鲁行
你的 AI 旅行搭子,懂山东更懂你
What it does
鲁行是一款专注于山东旅游的 AI 智能行程规划助手。用户只需用一句话描述旅行想法,如"青岛3天海滨游"或"泰山日出2日",AI 即可自动生成包含景点推荐、路线规划、餐饮住宿、消费预算在内的完整行程方案。 产品基于大语言模型驱动,结合高德地图实时 POI 数据和维基百科景点图库,为用户呈现图文并茂的行程卡片。每个景点都配有详细信息,包括地理位置、开放时间、评分、周边推荐等,帮助用户全面了解目的地。 鲁行同时支持桌面端和移动端访问,桌面端采用双面板布局——左侧为 AI 对话窗口,右侧实时展示行程详情;移动端则针对小屏进行了专项优化,提供流畅的触控交互体验。系统会根据用户设备自动切换最佳界面。 产品特色包括:AI 一键生成行程、景点图片智能匹配、多日行程时间线规划、消费预算自动估算、行程一键导出分享。无论是第一次来山东的游客,还是想深度探索齐鲁文化的旅行爱好者,鲁行都能成为贴心的旅行规划伙伴,让旅行准备变得轻松有趣。
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I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
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Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
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With social media and now AI, its important to keep the indie web alive. There are many people who write frequently. Blogosphere tries to highlight them by fetching the recent posts from personal blogs across many categories. There are two versions: Minimal (HN-inspired, fast, static): https://text.blogosphere.app/ Non-minimal: https://blogosphere.app/ If you don't find your blog (or your favorite ones), please add them. I will review and approve it.
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