LLM (Large Language Model)

A large language model (LLM) is a highly advanced artificial intelligence trained to understand and generate natural language. LLMs are based on deep neural networks, specifically transformers, and are capable of analyzing, completing, and generating context-dependent text.

These models are trained on massive amounts of data to recognize patterns in language and provide coherent answers to complex questions. Well-known examples include GPT (Generative Pre-trained Transformer) by OpenAI, Claude by Anthropic, or Gemini by Google DeepMind. They are used for a variety of applications, including chatbots, translations, content creation, code generation, and semantic search.

An example of using an LLM is an automated customer service system, where the model understands customer inquiries in natural language and provides appropriate responses. Similarly, businesses use LLMs for content creation in marketing, generating blog articles, social media posts, or email campaigns.

A major advantage of LLMs is their ability to produce human-like language and adapt to different contexts. Through fine-tuning, they can be optimized for specific industries or business requirements. However, they require enormous computing power and, in some cases, can generate misinformation ("hallucinations"), which is why careful control of the generated content remains important.

LLMs are a central component of modern AI applications and are continuously evolving. Through advancements in model architecture, efficiency, and scaling, they are increasingly integrated into businesses, research, and everyday applications, revolutionizing the way humans communicate with machines.