Exploring the Opportunities and Challenges of Developing Large AI Models and their Commercialization

Abstract

This article explores the evolution and impact of large models in artificial intelligence (AI), with a focus on their role in advancing fields like natural language processing and image recognition. It categorizes this evolution into three stages: deep learning revival, big data and distributed computing, and self-supervised learning. The capabilities of large-scale models, especially in generating AI content, are discussed, along with the role of small models in personalized enterprise requirements and resource-limited environments. Discusses the development of large AI models and the opportunities they bring, as well as the importance of considering user needs when transitioning from a model to a product. The commercialization of AI products is also explored, with attention paid to the details of this process. The future of AI is predicted to be a dynamic balance between large and small models, depending on task requirements and resource limitations. The article concludes with a discussion on the commercialization of AI products, emphasizing the importance of data, algorithms, user-centric design, and viable business models.