Enhancing Computational Processing Performance for Generative AI Large Models with Autonomous Decision-Making in Metaverse Applications
We explore how to enhance the computational processing performance for generative AI large models with autonomous decision-making in metaverse applications. We first introduce the relationship between AI large models and the Metaverse. We elaborate on the application scenarios of generative AI large models in Metaverse, including real-time weather simulation, embodied intelligence of agents, dynamic environment interaction, and user emotion recognition. We then propose the method of Multi-Dimensional Optimization Generation Framework (MDOGF) to improve computational processing performance. The experiment results show great improvement in computational processing performance.
Authors
- Li Li (ORCID: https://orcid.org/0000-0001-8485-2216)
- Hong Liu (ORCID: https://orcid.org/0000-0003-3389-2765)
- Jiarong Liu (ORCID: https://orcid.org/0000-0002-4603-4340)
- Min Sun (ORCID: https://orcid.org/0009-0007-2145-1715)
- Pengyong Ding
Institutions
- China Mobile (China) (CN)
Publication Details
- Published
- 2024-08-12
- DOI
- https://doi.org/10.1109/metacom62920.2024.00048
- Primary Topic
- Scientific Computing and Data Management
- Type
- article
- Field-Weighted Citation Impact
- 0.00