Definition
The computational layer in RAG pipelines and AI Agents responsible for converting unstructured human language into high-dimensional vector representations for retrieval and translating model outputs back into coherent text. It involves balancing the architectural trade-off between semantic precision (using computationally expensive transformer-based models) and operational speed (using lightweight tokenizers and encoders).
Distinguish from general linguistics; in AI, it refers specifically to the transformation of text into machine-interpretable numerical tensors.
"A Universal Translator that turns messy, handwritten scribbles into precise GPS coordinates on a 3D semantic map."
- Vector Embeddings(Component)
- Tokenization(Prerequisite)
- Named Entity Recognition (NER)(Component)
- LLM(Core Engine)
Conceptual Overview
The computational layer in RAG pipelines and AI Agents responsible for converting unstructured human language into high-dimensional vector representations for retrieval and translating model outputs back into coherent text. It involves balancing the architectural trade-off between semantic precision (using computationally expensive transformer-based models) and operational speed (using lightweight tokenizers and encoders).
Disambiguation
Distinguish from general linguistics; in AI, it refers specifically to the transformation of text into machine-interpretable numerical tensors.
Visual Analog
A Universal Translator that turns messy, handwritten scribbles into precise GPS coordinates on a 3D semantic map.