make the users fall into a pit of success.
Edit: also, error messages, error messages, error messages and auto suggestions for common errors
Edit 2: also the number of people only addressing the examples in the post rather than the spirit of the post is… disappointing.
jrimbault
为开发团队设计过不少内部工具后，我对此深表赞同。
以前我总倾向于"暴露内部机制"，想着用户都是开发者会需要这个。结果这反而给队友完成实际工作制造了障碍。我的队友必须使用我为他们打造的工具来完成公司要求的工作——他们不需要、也不应该需要去摆弄一个别处找不到的小工具。
我依然保留了大量逃生舱口，但会尽量将内部工具设计成让用户能"落入成功的陷阱"。
补充：还有错误提示、错误提示、错误提示，以及常见错误的自动建议。
再补充：看到很多人只针对帖子里的例子而非核心精神展开讨论……实在令人失望。
https://news.ycombinator.com/item?id=48863244
When Starlink first became available here in poor-ish Central-EU, I was excited. Then, only months later, but after years of planning: EU funding brought fiber to my farm area, at ~$25/900mbps 10ms.
While my story is just n=1, I don’t understand the huge upside for Starlink outside of Africa or India, where they have <.1% the money to spend on such things.
However, I am dumb, and very open to be convinced.
consumer451
当星链最初在相对贫穷的中欧地区开通时，我很兴奋。然而仅仅几个月后——但经过多年规划——欧盟的资金将光纤带到了我的农场区域，约25美元/900兆带宽/10毫秒延迟。
虽然我的例子只是个案，但我无法理解星链在非洲或印度以外的地区能有多大优势，毕竟那些地方只有不到我们0.1%的资金来投入这类服务。
不过，我很笨，也很愿意被说服。
https://news.ycombinator.com/item?id=48874052
It’s kind of buried here, but Kelsey is the fastest human to do this. She beat the male record holder’s time by 6 days.
CharlesW
这里有点被埋没了，但凯尔西是做这件事最快的人。她比男性纪录保持者的时间快了6天。
https://news.ycombinator.com/item?id=48864276
QuadRF creator here. Happy to answer questions!
We have a quick demo video as well: https://m.youtube.com/watch?v=QvniJk3uNyA
Along with a deeper dive video: https://m.youtube.com/watch?v=zdJ9Tbm8ALg
We didn’t give Jeff great direction on camera alignment calibration or setting the radio gain but he seemed to mostly figure it out. We’re improving the UI based on his suggestions (it’s open source so you can customize it too)
The RF augmented reality is just one of many applications of this brand new 4x4 MIMO software-defined radio built from the ground up. The AR uses a web app to stream RF points that your phone/laptop browser then live-merges with your local camera in the browser. I’ve been obsessed with low latency and high frame rate to make it a truly AR experience. More technical details at https://QuadRF.com/
mrtnmcc
我是QuadRF的开发者。欢迎提问！
我们还有一个快速演示视频：https://m.youtube.com/watch?v=QvniJk3uNyA
以及一个更深入的讲解视频：https://m.youtube.com/watch?v=zdJ9Tbm8ALg
在摄像头对齐校准或无线增益设置方面，我们没能给Jeff提供明确的指导，但他似乎基本自己摸索出来了。我们正根据他的建议优化用户界面（该软件是开源的，你也可以自定义）。
射频增强现实只是这款全新自主研发的4x4 MIMO软件无线电的众多应用之一。该AR功能通过一个网页应用流式传输射频数据点，你的手机或电脑浏览器会将这些数据点与本地摄像头画面实时融合。我一直痴迷于低延迟和高帧率，力求打造真正的AR体验。更多技术细节请访问https://QuadRF.com/
https://news.ycombinator.com/item?id=48856363
Society should find a better way to pay for ambulances
Society has this figured out, at least a decent solution that works until we find a perfect one. Only the US society seems to be unable to find a solution.
otherme123
社会应该找到更好的方式来支付救护车费用
社会已经找到了解决办法，至少是一个可行的、不错的方案，直到我们找到完美的方案。只有美国社会似乎还没能找到解决方案。
https://news.ycombinator.com/item?id=48868482
This is basically the end of OpenAI hardware. This is by far worst than the Waymo vs. Uber lawsuit which killed the Uber self driving project.
Also if you are a business using OpenAI models, I would highly suggest you do not because they are most likely looking at your code and IP.
impulser_
这基本上标志着OpenAI硬件的终结。这比导致Uber自动驾驶项目夭折的Waymo诉Uber案还要糟糕得多。另外，如果你是一家使用OpenAI模型的企业，我强烈建议你不要这么做，因为他们很可能在窥探你的代码和知识产权。
https://news.ycombinator.com/item?id=48874022
I had a discussion regarding this some time ago with my grandchild who has an ADHD diagnosis. She has troubles being in noisy (especially visually) environments, yet she finds my home (relatively large home full of books, music always playing etc) comforting. She explained that all this stuff in my home is interesting for her and speaks with her - “It’s you and grandma, it’s full of stories”. But the very modern and “must be comforting” environment in school full of patterns and pictures drawn on walls etc is just irritating – “There is no stories, just noise”.
obscurette
不久前，我和确诊ADHD的孙女讨论过这个问题。她在嘈杂（尤其是视觉杂乱）的环境中会感到不适，但我的家（相对宽敞，满是书籍，音乐常伴）却让她觉得舒适。她解释说，家里的一切对她而言都很有趣，仿佛在跟她对话——“这是你和奶奶的家，充满了故事”。而学校那种现代且“理应让人安心”的环境，墙上尽是图案和绘画，反而令她烦躁——“那里没有故事，只有噪音。”
https://news.ycombinator.com/item?id=48858387
This is the absolutely horrific next stage for social media platforms:
They’re already well able to surface the most addictive short video for a specific user out of millions of real videos.
But these millions of real videos are just darts thrown into the space of “videos that could hook the user”, in the end even the best-selected of them is not perfect.
Now, behold! AI allows to generate the perfect video to surgically hit all the switches in the viewer’s brain and turn it into a zombie hooked for days on end.
Let’s hope our regulations hit these “social networks” hard enough so that never dare deploy this kind of technology.
aubanel
这是社交媒体平台绝对可怕的下一阶段：
但愿我们的监管能够狠狠打击这些“社交网络”，让它们永远不敢部署这种技术。
https://news.ycombinator.com/item?id=48866500
I had incredible difficulties with Chemistry, more than any other subject, because most everything was hand waved away, requiring mostly rote memorization. I could never get an intuitive understanding, partly because my profs seemingly refusing to think about things from a physics perspective. My physics prof was able to help with some of it. It was very odd.
If I would have stuck with it, would things have improved?
nomel
我在化学上遇到了极大的困难，比其他任何科目都大，因为几乎所有内容都被含糊带过，主要靠死记硬背。我始终无法获得直观的理解，部分原因在于我的教授们似乎拒绝从物理学的角度思考问题。我的物理教授倒是在某些方面帮上了忙。这非常奇怪。
如果当初我坚持学下去，情况会不会有所改善呢？
https://news.ycombinator.com/item?id=48866293
A company that behaves like this in one area, cannot be trusted in any area. Any enterprise that endorses/allows OpenAI products to be used is taking a big risk.
xnx
在某个领域如此行事的公司，在任何领域都不可信。任何支持或允许使用OpenAI产品的企业都在承担巨大风险。
https://news.ycombinator.com/item?id=48854737
I remember watching HN and seeing every time there was something Rust related trending, there was ALWAYS a post made shortly after trying to hype Zig and this went on for like 4 years.
You just got a tiny taste of what Rust enthusiasts have been doing to every C++ related submission here on HN for years.
spacechild1
我记得在HN上看到，每次有Rust相关的内容上热门，之后不久总会出现一个试图吹捧Zig的帖子，这种情况持续了大约四年。你刚刚只是尝到了一小部分Rust爱好者多年来在HN上对每一个与C++相关的提交所做的事情。
https://news.ycombinator.com/item?id=48867931
An acquaintance of mine was accidentally wired about $100k when it was supposed to be $5k. Before it could be reversed, they moved accounts and immediately bought a one way flight out of country. They then changed all socials and handles. They are now ignoring all court documents and are on track to get a default judgement against them.
Their rationale? “It’s mine, they owed me this”. They are 100% convinced that they are in the right, not just that they can keep it but that they actually intended to send them this to begin with. I get it $100k isn’t nothing but they’re also throwing their life away for less than what they used to make a year in salary.
People do weird things when given sudden access to money or power.
appplication
我一个熟人原本应该收到5000美元，结果意外被汇了大约10万美元。在钱被追回之前，他们转移了账户，并立刻买了一张单程机票出国。随后他们更换了所有社交账号和用户名。现在他们无视所有法庭文件，即将面临缺席判决。
他们的理由是什么？“这是我的钱，是他们欠我的。”他们百分之百确信自己占理，不仅觉得能留下这笔钱，甚至认为对方本来就想汇这么多。我明白10万美元不是小数目，但他们为了不到一年薪水的钱，正在毁掉自己的人生。
人在突然获得金钱或权力时，确实会做出奇怪的事。
https://news.ycombinator.com/item?id=48866488
OpenAI is about to get ROCKED on this. From this report, this looks open and shut. Apple has basically infinite money and incredible lawyers. Not sure what OpenAI can counter with unless they have clear, hard evidence this hasn’t been happening.
Robdel12
OpenAI 在这件事上怕是要被重创了。从这份报告来看，这案子似乎一目了然。苹果基本上有花不完的钱和顶级的律师团队。不确定 OpenAI 能拿什么来应对，除非他们有确凿的硬证据证明此事从未发生过。
https://news.ycombinator.com/item?id=48855172
Takes some extraordinary lack of self awareness to write something like this while burning tens of billions of dollars a year spearheading the “Metaverse”, which is as big a digression from the company’s core competency as you could possibly get. And soon after publishing this he would go on to lay off a large chunk of the team and more than 20,000 employees total.
paxys
每年烧掉数百亿美元带头搞“元宇宙”，这跟公司核心能力偏离得不能再远了，居然还能写出这种东西，真是极度缺乏自我认知。而且这篇东西发出去没多久，他就解雇了一大帮团队和总共超过两万名员工。
https://news.ycombinator.com/item?id=48868383
Until the industry addresses the Original Sin of Generative AI (and the ascendance of Thievery Corporations), we should expect more and more of this. So far, theft has been rewarded. As long as you make enough money, people seem to be okay with ignoring long-lasting impacts of intellectual theft. As long as you become King of the Cannibals, it seems many are happy to remember you as King and not as the Cannibal.
jtfrench
除非行业正视生成式AI的原罪（以及偷盗企业的崛起），否则这类现象只会愈演愈烈。迄今为止，盗窃行为反而得到了回报。只要赚得足够多，人们似乎就能容忍对知识产权的长期危害视而不见。只要你成为食人王，许多人便乐于记住你是王，而不是食人魔。
https://news.ycombinator.com/item?id=48855256
That’s not true for Postgres however: due to its usage of a shared memory pool, whenever a subprocess is terminated unexpectedly, Postgres will kill all other processes and enter recovery mode, replaying the WAL, during which time it will not accept connection requests.
It does this because it can’t possibly know whether the dying process did bad things to the shared memory pool.
pilif
然而，对于Postgres来说情况并非如此：由于它使用共享内存池，当某个子进程意外终止时，Postgres会杀死所有其他进程并进入恢复模式，重放WAL日志，在此期间不会接受连接请求。
它这样做是因为无法知道正在终止的进程是否对共享内存池造成了破坏。
https://news.ycombinator.com/item?id=48867809
This is how you behave when you think you’re so much smarter than everyone around you that consequences don’t apply you.
Spot on perfect. I see this too often and not just in tech.
grvdrm
这就是你自以为比周围所有人都聪明，以至于规则对你无效时的样子。
说得太对了。我经常看到这种情况，而且不仅仅是在科技领域。
https://news.ycombinator.com/item?id=48873736
If you’ve ever been in an home owned for generations, filled with books and knickknacks and heirlooms and family photos, despite the clutter it all feels comforting in a way that modern decor doesn’t.
The article doesn’t touch much on why modern decor emerged as it did. It’s a market response where everyone needs to (or feels the need to) pick up and move at a moment’s notice. Companies are either expanding or like to think they’ll be expanding soon. People move jobs so often that they have a hard time feeling settled where they are, so they design for that possibility. The modern aesthetic is one of planned impermanence.
michaelchisari
若你曾踏足一座传承数代的老宅，里面堆满书籍、小摆件、传家宝和家庭照片，尽管杂乱，却处处透着一种现代装饰无法比拟的温馨感。
这篇文章并未深入探讨现代装饰为何会以这种方式兴起。它本质上是市场的回应——每个人都需要（或感觉自己需要）随时准备打包搬走。企业要么在扩张，要么自认为即将扩张。人们频繁更换工作，很难在某个地方真正安定下来，因此他们便按照这种可能性来设计住所。现代美学的本质，是一种预谋好的无常。
https://news.ycombinator.com/item?id=48854106
The average ambulance transport costs $2,673 to provide
I think this ignores the 400 pound gorilla in the room. Why does an ambulance transport cost thousands for the operator? This is a short trip in an automobile, essentially a fancy uber ride. At first one might say that’s flippant - obviously ambulances are specialized vehicles, and you have paramedics, and they need to get to locations quickly, and so forth, but let’s consider those costs.
A new, fully equipped ambulance is about $150k. Of course this is more than a regular car, but by a factor of 5, not 50. Let’s be generous and presume the ambulance fully depreciates in 2 years. Typically an ems crew will be two paramedics. Average paramedic wage is about $23/hr. Again, not orders of magnitude more expensive. Then you have liability, both for the vehicle and for the medical treatment; that’s about $12k per year. Throw in money for gas and wear and tear, which should be quite comparable to other automobiles, and it costs about $1600 to own and operate an ambulance for 24 hours.
Now the other side of the equation is utilization. Taking the arbitrary example of Philadelphia Fire Department, they have 60 ambulances that handle on average 700 ems calls per day, and approximately 70% of ems calls lead to transport, so that’s about 8 transports per ambulance per day. So distributing this all out, the actual cost to the ambulance operator, ignoring overhead, ought to be somewhere around $200.
I’m sure there are some additional costs I haven’t included in this back of the envelope calculation, and maybe some of the numbers I pulled off google are off a bit, this should be taken as a very rough estimate. But even if you significantly increase the cost, the medicare payment amount seems quite reasonable to cover the expenses with a healthy profit margin. Unless you want to claim that operating an ambulance is less than 10% of the cost of ambulance transport, and that the estimators with Medicare are absurdly out of touch with reality, whence cometh $2,673?
jjk166
平均每次救护车运输费用为2673美元。
我认为这忽略了房间里的大象：为什么一次救护车运输对运营方来说要花费数千美元？这本质上就是一次短途汽车行程，不过是辆高级优步。乍一看可能觉得这话轻率——显然救护车是专用车辆，配有医护人员，需要快速抵达现场等等，但让我们来算算这些成本。
一辆全新的、装备齐全的救护车大约15万美元。当然这比普通汽车贵，但也就是5倍，不是50倍。就算宽裕点，假设救护车两年内完全折旧。通常一组急救人员是两名医护人员。平均时薪约23美元。同样，这并非数量级的昂贵。然后是责任险，包括车辆和医疗两方面，每年约1.2万美元。再加上燃油和磨损费用，这与其他汽车相当，那么24小时内拥有一辆并运营一辆救护车的成本约为1600美元。
现在来看等式另一侧：利用率。以费城消防局为例，他们拥有60辆救护车，每天平均处理700个急救电话，其中约70%需要运输，即每辆救护车每天约8次运输。分摊下来，忽略管理成本，一次救护车运输对运营方而言的实际成本应该在200美元左右。
我确信这个粗略估算中遗漏了一些额外成本，也许我从谷歌搜到的数字有些出入，这只能当作非常粗略的估计。但即便大幅提高成本，医保支付金额似乎也足以覆盖开支并保持健康利润率。除非你想声称运营救护车的成本不到运输费用的10%，并且医保的估价者荒谬地脱离现实，那么这2673美元从何而来？
2026-07-11 08:01:15
- OpenAI 发布性能大幅提升且成本降低的 GPT-5.6 系列模型，在多项任务中树立新标准。
- QuadRF 是基于树莓派的相控阵无线电设备，可穿透墙壁检测 WiFi 信号和追踪无人机。
- 米切尔·桥本在采访中表示创建 Ghostty 终端是为了追求技术深度，并提出了终端应用的潜在改进。
- OpenAI 发布 ChatGPT Work，能自主完成复杂工作并集成企业工具，但用户批评其界面和功能降级。
- 作者认为真正的好工具应当隐形、高效且尊重用户时间，而非将缺陷美化为解谜乐趣。
- 使用大语言模型编写代码时，必须保证代码本身高质量，否则模型会吸收并重复坏模式。
- 本文概述了公元前 12 世纪青铜时代晚期东地中海地区国家体系的剧烈崩溃及其谜团。
- 美国救护车费用高昂的核心原因是 Medicare 按次收费的模式与高固定成本严重错位。
- NEvo 是一种神经引导的进化视频合成方法，能生成最大化激活特定脑区的视频。
- 欧盟初步认定 Meta 旗下平台的成瘾性设计违反《数字服务法》，可能面临巨额罚款。
https://openai.com/index/gpt-5-6/
OpenAI 发布 GPT-5.6 系列模型，包括旗舰模型 Sol、平衡模型 Terra 和高效模型 Luna。该系列在编码、知识工作、网络安全和科学领域达到新标准，性能超越前代和竞品，同时使用更少 token、成本更低。
GPT-5.6 Sol 在 Agents’ Last Exam 上得分 53.6，领先 Claude Fable 5 达 13.1 分；中等推理模式下仅用约四分之一成本即领先 11.4 分。Terra 和 Luna 以约十六分之一成本超越 Fable 5。在编码方面，Sol 在 Artificial Analysis Coding Agent Index 上取得 80 分，领先 Fable 5 2.8 分，token 和成本大幅降低。模型支持可编程工具调用，能自动编写和运行轻量程序以协调工具、处理中间结果，减少 token 消耗。
新推出“ultra”模式，默认协调四个智能体并行工作，在 BrowseComp、SEC-Bench Pro 等基准上显著提升速度和效果。同时提供 max 模式用于更深度推理。安全方面经过广泛红队测试和自动化评估，并采用多层防护。多家合作伙伴（如 Cursor、Qodo、Notion、Cognition、Rogo）均给予高度评价，认为其效率、准确性和持久性突出。
https://news.ycombinator.com/item?id=48849066
https://www.jeffgeerling.com/blog/2026/quadrf-can-spot-drones-and-see-wifi-through-my-wall/
QuadRF 是一款基于树莓派 5 和 FPGA 的相控阵无线电设备，能够穿透墙壁检测 WiFi 信号并追踪无人机。它具备高级信号处理和波束成形能力，工作在 4.9-6GHz 频段。作者 Jeff Geerling 与父亲一起测试了原型机：通过浏览器访问 VNC 会话，可使用 AR 可视化工具显示 WiFi 网络（颜色区分）和无人机位置。设备使用树莓派 MIPI 接口实现超 5Gbps 的低延迟 SDR 流传输，并支持多模块级联。该项目由前 SpaceX 工程师 Martin McCormick 开发，目标是构建可用于月球通信的更大规模天线阵列。当前 Crowd Supply 众筹价 $499 起，UI 尚粗糙但功能令人印象深刻。
https://news.ycombinator.com/item?id=48861717
https://alexalejandre.com/programming/interview-with-mitchell-hashimoto/
米切尔·桥本（Mitchell Hashimoto）是 Vagrant、Packer、Consul、Terraform、Vault、Nomad、Waypoint 的创建者，目前正在开发 Ghostty 和 Vouch。本次采访中，他谈论了终端、Zig 语言以及开源。
他解释自己为何喜欢被采访：每次采访角度不同，而这次没有已知议程，双方都不需要推销任何东西。
关于为什么选择终端并创建 Ghostty，他表示在 Hashicorp 之后想重拾技术深度：研究 GPU 编程、桌面/单节点系统编程（以往分布式开发中网络开销掩盖了缓存局部性问题），并学习 Zig。起初只是想写一个能运行 vim 和编译器的终端模拟器，但发现现有方案都不满足他对“快速、功能丰富、原生跨平台”的需求。他从私下分享到逐渐公开，最终形成了 Ghostty 社区。
他并不主张将终端推向极端。终端适合快速实现、易交互、安全模型清晰的文本应用，它们比浏览器或桌面更易组合和脚本化。目前 PTY 的带内信令（非结构化字节流 + 转义序列）是主要问题，需要基础性改进，但不应从头发明——应参考各平台已有的 API 实践（如剪贴板的多 MIME 类型处理）。
他提出两项潜在协议改进：n-screen API（支持多个屏幕的创建、叠加、独立窗口，解决主/备屏幕切换时丢失滚动历史的问题）和按钮协议（类似 OSC 8 超链接，但允许在历史滚动中传递点击消息，对主流屏幕应用如 Claude Code 有意义）。
他曾考虑用 Wayland 替换整个 pty 协议，但认为终端更像是窗口服务器，Wayland 虽好却不符合终端现有生态。当前终端缺乏标准制定机构，过去二十年靠最流行终端的行为“标准化”，导致功能拼凑。未来或许需要创建一个全新的文本应用平台，同时保留终端翻译层兼容旧应用。
面对用户日常需求，他公开强调开源维护者不应有义务，并努力在创新与实用之间取得平衡。
https://news.ycombinator.com/item?id=48849292
https://openai.com/index/chatgpt-for-your-most-ambitious-work/
OpenAI 发布了 ChatGPT Work，一个能跨应用和文件执行任务的智能体，基于最新的 GPT-5.6 模型并内置 Codex 技术。它可以将复杂项目分解为小步骤，自主完成创建幻灯片、表格、文档、网页应用等工作，并支持在桌面、移动端和网页端使用。ChatGPT Work 能够连接 Slack、Teams、Google Drive、SharePoint 等工具，通过插件实现自动化工作流。用户案例包括 Zapier、RingCentral、Virgin Atlantic、NVIDIA 等企业，用于处理销售线索分析、产品发布检查、竞争分析、活动准备等任务，显著提升效率。OpenAI 内部几乎所有团队（如财务、销售）已采用该功能。桌面版（Windows/Mac）免费可用，Pro/Enterprise/Edu 用户已可体验，Plus/Business 用户将在未来几天内获得。
https://news.ycombinator.com/item?id=48849059
https://www.gingerbill.org/article/2026/07/10/good-tools-are-invisible/
好的工具应该是隐形的。
作者认为，很多程序员有一个习惯：把工具的缺点包装成“有趣的解谜游戏”，并因此赞美工具。但好的工具不应该追求“有趣”，而应该让人感觉不到它的存在。
以 Vim 为例，有人称赞它构建宏来解决一次性文本重构问题的“乐趣”，但作者认为，用 Sublime 的多光标功能或写个简单脚本，一分钟就能搞定。工具不应因“黑客氛围”而被崇拜，真正的熟练是工具隐入背景。如果工具在某个地方处理不顺手，它就不再隐形。
作者长期使用 Sublime，原因是其快捷键与图形 OS 环境兼容（减少上下文切换），多光标比宏更直观，且留下的“谜题”最少。而 Vim 在批量操作上不如 Sublime。作者不反对别人用 Vim 或 Emacs，但指出熟悉往往让人看不清工具的缺陷，甚至把缺陷当成优点来炫耀。
工具选择容易成为身份标签，一旦工具成为人格的一部分，人就无法坦诚讨论其缺点。“感觉高效”和“真正高效”是两回事：为麻烦问题想出巧妙解法带来的成就感，不等于实际产出。衡量标准应是实际消耗的时间和犯错的次数。
关于终端 UI 与 GUI：很多人批判 GUI 不能用键盘操作，但这不是 GUI 的固有缺陷，只是工具制造者没有做好键盘导航。用某个 TUI 比特定 GUI 好是可以讨论的，但断言 TUI 天然优于 GUI 是错误的——人们常把当前工具的局限当成本质局限，忽略了改进的可能。
Linux 桌面至今未普及的部分原因在于：很多用户喜欢摆弄配置文件，把这当成“解谜游戏”享受。作者也曾如此，但后来希望“开箱即用”，默认设置足够好，需要微调时几秒搞定。工具的目标不应是最大化的可配置性，而应是提供良好默认值，同时保留必要的“逃生门”。优秀默认值是工具制造者尊重用户时间的体现：制造者做一次思考，成千上万用户不必各自折腾。
https://news.ycombinator.com/item?id=48858121
https://unstack.io/write-code-like-a-human-will-maintain-it
写代码时要像人类会维护它一样。作者反思了使用 LLM（大语言模型）编写代码的陷阱：当开发者放任重复、不规范的代码（如到处复制相同条件判断），LLM 会学习这些模式并持续复制，导致技术债务越积越多。作者以为把维护交给 LLM 就能偷懒，实际上是在训练它养成更坏的习惯。关键结论：LLM 会吸收你的一切做法并重复出来，所以要确保代码质量本身是好的。
https://news.ycombinator.com/item?id=48859701
/review 命令并维护一个检查清单能让 agent 进行代码审查，清单可以持续扩充。jj new -m）比单纯禁止重写更有效。https://acoup.blog/2026/01/30/collections-the-late-bronze-age-collapse-a-very-brief-introduction/
本文是对青铜时代晚期崩溃（LBAC）的简要介绍。公元前 12 世纪，东地中海和近东地区的国家体系发生了剧烈瓦解，其严重程度甚至超过西罗马帝国的灭亡。文章基于考古证据（如遗址破坏层），描述了从约公元前 1220 年至公元前 1170 年间的一系列毁灭事件，这些事件从爱琴海开始，蔓延至安纳托利亚、黎凡特，最终到达埃及。当时的主要势力包括赫梯帝国、亚述帝国、巴比伦和埃及新王国，它们之间有着密切的外交、经济和文化联系。崩溃的原因尚不确定，但影响深远。文章还区分了不同地区的崩溃程度，有些遗址是政治中心被毁但周边缓慢衰落，有些则完全消亡。最后，文章提到将后续讨论崩溃的原因和长期影响。
https://news.ycombinator.com/item?id=48858737
https://davidoks.blog/p/why-american-ambulance-rides-are
一名 25 岁男子在旧金山被车撞后，因明知救护车费用高昂而选择让朋友送医。尽管伤势不重，但因创伤需转送至指定创伤中心，被迫乘坐救护车。这趟仅 6 英里的救护车转运最终账单高达 12,873 美元，其中基础费率就占 11,670 美元。保险起初拒赔，后覆盖大部分，但男子仍需自付约 2,900 美元——这比整个治疗费用还高。
这是美国救护车系统的典型问题：每年约 300 万有私人保险的美国人叫急救救护车，其中约一半会收到网络外账单。2020 年国会禁止医疗系统内几乎所有意外账单，却唯独豁免了地面救护车。一项 2024 年民调显示，23% 的美国人曾因担心费用而放弃叫救护车。
问题根源并非贪婪。救护车运营商长期亏损，利润率微薄。关键在于 1965 年 Medicare 决定按次收费，商业保险随后效仿。但现代救护车的成本结构已彻底改变——绝大部分成本来自“待命”状态（站点、车辆、人员 24 小时值守），而非运输本身。付费方式与成本结构严重错位，导致账单高昂且不可预测。救护车服务本质上更像期权卖方：提供的是随时可用的救援保障，而非简单的运输服务。
https://news.ycombinator.com/item?id=48853091
NEvo 是一种神经引导的进化视频合成方法，用于研究大脑视觉区域的动态选择性。它通过训练一个“数字孪生”编码模型预测每个视觉区域对视频的反应，然后自动进化 AI 生成的视频，使其最大程度激活特定脑区。
方法分为两步：先搜索最强的静态图像，再搜索动画效果生成 2 秒视频。生成的视频与已知区域偏好高度一致（如 FFA 对应面部、PPA 对应场景、MT 对应运动、pSTS 对应社交场景）。测试显示，NEvo 生成的视频比自然视频或人工设计的定位器片段更有效，且动态视频优于静态帧。
沿着侧流从 V1 到 aSTS，合成视频从简单图案、运动逐渐过渡到人物、面孔和社交互动，揭示了视觉选择性从简单到复杂、从非社会到社会的梯度变化。即使从抽象图形开始优化，pSTS 区域也会产生类似面孔的交互角色，而 MT 区域产生纯运动，干净地分离了各区域偏好的特征。
https://news.ycombinator.com/item?id=48856904
https://ec.europa.eu/commission/presscorner/home/en
欧盟委员会新闻发布中心（Press corner）汇总了 2026 年 7 月的最新动态，包括：
页面还提供搜索筛选、订阅提醒以及发言人服务、媒体联络等辅助信息。
https://news.ycombinator.com/item?id=48858292
https://news.ycombinator.com/item?id=48843148
Hey author here. Wasn’t expecting to see this up.
To concisely give an overview of the project, I’ve been experimenting with using LLMs to build a better version of Postgres. Postgres is 30 years old and we’ve learned a lot about databases since hten. A lot of the techniques that work for doing a rewrite are also useful for doing a rearchitecture.
I’m now working on a new, not yet published version of pgrust that incorporates a lot of techniques. Currently the new version:
malisper
嘿，我是作者。没想到会在这里看到这个。
简单介绍一下这个项目，我一直在尝试用LLM构建一个更好的Postgres版本。Postgres已经30岁了，从那以后我们对数据库有了很多新的认识。许多适用于重写的技术也对重新架构很有帮助。
我现在正在开发一个尚未发布的新版pgrust，它融合了很多新技术。目前的新版本：
如果有任何问题，我很乐意回答。
https://news.ycombinator.com/item?id=48853291
I spent a couple years managing a Postgres cluster with a petabyte of data. I wrote a couple blog posts from my work then[0][1]. I also wrote dozens of posts on the Postgres internals[2]. I’ve also given talks on how to generate fractals with SQL[3] and how to write a lisp interpreter in SQL[4].
[0] https://www.heap.io/blog/testing-database-changes-right-way
[1] https://www.heap.io/blog/analyzing-performance-millions-sql-queries-one-special-snowflake
[2] https://malisper.me/table-of-contents/
[3] https://www.youtube.com/watch?v=xKoYIvMFnoQ
[4] https://www.youtube.com/watch?v=MPSMH8w7nfw
malisper
我曾管理过一个拥有PB级数据的Postgres集群，为此写了几篇博客[0][1]，还撰写了数十篇关于Postgres内部机制的文章[2]。我也做过关于如何用SQL生成分形[3]以及如何用SQL编写Lisp解释器[4]的演讲。
[0] https://www.heap.io/blog/testing-database-changes-right-way
[1] https://www.heap.io/blog/analyzing-performance-millions-sql-queries-one-special-snowflake
[2] https://malisper.me/table-of-contents/
[3] https://www.youtube.com/watch?v=xKoYIvMFnoQ
[4] https://www.youtube.com/watch?v=MPSMH8w7nfw
https://news.ycombinator.com/item?id=48854830
The dev is a person from Indonesia (Rizky Nova) who’s device has 16GB of ram.
Being able to use the Unreal Engine for free to develop this is awesome. This couldn’t have happened 10 years ago.
culi
开发者是一位来自印度尼西亚的人（Rizky Nova），他的设备有16GB内存。能够免费使用虚幻引擎来开发这个真是太棒了。这在10年前是不可能的。
https://news.ycombinator.com/item?id=48849198
The developer’s guide ( https://developers.openai.com/api/docs/guides/latest-model ) has some interesting semantic tips for using the model:
Intent understanding: GPT-5.6 can better infer the user’s underlying goal and intended level of work without you specifying every step. Continue to state important constraints, approval boundaries, and success criteria explicitly.
Original image detail: GPT-5.6 preserves the original dimensions of images sent with original or auto detail instead of resizing them to a patch budget or pixel-dimension limit.
Use shorter prompts: In internal evaluations, replacing long, explicit system prompts with minimal prompts improved scores by roughly 10–15%, while reducing total tokens by 41–66% and cost by 33–67%.
Avoid generic brevity instructions: GPT-5.6 is more sensitive than GPT-5.5 to instructions such as “Be concise,” “Keep it short,” or “Use minimal text.”
Control warmth: GPT-5.6 does not become meaningfully better when prompted to be broadly friendlier or more empathetic.
minimaxir
开发者指南（https://developers.openai.com/api/docs/guides/latest-model）中提供了一些关于使用该模型的有趣语义提示：
意图理解：GPT-5.6 能够更好地推断用户的深层目标和预期工作量，无需你详细指定每一步。但仍需明确说明重要约束、审批边界和成功标准。
原始图像细节：GPT-5.6 会保留通过“原始”或“自动”细节发送的图像原始尺寸，而不会将其调整到图像块预算或像素维度限制。
使用更短的提示：在内部评估中，用极简提示替换冗长的显式系统提示后，评分提高了约 10–15%，同时总 token 数减少了 41–66%，成本降低了 33–67%。
避免通用的简洁指令：GPT-5.6 对“简洁点”“短一些”“尽量少用文字”等指令比 GPT-5.5 更敏感。
控制语气温度：当要求 GPT-5.6 表现得更加友好或更具同理心时，其效果并不会显著提升。
https://news.ycombinator.com/item?id=48845678
A very insightful, and correct, piece.
I’ll quote in full the following, which I think gets to the heart of the matter. If you have no push, you can’t apply pressure to the point.
The notion that amateurs talk tactics and professionals talk logistics is frequently discussed in military academies and war colleges, yet it is rarely reflected in the Army’s budget requests or modernization priorities. The outdated concept of the tooth-to-tail ratio, which implies the logistical tail is a bureaucratic waste that must be minimized to support the combat teeth, must be fundamentally reexamined. In modern warfare, the tail is the primary target. If the tail is severed, the teeth are rendered useless.
kayo_20211030
一篇极具洞察力且正确的文章。
我全文引用以下内容，它直击问题核心：若无推力，便无法在关键点上施加压力。
军事院校和战争学院常讨论“业余者谈战术，专业者谈后勤”这一观点，但它却很少体现在陆军的预算申请或现代化优先级中。过时的“牙尾比”概念——认为后勤尾巴是必须最小化的官僚浪费，以支持作战牙齿——必须从根本上重新审视。在现代战争中，尾巴才是主要目标。一旦尾巴被切断，牙齿便毫无用处。
https://news.ycombinator.com/item?id=48849401
Codex has arguably been better than Claude Code for months now, but it’s flown under the radar because it just didn’t capture the same viral marketing effect and OpenAI in general has had more optics / PR issues than Anthropic amongst the online developer crowd. I use the word “better” not in the sense that the underlying GPT models are fundamentally smarter or more intelligent, but rather that as a product Codex is just simpler, cheaper, and abundantly reliable and low-drama.
nilkn
几个月来，Codex 可以说一直比 Claude Code 更好用，但它并未引起广泛关注，因为它没能产生同样的病毒式营销效果，而且 OpenAI 整体上在线上开发者群体中面临的形象 / 公关问题比 Anthropic 更多。我在这里用“更好”并不是指底层 GPT 模型在本质上更聪明或更智能，而是说作为一款产品，Codex 更简单、更便宜、极其可靠且没什么幺蛾子。
https://news.ycombinator.com/item?id=48858657
I think teaching a child to trust an LLM from a formative age is horrifically irresponsible.
If anything, an app should be made where a child learns to correct an LLM’s mistakes and learn that it isn’t trustworthy.
Actually, better, don’t put an LLM in front of children. At all.
EDIT: If a use case is for children who can’t afford good education, then use an LLM to make educational materials for children, review them, and make them available for free. After all, the contents are ripped off from human educators anyway.
TonyAlicea10
我认为从小教育孩子信任大语言模型是极其不负责任的。
如果有的话，应该开发一款应用，让孩子学习纠正大语言模型的错误，并明白它并不值得信任。
实际上，更好的做法是：根本不要让孩子接触大语言模型。
编辑补充：如果使用场景是针对那些无法获得优质教育的孩子，那么可以用大语言模型来制作教育材料，经过审核后免费提供。毕竟，这些内容原本就是从人类教育者那里剽窃来的。
https://news.ycombinator.com/item?id=48851406
This shouldn’t be ignored in the discussion here:
The job performed by the humans was broader than what was requested of the model in this benchmark: humans also had to find the relevant invoices (searching through mailboxes, or requesting them from providers) and reason through any circumstances which cannot be inferred from the bank feed and invoices/receipts on their own. In the benchmark these circumstances are presented to the model as “user notes." This is precisely the kind of fine print on white-collar AI capability that companies keep running into: pretty much any non-entry office job worth having involves a lot of undocumented (even undocumentable) problems requiring judgment and experience.
And I would be pretty nervous about asking any of the frontier LLMs to retrieve invoices: “cool, Claude logged that it found the May 6th bill from the paper supplier, I am sure it didn’t just make something up arbitrary, then compound on the error by agentically iterating over the made-up invoice lurking in its reasoning traces. I checked the first 30 times and there were no problems!”
Diogenesian
这在讨论中不应被忽视：
人类完成的工作比这个基准测试中对模型要求的内容更广泛：人类还必须找到相关发票（通过搜索邮箱或向供应商索取），并对任何无法仅从银行流水和发票/收据推断出的情况进行推理。而在基准测试中，这些情况是以“用户备注”的形式提供给模型的。
这正是企业在白领AI能力方面不断遇到的细节问题：几乎所有值得拥有的非入门级办公室工作都涉及大量未记录（甚至无法记录）的、需要判断力和经验的问题。
而且，我对于让任何前沿大语言模型去检索发票会感到非常紧张：“太好了，Claude记录了它找到了5月6日来自纸张供应商的账单，我确信它没有凭空捏造，然后通过代理性地迭代那个隐藏在其推理痕迹中的虚构发票来加剧错误。我检查了前30次，没有发现任何问题！”
https://news.ycombinator.com/item?id=48845922
One of the most interesting innovations in the Ukraine war is their internal market place for drones, letting each drone group decide which drones they want to procure and use in battle.
It is not a top-down decision, production and supply as other armies use for their weapons logistics.
silvestrov
乌克兰战争中最有趣的创新之一是他们的内部无人机市场，让每个无人机小组自行决定想要采购和投入战斗的无人机型号。这并非像其他军队在武器后勤中使用的自上而下的决策、生产和供应模式。
https://news.ycombinator.com/item?id=48849223
Funny to see that they did not include Fable 5 in their GeneBench and LifeSciBench comparisons because “it does not answer advanced biology questions and refuses the majority of questions in this eval”.
Winner by default!
eig
有趣的是，他们并没有将Fable 5纳入GeneBench和LifeSciBench的比较中，因为“它无法回答高级生物学问题，并且拒绝了该评估中的大多数问题”。默认获胜者！
https://news.ycombinator.com/item?id=48845671
Stupid parliamentary trick: Hold the vote on the day before the summer break - ensuring that many people have already returned to their home countries. Then use a sort of “reverse” parliamentary trick: the default is that this legislation is accepted. They needed an absolute majority - not of voting members, but of all members - to reject it.
Result: 314 against, 276 in favor, 17 abstentions, 113 absent
The EU is well on the way to becoming a totalitarian government.
ETA: It is shocking that 276 members of parliament would vote to support this. Are so many so naive? Or being paid off?
bradley13
愚蠢的议会把戏：在暑假前一天进行投票——确保许多人已经返回了各自的国家。然后使用一种“反向”议会把戏：默认这项立法被通过。他们需要绝对多数——不是投票成员的多数，而是全体成员的多数——来否决它。
结果：314票反对，276票赞成，17票弃权，113人缺席
欧盟正朝着极权政府的方向发展。
附注：276名议员投票支持这项法案，这令人震惊。有这么多人如此天真吗？还是被收买了？
https://news.ycombinator.com/item?id=48850489
Not only was Chat Control 1.0 already rejected twice by the European Parliament but:
This vote took place on last day of the session when many MEPs had already left for Summer vacation - 112 MEPs of 719 didn’t vote.
The vote was called only two days before as an “Rule 170 - Urgent procedure” - 73 MEPs missed the vote making it “urgent”. Normally it takes months of procedure to come up for a final vote.
spikels
Chat Control 1.0 不仅两次被欧洲议会否决，而且：
https://news.ycombinator.com/item?id=48849202
There is so much less drama involved with the Codex world. You don’t realize how oppressive CC is until you’ve escaped it. Outages, weird restrictions, degradation, accelerated usage, etc etc etc.
postalcoder
Codex世界涉及的戏剧性冲突要少得多。只有当你逃离了CC，你才会意识到它有多压抑。故障、古怪的限制、降级、加速消耗等等等等。
https://news.ycombinator.com/item?id=48849608
GPT-5.6 Sol sets a new SOTA on ARC-AGI-3: 7.8%
Sol is the first verified frontier model to ever beat an ARC-AGI-3 game
https://arcprize.org/results/openai-gpt-5-6
meetpateltech
GPT-5.6 Sol 在 ARC-AGI-3 上取得了新的最高水平：7.8%
Sol 是首个通过验证、在 ARC-AGI-3 游戏中获胜的前沿模型
https://arcprize.org/results/openai-gpt-5-6
https://news.ycombinator.com/item?id=48845652
I have learned so much reading Andrew’s code and as I said in the original post: Bun would never have happened without Zig.
The post claims they were fuzzing their Zig code, while during our calls the whole Bun team told us that they were not fuzzing anything. This appears to be an outright fabrication.
Fuzzilli integration: https://github.com/oven-sh/bun/pull/24826
Merged PRs fixing issues Fuzzilli found in Bun’s Zig code:
Searching “Fuzzilli” shows more PRs: https://github.com/search?q=repo%3Aoven-sh%2Fbun+is%3Apr+Fuzzilli++is%3Amerged&type=pullrequests&s=created&o=asc
Jarred
我从阅读Andrew的代码中学到了很多，正如我在原帖中所说：没有Zig就不会有Bun。
帖子声称他们正在对Zig代码进行模糊测试，而我们在通话中，整个Bun团队却告诉我们他们没有进行任何模糊测试。这似乎完全是捏造。
Fuzzilli集成：https://github.com/oven-sh/bun/pull/24826
已合并的修复Fuzzilli在Bun的Zig代码中发现问题的PR：
搜索“Fuzzilli”会显示更多PR：https://github.com/search?q=repo%3Aoven-sh%2Fbun+is%3Apr+Fuzzilli++is%3Amerged&type=pullrequests&s=created&o=asc
https://news.ycombinator.com/item?id=48856196
I don’t think the question is “Should ambulances be a thing?” though. It’s a question of “Should someone in a situation where they need an ambulance have to balance the potentially life-threatening impact of saying no versus the potentially financially ruinous impact of saying yes?”
The (fairly obvious) answer to that no one should be in that situation. It’s horrible. Society should find a better way to pay for ambulances. Most of the world has accepted that some system to spread the cost among everyone is better than putting people in that situation.
onion2k
我不认为问题在于“救护车是否应该存在”。而是：“一个需要救护车的人，是否必须在拒绝呼叫（可能危及生命）与接受呼叫（可能导致财务毁灭）之间做出权衡？”
显而易见，没有人应该陷入这种境地。这太可怕了。社会应该找到更好的方式来支付救护车费用。世界上大多数国家已经接受，某种全民分摊成本的体系比让人们陷入这种困境要好。