AI's Halftime: From Model-centric to Application-centric

This article outlines two phases of AI development. The first phase focused on developing better training methods and models, achieving remarkable feats like AlphaGo defeating Go world champions. The second phase shifts focus from solving problems to defining problems, prioritizing evaluation over training. The author argues that current AI models are capable of solving various tasks, but their real-world utility needs improvement. Future AI research should concentrate on real-world applications, developing evaluation methods and models that better meet real-world needs, thus driving AI to truly benefit humanity.