Smart Content Ingestion for Generative AI Workloads
The evolution of machine learning has progressively changed where intelligence resides in an AI system. In conventional machine learning the task, data representation, labels and model architecture were tightly coupled, so data preparation was narrow, schema-bound and visible. Generative AI decouples the model from any single task: one foundation model serves open-ended downstream tasks, and the generality gained on the model side is matched by heterogeneity on the data side, because enterprise knowledge is authored in the formats people use (PDF, presentations, spreadsheets, scanned documents, forms, tables, diagrams and mixed-layout files) that carry textual, visual, geometric and struc...
| Authors | Abbas Raza Ali, Muhammad Ajmal Siddiqui, Moona Zahid |
|---|---|
| Primary category | cs.AI |
| Published | 5 October 2026 |
| Last updated at source | 5 October 2026 |
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