Large AI Models and Their Applications: Classification, Limitations, and
Potential Solutions
- Jing Bi,
- Ziqi Wang,
- Haitao Yuan,
- Xiankun Shi,
- Ziyue Wang,
- Jia Zhang,
- Mengchu Zhou,
- Rajkumar Buyya
Haitao Yuan
Beihang University
Corresponding Author:yuan@buaa.edu.cn
Author ProfileZiyue Wang
Beijing Information Science and Technology University
Author ProfileAbstract
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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.16 Aug 2024Submitted to Software: Practice and Experience 19 Aug 2024Submission Checks Completed
19 Aug 2024Assigned to Editor
19 Aug 2024Review(s) Completed, Editorial Evaluation Pending
02 Sep 2024Reviewer(s) Assigned
30 Oct 2024Editorial Decision: Revise Major