开发者工具1 month ago
Codex 额度重置提醒｜别错过 reset credits
自动监控 Codex 额度重置，通过 Telegram 推送及时提醒。
zemul · V2EX
每次 Codex 额度刷新全靠社区消息，反应慢一步直接错过 所以我搭了个自动化服务： - 抓取 OpenAI 员工的公开推文 - 新推文丢给 LLM 做语义判断：是不是在说额度重置 / 限额恢复 - Telegram 推送 地址： https://divin.cc/
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自动监控 Codex 额度重置，通过 Telegram 推送及时提醒。
zemul · V2EX
每次 Codex 额度刷新全靠社区消息，反应慢一步直接错过 所以我搭了个自动化服务： - 抓取 OpenAI 员工的公开推文 - 新推文丢给 LLM 做语义判断：是不是在说额度重置 / 限额恢复 - Telegram 推送 地址： https://divin.cc/
提交 LLM 推理优化内核，在专用硬件上进行基准测试并竞争排名。
carsenk · HN
Frontier.fast – Help push the frontier of LLM speed forward
为任何主题生成动画视觉解释来学习。
u/Top-Relationship8196 · Reddit
AI teacher that explains anything visually. Hi, I built this free tool called bestie. It's basically an AI teacher that explains anythingany topic visually. Instead of watching a 3hr Youtube to learn something specific or struggle through the text Chatgpt gives you, you can use this for free to learn anything fast. you can find it at bestie.chrestic.com you just have to type the topic and your visuals will arrive in less than a minute. Don't forget to try and leave Y
用AI为任何主题生成个性化课程，含互动教学和练习。
@DevSanghav15604 · X
The Duolingo for everything. Type in a prompt and get a full, personalized course built for you.
Axon grades your AI agents’ real conversations with an LLM judge: A–F scorecards, cited evidence, fixes and FinOps.
@tech_maju · X
humm turns what you mumble into a ready-to-send message, runs deep research in any field, and drafts autonomously — voice-first, in 3D.
@Raj_kabadi · X
Check out what I just built with Lovable! @Lovable do u use this , if u like make even use this!!!!!!
Create smart links, QR Codes, Rels Pages, and managed file deliveries, then understand what happens next.
@RelsHQ · X
通过 API 或 URL 替换将 X posts 转换为干净的 Markdown，供 LLMs 和 agents 使用
@larsbuilds · X
观看两个随机LLM在物理竞技场中剑战，盲投谁表现得更聪明。
u/Time-Shelter-35 · Reddit
I built a site where two LLMs sword-fight in real physics and you blind-vote who's smarter Two months ago I thought: what if the AI benchmark was just… watching them fight. So: https://stickblade-arena.vercel.app Two random LLMs get stickman bodies in a pymunk physics arena They each turn output JSON moves (swing, block, dash, shoot bow, throw flail…) Ragdolls, momentum, weapon collisions, the whole bit You watch the replay without knowing which model is which and vote who f
预览内容效果并获得反馈，优化后再发布。
@petropavliuk · X
Hi mate. My projects
