NANJING, China, Sept. 26, 2018 (GLOBE NEWSWIRE) -- Recently, the 15th Pacific Rim International Conference on Artificial Intelligence (PRICAI 2018), co-hosted by Jiangsu Association for Artificial Intelligence and Southeast University, was successfully held in Nanjing. More than 200 well-known university professors, scholars, as well as enterprises and experts in the field of Artificial Intelligence from all over the world discussed deeply and exchanged their opinions on topics related to Artificial Intelligence, Knowledge Discovery in Database, Machine Learning, Natural Language Processing, etc. Dr. Cui Wei, chief scientist with Squirrel AI Learning, was invited to the conference. He delivered a wonderful speech and became the focus among the distinguished guests.
It is known PRICAI is a biennial international conference on Artificial Intelligence in the Asia-Pacific region. The conference contents mainly include Artificial Intelligence theory, technology and applications, covering important sectors such as society and economy in the Pacific Rim countries. It is an international event with far-reaching influence in the field of science & technology in the Asia-Pacific region.
As the chief scientist of Squirrel AI Learning, Dr. Cui Wei delivered a wonderful keynote speech at the meeting. He shared the technical advantages of the Squirrel AI Adaptive Learning System and the achievements in the technology-driven application process. The participants learned about the development and application of Artificial Intelligence in the field of education, which attracted great attention of famous experts and scholars in the international Artificial Intelligence field.
Dr. Cui Wei said that the squirrel AI Adaptive Learning System is a "full-circle" AI education product introduced by Yixue Education with the aim to implement it in the core process of "teaching" and "learning". It applies Intelligent Evaluation Algorithms, Capability Diagnosis and Students’ State Representation Models, as well as recommended algorithms applied in both Learning Path Planning and Learning Content Planning. In addition, Dr. Cui Wei also revealed that the Squirrel AI Learning is now working on the of algorithms such as learning mode selection and early warning/intervention through deep learning.
The key is that by collecting and analyzing learning data, the target-related knowledge points will be identified/mastered in minimum time with the combination of AI and “nano-scale” knowledge maps. We can establish the personalized and dynamic student portrait via continuous measurement of students' knowledge status, understand each student's learning state and problems encountered, so as to design test and learning paths accordingly, adjust teaching activities, and continuously recommend the most appropriate learning materials during the learning process, measure learning effects, as well as foster self-learning and provide feedback to AI predictive ability and effect.
Dr. Cui Wei introduced three modeling elements of Squirrel AI Learning, which are: 1) user portrait of students — the student's preference and interest, learning style, cognitive characteristics, ability level and knowledge status; 2) model the learning content and build “nano-scale” knowledge maps — present different forms of learning resources in the forms of video, text, audio, picture and exercise, and at the same time, establish algorithms to “tag” knowledge points and exercise as well as provide corresponding difficulty coefficients; 3) Personalized matching — match each student with the most suitable learning paths and courses, and recommend personalized learning contents to maximize learning efficiency via the data generated in the previous two steps.
Finally, Dr. Cui Wei mentioned an unprecedented man-machine teaching competition held across the country in 100 cities by Squirrel AI Learning, where the Squirrel AI Adaptive Learning System and experienced public school teachers experienced fair competition. The results showed that the teaching quality and efficiency of Artificial Intelligence Adaptive Learning System was significantly higher than human teachers. In addition, Squirrel AI Learning has successively established a joint laboratory for Artificial Intelligence adaptive learning in cooperation with Stanford Research Institute (SRI). Squirrel AI Learning has also established a parallel AI intelligent adaptation joint laboratory with the Institute of Automation of the Chinese Academy of Sciences. In the future, they will jointly explore the ability of continuous technological innovation in the era of Artificial Intelligence.
A photo accompanying this announcement is available at http://www.globenewswire.com/NewsRoom/AttachmentNg/30884440-cb83-4526-973f-c58039262be5
After the meeting, Dr. Cui Wei communicated and discussed with Yang Qiang (Fig. 1), Dean of the Department of Computer Science and Engineering of Hong Kong University of Science and Technology; Zhou Zhihua (Fig. 2), Dean of the Institute of Artificial Intelligence of Nanjing University, Professor Stephen Muggleton (Fig. 3) of Machine Learning, Department of Computing at Imperial College London as well as other well-known experts and scholars in the fields of Artificial Intelligence and Knowledge Discovery in Database.
As an international expert and leading figure in Artificial Intelligence research, Professor Yang Qiang has played an important role in guiding and promoting the development of Artificial Intelligence (AI) and Knowledge Discovery in Database (KDD) in China. He is the first and the only AAAI Chinese executive member and also the first Chinese scientist serving as chairman of the IJCAI Board of Trustees. Professor Zhou Zhihua, who has worked as AAAI Fellow, IEEE Fellow, IAPR Fellow, ACM Fellow and AAAS Fellow successively, is the first Chinese person who has participated in all the important international association of Artificial Intelligence. AAAI recently announced that Professor Zhou Zhihua would serve as co-chairman of the Program Committee of AAAI 2019 Conference with Professor Pascal Van Hentenryck from the University of Michigan. Professor Stephen Muggleton, graduated from the University of Edinburgh, has served as postdoctoral researcher at Turing Academy at University of Glasgow and EPSRC Senior Research Fellow at Oxford University Computing Laboratory (OUCL).
After understanding the leading algorithms and models of Squirrel AI Learning as well as the practical application of intelligent adaptation technology, they expressed great appreciation to the achievement of Squirrel AI and the endeavors to apply Artificial Intelligence technology in order to promote fair, efficient and personalized education. They were confident that Squirrel AI Learning would become the forerunner and leader in the field of global Artificial Intelligence technology in the education sector.
In addition, members of the Squirrel AI team exchanged and interacted with experts in the field of Artificial Intelligence and listened to their research report,including Deborah Richards(fifth from right), professor with Department of Computer Science,Australia's Macquarie University; Paul Compton (fourth from right), honorary professor from the University of New South Wales, Australia.
A photo accompanying this announcement is available at http://www.globenewswire.com/NewsRoom/AttachmentNg/df4ccfb6-8618-4e7f-a27d-16db6b23aed3
Deborah Richards specializes in the application research on Artificial Intelligence technologies, such as the application of Artificial Intelligence to educational data, government public data, Internet data and many other fields. She gave a report entitled "Towards real time adaption: uncovering user models from experimental data" at the conference. "By exploring student data as well as using big data and Artificial Intelligence technology, we can learn the learning patterns of students and conduct real-time adaptive education," she said. She also mentioned that one of their educational software, PALLAS, is on sale in China.
Being the former Dean of the School of Computer Science and Engineering at the University of New South Wales, Paul Compton presented this conference as Session Chair. He elaborated his famous algorithm Ripple-Down Rules in his report. The algorithm is a kind of expert system methodology, which is a method for knowledge representation and acquisition. Paul Compton said that in a sense, the RDR algorithm is an extension or variant of the CBR (Case-base Reasoning) method. By introducing rules into CBR, RDR applies rules to index cases, and uses error-driven mechanisms to acquire knowledge.
Moreover, we know that Squirrel AI Learning will further expand its data open plan, and welcome the cooperation with global researchers and teams to conduct more extensive academic research on the application of Artificial Intelligence technology to the field of intellectual adaptation.
About YiXue Squirrel AI Learning Inc.
YiXue Squirrel AI Inc. is a leading AI-based adaptive learning service provider for K-12 students in China. Headquartered in Shanghai, China, YiXue offers after-school courses for Math, English, Chinese, Physics and Chemistry subjects, powered by its proprietary AI adaptive engine and custom-built courseware. Students on Squirrel AI 's platform enjoy a supervised adaptive learning experience that has been proven to improve both efficacy and student engagement across Squirrel AI's online learning platform and in-person learning centers.
To learn more about YiXue Squirrel AI Learning, please visit http://www.squirrelai.us/.