Summary

Intelligent applications represent a new paradigm in software development, combining AI with traditional application components to deliver highly personalized, context-aware experiences. This chapter details the core components of intelligent applications, highlighting the pivotal role of LLMs as reasoning engines. LLMs serve as versatile computational tools capable of performing diverse tasks, including chat, summarization, and classification, due to their general-purpose design.

Complementing these reasoning engines are embedding models and vector databases, which function as the semantic memory of intelligent applications. These components enable the reasoning engine to retrieve pertinent context and information as needed. Additionally, the hosting of AI models demands dedicated infrastructure, as their unique hardware requirements differ significantly from traditional software needs. Using building blocks such as LLMs, embedding models, vector databases, and model hosting...