yewnork

After watching the Moltbot (formerly Clawd Bot, now OpenClaw) craze unfold this week, we built a template for running it in the cloud.

The Mac Mini approach works but has clear issues: - Hardware cost - Always-on power consumption - Exposed credentials (we've seen the Shodan posts) - No sandboxing or isolation - Difficult to scale or replicate

The template provides: - One-click containerized deployment - Persistent storage for agent state - Secure secrets management (keys never in code) - Auto-scale to zero when idle - VNC + web interface access

Template: https://lightning.ai/lightning-ai/environments/openclaw~01hy...

Technical details: Docker-based environment with mounted persistent volumes, environment variable injection for secrets, and standard Lightning Studios networking with configurable egress.

Not trying to compete with local setups, just providing an alternative for those who want isolation and don't want to manage hardware.

Open to feedback on the implementation.

curious the performance / price tradeoffs between deepseek-r1 671b, 70b, 32b

I see this as a win for the AI community. The key for LLMs is to enable people to train collaboratively and innovate more quickly in this space. Are there any examples or demos available that showcase the capabilities of "lit-llama"?