WebAssembly 3.0 and the Infrastructure We Actually Need
Dev.to AI
•
Machine Learning
AI Hardware
"We've finished the model. when do we get to the value?" Here's what I'm watching happen in real time: DevOps teams are spending annually on cloud egress fees just to move ML models between environments, and flow data to centralized hosting. Platform engineers are debugging why a 1.1GB model requires a 7GB container. SREs are explaining why edge inference needs a 30-second cold start. Everyone knows something's wrong. But we keep reaching for the same solution: bigger containers, faster networks, centralized infrastructure. WebAssembly 3.0, released last week, MAY have another way.