lawflow
碎片输入，AI整合，案件主线清晰呈现
What it does
法律案情结构化引擎 LSE 律师每天面对的，是录音、微信记录、手写笔记堆成的信息废墟。从这堆噪声里提炼出一份能上庭的案情摘要，最快也要花掉一个小时——而这一个小时，本可以用来做真正的法律判断。 LSE 解决的就是这个问题。 将录音或对话记录上传，30秒内，系统自动完成情绪剥离、术语对齐、要件扫描，输出一张五维度结构化卡片：主体关系、时间线、核心诉求、争议焦点、缺失要件。不只是总结，更是"体检"——LSE 会明确告诉律师，还差哪张证据、还需要追问当事人什么。 结构化完成后，系统自动驱动类案检索，匹配裁判文书库中的高相关判例，附上相似点与差异点分析，让年轻律师的第一份案情报告，达到资深律师的判断水准。 每一次律师对 AI 结果的修正，都会被记录为高质量标注数据，持续反哺模型——用得越多，越懂法律。 LSE 不替代律师的判断，它只是把律师从60分钟的信息整理中解放出来，让专业判断发生在它该发生的地方。
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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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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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