Дослідження підходів до створення AI-орієнтованих систем генерації текстового контенту

Abstract

The article examines methods for developing AI-oriented text generation systems. The evolution of text generation approaches is considered, ranging from statistical models to modern transformer-based architectures. The key principles of training large language models are analyzed, including pretraining, fine-tuning, and reinforcement learning with human feedback. The main advantages, limitations, and application areas of these systems are identified.