Operations | Monitoring | ITSM | DevOps | Cloud

What is physical AI? Physical AI embeds machine learning directly into hardware, enabling algorithms to interact, move, and perform autonomous tasks in the physical world. Traditionally, robots relied on precise, hardcoded coordinates; if an object shifted by a single millimeter, the entire system failed. Today, robotics is moving past rigid automation toward truly adaptive architecture. Neural networks help machines process raw sensor data in real time. Consequently, machines can dynamically reason through the unpredictable physical world.

If your incident response still depends on engineers stitching alerts together… You don’t have observability. You just have dashboards. Correlation has to be automatic, contextual, and system-aware, or it becomes expensive noise.

Reach any destination on a global network in about 60 seconds. Here’s what we actually do, explained by our SA Chris off the rip.

AI is changing software development fast. But what does that actually mean for platform engineering teams? In this conversation, Civo's John Dietz and M R Rishi dig into what they're seeing on the ground, the 10x effect of AI on app count, what it means for platform team workloads, the debugging skills that are quietly being lost, and whether Kubernetes itself might eventually become just another abstraction.