  Due to the increased number of parameters and data in the pre-trained model
exceeding a certain level, a foundation model (e.g., a large language model)
can significantly improve downstream task performance and emerge with some
novel special abilities (e.g., deep learning, complex reasoning, and human
alignment) that were not present before. Foundation models are a form of
generative artificial intelligence (GenAI), and Model-as-a-Service (MaaS) has
emerged as a groundbreaking paradigm that revolutionizes the deployment and
utilization of GenAI models. MaaS represents a paradigm shift in how we use AI
technologies and provides a scalable and accessible solution for developers and
users to leverage pre-trained AI models without the need for extensive
infrastructure or expertise in model training. In this paper, the introduction
aims to provide a comprehensive overview of MaaS, its significance, and its
implications for various industries. We provide a brief review of the
development history of "X-as-a-Service" based on cloud computing and present
the key technologies involved in MaaS. The development of GenAI models will
become more democratized and flourish. We also review recent application
studies of MaaS. Finally, we highlight several challenges and future issues in
this promising area. MaaS is a new deployment and service paradigm for
different AI-based models. We hope this review will inspire future research in
the field of MaaS.
