问HN：机器人工程师们，搭建GPU仿真基础设施有多困难？
我正在探索一种服务，当你推送代码时，它会在云GPU上自动运行机器人物理仿真，类似于Vercel的持续集成/持续部署，但针对Isaac Sim、Gazebo或MuJoCo。GPU在推送时启动，无头运行，将指标发布到托管的结果仪表板，然后关闭。
对于那些已经解决了GPU基础设施问题的人：如果你今天必须从头开始，面对新的工作、新的团队和新的项目，你会对未来感到畏惧吗？还是这只是一次性的小麻烦，你已经忘记了？
我真心想了解这是否足够痛苦，以至于值得花钱去避免，还是只是几周的烦恼，之后就没事了。
（我有一个着陆页，但还没有产品，发布这个是为了验证想法，在构建之前！）
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I'm exploring a service that auto-runs robot physics simulations on cloud GPUs when you push code, think Vercel CI/CD but for Isaac Sim, Gazebo, or MuJoCo. GPU spins up on push, runs headlessly, posts metrics to a hosted results dashboard, tears down.
For those of you who've already solved the GPU infra problem: if you had to start over from scratch today with a new job, new team, new project, would you dread what lies ahead? Or was it a one-time annoyance you've forgotten about?<p>Genuinely trying to understand if this is painful enough to pay to avoid or just annoying for a few weeks and then fine.<p>(I have a landing page but no product yet, posting to validate before building!)