GPT Model

Generative Pre-trained Transformer (GPT) models are large language models designed to generate human-like text, with research focusing on improving their accuracy, mitigating biases, and enhancing their applicability across diverse fields. Current research explores architectural improvements, such as optimizing attention mechanisms and employing sparsity techniques for efficient training, alongside investigations into bias mitigation strategies and the development of specialized GPT models for specific domains (e.g., biomedical text summarization, financial analysis). The impact of GPT models is significant, offering potential for automating tasks, improving accessibility to information, and advancing research in areas like natural language processing and scientific simulation, although concerns regarding bias and privacy remain active research areas.