Towards Building Specialized Generalist AI with System 1 and System 2
  Fusion
Authors: name: Kaiyan Zhang, name: Biqing Qi, name: Bowen Zhou

In this perspective paper, we introduce the concept of Specialized Generalist
Artificial Intelligence (SGAI or simply SGI) as a crucial milestone toward
Artificial General Intelligence (AGI). Compared to directly scaling general
abilities, SGI is defined as AI that specializes in at least one task,
surpassing human experts, while also retaining general abilities. This fusion
path enables SGI to rapidly achieve high-value areas. We categorize SGI into
three stages based on the level of mastery over professional skills and
generality performance. Additionally, we discuss the necessity of SGI in
addressing issues associated with large language models, such as their
insufficient generality, specialized capabilities, uncertainty in innovation,
and practical applications. Furthermore, we propose a conceptual framework for
developing SGI that integrates the strengths of Systems 1 and 2 cognitive
processing. This framework comprises three layers and four key components,
which focus on enhancing individual abilities and facilitating collaborative
evolution. We conclude by summarizing the potential challenges and suggesting
future directions. We hope that the proposed SGI will provide insights into
further research and applications towards achieving AGI.