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.

¿Qué es un LLM (modelo de lenguaje grande)?

Imagina un campo de flores silvestres que se extiende hasta donde alcanza la vista, donde un enjambre de abejas de gran tamaño zumban ocupadamente. Revolotean, recolectan polen de cada flor y lo convierten en miel increíblemente compleja. Esa miel es lenguaje. Y estas abejas son los LLMs (Large Language Models), esos gigantescos modelos de lenguaje que trabajan incansablemente para transformar vastas cantidades de datos textuales en algo estructurado, coherente y a veces incluso altamente creativo.

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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