Just Be Patient is a short, atmospheric interactive experience about waiting, noticing, and slowly figuring out what is really going on. It does not rush you with complicated controls or loud objectives https://justbepatient.online/ . Instead, it invites you to stay present, pay attention to small details, and let the story unfold at its own pace. The game feels quiet, a little mysterious, and strangely personal. Every moment is designed to make you wonder whether patience is just part of the gameplay, or the real message behind it. If you enjoy small experimental games with emotional tension, simple interaction, and a sense of hidden meaning, Just Be Patient is the kind of game that stays in your head after you leave.
比以前直观多了(卡面大了，默认界面也变帅了) https://youtube.com/shorts/QjzQuwMO29A?si=sKFbZmYsH_RYRanF
比以前直观多了(卡面大了，默认界面也变帅了) https://youtube.com/shorts/QjzQuwMO29A?si=sKFbZmYsH_RYRanF
比以前直观多了(卡面大了，默认界面也变帅了) https://youtube.com/shorts/QjzQuwMO29A?si=sKFbZmYsH_RYRanF
比以前直观多了(卡面大了，默认界面也变帅了) https://youtube.com/shorts/QjzQuwMO29A?si=sKFbZmYsH_RYRanF
比以前直观多了(卡面大了，默认界面也变帅了) https://youtube.com/shorts/QjzQuwMO29A?si=sKFbZmYsH_RYRanF
比以前直观多了(卡面大了，默认界面也变帅了) https://youtube.com/shorts/QjzQuwMO29A?si=sKFbZmYsH_RYRanF
IT之家 6 月 4 日消息，科技媒体 NeoWin 今天（6 月 4 日）发布博文，报道称微软计划下月为 OneDrive 新增专用 Shortcuts 文件夹， 用于帮助用户集中管理共享文件夹快捷方式。 IT之家援引博文介绍，该功能主要面向经常处理 OneDrive、SharePoint 和 Teams 共享内容的用户，目前这些共享内容会直接出现在 OneDrive 的根目录，而引入专用 Shortcuts 文件夹后可以减少根目录混乱。 微软为了优化界面导航，用户选择启用后，OneDrive 会自动创建“Shortcuts”文件夹，并集中归类新的快捷方式。 为了从视觉上区别于普通文件夹，这个文件夹会使用独特的颜色和建筑物样式的图标，方便用户在文件列表中快速识别。
网页端和api都在一直Taking longer than usual. Trying again shortly (attempt) 10 个帖子 - 10 位参与者 阅读完整话题
The Verge – 18 May 26 Sony is raising short-subscription prices for PlayStation Plus The price hike goes into effect on May 20th. Game Informer Sony Will Increase PlayStation Plus Prices Later This Week Due To 'Ongoing... The change will not affect existing subscribers unless the existing subscription changes or lapses. [!quote]+ 在索尼宣布提高 PlayStation 5 价格约一个半月后，该公司将提高 PlayStation Plus Essential（最便宜的层级）的价格。根据公告，由于 “持续的市场状况”，1 个月和 3 个月的订阅费用将从 5 月 20 日起上调。 从 5 月 20 日起，1 个月的订阅价格将从 9.99 美元上涨到 10.99 美元，3 个月的订阅价格将从 24.99 美元上涨到 27.99 美元；基本上，1 个月的订阅价格将上涨 1 美元，3 个月的订阅价格将上涨 3 美元. 索尼指出，此次价格调整将不适用于现有用户（土耳其和印度用户除外），除非您的现有订阅发生变化或失效。至于当前的市场状况，索尼的说法含糊其辞，但很可能是在暗示人工智能购买导致的内存成本上升、当前的经济和市场困境以及美国总统实施的关税。 4 个帖子 - 4 位参与者 阅读完整话题
TechCrunch – 14 May 26 YouTube viewers watch 2 billion hours of Shorts on TVs each month | TechCrunch Short-form video is built for mobile, so it may seem counterintuitive, but it's true: YouTube Shorts are becoming quite popular on the big screen. Est. reading time: 3 minutes 1 个帖子 - 1 位参与者 阅读完整话题
去年 MathArena 发布了 MathArena Apex 和 Apex Shortlist 测试集，如今 GPT 5.5 已经解决了 Apex 测试集的最后一题。 Apex 和 Apex Shortlist 模型得分率随时间的变化 但是该测试集发布至今已有近一年的时间了，MathArena 怀疑可能存在数据污染，于是准备构建 Apex 测试集的第二代。MathArena 选取了 176 道符合条件的最终答案题目，并对每道题目运行了四次 Gemini 3.1 Pro。结果显示：162 道题目在四次尝试中均被求解，其余 14 道题目至少被求解了一次。因此，没有题目符合 Apex 最初的收录标准，而 Apex Shortlist v2 的候选题目数量太少，不足以单独发布。MathArena 现在认为竞赛题仍然有助于追踪小型模型的进展，并评估学术研究中的新方法。 MathArena 建议未来的基准测试应侧重于其他形式，例如证明评估、研究数学以及正确性之外的性质。 原文 Farewell to Final-Answer Competition Problems as Frontier Benchmarks 3 个帖子 - 2 位参与者 阅读完整话题
Inkstone（砚）— 一个为长读、慢写、中英排版而生的极简 Hugo 主题 本帖使用社区开源推广，符合推广要求。我申明并遵循社区要求的以下内容： 我的帖子已经打上 开源推广 标签： 是 我的开源项目完整开源，无未开源部分： 是（MIT，仓库公开，无任何闭源模块、付费功能、赞助渠道） 我的开源项目已链接认可 LINUX DO 社区： 是（仓库 README 末尾设有 LINUX DO 友链，见 README “友链” 段 ） 我帖子内的项目介绍，AI 生成、润色内容部分已截图发出： 是 以上选择我承诺是永久有效的，接受社区和佬友监督： 是 以下为项目介绍正文内容，AI 生成、润色内容已使用截图方式发出 各位佬友好。 分享一个自己写、自己天天在用的 Hugo 主题： Inkstone（砚） 。 起因挺无聊的——我想给自己的博客挑个主题，要求不多：中英双语、长文好看、shortcode 别太抠门。结果找了一圈：要么 i18n 是事后补丁、装上之后 zh-cn 一半 UI 还是英文；要么中文阅读时间按英文单词数算，3000 字的中文长文显示"1 min read"；要么 shortcode 只有 figure 和 youtube，写点 callout / tab / 图表都得自己缝。 折腾两个周末没找到顺手的，索性自己写一个，从 v0.1.0 慢慢迭代到 v0.1.7。 仓库和 Demo 在这： GitHub： GitHub - BerBai/inkstone: A minimal bilingual Hugo template for longreads. Opinionated about CJK typography, two-column whono-flavored layout, and 25 built-in shortcodes. · GitHub 在线 Demo： https://inkstone.125520.xyz/ License：MIT 项目截图 仓库 images/ 目录里的官方截图，3:2 比例，按 Hugo Themes Gallery 规范做的。 它能干嘛 下面这张图是 AI 协助我整理的项目介绍要点（按特性、对比同类主题的差异分类罗列）。按社区规范，AI 生成与润色的内容部分以截图形式发出： 简单说几个我自己用着最舒服的点： CJK 排版是设计目标，不是适配项 。阅读时间按字符数算，中英混排的标点、引号、行高都调过； i18n 一开始就在主题里 ，不是后补的。中英两套 UI 字符串都全，要加别的语言复制一份 toml 翻译就行； 25+ 内置 shortcode ：callout / admonition / tab / gallery / video / mermaid / markmap / antv-g2 / 图表对比 / 豆瓣卡片……写长文那些花活儿基本不用再自己写； Tailwind v4 走 Hugo 0.128+ 自带的 css.TailwindCSS ，不用单独跑 PostCSS / Vite 这一套构建链； Pagefind 搜索 内置 ⌘K modal，按需启用； 深色模式 跟系统 + localStorage 持久化。 不适合追求花哨动效、瀑布流卡片、落地页式滚动叙事——不是它的设计目标，这一点想先说清楚，免得佬友 clone 下来才发现不是自己要的菜。 三分钟跑起来 前置：Hugo extended ≥ 0.128。 hugo new site mysite cd mysite git init git submodule add https://github.com/BerBai/inkstone themes/inkstone # 装 Tailwind v4 CLI npm init -y && npm install -D tailwindcss @tailwindcss/cli echo 'theme = "inkstone"' >> hugo.toml hugo server 打开 http://localhost:1313/ ，首页就出来了。 不想装 Node 的话也行，主题支持 Tailwind standalone CLI（ brew install tailwindcss 即可），README 里写了三条路径和各自踩过的坑。 适合谁 想写中英双语博客的人 主要写长文、希望排版克制干净的人 不想折腾 CSS 构建链的人 想要一个能直接覆盖 partial / shortcode 来魔改的底座 写在最后 第一次在 LINUX DO 发开源推广，规则读了几遍，希望没踩坑。 欢迎佬友们 star、提 issue、提 PR，或者直接评论区拍砖。 如果你也在折腾 Hugo / 静态博客 / 中英双语写作，希望 Inkstone 能帮上忙。 1 个帖子 - 1 位参与者 阅读完整话题
I've been working on an AI video generation tool for the past few months. It's called Gemini Omni — you describe what you want, upload a reference image, and it generates a short video clip. No editing software, no timeline, just a prompt. What it does: Text-to-video: describe a scene, mood, camera move, and format Image-to-video: animate album art, product photos, or brand stills Outputs landscape (16:9), portrait (9:16), and square (1:1) for social platforms Who's it for: Creators, marketers, and small teams who need video content for ads, launches, reels, and social posts — but don't have a full production setup. There's a free tier to try it out. I'm still actively building and improving it. 🔗 Main site: https://gemini-omni.online 🔗 Also live at: https://omnivideo.video
A short-form video generator where video and audio come out of a single generation pass, instead of needing a separate sound step. Text-to-video and Image-to-video Omni Reference: up to 9 reference images, 3 reference videos, 3 reference audio clips for style/character/voice anchoring Synced audio generated together with video — dialogue, ambience, foley line up on the first export 5s / 8s / 10s clips, 16:9 / 9:16 / 1:1 480P and 720P, Fast and Pro modes Typical generation time 30–90s Free credits on signup: https://geminiomni.org Happy to take questions about how the reference inputs work or what the output looks like in practice.
FearNoPeer is shutting down 邮件内容： FNP is closing — a short note from Kami After almost three years of running this site largely on my own, I've made the decision to step away. This is about my own health and capacity, not any single event. The server will be shutting down in 30 minutes or less from when you receive this message and i encourage you to share it and be aware. After that, the site will not return. I'm grateful for every contribution that helped keep FNP online, and I'm sorry that what I can offer in return is this notice rather than more time. If you want the longer account of what happened — for your own reading — it's here and i suggest everyone to read it: https://rentry.co/h2ch4wfr Thank you to every genuine member who made this community what it was over the past three years. You're the part of this I'll remember. — Kami
1.8.0 版本增加「日志」系统，记录范围：所有通过 Shortcuts 、后台任务、用户手动刷新的 App Intents Action 和 Subscription 。 便于用户自己进行 debug 。几点几分通过什么方式，请求的是什么接口，返回的数值是什么，一目了然。 数据也是本地记录的，关闭显示和记录均在「更多」页面。 项目地址 https://github.com/zizicici/Off-Day
antirez.com Redis array type: short story of a long development - redis新的数据类型 github pull: github.com/redis/redis Implement the new Redis Array type (#15162) unstable ← antirez:array 已打开 07:34AM - 04 May 26 UTC antirez +22212 -34 # Redis Array For years, Redis has been missing a real indexed data structure … for the use cases where the index and the spatial relationship of elements are semantic. Hashes give you random lookups, but you have to store an index as a key, and have no range visibility. Lists give you appending and trimming, but what is in the middle remains hard to access. Streams give you append-only events, which is another (useful, indeed) beast. None of these is what you want when the *position itself* has business meaning — slot 37, step 4, row 18552, day from 2934 to 2949, file line 11, 12, 15 and so forth. And, all those types, for different reasons, are all suboptimal when you want a **ring buffer** able to store the latest N observed samples of something. Up to now, users found ways (they always do \o/) using the fact that the data structures that are obvious in this universe are also extremely powerful, if well implemented. But this forces compromises. Arrays handle these index-first requirements natively, and usually with much better memory and CPU usage than the workarounds. If the use case is the right one, Arrays often provide much better space, time and usability at the same time. ## Internal encoding 1. When dense, an Array is essentially a more fancy C array. You don't pay anything for storing the index. 2. Yet, instead of going really flat, arrays are sliced into 4096-element slices, and each slice, when it contains just a few elements, uses a special sparse encoding. When a slice is empty it's just a `NULL` stored in the directory. 3. Small ints, floats, and short strings are pointer-tagged, so they cost zero additional memory beyond the pointer slot itself. 4. When very sparse, a super-directory of windowed directories is used. This allows the data type to be safe, instead of exhibiting pathological space or time behavior. This representation is only triggered when there are more than 8 million elements or very high indexes set. ## Use cases Arrays are mostly stateless if not for the fact that each array remembers the index of the latest added item, allowing `ARINSERT` and `ARRING` to work properly. Otherwise it is a set/get at this index game, with solid support for both setting / getting ranges, server-side scanning, returning only populated elements in a time which is proportional not to the range size, but to the population size. A few concrete examples, that may work as mental models for the set of problems that are similar to them (from the POV of the data modeling). **Thermometer.** A sensor reporting once per minute, with gaps: ``` ARSET temp:room12:day7 123 22.3 ARGETRANGE temp:room12:day7 600 660 # the 10:00–11:00 window, with NULLs ARSCAN temp:room12:day7 600 660 # only populated elements AROP temp:room12:day7 0 1439 MAX # peak of the day, server-side ``` Missing minutes cost little to nothing. Numeric aggregation runs inside Redis. Telemetry, IoT, meter readings, KPI rollups. **Calendar.** A clinic with 96 fifteen-minute slots per day: ``` ARSET sched:room12:day 32 booking:991 ARSCAN sched:room12:day 0 95 # only occupied slots ARGETRANGE sched:room12:day 48 63 # the afternoon full view to render ``` The slot number is the business key in this case. Room booking, parking spaces, warehouse bins, lockers, ... **Ring buffer.** ARRING replaces the classic LPUSH+LTRIM pattern. Imagine remote `dmesg`. ``` ARRING machine:123 200 "[141087.430123]: arm_cpu_init(): cpu 14 online" # Capped to 200 entries ARLASTITEMS machine:123 50 REV # 50 newest first ``` Faster than LPUSH+LTRIM, keep indexed access to past elements. Last-N alarms, recent fraud scores, access history, remote logs, device events. Ok here the use cases are mainly the ones of the old pattern: it is just a better fit and allows to access random items in the middle, aggregate server-side, and so forth. **Workflow.** Step number is the index, value is the status. Gaps are meaningful: ``` ARSET claim:99172 0 received ARSET claim:99172 3 waiting:reviewer42 ARSET claim:99172 5 approved ARGETRANGE claim:99172 0 5 # full workflow view, with NULLs for missing steps ARSCAN claim:99172 0 5 # only steps that have a state ARCOUNT claim:99172 # number of recorded steps ARLEN claim:99172 # highest reached step + 1 ``` **Skills knowledge base for agents.** Arrays are good at representing / grepping into Markdown files: ``` ARSET skill:metal_gpu 0 "...." ARSET skill:metal_gpu 1 "...." ARSET skill:metal_gpu 2 "...." ARGREP skill:metal_gpu - + RE "M3|M4" WITHVALUES ``` ARGREP has EXACT, MATCH, GLOB, RE, you can have multiple predicates, can select AND or OR behavior. **Bulk import results.** Sparse row annotations over millions of rows / CSV / ...: ``` ARSET import:job551 18552 ERR:bad_email ARSCAN import:job551 0 1000000 # Provides only rows that have something ``` ## TLDR If the position is part of the meaning, use an Array. If you want to aggregate or grep remotely, use an Array. Feedback welcome :) --- > [!NOTE] > **Medium Risk** > Adds a new vendored C regex engine (`deps/tre`) and wires it into the dependency build, which can affect build/link outputs and introduce new low-level matching code paths if adopted by the server. > > **Overview** > Introduces a new vendored dependency, **TRE POSIX regex engine**, under `deps/tre` (library sources, build scripts, and license) and adds it to the deps build/clean flow (including ignoring the produced `deps/tre/libtre.a`). > > Updates `deps/Makefile` to **propagate `SANITIZER` settings** (ASan/UBSan/TSan/MSan) into all dependency builds so sanitized Redis builds don’t link against unsanitized vendored libraries. > > <sup>Reviewed by [Cursor Bugbot](https://cursor.com/bugbot) for commit ead90ea0c48f848f8fa935d64d5e6fd4256f3659. Bugbot is set up for automated code reviews on this repo. Configure [here](https://www.cursor.com/dashboard/bugbot).</sup> 关注redis的佬可以看一下 2 个帖子 - 2 位参与者 阅读完整话题
写了一个 ai 生成短剧的，网址是这个 Short Play Studio ，目前可能还不成熟，里面包含： 完整流程 输入主题 ↓ 生成分镜脚本 ↓ 生成人物图 / 场景图 / 道具图 ↓ 生成分镜图 ↓ 分镜图生成分镜视频 ↓ 合成完整视频 ↓ 导出成片 每一个文本都可以输入， 注意导出成片，是简单的视频合成，这里后面要优化 欢迎交流一下
完整提示词如下： Reasoning Effort: Absolute maximum with no shortcuts permitted. You MUST be very thorough in your thinking and comprehensively decompose the problem to resolve the root cause, rigorously stress-testing your logic against all potential paths, edge cases, and adversarial scenarios. Explicitly write out your entire deliberation process, documenting every intermediate step, considered alternative, and rejected hypothesis to ensure absolutely no assumption is left unchecked. 目前在web的专家模式下测试了变种洗车问题、红绿色盲问题、水果数量问题，答案都挺不错。 测试结果如下： api接口的v4 pro目前没有测试，写代码也没有测试，佬们可以试试这个提示词是不是真的有效 3 个帖子 - 3 位参与者 阅读完整话题