In this article, we will delve deep into the world of AI agents, exploring their foundations, their architecture, and the various building blocks that compose them. We will also look at how they can be integrated into different fields, the benefits they bring, and why these technologies are attracting growing interest in businesses and among the general public.

Introduction​

In recent years, artificial intelligence (AI) has gained increasing popularity, fueled notably by the democratization of powerful natural language processing (NLP) models and large language models (LLMs). Nowadays, these technologies go beyond mere text generation or auto-completion: they give rise to more complex, more autonomous systems capable of acting and interacting on behalf of the user. These systems—commonly referred to as AI agents—are designed to handle all sorts of tasks, from simply answering frequent questions to managing an entire complex process.

Forestil dig et felt af vilde blomster, der strækker sig så langt øjet kan se, hvor en overdimensioneret sværm af bier travlt summende flyver rundt. De flakser, samler pollen fra hver blomst og forvandler det til utrolig kompleks honning. Den honning er sprog. Og disse bier er LLMs (Large Language Models), de enorme sprogmodeller, der utrætteligt arbejder på at omdanne store mængder tekstdata til noget struktureret, sammenhængende og nogle gange endda meget kreativt.

If language were a symphony, its score would be infinitely complex—sometimes grand, sometimes intimate—driven by the diversity of languages, contexts, and cultural nuances. At the heart of this symphony lies a subtle yet crucial orchestra: NLP (Natural Language Processing), which orchestrates words and meaning in the world of AI.

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