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.

Iedomājieties savvaļas ziedu lauku, kas stiepjas tik tālu, cik acs redz, kur pārmērīgs bites pūlis rosīgi buzzing apkārt. Tie plivinās, vāca ziedputekšņus no katra zieda un pārvērš to neticami sarežģītā medū. Tas medus ir valoda. Un šīs bites ir LLM (Lieli Valodas Modeļi), tie milzīgie valodas modeļi, kas nepagurstoši strādā, lai pārvērstu milzīgas teksta datu apjomas kaut kas strukturētā, koherētā un dažreiz pat ļoti radošā.

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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