The Triforce of AI Infrastructure: Why Storage, Orchestration, and Retrieval Must Be One System

Building multimodal AI applications involves integrating storage, orchestration, and retrieval capabilities, which are traditionally managed by separate systems like object stores, DAG runners, and vector databases, leading to a fragmented infrastructure. The text argues for the unification of these capabilities into a single system, termed the "Triforce," which would streamline operations by allowing data, processes, and results to be managed cohesively. This unification addresses key issues such as synchronization, incrementality, lineage, and experimentation, all of which are challenging under a disjointed system architecture. The proposed solution, exemplified by Pixeltable, integrates native multimodal data types, automated orchestration through computed columns, and built-in embedding indexes, facilitating efficient and seamless AI development. Such a system enables atomic operations, incremental recomputation, and automatic lineage tracking, thus simplifying experimentation and enhancing operational efficiency in AI applications.

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