Summary of Kunpeng: An Embodied Large Model For Intelligent Maritime, by Naiyao Wang et al.
KUNPENG: An Embodied Large Model for Intelligent Maritime
by Naiyao Wang, Tongbang Jiang, Ye Wang, Shaoyang Qiu, Bo Zhang, Xinqiang Xie, Munan Li, Chunliu Wang, Yiyang Wang, Hongxiang Ren, Ruili Wang, Hongjun Shan, Hongbo Liu
First submitted to arxiv on: 12 Jul 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: None
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper proposes a novel artificial intelligence model called KUNPENG that integrates advanced AI technology with data analysis methods for intelligent maritime applications. Specifically, it addresses the challenges of real-time decision-making in complex and dynamic maritime environments by developing an embodied large model that perceives multi-source heterogeneous data to make autonomous decisions. The model consists of six systems that enable intelligent vessels to perform navigation behaviors under safety and emergency guarantees while continuously optimizing power. In comprehensive evaluations, KUNPENG demonstrates excellent performance for various maritime tasks. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary In this paper, researchers create a new AI system called KUNPENG to help make smarter decisions in the ocean. The system uses lots of different data sources to understand how things work together in the marine environment and make good choices. This helps ships navigate safely and efficiently, which is important for using ocean resources well and keeping transportation networks smart. |
