
Demo | 1771 Technologies
试试这个高性能的 React 数据网格组件,已针对企业使用优化。
@leethatengineer · X
Building LyteNyte Grid
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试试这个高性能的 React 数据网格组件,已针对企业使用优化。
@leethatengineer · X
Building LyteNyte Grid

计算LLM微调和推理所需的GPU显存。
@FaiqAdzlan · X
Built a GPU VRAM calculator to try out Claude Code (#cursorfanboy). I wanted it as granular as possible so I based it off of LLMem) which really just covers fine-tuning tbh. Please tear it to shreds: GitHub:

用于集中管理和调度多个数字显示屏内容的云平台。
@xenovimapp · X
Introducing XENOVIM A cloud-based Digital Signage Platform built for modern businesses. ✔ Centralized Screen Management ✔ Offline Playback ✔ Content Scheduling ✔ Multi-Device Control Smart Displays. Centralized Control. Built to Connect. 🌐


用多个模型实时审计AI回应以判断其可靠性。
u/inc_23 · Reddit
Hey, I created a tool that catches when your LLM is confidently wrong, in production, in real time — looking for beta testers. Your bot sounds sure of itself even when it's wrong, and you usually only find out when a customer complains. Auscope audits every LLM response in the background: 3 models from 3 different providers independently check it, a 4th "chairman" model resolves disagreements, and you get one verdict — verified, uncertain, or unreliable. Runs async, doesn't slow your respon

LangevinAI 上传总账文件自动生成损益表和AI差异分析。
@VictorVDPN · X

@konig0000 My whole architecture is vibe coded. https://t.co/t2PKhujHIT
@HathornWarren52 · X
My whole architecture is vibe coded.

Identifica gli scostamenti tra la capacity dichiarata e le ore effettivamente tracciate su Azure DevOps, così puoi verificarli con la persona giusta.
@PieroDeTomi · X
Building SprintGauge, a tool for connecting to Azure DevOps and be able to view and analyze useful metrics useful for PMs, Scrum Masters, Team Leaders and even developers.

AI成本、硬件、自动化和网站规划的浏览器本地计算器和工具。
@Erko95261453 · X

为现代团队自动化负载测试,无需复杂设置或手动脚本编写。
@GorodkovVi85373 · X
- load testing made easy even without enginnering team. Faster, cheaper, distributional


Standara 为安保公司调度技术员并管理客户的现场服务平台。
@StandaraAI · X