Large AI Models and Their Applications: Classification, Limitations, and Potential Solutions

not-yet-known not-yet-known not-yet-known unknown In recent years, Large Models (LMs) have been rapidly developed, including large language models, visual foundation models, and multimodal LMs. They are updated and iterated at a very fast pace. These LMs can accomplish many tasks, e.g., daily work assistant, intelligent customer service, and intelligent factory scheduling. Their development has contributed to various industries in human society. However, the architectural flaws of LMs lead to several problems, including illusions and difficulty in locating errors, limiting their performance. Solving these problems properly can facilitate their further development. This work first introduces the development of LMs and identifies their current problems, including data and energy consumption, catastrophic forgetting, reasoning ability, and localization fault. Then, potential solutions to these problems are provided. Finally, LMs’ applications in autonomous driving technologies and smart industrial productions are discussed. By embracing the advantages of LMs, many industries are expected to achieve promising prospects in the future.