Artificial General Intelligence
Artificial General Intelligence (AGI) aims to create AI systems possessing human-level cognitive abilities across diverse domains, encompassing reasoning, learning, and problem-solving. Current research heavily focuses on leveraging large language models (LLMs) and their extensions, such as multimodal LLMs and LLM-based agents, to achieve this goal, exploring their capabilities in various tasks and environments, including game playing, scientific discovery, and even autonomous driving. This pursuit holds immense significance, potentially revolutionizing numerous fields through the development of more adaptable and versatile AI systems capable of tackling complex real-world problems. The integration of techniques like mixture of experts and the exploration of "specialized generalist" AI models are also key areas of investigation.
Papers
AGI for Agriculture
Guoyu Lu, Sheng Li, Gengchen Mai, Jin Sun, Dajiang Zhu, Lilong Chai, Haijian Sun, Xianqiao Wang, Haixing Dai, Ninghao Liu, Rui Xu, Daniel Petti, Changying Li, Tianming Liu, Changying Li
SAM Struggles in Concealed Scenes -- Empirical Study on "Segment Anything"
Ge-Peng Ji, Deng-Ping Fan, Peng Xu, Ming-Ming Cheng, Bowen Zhou, Luc Van Gool