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What is Scaling ML Infrastructure

Beginner

Answer

Scaling ML infrastructure means expanding the computing resources and systems needed to train and serve AI models as usage or data volume grows.
Real-world example A growing app scales its ML infrastructure by moving from a single server to a distributed cloud setup to handle millions of daily predictions.

Common follow-ups: What is AI Model Deployment & MLOps, How is Scaling ML Infrastructure evaluated in practice, What tools are commonly used for Scaling ML Infrastructure

AI Model Deployment & MLOps topics: Introduction to MLOps Model Versioning CI/CD for Machine Learning
All 7 Scaling ML Infrastructure questions