Qualitative Data Analysis in the Age of Artificial General Intelligence

Abstract

Artificial General Intelligence (AGI) is a rapidly developing field in the domain of artificial intelligence. AGI systems aim to replicate human-like intelligence and adaptability by possessing the capacity to perform a variety of intellectual tasks that are commonly associated with human beings. As opposed to narrow or weak AI systems, which are designed to perform specific tasks or solve particular problems, AGI seeks to generate machines that can reason, learn, and solve problems with the same level of competence and flexibility as humans. The multimodal nature of data makes it possible to obtain high-quality solutions to problems of analyzing corrupted or visually attacked images, provided that additional, nonvisual information is available. Additionally, the trend in artificial intelligence towards models with billions of parameters is due to the growth of data modality, leading to significantly higher complexity of models. The paper discusses the field of Artificial General Intelligence (AGI) and its potential to replicate human-like intelligence and adaptability. AGI systems aim to perform a variety of intellectual tasks that are commonly associated with human beings. Overall, the paper provides insights into the current state and future prospects of AGI research, highlighting both the potential and challenges of this rapidly developing field.