Joined August 2011
赞同,我觉得输入法最重要的就是快速输入,程序响应速度和完全贴合自己的词库才是最重要的,所以我最近基于这个输入法做了大量贴合自己改动,github.com/chenyukang/qingji… ,在 AI 时代做这些太容易了。
最近在找词典时,就有人推荐了两个这样的输入法,我真觉得这是个糟糕的想法。打字都是一闪而过,像我这种用五笔的人,最快一分钟能打120个字,平均一个字也就0.5秒就上屏了,谁会停下来去看它的英文? 从工程上讲,这也违背了单一职责原则,一个软件,最好只解决一个问题。
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LLM 这个词已经用了这么几年了,好多翻译服务还是“法学硕士” 🤣
去年想弄清 LLM 怎么转,课要么只讲概念,要么一上来就调 transformers,中间那层永远看不见。 Train LLM From Scratch 用纯 PyTorch 把 Transformer 拆开:token、注意力、多头、整块、预训练,再到 SFT、Reward、DPO/PPO/GRPO。不靠 trl、peft、transformers;分词走 tiktoken。模块旁边有说明和预期输出,适合对着跑。 单卡先玩百万级最顺。文档里的示范底座大约 4 亿参数;十亿要看显存,可多卡。 github.com/FareedKhan-dev/tr…
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yukang retweeted
It is with great sadness that we share the news of the passing of Johannes Doerfert. Johannes was one of the most prolific and respected contributors to the LLVM compiler project, and his loss will be deeply felt. blog.llvm.org/posts/2026-09-…
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I'm not sure, the good thing is Rust is used in more and more projects, the bad thing is AI is so good at writing Rust 😅
BunのRust rewriteの話とか、最近色んなところで Rust の話題を見かけるけど、この流れで Rust の仕事もより増えていってほしい。
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一直沉迷 TUI,五一假期花了点时间打磨 Github 工作流 TUI,基本日常所有操作都支持,diff review 代码、写 comment,甚至加 emoji 等等,数据本地会做缓存,但会及时从远程更新,所以体验上非常快 catcoding.me/ghr/
What a delightful TUI! Next version of Omarchy will ship it as a lazy-installed default. So you can just type ghui and it'll get pulled, just like we do with opencode, codex, etc. github.com/basecamp/omarchy/…
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经常参与开源的朋友都可以尝试申请这个 Codex for Open Source,我已经完全用 codex 一个多月,彻底改变了我的工作方式。
Replying to @HiTw93
GPT 5.5 High or Extra High will blow your brains out after a week of usage It is a model that actually suits a lot of your projects perfectly The Codex App / CLI also comes with a migration skill, just ask it to help use the migration tool Also, since you are an open source maintainer you will get 6 months for free (like me) of Pro plan developers.openai.com/commun…
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一直没 get 到 Ghostty 的好处,试了两次就退了 😅
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yukang retweeted
rust is a perfect language for agents, given that if it compiles it's ~correct
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最近和微软的朋友聊天,听闻现在公司有各种考核 AI 的指标,会让大家安装 vscode 插件跟踪数据,会衡量每个部门所的 AI 使用率,各 leader 们也在全面拥抱 AI。我觉得是不是有点过了,到底是高质量的代码重要还是代码一定是 AI 写的重要?1/4
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我好奇翻看了一下最近的 PR github.com/microsoft/vscode-…,好家伙,全是 Copilot 在修复 bug,员工只是定期 review 和监工。我想,未来我们肯定会怀念手工搓代码的年代。3/4
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xitter.cf/valigo/status/20034249… 一个员工,一个月,用 AI 重构 100w 行 C/C++ 代码,难道还嫌现在的系统 bug 不够多么?4/4
Man I'm so tired but Microsoft just can't stop losing. This will be a colossal failure that they will most likely have to backtrack. You can't even physically READ one million lines a month, let alone understand them. And we all know how bad AI is at writing systems level code
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这和我之前犯的错很像,catcoding.me/p/avoid-mistake… 里的 `配置错误`,只是我用的是正则,这里的配置是个模型文件。另外,这么重要系统的代码里,随意地 unwrap 总归是踩坑了。
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After 3.5 years building GreptimeDB (@Greptime ), here's what I wish I knew before starting: The harsh reality: We jumped into execution without proper business validation. Our idea wasn't wrong, but we skipped the unglamorous work of talking to 50-100 potential customers first. What this cost us: 1. Chased SaaS/PLG strategies that looked good on paper but didn't match market reality for data infrastructure 2. Built features for "someday" instead of "today's customers" 3. Underestimated what it takes to build a database - it's a 5-year minimum commitment What actually worked: 1. Finding co-founders with resilience, not just skills, couldn’t have asked for a better partner than @Sunng 2. Treating everyone as adults - transparency over "protecting the team" 3. Listening to the harshest critics first The biggest lesson: Find 5-10 design partners who will run with you before writing code. The fear of "custom work" is pointless when you haven't proven PMF yet. That’s like worrying about scaling before you even have users. Building infrastructure is a long game. Snowflake spent 8 years before their IPO. MongoDB built community for 9 years before cloud revenue mattered. For data infra founders: the path is longer and messier than it looks. But find the right people, stay honest about what's working and what isn't, and keep shipping. ✊ #startups #databases #opensource #productmarketfit #founders #datainfrastructure #lessonslearned
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我曾发誓再也不要陷入无尽的配置中,所以我放弃了 emacs 转入 vscode 门下。上周末切换到 github.com/rime/squirrel 输入法,然后又开始了 clone 上百 MB 的各种配置,尝试写 Lua 来控制琐碎的输入细节,然后一个周末就没了。细节控的好奇心真不能太强,好费时间。
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找工作本来就是个双向选择的过程,大部分公司不关心你是否做过开源,识货的面试官能识别简历上有价值的开源贡献。从我的个人经历来说,幸亏参与 rust 相关的开源碰巧找到了适合的工作。
感觉对我来说,在找工作的时候开源经历加了很大的分,有可能是因为我是学生,有豁免权😅
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如果对 rust 开源感兴趣而又不排斥区块链,可以了解一下 cryptape.com,我们在尝试 Proof-of-Contribution 的招聘方式。
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