The article argues for AI Engineering as a distinct discipline, necessitated by the non-deterministic nature of AI models compared to traditional software. It illustrates the complexity and potential failure modes within a typical LLM-based system architecture.
This article emphasizes that audit is a crucial, often overlooked layer in healthcare RAG systems, essential for managing liability where occasional hallucinations are unacceptable. It argues for building audit in from the start, rather than bolting it on later, to ensure enterprise-grade reliability and compliance.
Google recently launched TurboQuant, a novel algorithmic suite and library for applying advanced quantization and compression to large language models (LLMs) and vector search engines. This tool is an indispensable element of RAG systems.
