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.

გაიხსენეთ ველური ყვავილების მინდორი, რომელიც თვალის გაწვდამდე ვრცელდება, სადაც უზარმაზარი ბზების გუნდი აქტიურად ბზარებს. ისინი დაფრინავენ, აგროვებენ მტვერს თითოეული ყვავილიდან და გარდაქმნიან მას უკიდურესად კომპლექსურ თაფლში. ეს თაფლი არის ენა. და ეს ბზები არიან LLMs (დიდი ენობრივი მოდელები), ის უზარმაზარი ენობრივი მოდელები, რომლებიც tirelessly მუშაობენ, რათა გარდაქმნონ უზარმაზარი რაოდენობის ტექსტური მონაცემები რაღაც სტრუქტურირებულ, თანმიმდევრულ და ზოგჯერ ძალიან შემოქმედებით რამეში.

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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