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Establishing a Common Lexicon for AI Systems As engineers, when we embark on integrating AI capabilities into our existing systems, a shared understanding of the underlying terminology and architectural components is paramount. It’s not just about training a model; it's about seamlessly weaving that intelligence into a larger application fabric. Without a clear foundation, discussions around deployment, performance, and maintenance can quickly become muddled. Let’s lay down some essential concepts. The AI Model Lifecycle: From Data to Prediction At the heart of AI integration is the Model itself – the trained artifact, typically a serialized file (e.g., a .pkl for...