on july 13, china ai development report 2018 press conference and symposium took place in the main building reception hall of tsinghua university. zhou yu, dean of office of scientific r&d at tsinghua university, delivered a welcome speech. li guojie, former director of the institute of computing technology chinese academy of sciences and honorary chairman of the china computer federation, zhang jingan, former member of cpc leading group of the ministry of science and technology of china and director of china science and technology of administrative reform, made invitational report. xue lan, dean of tsinghua university school of public policy and management and director of china institute for science and technology policy at tsinghua university, introduced the contents of the report in detail.
zhou yu said in his speech that tsinghua university is speeding up the pace of building the “double-first class” initiative, interdisciplinary research has become a common consensus among the entire university and promoted the development of new interdisciplinary research institutions. he wished the china ai development report 2018 press conference and symposium a great success, and sincerely appreciated the care, support, and help from all the honorable guests.
in the following keynote speech session, li guojie and zhang jingan each made invitational reports on “how to speed up the indigenous innovation of ai and make ai become the new driving force for development” and “ the development of artificial intelligence from a global perspective”.
xue lan said when introducing the china ai development report 2018, that the perspective of the report not only was based on the current situation, but also look forward to the future; the report is a systematic analysis of ai development in china that includes comparison with world-wide data; the report use first-hand data with high reliability. xue lan presented the basic picture of ai development in china, including scientific and technological output, intellectual investment, total amount of literature, amount of highly-cited literature, number of patents, total amount of ai intellectual investment, industrial development, application prospects and other aspects.