游戏娱乐1 month ago
Football AI Predictions, 2026 World Cup Picks & Match Analysis
获取AI足球预测与多联赛比赛分析。
footballaipredictionking · Product Hunt
Football AI Prediction King Free AI football predictions and match analysis
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获取AI足球预测与多联赛比赛分析。
footballaipredictionking · Product Hunt
Football AI Prediction King Free AI football predictions and match analysis
查看英雄联盟、CS2和Dota2职业比赛的AI胜率预测与赔率。
ducntq · Product Hunt
zest.win AI-powered & ML-backed predictions for eSports Dota2/CS2/LOL
从单一简报为多个平台生成社交媒体帖子、视觉素材和视频
@Meet_Archy_AI · X
Craft social media campaigns in minutes - from one brief to multi-network campaign in minutes
创建或加入足球预测联赛，预测英超、西甲、欧冠和2027女足世界杯比赛。
@henrikcamber · X
Check out what I just built with Lovable!
查看World Cup 2026实时最佳阵容、分析和比赛预测。
@WorldCup_XI · X
And the twist: it's my first ever 'vibe-coded' project — built solo with AI, shipped live through the whole tournament. £0 marketing → 7,000 visitors from 100 countries. The single biggest day? The final itself. ⚽
查看2026世界杯和顶级足球联赛的AI预测、实时比分和赔率。
@kmlyyll · X
now speaks #MCP. Ask any AI agent about World Cup 2026 fixtures, team stats, or match predictions: Live data, not scraped guesses. Also shipped: Link headers, an #API catalog, #WebMCP, and a #Claude Code plugin. Made in Cambridge with a lot of love and passion.😍
记录团队运营事件，查询共享历史记录。
markogg · HN
Trailogs – A team's operational history you can ask questions about
Open AI-agent market forecasts, recently settled outcomes, and a sample-qualified public leaderboard from Headline Arena.
@Kopei_Nan · X
追踪100+来源的AI和LLM新闻和模型发布。
jonam21 · HN
KBlip – turns AI/LLM news across 100 sources into daily digest threads
FeedLog是开源AI反馈工具，免费收集和管理用户需求。
@kngkng182542 · X
If you're paying for Canny, give FeedLog a look. Same workflow for collecting feedback and managing feature requests, but free during launch.
查看和对比主流AI模型的公众意见和基准评分。
u/TasteMysterious5285 · Reddit
I built AI Census, a live field bulletin for how people are actually talking about AI models I’ve been building AI Census, a public “field bulletin” for how people are talking about current AI models. I kept running into the same problem: benchmark tables tell me how a model performs on a test, but not whether people are actually finding it useful, frustrating, reliable, etc. So I built a rolling view from public technical conversations across Reddit, Hacker News, Bluesky, GitHub, and Huggi
Wetter 支持本地计算和自定义聚合模式的天气预报和可视化应用。
__mp · HN
I built my own weather prediction / visualization app: https://wx.rsp.li (on-device temperature lapsing, on device interpolation modes, user-selectable aggregations, etc…). One of these days I should do a writeup. I also asked Claude to build a photo gallery for me https://places.pascalspoerri.ch (HDR, map support, similar images)