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What is Scaling ML Infrastructure

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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