ahmedxuhri · HN

Postroom – HN thread 2D Visualizer as auditorium AI-powered summaries

AI 室内设计 — 上传房间照片生成多种风格的装修设计，装修前即可预览效果

@mesbahlab · X

@palettetowncc · X

HomeDesign — AI 空间与家装设计工具，上传房间实拍、建筑外观或户型图，即可预览室内外装修改造效果，并生成 2D 布局、3D 效果图与 360° 全景

plutozc · V2EX

做了个 Codex Desktop 主题预览和切换工具，先调好再安装 最近一直在用 Codex Desktop ，觉得默认界面看久了有点单调，就顺手做了个主题编辑工具，分享一下： [Codex Skin]( https://getcodexskin.com) 可以先在网页里预览主题，调整背景透明度、面板透明度、颜色、模糊和圆角等参数，满意之后再下载并切换到 Codex Desktop 。 目前支持： - 自定义 JPG 、PNG 、WebP 背景 - 在线实时预览主题效果 - 调整透明度、颜色、模糊、圆角 - 预览满意后生成安装命令 - 不喜欢了可以恢复默认外观 目前主要面向 macOS 上的 Codex Desktop ，还是个人项目，功能和兼容性都在继续打磨。 欢迎试试，也想听听大家对主题参数、预览效果和安装流程的反馈。 直接网址： https://getcodexskin.com [轻喷 轻喷，可能还有些 bug

@pixelcave_john · X

Hey Germán! I recently launched and a major update to Tailkit!

u/dimabreezy · Reddit

Hey, I built a tech that predicts human attention (it's Machine Learning + Data project). I've being using it for the past 2 months and it gives amazing results to AI agents I'm a software engineer and I also love good visuals. And I hate when AI build UI but it doesn't understand what should be GRABBING the attention, so I've build a tech that solves that https://attentionproof.com/ Here you can sign in with the ChatGPT account and get free 2 tries (I got limited compute) so please g

u/LeonHelloWorld · Reddit

Build update: testing whether visual AI maps are actually clearer than chat This week I finished a public beta of BranchAI, a web app that turns a complex question into a visual tree instead of a single long AI conversation. The hypothesis is simple: people lose useful context once a chat has several follow-ups. Keeping those follow-ups visible as branches should make research and complicated topics easier to revisit. What is working now: - Generate a starting map from a question - Op

@ramio_io · X

@imsudipcreator · X

i created for freelancer portfolios

chenglong-hn · HN

Data visualizations are the bridge between user and data. But building AI agents that can generate visualizations reliably can be very tricky: - simple chart specs can be reliable, but generated charts are often of low quality due to reliance on system defaults; - complex chart specs with explicit details can produce good-looking charts, but they are verbose and agents can struggle with reliability We figured out it is a limitation on the language issue (not just AI capability thing) -- current visualization languages are a bit too low-level for AI agents, requiring them to explicitly make visual decisions that are supposed to be handled by a good compiler. Flint is a visualization intermediate language to address this issue, allow AI agents to solve this last-mile human-agent interaction problem. It provides a simple semantic-type based specification, and contains a layout optimization engine that can produce good-looking charts (filled with derived low-level details) from simple