Why does a GenAI stack need synthetic data as its own layer?
Real-world training data is often scarce, imbalanced, or restricted by privacy requirements for the exact scenarios a model needs to handle well — rare edge cases, sensitive categories, underrepresented classes. Synthetic data tools generate artificial examples that fill those gaps, letting teams augment training data for scenarios where collecting enough real examples isn't feasible or isn't allowed.
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The Generative AI Tech Stack, Layer by LayerFrom GPU infrastructure to model safety, a working map of the nine layers that turn a foundation model into a shippable GenAI product.
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