
StockAI — AI Stock Predictions, Signals & Screener
AI 股票预测和信号生成器,支持 backtesting 和 paper trading。
@useStockAI · X
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AI 股票预测和信号生成器,支持 backtesting 和 paper trading。
@useStockAI · X

Vulnsy是为安全团队提供的渗透测试报告平台,可10倍快速交付客户报告。
@TurvSec · X

对比和评估 AI 模型在编码、推理、代理和其他基准测试中的表现。
davidtsong · HN
Benchmarklist: track AI benchmarks (2.4k+), models, and capabilities

在多种格式中与AI进行实时辩论练习,获得性能反馈。
@prof_safezone · X
Gambling on debate rounds with AI judges.

在 leaderboard 上按官方基准对比 AI 大模型的性能排名
fcten · V2EX
做了一个大模型 leaderboard 网站 最近一个月 CodeX 疯狂送重置,token 根本用不完,顺手做点东西。 地址:[知行录]( https://leaderboard.cn/) 排行依据主要为模型官方基准测试成绩。非主观排名。 数据会持续更新。如果有点用,欢迎各位 v 友收藏~

由AI驱动的代码审查工具,在microVM中运行代码来捕获更多错误。
u/dumbfoundded · Reddit
Ito, AI Code Review that Runs Code I've been using AI code review tools but none of them actually run code so I built one: https://www.ito.ai/ The way it works is that it uses microVMs to spin up your environment with all of the services running. Then a bunch of AI agents go and test the application to collect runtime evidence. The result is you get test cases along with evidence about whether or not the test cases pass or fail. The runtime evidence can be videos, request/response curls, db

在智能代理笔记本中构建、运行和评估机器学习工作流。
eldar_hsnv · HN
Show HN: AI Notebook for Data Science – Kind of Like Cursor but for Jupyter

评估AI系统是否符合负责任和道德AI实践。
@TheWhiz351 · X
I built two versions of the same responsible AI app using different vibe-coding platforms. Perplexity Computer: Base44: Try both. Which has the better design and user experience? #VibeCoding #ResponsibleAI

为你的AI代理添加评估报告,生成可分享的URL展示性能。
adeeonline · HN
AgentsProof – a small project for testing AI agents

PRcade 通过团队排行榜和分析可视化GitHub代码审查性能
u/SnooStrawberries827 · Reddit
my team had 47 open PRs and nobody was reviewing them, so I gamified it our team hit 47 open PRs at one point last month and nobody was reviewing them. tried slack reminders, deadlines, rotating reviewers, none of it really stuck. might be related to the fact that everyone's hyped about how fast AI can write code now, copilot cranking out entire features in hours, but none of that matters if the PR just sits there for a week. feels like writing code stopped being the bottleneck a while back

用 Etch 追踪、回放和验证 AI 代理的决策。
u/Funky_Chicken_22 · Reddit
OSS to SaaS positioning problem: when the user persona and the buyer persona are completely disjoint Founder here. Sharing a positioning problem I think a lot of OSS-to-SaaS founders hit and don't talk about publicly. Context: I have been running an OSS project (world-model-mcp) with ~2,500 monthly PyPI installs. Two weeks ago I opened up the hosted companion, Etch, at etch.systems. Launched publicly on Product Hunt at 12:00 PDT yesterday. The positioning problem: OSS user persona: in

将自然语言描述转换为生产就绪的后端API和服务
u/yousefemz · Reddit
18 months ago we weren't sure it was possible. Today we launched it. We kept asking ourselves one question for a year and a half: can an AI actually design a scalable backend from a description of how it should behave, not demo-ware, something that holds up in production? We didn't know. Some weeks it felt like the answer was no, or that we'd end up with code that looks right and falls apart the second real traffic hits it. We just launched it. You describe how your backend should behave,