AI engineering vs traditional software engineering: what changes in architecture?
The question is about AI Engineering .
In AI engineering, architectures shift from deterministic business logic and static flows to flexible, data-driven components powered by training data and models. Systems need to support data pipelines, large-model storage, frequent retraining, uncertainty control, and tighter hardware integration for ML tasks - unlike classic rule-based systems in traditional software engineering.
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