AI framework cuts computing use by two-thirds while more than tripling success in virtual tasks

A research team led by professor Minhae Kwon of the School of Electronic and Electrical Engineering has developed two core next-generation artificial intelligence (AI) technologies that enable AI systems to handle complex, long-horizon tasks more effectively while reducing computational costs and improving safety. The findings address key challenges that have hindered the commercialization of costly AI assistant services as well as the deployment of AI in safety-critical areas such as robotics and autonomous driving. The findings are published on the arXiv preprint server.

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