教育学习8 hours ago
Voynich Grammar Lab — Inferred Structure & Candidate Readings
通过统计语法推理探索 Voynich 手稿的候选翻译和词类。
@geeky_gamer25 · X
Check out what I just built with Lovable!
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通过统计语法推理探索 Voynich 手稿的候选翻译和词类。
@geeky_gamer25 · X
Check out what I just built with Lovable!
用真实句子和间隔重复闪卡学习语言。
@LinguExcel · X
Become fluent in any language faster than ever by reviewing thousands of real life sentences. Treat language learning like a HIIT workout.
将AI生成的文本转化为自然人类语言，支持语法检查、检测和SEO优化。
@RohanAhmed06 · X
🚀 Built Humanely. An AI writing toolkit with: • AI Humanizer • AI Detector • Grammar Checker • Text Summarizer • SEO Tools I'd love your honest feedback 🙌
通过调整限流规则看AI提供商如何在需求激增时分配强模型。
eliotho · HN
I built a tool showing how AI providers (should) throttle their models
探索语言模型如何解释和处理文本的交互式平台。
belluxx · HN
Nanointerpret – LLM Interpretability Playground
估算LLM推理所需的显存、延迟、TTFT、TPOT与吞吐量。
popopanda · HN
LLM Inference Calculator – Estimate VRAM, Latency, and Throughput
AutoDocParse extracts structured data from invoices, receipts, and business documents with AI confidence scoring, review queues, webhooks, and team workspaces.
@robingeekydev · X
I'm a solo dev and I just launched something I'm genuinely proud of 🧵 — AI document parsing with confidence scores Here's the problem it solves: Every day, finance & ops teams manually re-type data from invoices, receipts, and purchase orders. It's slow. It's error-prone. And it scales terribly. AutoDocParse lets you: → Upload any business document → Get structured data extracted by AI instantly → Review only the fields the AI isn't sure about → Push data anywhere via API or webhook Built this as a solo dev. Would mean the world if you tried it 🙏 👉 — 20 free parses/month
在一个地方捕捉会议、用AI写笔记、在共享画布上创建图表。
@rubs_murga · X
Semantic Overlays 通过适配器修改冻结语言模型对标记文本的感知。
joshua_s_penman · HN
Semantic Overlays – an NX bit for LLM prompt injection (live demo)
在浏览器中测试小型语言模型（8M-13M 参数），离线可用。
u/Live_Confusion_3003 · Reddit
I trained an LLM that runs on an ESP32 and directly in the browser Link to try it out yourself is: topk.sh The models download their weights directly in the browser so it works offline. Keep in mind they are very small and inaccurate. (8M and 13M parameters) However, I am building 500M and 1B+ parameter local models for agent based coding and other purposes. I will be shipping hardware designed for these tasks which connect directly to you computer or other device.
上传数据集自动发现具有统计意义的相关性和因果关系。
@matthew_meadows · X
Correlation Studio - Discovery Mining • Causation Analysis A powerful new SaaS statistics application that brings the insights of correlation data science to everyone. Data science without the code.