What is Large Language Model (LLM)?

Large Language Model (LLM) is a class of artificial intelligence models built on large-scale neural networks, trained on extensive text corpora to understand and generate natural language. Architecturally, LLMs are primarily based on transformer architectures and use self-attention mechanisms to model dependencies between tokens in a sequence. Training of such models includes self-supervised pretraining followed by fine-tuning for specific tasks, enabling the model’s behavior to be adapted to instructions and applied scenarios.

In practical applications, LLMs are used for text generation, conversational systems, document analysis, code automation, and the development of intelligent assistants. Model integration involves the use of APIs, retrieval-augmented generation (RAG) approaches, agent-based architectures, and response quality control mechanisms. Operation of LLMs in production environments requires significant computational resources, inference optimization, control of hallucinations, and continuous monitoring of model behavior over time.