Squirrel AI Learning by Yixue Group invited to deliver a speech on AI+ education at CogX, the festival of AI and emerging technology of London

LONDON, July 15, 2019 /PRNewswire/ -- The largest technology summit of Europe was held from June 10 to 14. CogX, one of the exhibitions of London Tech Week for years, attracted many attendees this year. CogX, a festival of AI and emerging technology, was held from June 10 to 12. By inviting industrial representatives, governmental representatives and academic experts to deliver thematic speeches, the event showed that AI and emerging technology are providing huge opportunities for ushering in a blessed society in the future as well as shaping the human's future.

CogX 2019 mainly focuses on how mobile learning and working modes will be reshaped by emerging technologies such as digitization, artificial intelligence, DNA gene editing, driver-less transport and logistics, block chain, Internet of things, VR and AR. The list of winners of the third Annual Awards was announced on June 10, which recognized the 50 most innovative products and technologies of all key sectors and technical fields. Special awards were designed too. The awards for innovation were designed to commend the best technologies in AI and emerging technology. Previous winners include Tesla, DeepMind, Babylon Health, and Darktrace.

At the start of the conference, Knight Jeremy Wright, the minister of digitization, media, culture and sports, expressed the determination of the British government to develop AI and the UK's leading status in Europe in the valuing and investment of AI. Kay Firth-Butterfield, the director of AI and machine learning with the fourth scientific revolution center of Davos Forum, introduced and promoted the rapid development of Davos Forum and said that 15 cities would join the event next year and presided over the round-table meeting. Those who were involved in the discussion included Jesus Mantas, a global business service partner of IBM global strategy and innovation platform, and Alex Benay, CIO of Canada and vice president of the Secretariat.

Liang Jing, a partner of Squirrel AI Learning by Yixue Group, indicated that the future of AI+ education is a deep integration of education and technology. Education resources are distributed unevenly across China. The investment of first-tier cities such as Beijing and Shanghai in education resources is unrivalled by the mid-and-western regions. The differences of education funds and resources will ultimately lead to gaps in teaching achievements and be reflected in a huge gap in undergraduate admission rate in the College Entrance Exam. The chances for right-age students to receive education should be equal. The best way to improve this issue is the level of science and technology. New technologies can be used to empower and optimize the traditional education.

Through splitting of knowledge points at the most basic level and the accurate analysis and diagnosis of AI, Squirrel AI Learning can judge the knowledge mastery of the students, realize targeted teaching and knowledge map of error cause reconstruction and identify the non-relevant knowledge points, thus turning education into a science that can be defined, measured and imparted.

In terms of technical advantages, Squirrel AI Learning has many of the world's first AI application technologies, such as MCM capability value training, knowledge map of error cause reconstruction, knowledge point splitting at the most basic level, relevance probability of non-relevance knowledge points, and MIBA. At AIED, AREA, IJCAI, KDD and other top AI or educational academic conferences in the world, it has won awards for papers or been invited to give lectures. It has shined brilliantly on the international stage, showcasing to the world the scientific achievements of China's AI in the field of education. Through knowledge mapping at the most basic level and the nine-level splitting of knowledge points, MCM system can quickly detect the learning capabilities and qualities of students, develop an accurate user persona of the students, predict their learning path and time, and ultimately recommend personalized learning contents for them. All these are the technical advantages of Squirrel AI Learning. Besides, by monitoring with the multi-modal integrated behavior analysis (MIBA), Squirrel AI Learning can analyze the facial expressions and behaviors of students, evaluate their degree of concentration, detect and analyze their learning emotions so as to accurately identify the learning state of students and help the teachers infer where the problems and difficulties of students lie.

What is MCM system? The MCM system of Squirrel AI Learning can quickly detect the learning capabilities and qualities of students. By splitting every kind of thinking in learning, it can detect the model of thinking, learning capacity and methodology of the students. By taking math skills as an example, Liang said that the model of thinking for the learning of math skills can be split into imagination ability, inferential ability, exploration ability, core information extraction ability, and summarizing ability. After every student takes an evaluation test, the MCM system can analyze the different learning capacity of different students, their different ability in absorbing and digesting knowledge points and their differences in blind and weak areas. Through the accurate user persona, Squirrel AI Learning can provide a more accurate "customized" learning plan for the students.

Technically, Squirrel AI Learning's self-adaptive learning system applies knowledge mapping technology and knowledge space theory to evaluate the students' knowledge mastery, and applies Bayesian network, Bayesian inference, Bayesian knowledge tracking and Item Response Theory (IRT) to follow up the students' real-time learning progress, thus evaluating every student's knowledge mastery and predicting their future learning skills. It applies the self-adaptive learning engine and algorithms, contents, data and teaching design to recommend the most suitable learning contents to the students in a dynamic manner. In this way, it can mine the learning data of students, plan a learning path for them through the limitless computing power and intelligent analysis of AI and offer personalized tutoring based on the index data spectrum of the students. 

As the first AI self-adaptive education brand across the Asia-Pacific region, Squirrel AI Learning has made gratifying achievements on the path of AI+ education. Its R&D achievements include self-adaptive learning engine with complete intellectual property rights and designed based on senior algorithms. Squirrel AI Learning's self-adaptive learning system is an imitation of excellent teachers, which can improve the efficiency by five to ten times compared with traditional education. In several man-machine competitions held in China, the teaching team of Squirrel AI Learning helped each student to learn 42 knowledge points in eight hours on average, far better than the human teaching team that helped each student to learn 28 knowledge points in eight hours on average.

At the venue of the conference, Liang Jing received an interview from John Thornhill, associate editor-in-chief of Financial Times and a senior editor for the column of technology and innovation, who was also a speaker of the conference. John Thornhill was appointed as an innovation editor in February 2016. When he served as the associate editor-in-chief and news editor, he helped and guided the global news agenda of Financial Times of the UK. Since he joined Financial Times as an intern in 1988, he had ever served as editor for European edition, director of Paris Bureau, world's news editor, Asian news editor, director of Moscow Bureau, a column writer of Lex and a business reporter. He has established and run the forum of FT 125. The forum holds a series of senior management meetings each month. The previous speakers include Bill Gates, Jack Dorsey, Ana Patricia Botin and Mark Carney. Giants of science and technology community have also been invited recently, such as Knight Tim Berners-Lee, Andrew Ng, Maja Pantic and Chris Bishop.

At the CogX 2019, Andy Haldane, chief economist of the Bank of England also voiced his opinions on what artificial intelligence means to economy and charity in the fourth industrial revolution. Andy believed that the fourth industrial revolution will no doubt bring huge opportunities to economy. The cross-industry application is worth considering and practicing. Besides, the power of industrial transformation is amazing. Particularly for small and medium-sized enterprises and even small areas beyond large cities, today any scientific and technological progress can gain the maximum benefits. For this reason, changes are important to every enterprise. There is a huge gap between the sector of science and technology and other sectors in the UK and the entire Western world. He said that the two should be linked through integration and communication. Andy is a member of the Monetary Policy Committee of the World Bank and Chairman of the Industrial Strategy Committee of the government, an honorary professor of the University of Nottingham, a visiting scholar of Nuffield College of Oxford University, an academician of the Academy of Social Sciences and chairman of the National Economic and Social Research Institute. Meanwhile, he is also a founder and trustee of Pro Bono Economics, an economic broker for charity programs of the charity organization, a trustee of national digital and sponsor of Rence and Speakers for Schools.

Stuart Russel, a professor of computer science with University of California-Berkeley is a pioneer in the understanding and use of AI and an authority in the robotics research and bio-informatics. He is also an author or co-author of three books on knowledge, inference and machine learning as well as standard textbooks of AI. As an authority in the AI community, he delivered a thematic speech "Present and future of AI" and said that the AI of the humankind level was not at a corner. On the contrary, since some problems still need to be solved, this level can be reached, e.g. truly understanding a language; the integration of learning and knowledge; a long-distance thinking at several abstract levels; and accumulation of concepts and theories. He continued to point out, the real mastery and learning capacity for a language is not only learning based on data, but based on knowledge. For example, the learning of physics is not memorizing and applying the rules, but understanding the data with the knowledge mastered. This is completely at a level different from our current learning capacity. The professor said humorously, "The humankind has managed to do things that they have not touched in time. AlphaGo has made an attempt to understand the future by foreseeing 50-60 steps in the go game. After you decide to reach here, you have also made an attempt to foresee the future after 1.50 million steps. This is the physical sport you need to do for you to arrive here."

SOURCE Squirrel AI Learning