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Serverless GPU Platform for AI Inference | Runpod
Runpod是无服务器GPU推理平台，冷启动低于200ms，按秒计费。
@svpino · X
You can check out Runpod here: Thanks to the Runpod team for partnering with me on this post.
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Runpod是无服务器GPU推理平台，冷启动低于200ms，按秒计费。
@svpino · X
You can check out Runpod here: Thanks to the Runpod team for partnering with me on this post.
Real Android device hardware database — sensors, SoC, GPU, memory, display, and fingerprints from thousands of real devices.
@DevCheckAI · X
Building DevCheck AI — spot fake/refurbished Android phones & sketchy IPs & hardware self-test. 80,000+ real device specs at 📲
NEURL-OS is a free 2-minute weekly calibration that transforms your weekly habits into a predictive model of your performance.
@NEURL_OS · X
Hey we’ve built NEURL-OS, a tool that turns daily habits into data and a weekly capacity score. For founders juggling constant decisions, it helps reveal what’s fueling your focus and output—and what’s quietly draining it. Try it free:
在浏览器中从文本或图像生成4K视频,无需GPU。
Wan3Pro — AI 在线视频生成工具
提交网站获得每日速度排名和性能监控。
@thefastestweb · X
daily speed monitoring for indie sites. Submit your URL, get ranked on a public leaderboard, and know the moment your performance drops.
The fastest infra for AI agents. Deploy browsers, sandboxes, and execution environments to automate at scale.
@getsolari · X
the worlds fastest agent infra
Your OpenAI client, a different base URL, a much smaller invoice. Frontier open-source models on a decentralized GPU network.
@runnoclip · X
AI inference service that cuts your token bills by 50-90%
在浏览器中将文字和图片转换成 HD AI 视频，无需安装。
seedance 2.0 mini — 浏览器直出 AI 视频，文字/图片/音频多模态输入，30 秒内生成 HD 短片，无需安装
NodeESP是ESP32的可视化编程工具，通过节点拖拽创建GPIO逻辑和MQTT工作流。
@NodeESP · X
- Project for sale
用 GPT Image 2 为营销和社交媒体生成编辑 AI 图像。
Gptimage2 — AI 图片生成工具
在分布式WebGPU网络上运行AI工作负载
u/Spiritual-Can7428 · Reddit
Testing WebGPU for distributed AI compute in the browser — feedback wanted Demo: https://www.projectmosaic.in/ Hey everyone ,been working on a project called Project Mosaic, testing how far browser-based compute (via WebGPU) can go for distributed AI workloads across regular consumer devices, instead of needing dedicated GPU clusters. Current setup: Runs compute pipelines directly in the browser using WebGPU Uses quantization and sharding to keep per-device memory usage low (aroun