| Editorial |
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| Special issue on artificial intelligence 2.0 |
| Yun-he Pan |
| Zhejiang University, Hangzhou 310027, China; Chinese Academy of Engineering, 100088, China |
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Abstract With the ever-growing popularization of the Internet, universal existence of sensors, emergence of big data, development of e-commerce, rise of the information community, and interconnection and fusion of data and knowledge in human society, physical space, and cyberspace, the information en-vironment surrounding artificial intelligence (AI) development has changed profoundly, leading to a new evolutionary stage: AI 2.0. The emergence of new technologies also promotes AI to a new stage (Pan, 2016). The next-generation AI, namely AI 2.0, is a more explainable, robust, open, and general AI with the following attractive merits: It effectively inte-grates data-driven machine learning approaches (bottom-up) with knowledge-guided methods (top-down). In addition, it can employ data with different modalities (e.g., visual, auditory, and natural language processing) to perform cross-media learning and inference. Furthermore, there will be a step from the pursuit of an intelligent machine to the hybrid-augmented intelligence (i.e., high-level man-machine collaboration and fusion). AI 2.0 will also promote crowd-based intelligence and autonomous-intelligent systems. In the next decades, AI2.0 will probably achieve remarkable progress in aforementioned trends, and therefore significantly change our cities, products, services, economics, environments, even how we advance our society. This special issue aims at reporting recent re-thinking of AI 2.0 from aforementioned aspects as well as practical methodologies, efficient implemen-tations, and applications of AI 2.0.
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Published: 20 January 2017
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