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
Towards AGI in Computer Vision: Lessons Learned from GPT and Large Language Models
Lingxi Xie, Longhui Wei, Xiaopeng Zhang, Kaifeng Bi, Xiaotao Gu, Jianlong Chang, Qi Tian
Unraveling the ARC Puzzle: Mimicking Human Solutions with Object-Centric Decision Transformer
Jaehyun Park, Jaegyun Im, Sanha Hwang, Mintaek Lim, Sabina Ualibekova, Sejin Kim, Sundong Kim