This study is led by Dr. Ran He (Institute of Automation, Chinese Academy of Sciences). His research team has conducted a comprehensive review of the development of Generative Artificial Intelligence (Generative AI) over the past half-century. Their work systematically traces the evolution of Generative AI, identifying key milestones such as the rise of deep learning, transformer architectures, and foundation models. To provide a structured understanding, they organized the development of Generative AI into four distinct stages:
They also compiled a representative timeline illustrating the development trajectory of Generative AI methods and applications (see the below figure titled 'Evolution of Design Principles in Generative AI'). Their work delves into representative approaches, evaluates the strengths and limitations of different generative technologies, and highlights successful applications in various fields. Additionally, they identify open challenges in the field, emphasizing that issues such as safety concerns and breakthroughs in theoretical paradigms urgently require further attention and development.
See the article:
Generative Artificial Intelligence: A Historical Perspective
https://doi.org/10.1093/nsr/nwaf050
National Science Review