报告题目：Build AI systems that can learn not only from data but also from knowledge
构建不但能从数据并且也能从知识中学习的人工智能系统
报告人：宫雷光
报告时间：2018-05-09 10:00

报告地点：bat365中文官方网站207
报告人简介：
从事计算机科学技术研究及高等教育工作40余年。曾先后任吉林大学计算机科学系助教、讲师；美国Rutgers大学计算机科学系博士研究生、助理研究员、博士后研究员和助理教授；美国朗讯公司贝尔（Bell）实验室资深研究员，美国IBM-Watson研究中心资深研究员，吉林大学客座教授、兼职教授、博士导师，烟台威兹曼智能信 息技术有限公司首席顾问。
主要研究领域:
知识表达及系统、语义建模、模式识别及图像分析、数据分析、智 能物联网和医学信息学及应用。
报告摘要：
For the last seven or eight years, Big data and AI are two hottest areas of research
and business development. With the availability of massive diversified data and high performance computers, the main school of AI researchers are mostly focusing on deep learning that learn, from data, classifiers and predictors for various speech recognition and computer vision applications. Interestingly enough, an area, once for many years, at the center of AI research known as knowledge representation and knowledge systems has been taking a back seat, though some serious efforts in the field have just begun to make significant impact during the last few years. In this presentation, I will talk about knowledge, data and their interplay, followed by a discussion of some recent research efforts in developing AI knowledge systems that can also learn from knowledge.

信息管理与电子商务研究所