While artificial intelligence (AI) technology, boosted by big data, has been applied to a variety of industries, experts noted that the "bonus" effect brought by big data is declining and simple breakthroughs in AI cannot support the further development of the industry.
The warning was given at the 667th session of the Xiangshan Science Conferences (XSSC), which was held from Nov 22 to 23 in Beijing.
"There is a huge gap between the real complexity of data and the simple assumptions of algorithms, which makes classical intelligent algorithms act poorly in many complex tasks," said Mei Hong, an academician of the Chinese Academy of Sciences.
Mei noted that big data is the material basis for the current success of AI, yet the great majority of AI algorithms don't give full consideration to the complexity of big data.
Tao Jianhua, a researcher from the Automation Research Institute of the Chinese Academy of Sciences, stated that the reasoning mode of human-computer integration can effectively make up for the weaknesses of AI in automatic data reasoning.
Liu Tieyan, assistant managing director of Microsoft Research Asia (MSRA), said that the characteristics of big data are becoming more and more complex, which requires that the new intelligence algorithms to deal with problems according to the characteristics of data to bolster the value of AI.