@abhigyantr04 · X

@sreebuildss · X

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

@useStockAI · X

@0xLingjieKong · X

Hey @Sarakhan49309, I'm currently building an agent specialized in data analysis that reduces hallucinations. would love to connect!

@TunaSignalAI · X

Any day traders / swing traders check out Its live since 2024 build with AI and using AI models and Machine learning to predict small cap pump stocks!

@ourideaai · X

Free account and AI Readiness assessment here for anyone interested :)

@TheChrisMarrano · X

@0xdeusyu · X

想知道代理是不是真的把每个 AI 站都送到同一个出口？ 答案：并不是。 我做了一个 AI 分流测试： 它会探测 ChatGPT、Sora、OpenAI、Claude、Grok、Anthropic、Perplexity 等 AI 服务，通过读取各站点的 Cloudflare Edge Trace 信息，获取实际访问情况： 出口 IP Cloudflare 边缘节点（colo） HTTP / TLS / WARP 状态 访问延迟 然后根据落地位置进行归组。 这次测试结果： 6 个服务（覆盖 7 个域名）走美国出口。 唯一例外是 Sora，落在东京节点。 也就是说，同一个代理配置下，不同 AI 服务并不一定经过同一个出口。看起来“都能访问”，实际线路、节点和落地点可能完全不同。 整个测试工具纯前端实现，零后端。

Detector de IA — 西班牙语优先的 AI 文本复核网站，可检查粘贴文本和文档，查看概率信号、句子高亮和可导出报告

pro_methe5 · HN

I scrape an $8.5M-ARR company run by AI agents and chart it live

hubraumhugo · HN

Design slop is the feeling that tells you a website is purely AI-generated. This is an attempt to classify the design patterns behind it. Applying this scoring to recent ShowHN submissions shows that about a third of the submissions show medium to heavy design slop: https://slopcop.adriankrebs.ch/show How the scoring works: - A headless browser loads each site (Playwright) - A small in-page script analyzes the DOM and reads computed styles - Every pattern is a deterministic CSS or DOM check. There are false positives, but my manual QA run verified it’s maybe 5-10%. Is design slop bad? Not really, just uninspired. After all, the web was never about the fanciest design, and before the AI era, everything looked like Bootstrap. However, there is a difference between trying to craft your own design and just shipping with whatever defaults the LLMs output. And the same has been the case pre-LLM when using CSS/HTML templates. I guess people will get back to crafting beautiful design