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Squirrel AI Learning Attends the 2019 Stanford University MediaX Conference: Connecting the Learner and the Learning with Algorithms and Analytics

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Martha Russell, Executive Director of MediaX at Stanford University, Delivered a Welcome Speech

 

The 2019 Stanford University MediaX Conference was held at the School of Education, Stanford University on October 23, North American time. The theme of the conference is: Algorithms and Analytics: Connecting the Learner and the Learning.

The speakers that were invited to the conference include: Richard Tong, Chief Architect of Squirrel AI Learning, Daniel Schwartz, Dean at the School of Education, Stanford University, Mark Musen, Professor of Biomedical Informatics at Stanford University, Ajay Madhok, Founder of Reboot Digital, and other experts and scholars in the fields of artificial intelligence and education research.

Richard Tong, Chief Architect of Squirrel AI Learning, was invited to deliver a keynote speech. He shared with hundreds of researchers, technology practitioners and other audiences from Stanford University about the experience of Squirrel AI Learning in using AI to bring great changes to students’ learning and future education, and introduced in detail to the participants how the research collaboration projects between Squirrel AI Learning and the world’s top universities and research institutions overturned the traditional teacher-centered education model, so as to provide students with personalized and high-quality education.

The current overseas collaboration projects of Squirrel AI Learning include: joint technology development with SRI international, virtual personal assistant to help students find the root causes of mistakes, multimodal comprehensive behavior analysis, etc., as well as SimStudents simulation students collaboration with Carnegie Mellon University (CMU), etc.

MediaX is a member project of the Human-Sciences and Technologies Advanced Research Institute, which is affiliated to the School of Education, Stanford University. It brings together more than 20 interdisciplinary laboratories at Stanford University, high-quality and rich academic resources, professors, innovative companies and researchers to explore the application of information technology in the future industry. MediaX members include Facebook, Fujitsu, Omron, Hong Kong University of Science and Technology, Squirrel AI Learning by Yixue Group and other internationally renowned technology companies and universities.

Human Learning Code

Martha Russell, Executive Director of MediaX at Stanford University and a Senior Researcher at the Human-Sciences and Technologies Advanced Research Institute, Stanford University, first delivered an opening speech.

Russell currently leads the business alliance and interdisciplinary research of MediaX at Stanford University, covering a variety of business development and innovation in the fields of information science, agriculture, communications and microelectronics. Focusing on the power of a common vision, Russell developed planning/assessment systems, and provides professional consulting services on technological innovation for regional development.

In her speech, Russell expressed three views around the “Human Learning Code”:

First of all, human experience is based on the sharing of information among people and groups, and rational learning is the basis for creating a successful user experience.

Secondly, learning analytics is not only about “Analyzing Learning Data”, but also about having an in-depth understanding of which learning activities are effective, for whom and when.

Finally, the field of learning analytics has the potential to improve students’ success through a deeper understanding of the academic, social emotion, motivation, identity and metacognitive background behind each student. These insights can also be applied to business, entertainment and health.

 Using Intelligent Adaptive Education Algorithms

Richard Tong is the Chief Architect of Squirrel AI Learning. He has served as the Head of Implementation, Greater China Region for Knewton and the Director of Solution Architecture at Amplify Education. In addition, he is also a Member of the IEEE AIS (Adaptive Teaching System) Standard Working Group and Chairman of the Interoperability Group (IEEE 2247.2).

Richard said that at present, the development speed of AI is beyond people’s expectations and imaginations, and any applications and scenarios related to AI are experiencing blowout growth.

Soon, the role of AI will be increasingly reflected in education and other fields that related to human interest. Especially in the future of the education field, every student will have an adaptive AI tutor, even those children with special needs are no exception.

Richard believes that AI and human teachers can learn from each other’s strengths and close their gaps, and combine each other’s advantages to provide students with all-round quality teaching. For example, AI has more advantages in diagnosing students’ learning state and providing intelligent adaptive education, while human teachers are better at psychological support and encouragement.

In order to achieve these goals, AI needs different algorithm modules, such as multi-dimensional probability knowledge state prediction algorithms can help AI diagnose learning state, path optimization algorithms based on knowledge map can help AI better recommend tasks for students; active learning and human-in-the-loop methods can enhance cooperation between AI and human beings.

Since 2014, Squirrel AI Learning has been independently developing an intelligent adaptive learning system for Chinese K12 students. Its main goal is to accurately diagnose the mastery of students’ knowledge points, and then recommend personalized learning content and learning path planning.

As a leading intelligent adaptive education company in China, Squirrel AI Learning is also making efforts in research and development. At present, Squirrel AI Learning is using deep learning to enhance the Bayesian-based tracking algorithms of students’ knowledge points and KST algorithms, etc.; using SimStudent and Apprentice Learner to establish recommendation strategies through reinforcement learning; and introducing human-in-the-loop methods in machine learning.

Currently, Squirrel AI Learning has set up a laboratory to carry out joint technology development with the Stanford Research Center. Squirrel AI Learning and the Institute of Automation of Chinese Academy of Sciences have set up a joint laboratory for AI intelligent adaptive education. This year, Squirrel AI Learning has set up a joint laboratory with Carnegie Mellon University (CMU), aiming to apply the most advanced artificial intelligence research results to teaching practice.

What is important to measure?

Daniel Schwartz is the Dean at the School of Education, Stanford University and an Expert in human learning and educational technology. At present, the laboratory that managed by Schwartz is conducting research on the basic problems of learning. Schwartz’s latest book, ABCs How We Learn: 26 Scientific Proven Methods, How They Work, and How Long They Work, refined learning theory into practical solutions and was listed by NPR as one of the “Best Books” in 2016.

Schwartz said that in a vibrant future, it’s important to measure whether and how people choose to learn beyond rigorous classroom instructions: Firstly, what we need to be measured now is the learning process, not just the results. This is important, because we need people to know how to learn.

Secondly, people actually know a lot of good learning strategies, and the key question is whether they choose to use these strategies. Finally, the core of design thinking is to avoid ending prematurely, for example, do not commit to your first idea. It turns out that it is actually good for learning, and can teach students the learning strategies they are willing to adopt.

Intelligent Agents, Knowledge Maps and Open Learning Data

Mark Musen is a Professor of Biomedical Informatics at Stanford University and the Director of the Biomedical Informatics Research Center at Stanford University. Musen is engaged in research related to intelligent systems, reusable ontologies, metadata for the release of scientific data sets, and biomedical decision support. His team developed Protégé, the world’s most popular technology for building and managing terminologies and ontologies.

Musen is also a Lead Researcher at the Center of Extended Data Annotation and Retrieval (CEDAR). CEDAR is a center of excellence supported by NIH big data to knowledge program. Its goal is to develop new technologies to simplify the compilation and management of biomedical experimental metadata.

Musen said that knowledge maps provide a formal representation of human knowledge and have the ability to link the concepts in these maps to related data sets and structures, people and intelligent agents can search these data sets and structures to discover new relationships between what we know and the data that may support these conclusions.

Technologies such as CEDAR can make the metadata describing experimental data sets easier to discover and reuse, thus providing opportunities to “Post” data linked to knowledge maps, thus enhancing the way we learn from scientific results

Musen believes that the results of the scientists’ work are not their published papers, but the data generated by their experiments. Current technologies make scientific data easier to find, access, interoperate, and reuse (FAIR). Future technologies will enable intelligent agents to help scientists understand information from data, plan new research, and make new discoveries.

Connecting the Learner in Learning Management Systems

Ajay madhok is a Founding Partner of Reboot Digital, a digital creative and marketing agency, and an Advisor of Playground Global, a venture fund. He has been involved in establishing four joint ventures, two of which were acquired and one was merged. At present, he is studying innovation models that large enterprises can practice maintaining competitiveness and correlation.

Madhok mainly introduced a digital learning management system designed by his team, which can provide the learning experience environment that students need. The goal of the system is to engage students to participate in guiding their own learning, help them set goals, track progress through dashboards, and select materials and challenges that meet their current capabilities.

Madhok said, “Effective learning depends on understanding students’ previous knowledge, experience, motivation, interests, language, and cognitive skills. Attracting students in the learning environment with emotional support can promote their sense of belonging, adaptability, initiative and learning achievements. Meanwhile, through the arrangement of interrelated concepts, students and learning are linked, so as to achieve personalized learning experience layer.

Meeting of Three Algorithmists and “Robin Hood“

Bruce Cahan is a Consulting Professor at the School of Engineering, Stanford University, where he designs and applies new theories to create financial and insurance markets, so as to improve the quality of regional living systems. Cahan is also the CEO and Co-founder of Urban Logic, a non-profit organization that uses finance and technology to change the way of systems thinking, behavior and feeling. Cahan has served as an International Financial Lawyer at Weil Gotshal＆Manges in New York for more than 10 years and as a Banker at Asian Oceanic in Hong Kong.

Cahan said that by 2050, AI workers could be divided into three categories: receivers collect and sell generic “Big Data”; amplifiers broadcast and seek to conform to any behavior or view that the government or business community want to fund; tuners ask whether, under the influence of all receivers and magnifiers, the results are beneficial to the people or small businesses that affected and manipulated by them.

According to Cahan, Stanford University is organizing research, teaching and practice to ensure that we apply artificial intelligence to business and social undertakings. Cahan believes that receivers, magnifiers and tuners cannot coexist naturally. Various ethical problems that arise in the development of AI, as well as challenges and threats to human society are all need to implement solutions as soon as possible.

Cahan proposed a concept of “Robin Hood AI Clinic” in his speech. Just as medical schools use teaching hospitals, or law schools use law clinics to check whether the diagnosis and treatment options learned and practiced by students and faculty really help real humans, Cahan believes that humans also need an institution like “Robin Hood AI Clinic” to perform similar teaching functions, so as to iterate and improve the possibility of AI comprehensively solving actual human problems and opportunities.

SOURCE Squirrel AI Learning

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Wladimir P. is a Content Editor at European Gaming Media and at PICANTE Media and covers a large variety of industries.

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FinVolution to Hold 9th Global Data Science Competition, Focus on Deepfake Speech Detection in LLM era

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May 10, 2024

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The 9th FinVolution Global Data Science Competition targets deepfake speech detection, tackling the challenge of distinguishing between cloned and authentic voices in the LLM era.The contest is part of the IJCAI 2024 Competitions and Challenges track, encouraging global collaboration and innovation among AI enthusiasts.By integrating LLM-generated fake voices in the test dataset, the competition increases complexity and spurs innovation.SHANGHAI, May 10, 2024 /PRNewswire/ — FinVolution, a leading fintech service provider, launches the 9th FinVolution Global Data Science Competition today, with a focus on “Deepfake Speech Detection.”  The contest is part of the IJCAI (International Joint Conference on Artificial Intelligence) Competitions and Challenges track, a top international AI conference.

As voice synthesis technology continues to evolve, the line between cloned and genuine voices has become increasingly blurred in the era of large language models (LLMs), posing significant challenges to data security and asset protection.
The competition aims to inspire global AI enthusiasts and experts to innovate in combating voice cloning and deepfake scams. Contestants will utilize deep learning technologies to develop models and algorithms based on FinVolution’s test dataset. The competition will include LLM-generated fake voices to elevate complexity and spur innovation.
With a total prize pool of RMB 310,000, the contest will consist of preliminaries, semifinals, and a final, with an aim to authenticate true and false voices. Highest-ranked contestants will attend IJCAI 2024 in Jeju of South Korea, to receive the awards and engage with academic and industry experts. FinVolution proudly sponsors IJCAI 2024.
Tiezheng Li, CEO of FinVolution, stated, “Since its inception nine years ago, the FinVolution Global Data Science Competition has evolved into a widely recognized event in the field of data technology, facilitating technical exchange worldwide. Partnering with IJCAI this year, a top-tier international AI conference, demonstrates our commitment to advancing deep speech recognition technology.”
The Deepfake Challenge
During the preliminaries (May 10 to June 12), participants will design algorithms based on the white-box dataset supplied by FinVolution and submit scoring results to qualify for the semifinals. The dataset primarily comprises voice recordings totaling 20-40 hours.
At the semifinal stage (June 13 to June 28), contenders are expected to refine their algorithms based on the black-box dataset provided by the competition organizer, vying for a spot in the final. The dataset, composed mainly of private data, contains five to 10 hours of recordings.
Participants can register on the official website from May 9 to June 3, to download and view the datasets.
Upholding AI Ethics
Voice cloning has emerged as a major form of telecom fraud, as scammers exploit AI technology to make distinction between genuine and fake voices increasingly tricky.
The competition focuses on safeguarding user privacy and combating fraudulent activities by identifying cloned voices accurately.
Lei Chen, Vice President of FinVolution and Head of its Big Data and AI Division, said, “The applications of Large Language Models far exceed the corresponding detection technology, posing great challenges to information security. We hope to see AI deepfake voice detection technology keep pace with the developments of LLMs, thus safeguarding the data security of the public. With this concept in mind, the FinVolution Global Data Science Competition is not only a platform for technical competition but also an opportunity to explore how AI can better adhere to ethical principles and serve the public.” 
To date, the FinVolution Global Data Science Competition has drawn nearly 10,000 participants globally in total, becoming a widely recognized event in the field of digital financial technology.
Organized annually since 2016, the contest themes have spanned diverse domains, all rooted in real-world fintech business scenarios. These themes range from risk control algorithms, financial data applications, and product development to semantic similarity recognition, asset portfolio cash flow prediction, and credit schemes for small- and micro-sized enterprises.
About FinVolution Group
FinVolution Group is a leading fintech company that connects millions of consumers as well as micro- and small-sized enterprises with financial institutions.
Founded in 2007 and listed on the New York Stock Exchange in 2017, we have been at the forefront of the pan-Asian credit technology industry, pioneering innovative technologies in credit risk assessment, fraud detection, big data, and artificial intelligence. With a proven track record of robust growth in pan-Asian countries, we have established leading fintech platforms in China, Indonesia, and the Philippines.
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XTEND SECURES $40M TO REDEFINE ROBOTICS WITH AI-POWERED COMMON SENSE

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May 10, 2024

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XTEND and its XOS operating system are unlocking the potential of robots and drones by empowering them with AI and partnering them with humans – providing them with the ‘common sense’ to navigate the unpredictable nature of real-world situations
TEL AVIV, Israel, May 10, 2024 /PRNewswire/ — XTEND, the developer of XOS, an AI-driven operating system that is revolutionizing the way humans interact with drones and robots, today announced its $40M Series B round, led by Chartered Group, with further participation from its existing and new strategic investors, including Clal-Tech. The new funding will further develop XTEND’s proprietary XOS operating system and its application in various time-consuming, dangerous enterprise and security scenarios worldwide. XTEND will also ramp up global sales of its own drones and robotics products.

XTEND provides a revolutionary human-supervised, AI-driven drone and robot operating system that enables operators to perform highly complex and dynamic missions in any environment with minimal training. When drones and robots are controlled by XTEND’s patented XOS operating system – which fuses the best of human intelligence and machine autonomy – it provides a new way for logistics, public safety, inspection, defense, and security professionals to interact with machines effectively from a safe distance. 
XTEND’s team believes that as the use of drones and robots become more prevalent, professional human oversight remains crucial, and therefore developing a seamless collaboration between humans and AI, where each play to their strengths for optimal results, is vital. Aviv Shapira, co-founder, and CEO, explains: “Robots and drones promise to transform everything from factories to our homes. However, a significant hurdle remains – equipping them with the common-sense abilities to deal with the unpredictable nature of real-world situations, understand their surroundings, and make decisions based on that information. XOS uses AI to enable robots to learn from data and experience. Training them to identify objects, navigate complex environments, and interact with humans safely. We are unlocking the true potential of robotics in complex scenarios, including first response, search and rescue, logistics, critical infrastructure inspection, defense, and security.”
“Our XOS operating system is based on “Practical Human Supervised Autonomy” which empowers drones and robots to handle specific tasks autonomously – entering buildings, scanning floors, or even pursuing suspects. However, crucially, it allows the “common sense” decisions – like judging situations or adapting to unforeseen circumstances – to remain in the hands of human supervisors. This human-machine teaming allows our robots to work alongside supervisors, who can manage dozens of robots simultaneously, and learn from that experience. That is why we believe that XOS will become the operating system of choice for anyone looking to maximize their robotic systems’ potential while decreasing the risks posed to their teams’ lives or concerns around lack of human oversight.”
Hundreds of XTEND’s drone and robotics systems are already operationally deployed worldwide, and the company is continuously developing its XOS operating system and those platforms to deliver the future of human-machine teaming. XOS is hardware agnostic, which allows it to control all sorts of platforms, including third party devices, complement existing technology, or create entirely new systems from scratch. XOS’s open architecture means that it can host applications developed by other companies, too. 
Matteo Shapira, co-founder, and CXO, adds: “Unlike self-driving cars, which operate in a world with mostly known rules and scenarios, XTEND specializes in enabling operations in “hypervariable” environments. Take a last-mile delivery robot. It can navigate autonomously indoors and outdoors but might need human help finding an office building entrance or understanding floor layouts to reach the elevator or stairway. These environments present limitless situations with the potential for the unexpected, requiring human-level decision-making skills specific to each profession. XTEND’s core technology, XOS, is built around this human-machine partnership. We are continually adding new “AI SKILLS” to our system, and those skills will allow robots to handle a growing portion of missions and tasks, freeing up human supervisors to manage more missions simultaneously, at scale.”
Eyal Agmoni, Founder and Chairman of Chartered Group, said: “We believe that the companies bringing the value of AI to massive and complex industries, such as robotics and drone operations, will be the tech giants of the 21st century. Having observed XTEND’s remarkable achievements thus far, we truly believe in the company’s potential to become the world leader in robotics and drone operations, and AI.” 
XOS has been developed for multiple markets, including logistics, public safety, inspection, and security. The U.S. Department of Defense Special Forces and Israel’s Ministry of Defense tier-1 units have also chosen XTEND for multiple multi-million-dollar programs to develop and deliver its systems for operational evaluation, so the company’s technology is already being used by some of the best in the business.
About XTENDXTEND provides revolutionary human-guided autonomous machine systems that enable any operator to perform extremely accurate manoeuvres and actions, in any environment with minimal training. The company’s patented XOS operating system fuses the best of human intelligence and machine autonomy to enhance the operator’s abilities, and simultaneously reduce the need for physical confrontation, thereby minimizing casualties and injuries. Hundreds of XTEND’s systems are already operationally deployed worldwide, and the company is continuously developing its XOS operating system and platforms to deliver the future of human-machine teaming to defense, HLS, and security professionals worldwide. Find out more here.
https://vimeo.com/802995851/2554c5485a – this footage shows XTEND’s team using drones and our XOS operating system to help with the recent rescue effort in Turkey. XOS enabled these drones to be operated in unsafe, confined, hard to reach spaces. Utilising additional cutting-edge technology, including robotic arms and thermal cameras, to enhance each drone’s rescue capacity. While this mission was carried out by XTEND’s own team, XOS enables anyone to easily connect and interact within remote environments using drones and other smart machines, without the need for prior knowledge or training.
About Chartered GroupChartered Group is an innovative global private equity firm providing extraordinary global investment funds and opportunities for a greener and more digitalized world across several disciplinaries with its VC of Disruptive Technologies as its cutting edge. Chartered is all about exposing accredited and institutional investors to the most extraordinary global investments and opportunities. As a global private equity firm, Chartered cut through the investment noise to deliver a variety of savvy financial products and services that not only support a greener and more digitalized world but also leverage robust financial returns, one tailored strategy at a time. To learn more please visit www.charteredgroup.com.
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Precisely Continues to Expand Reach and Capabilities for Data Enrichment and Geo Addressing

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May 9, 2024

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New global Address Fabric™ and Property Attributes offerings help customers access unparalleled location-based insights, supercharged by the PreciselyID
BURLINGTON, Mass., May 9, 2024 /PRNewswire/ — Precisely, the global leader in data integrity, today announced further expansions in the global coverage and capabilities of its data enrichment and geo addressing portfolio. New additions to the Address Fabric and Property Attributes products underscore the company’s continued commitment to helping customers easily unlock greater location-based context from their data, enabled by its unique and persistent identifier, the PreciselyID.

Virtually every business worldwide captures and stores address information, with the average large business in the United States now estimated to store over 100 million unique addresses. However, navigating the inherent data integrity challenges is notoriously difficult, as it involves new buildings, changing street names, different country formats, and more.
Expanded Address Fabric Reach
Precisely customers can now access the Address Fabric dataset for Great Britain, France, and New Zealand – providing the most current and comprehensive lists of all known physical addresses across these countries. The new datasets expand Precisely’s existing coverage for the United States, Canada, and Australia.
Address Fabric data is easy to use with any database and analytics environment without needing specific geospatial expertise or tools. Customers can analyze address locations for various applications, including identifying new serviceable addresses, discovering new customers through look-a-like analysis, or selecting a site for new stores or network expansion opportunities.
Comprehensive Property Attributes Information
Precisely also announced the expansion of its Property Attributes products for the United States with 26 new attributes now available via integration with Multiple Listing Service (MLS) data. The MLS database of property listings is used by real estate agents to share information about homes currently on the market, including whether a property is affiliated with a Homeowner’s Association or if it’s considered a rental property.
With the latest updates, Property Attributes products now include over 230 different property information attributes across virtually every county located in the United States, providing a highly comprehensive view of a property and its key characteristics, such as details on land use, square footage, construction materials, and year built.
Address Fabric and Property Attributes leverage best-in-class geo addressing solutions from Precisely to provide the most accurate location information possible. Because each record is appended with a unique PreciselyID that remains persistent even when address elements change, customers can unlock greater value by enriching their data with additional information such as points of interest data, risk factors, demographics data, and much more.
“Precisely continues to be at the forefront of data enrichment and geo addressing solutions, enabling customers where they are on their data journey and supporting them with access to consistent location-based insights across their countries of operation,” said Dan Adams, Senior Vice President and General Manager for Data Enrichment at Precisely. “An essential element of data integrity, our unique PreciselyID makes address management and enrichment simple by eliminating time-consuming data preparation and augmenting insights with rich, relevant context.”  
Precisely is renowned for its expertise in helping customers reveal maximum context from their data, with a comprehensive portfolio that includes over 400 datasets containing more than 9000 attributes. The company also recently joined the Overture Maps Foundation, founded by Amazon Web Services (AWS), Meta, Microsoft, and TomTom, providing guidance on location intelligence and data enrichment to help drive exciting new advancements in geospatial technology.
Learn more about the Precisely portfolio of data enrichment and geo addressing capabilities.
About PreciselyPrecisely is the global leader in data integrity, providing accuracy, consistency, and context in data for 12,000 customers in more than 100 countries, including 99 of the Fortune 100. Precisely’s data integration, data quality, data governance, location intelligence, and data enrichment products power better business decisions to create better outcomes. Learn more at www.precisely.com.
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