Artificial Intelligence

AIED2019: How the World’s Top AI Experts Apply AI to Education

Published

5 years ago

July 31, 2019

Reading Time: 7 minutes

AI has become the core driving force of the new round of industrial transformation and ushered in a new period of industrial explosion. How to break through the barriers between technology and industry has become a heated issue. AI in education has become a favorite target for capital investment. Information-based education, quality education, language training and K12 primary and secondary school extracurricular tutoring are witnessing iterative research results in “AI+Education”. What are the latest AI technologies in education? What is the current condition for their application? What’s the future for “AI+Education”?

On June 26-29, the 20th AIED (AI in Education) successfully ended in Chicago. Hundreds of top researchers and experts in AI+ education, computer science, psychology and other fields from all over the world gathered together at the conference to share and discuss the latest research results in AI, as well as the experience and challenges of AI application and AI products. First Insight, as an exclusively invited media in China, reported the whole process of AIED.

Organized by the 25-year-old International Association for AI Education (IAIED), AIED has over 1,000 members from more than 40 countries. They are experts and scholars in the fields of computer science, education and psychology. At the conference, Dr. Luis Von Ahn, founder of Duolingo, a famous language learning software; Candace Thille, professor of Stanford University and director of Amazon Learning Science Center; Nancy Law, professor of Hong Kong University; Jutta Treviranus, professor of OCAD University in Canada; and Richard Tong, chief architect of Squirrel AI Learning among others delivered keynote speeches and participated in round-table discussions. The co-chairs of the conference were Bruce McLauren, professor of Carnegie Mellon University in the US, and Rose Luckin, professor of education at University College London in UK.

AI is not a new thing in education. Although “AI+ Education” is a favorite target for capital investment, there are still doubts about its authenticity. Robby Robson, CEO of Eduworks and member of IEEE Standards Committee, pointed out that AI technology has been developing all the time and that all advanced machine behaviors are inseparable from AI, but there are five problems as follows:

1. Producers do not participate in research

2. Researchers are not engaged in production

3. Consumers do not know what to believe

4. Buyers do not know what to buy

5. Favorable technologies have not been applied to production.

In short, it is the separation between technology and industry that prevents AI from being applied. Parents of children in K12 primary and secondary schools are the true consumers of AI-related products, so it is especially crucial for them to understand and accept the important role of technology. Robby Robson also pointed out that the core of the application of AI technology is simple, that is, classification and decision. Only by understanding these two things can we find a way to connect machine learning with teaching.

At present, AI+Education mainly has two modes, namely the alternative and simplified traditional educational resources, and the personalized education. Alternative education emphasizes the application of technology to replace teachers in performing some tasks or strengthen teachers’ roles. Such products have developed rapidly, but their functions are relatively single. Personalized education using AI aims to complete the closed loop of “teaching, practicing and evaluating” and create customized learning method for each student, so that they will know which parts should be given up and which parts they should learn.

Intelligent adaptive system is a teaching method that uses algorithms to detect students’ learning paths and provide personalized and customized learning contents for students. Richard Tong, Chief architect of Squirrel AI Learning by Yixue Group said at the conference that, “Traditional school is like a bus which provides services in a simple and convenient manner, but it fails to take each student to the exact location they want to go to. Intelligent adaptive system is like a taxi that serves each student exclusively to meet their needs.”

Richard Tong, chief architect of Squirrel AI Learning, talked about the connection between human learning and machine learning as well as the way to completely change education and learning through AI. First, he talked about the reasons for applying AI in education and the significance of AI technology in replacing, enhancing, improving and redefining education. He then emphasized the continuous one-to-one individualized education for students and the change of the role of real teachers from instructors to psychological tutors for students, both of which are required by education revolution. He then introduced the reasons for the rapid development of Squirrel AI Learning from its business model, the experience of the application of AI, massive data in learning scenarios and strong computing power.

Squirrel AI Learning has created an adaptive learning engine driven by AI which integrates Mentality, Capability and Methodology (MCM), Probabilistic Knowledge State (PKS) model , Multimodal Integrated Behavioral Analysis (MIBA) using deep learning technology, Nano-Scale Knowledge Component (NKC) as well as other AI technologies like reinforced learning. This engine can promote the integration of AI and adaptive education and affect future education.

Richard Tong, chief architect of Squirrel AI Learning; Professor Rose Luckin, President of the Conference; and Ken Koedinger, Professor of Carnegie Mellon University and Chief Learning Scientist of Squirrel AI Learning, had a fireside dialogue. Richard Tong shared the success experience of Squirrel AI Learning in applying the above excellent researches into practice. The new model of “AI intelligent adaptive system + human teachers” makes for the maximum teaching effect and personalized learning experience for students. Professor Ken Koedinger of Carnegie Mellon University, a pioneer in cognitive science, shared his years’ experience of applying his research achievement in cognitive science and brain science to intelligent adaptive education products. Professor Ken Koedinger, chief learning officer of Squirrel AI Learning, discussed with Professor Rose Luckin about the technologies and values of Squirrel AI Learning’s intelligent adaptive teaching system and Professor Rose Luckin fully expressed his recognition. Richard Tong also held an industry forum discussion with Amy Baylor, program director of the National Nature Foundation of the United States, Brent Benson, online enterprise architect of Harvard Business School, and Kumar Garg, senior director of – Schmidt Futures, a public welfare organization set up by Eric Schmidt, co-founder of Google, to share the opportunities and challenges of their respective organizations in education science and technology. Richard talked about the importance of the cooperation between industry and academia. At present, there are four types of research fields and projects in education: learner model (to improve diagnosis and understanding of learning problems), domain model (to strengthen ontology and content), educational model (to enhance recommendation and channel optimization), and interactive model (to enhance interaction, feedback and communication). He also said that industry and academia can cooperate through various academic conferences and workshops, such as education-science and technology conferences, AI-machine learning conferences, industry conferences, workshops, tutorial samples, research papers and competitions.

On June 29, Squirrel AI Learning gathered IEEE AIS experts and professional audience of AIED to hold a workshop at DePaul University in the US to have a discuss on standardization of “AI+ Education”. Richard Tong, chief architect of Squirrel AI Learning; Robert Sottilare, senior director of Soar Technology; Robby Robson, member of IEEE Standards Committee and CEO of Eduworks; Xiangen Hu, professor of the University of Memphis; Avron Barr, Chairman of IEEE Learning Technology Standards Committee, together with experts, researchers and practitioners in AI education from Carnegie Mellon University, DePaul University as well as from Brazil, Cyprus and other countries, put forward their own opinions and had heated discussions about the standardization development of AI+ Education, AI’s integration with industry products, the application of intelligent adaptive education system, relevant algorithms and frameworks, etc.

For example, Robert Sottilare, senior director of Soar Technology, talked about the “Cases Study of Standards and Suggested Measures in Monitoring Tasks of Adaptive Teaching System”. AIS teaching areas include: cognition, problem solving and decision-making tasks, thinking; emotion, problem solving and decision-making, feeling; mental exercise, physical task; group, tasks involving two or more people, cooperated discussion. He finally asked a question to other scholars in the workshop: “The commonness in the instruction field can fulfill the following standards, namely the data exchanged in various AIS processes and the structural model in the domain. But what should the industry do to enable the AIS market to flourish? This is the next question to think about.”

As a leading enterprise in “AI+ Education”, Squirrel AI Learning is China’s first AI company to apply AI adaptive learning technology to primary and secondary education. It has successfully developed China’s first AI adaptive learning engine with complete independent intellectual property rights and advanced algorithms as the core. It uses more than ten algorithms and deep learning technologies and has developed many AI application technologies such as MCM capability value training, root cause reconstruction of knowledge map, nano-scale knowledge point splitting at the most basic level, relevance probability of non-relevance knowledge points, MIBA Multimodal Integrated Behavioral Analysis AI system, etc., the first of their kinds in the world.

As a Unicorn in China’s “AI+ Education” industry, Squirrel AI Learning has accumulated nearly 2 million student data in the past four years and has set up nearly 2,000 learning centers over 400 cities nationwide. Based on its deep understanding of education and continuous investment in technology, Squirrel AI Learning, a company with more learning data than others, will take personalized learning and improving learning efficiency as the direction of its future product development.

China’s AI technology is not inferior to that in foreign countries, but the development of AI+ Education lags far behind Europe and the United States since there are more than 50 AI education companies in Europe and the United Statesand 23 million users in the United States are using AI education products with an annual growth rate of between 30% and 40%. Given the rapid development of AI+education overseas and the huge development potential in China, Squirrel AI Learning, a leading enterprise in China, is actively tapping overseas resources and introducing and cooperating with global talents to develop the most advanced AI technology so as to make excellent intelligent adaptive learning products in line with the national conditions for Chinese students.

Squirrel AI Learning also plans to expand overseas to promote China’s advanced education platforms abroad, make products based on its existing educational knowledge maps, cooperate with overseas projects and build a curriculum system of mathematics that can be used worldwide.

At the conference, Professor Xiangen Hu of the University of Memphis shared his different views on the application of AI technology in education. He said: “AI technology should not be limited to the existing intelligent tutoring system – an easy-to-understand teaching system.” He proposed SIAIS (Self-Improvable Adaptive Instructional Systems) which consists of four parts. The key for this system is that learners and learning resources should match each other and they should make common progress. The core of “Self-Improvable Learning Resources” is educational games, functional teaching assistant systems and other dynamic contents. Therefore, it is necessary to define the variable but controllable modular components in the dynamic contents, combine them with big data and improve tutoring strategies through the interaction between learners and the dynamic resources.

As Nancy Law, a professor of the University of Hong Kong, said at the conference, “We should learn how to make full use of science and technology instead of being manipulated by it”. We should not turn technology into a gimmick, thus exacerbating arbitrary charge in the industry. Instead, we should use technology to provide better and fairer educational resources. Dr. Luis Von Ahn, founder of Duolingo and father of identifying code, said that although Duolingo is a technological product, his company always believes that education is the fairest way to change one’s fate, so they provide free services to customers and enhance learning entertainment with technology based on their understanding of learners’ changing learning psychology to help students become more motivated and improve users’ loyalty. Not just helping students solve learning problems and get high scores in exams, Squirrel AI Learning’s intelligence adaptive system aims to enable them to acquire good learning methods, get to know their advantages and disadvantages in thinking and personality. In this way, Squirrel AI Learning hopes to provide quality education for students.

Bruce McLauren, professor of Carnegie Mellon University, said in an interview that the new generation of users grow up together with technology. Students born in the era of Internet are eager for new technologies, new tools and new learning methods, which is both a challenge and an opportunity for enterprises. Only enterprises that provide quality education will be the winners.

SOURCE Squirrel AI Learning

Artificial Intelligence

IBM, Government of Canada, Government of Quebec Sign Agreements to Strengthen Canada’s Semiconductor Industry

Published

2 hours ago

April 26, 2024

CISION (PR Newswire)

ibm,-government-of-canada,-government-of-quebec-sign-agreements-to-strengthen-canada’s-semiconductor-industry

Up to $187M CAD to be invested to progress expansion of chip packaging capacity and capabilities and to strengthen R&D at IBM Canada’s Bromont plant
BROMONT, QC, April 26, 2024 /PRNewswire/ — IBM (NYSE: IBM), the Government of Canada, and the Government of Quebec today announced agreements that will strengthen Canada’s semiconductor industry, and further develop the assembly, testing and packaging (ATP) capabilities for semiconductor modules to be used across a wide range of applications including telecommunications, high performance computing, automotive, aerospace & defence, computer networks, and generative AI, at IBM Canada’s plant in Bromont, Quebec. The agreements reflect a combined investment valued at approximately $187M CAD.

“Today’s announcement is a massive win for Canada and our dynamic tech sector. It will create high-paying jobs, invest in innovation, strengthen supply chains, and help make sure the most advanced technologies are Canadian-made. Semiconductors power the world, and we’re putting Canada at the forefront of that opportunity,” said the Right Honourable Justin Trudeau, Prime Minister of Canada
In addition to the advancement of packaging capabilities, IBM will be conducting R&D to develop methods for scalable manufacturing and other advanced assembly processes to support the packaging of different chip technologies, to further Canada’s role in the North American semiconductor supply chain and expand and anchor Canada’s capabilities in advanced packaging.
The agreements also allow for collaborations with small and medium-sized Canadian-based enterprises with the intent of fostering the development of a semiconductor ecosystem, now and into the future.
“IBM has long been a leader in semiconductor research and development, pioneering breakthroughs to meet tomorrow’s challenges. With the demand for compute surging in the age of AI, advanced packaging and chiplet technology is becoming critical for the acceleration of AI workloads,” said Darío Gil, IBM Senior Vice President and Director of Research. “As one of the largest chip assembly and testing facilities in North America, IBM’s Bromont facility will play a central role in this future. We are proud to be working with the governments of Canada and Quebec toward those goals and to build a stronger and more balanced semiconductor ecosystem in North America and beyond.”
IBM Canada’s Bromont plant is one of North America’s largest chip assembly and testing facilities, having operated in the region for 52 years. Today, the facility transforms advanced semiconductor components into state-of-the-art microelectronic solutions, playing a key role in IBM’s semiconductor R&D leadership alongside IBM’s facilities at the Albany NanoTech Complex and throughout New York’s Hudson Valley. These agreements will help to further establish a corridor of semiconductor innovation from New York to Bromont.
“Advanced packaging is a crucial component of the semiconductor industry, and IBM Canada’s Bromont plant has led the world in this process for decades,” said Deb Pimentel, president of IBM Canada. “Building upon IBM’s 107-year legacy of technology innovation and R&D in Canada, the Canadian semiconductor industry will now become even stronger, allowing for robust supply chains and giving Canadians steady access to even more innovative technologies and products. This announcement represents just one more example of IBM’s leadership and commitment to the country’s technology and business landscape.”
Chip packaging, the process of connecting integrated circuits on a chip or circuit board, has become more complex as electronic devices have shrunk and the components of chips themselves get smaller and smaller. IBM announced the world’s first 2 nanometer chip technology in 2021 and, as the semiconductor industry moves towards new methods of chip construction, advances in packaging will grow in importance.
“Semiconductors are part of our everyday life. They are in our phones, our cars, and our appliances. Through this investment, we are supporting Canadian innovators, creating good jobs, and solidifying Canada’s semiconductor industry to build a stronger economy. Canada is set to play a larger role in the global semiconductor industry thanks to projects like the one we are announcing today. Because, when we invest in semiconductor and quantum technologies, we invest in economic security.” — The Honourable François-Philippe Champagne, Minister of Innovation, Science and Industry
“This investment by IBM in Bromont will ensure that Quebec continues to stand out in the field of microelectronics. An increase in production capacity will solidify Quebec’s position in the strategic microelectronics sector in North America.” — The Honourable Pierre Fitzgibbon, Minister of Economy, Innovation and Energy, Minister responsible for Regional Economic Development and Minister responsible for the Metropolis and the Montreal region
About IBMIBM is a leading provider of global hybrid cloud and AI, and consulting expertise. We help clients in more than 175 countries capitalize on insights from their data, streamline business processes, reduce costs and gain the competitive edge in their industries. More than 4,000 government and corporate entities in critical infrastructure areas such as financial services, telecommunications and healthcare rely on IBM’s hybrid cloud platform and Red Hat OpenShift to affect their digital transformations quickly, efficiently and securely. IBM’s breakthrough innovations in semiconductors, AI, quantum computing, industry-specific cloud solutions and consulting deliver open and flexible options to our clients. All of this is backed by IBM’s legendary commitment to trust, transparency, responsibility, inclusivity and service. Visit www.ibm.com for more information.
Media ContactLorraine BaldwinIBM [email protected]
Willa HahnIBM [email protected]
Photo – https://mma.prnewswire.com/media/2397908/IBM_Canada_employee_at_the_IBM_Bromont_plant_holding_a_wafer.jpg
Logo – https://mma.prnewswire.com/media/95470/ibm_logo.jpg

View original content:https://www.prnewswire.co.uk/news-releases/ibm-government-of-canada-government-of-quebec-sign-agreements-to-strengthen-canadas-semiconductor-industry-302128212.html

Artificial Intelligence

HITACHI ACQUIRES MA MICRO AUTOMATION OF GERMANY IN EFFORT TO ACCELERATE GLOBAL EXPANSION OF ROBOTIC SI BUSINESS IN THE MEDICAL AND OTHER FIELDS

Published

4 hours ago

April 26, 2024

CISION (PR Newswire)

hitachi-acquires-ma-micro-automation-of-germany-in-effort-to-accelerate-global-expansion-of-robotic-si-business-in-the-medical-and-other-fields

HOLLAND, Mich., April 26, 2024 /PRNewswire/ — Hitachi Ltd. (TSE: 6501, “Hitachi”) has signed a stock purchase agreement on April 26 to acquire all shares of MA micro automation GmbH (“MA micro automation”, headquartered in St. Leon-Rot, Germany) from MAX Management GmbH (a subsidiary of MAX Automation SE). MA micro automation is a leading provider of robotic and automation technology (robotic SI) including high-speed linear handling systems, high-precision assembly lines, and high-speed vision inspection technology for Europe, North America, and Southeast Asia, for EUR 71.5M million. The transaction is expected to close in the second half of 2024, pending completion of the customary regulatory filings. After the acquisition is completed, MA micro automation will join JR Automation Technologies, LLC (“JR Automation”), a market leader in providing advanced automation solutions and digital technologies in the robotic system integration business for North America, Europe, and Southeast Asia as a continued effort to expand the company’s global presence.

MA micro automation is a technology leader for automation solutions within micro-assembly. Through its state-of-the-art proprietary high-speed and high-precision automation know-how, combined with unique optical image inspection capabilities, MA micro automation serves high-growth med-tech automation end-markets, covering the production, assembly, and testing medical and optical components including contact lenses, IVD and diabetes diagnostics consumables, and injection molding for medical use. The company was established in 2003 through a carve-out from Siemens*1 and since 2013 has been part of the MAX Automation group.
JR Automation is a leading provider of intelligent automated manufacturing technology solutions, serving customers across the globe in a variety of industries including automotive, life sciences, e-mobility, consumer and industrial products. With over 20 locations between North America, Europe, and Southeast Asia, the leading integrator offers nearly 2 million square feet (185,806 sq. m) of available build and engineering floorspace. This acquisition allows JR Automation to further grow and strengthen both the company’s geographical footprint and their continued commitment on expanding support capabilities within the European region and medical market vertical.
“MA micro automation provides engineering, build and support expertise with established capabilities in complex vision applications, high-speed and high-precision automation technologies. When integrated with JR Automation’s uniform global process and digital technologies, this partnership will further enhance our ability to deliver added value and support to all of our customers worldwide and continue to grow our capabilities in the medical market,” says Dave DeGraaf, CEO of JR Automation. “As we integrate this new dimension, impressive talents and abilities of the MA micro automation team we further enhance our ability to serve our customers, creating a more robust and globally balanced offering.”
With this acquisition, Hitachi aims to further enhance its ability to provide a “Total Seamless Solution*2” to connect manufacturer’s factory floors seamlessly and digitally with their front office data, allowing them to achieve total optimization and bringing Industry 4.0 to life. This “Total Seamless Solution” strategy links organizations’ operational activities such as engineering, supply chain, and purchasing to the plant floor and allows for real time, data-driven decision-making that improves the overall business value for customers.
Kazunobu Morita, Vice President and Executive Officer, CEO of Industrial Digital Business Unit, Hitachi, Ltd. says, “We are very pleased to welcome MA micro automation to the Hitachi Group. The team is based in Europe, providing robotic SI to global medical device manufacturing customers with its high technological capabilities and will join forces with JR Automation and Hitachi Automation to strengthen our global competitiveness. Hitachi aims to enhance its ability to provide value to customers and grow alongside them by leveraging its strengths in both OT, IT, including robotic SI, and “Total Seamless Solution” through Lumada*3’s customer co-creation framework.”
Joachim Hardt, CEO MA micro automation GmbH says, “Following the successful establishment and growth of MA micro automation within the attractive automation market for medical technology products, we are now opening a new chapter. Our partnership with Hitachi will not only strengthen our global competitive position, but we will also benefit from joint technological synergies and a global market presence. We look forward to a synergistic partnership with Hitachi and JR Automation.”
Outline of MA micro automation
Name
MA micro automation GmbH
Head Office
St. Leon-Rot, Germany
Representative
Joachim Hardt (CEO)
Outline of Business
Automation solutions within micro-assembly
Total no. of Employees:
Approx. 200 (As of April 2024)
Founded
2003
Revenues (2023)
€ 46.5 million
Website

Home

*1
“Siemens” is a registered trademark or trademark of Siemens Trademark GmbH & Co. KG in the U.S. and other countries.
*2
“Total Seamless Solution” is a registered trademark of Hitachi, Ltd. in the U.S. and Japan.
*3
Lumada: A collective term for solutions, services and technologies based on Hitachi’s advanced digital technologies for creating value from customers’ data accelerating digital innovation. https://www.hitachi.com/products/it/lumada/global/en/index.html
About JR AutomationEstablished in 1980, JR Automation is a leading provider of intelligent automated manufacturing technology solutions that solve customers’ key operational and productivity challenges. JR Automation serves customers across the globe in a variety of industries, including automotive, life sciences, aerospace, and more.
In 2019, JR Automation was acquired by Hitachi, Ltd. In a strategic effort towards offering a seamless connection between the physical and cyber space for industrial manufacturers and distributers worldwide. With this partnership, JR Automation provides customers a unique, single-source solution for complete integration of their physical assets and data information, offering greater speed, flexibility, and efficiencies towards achieving their Industry 4.0 visions. JR Automation employs over 2,000 people at 21 manufacturing facilities in North America, Europe, and Asia. For more information, please visit www.jrautomation.com.
About Hitachi, Ltd.Hitachi drives Social Innovation Business, creating a sustainable society through the use of data and technology. We solve customers’ and society’s challenges with Lumada solutions leveraging IT, OT (Operational Technology) and products. Hitachi operates under the 3 business sectors of “Digital Systems & Services” – supporting our customers’ digital transformation; “Green Energy & Mobility” – contributing to a decarbonized society through energy and railway systems, and “Connective Industries” – connecting products through digital technology to provide solutions in various industries. Driven by Digital, Green, and Innovation, we aim for growth through co-creation with our customers. The company’s revenues as 3 sectors for fiscal year 2023 (ended March 31, 2024) totaled 8,564.3 billion yen, with 573 consolidated subsidiaries and approximately 270,000 employees worldwide. For more information on Hitachi, please visit the company’s website at https://www.hitachi.com.
Photo – https://mma.prnewswire.com/media/2398552/CENTAURI_IVD_Platform.jpg Logo – https://mma.prnewswire.com/media/2392427/4673549/JR_Automation_and_Hitachi_Combined_Mark_full_color_Logo.jpg

View original content:https://www.prnewswire.co.uk/news-releases/hitachi-acquires-ma-micro-automation-of-germany-in-effort-to-accelerate-global-expansion-of-robotic-si-business-in-the-medical-and-other-fields-302128612.html

Artificial Intelligence

$10 million Artificial Intelligence Mathematical Olympiad Prize appoints further advisory committee members

Published

6 hours ago

April 26, 2024

CISION (PR Newswire)

D. Sculley, Kevin Buzzard, Leo de Moura, Lester Mackey and Peter J. Liu appointed to the advisory committee for the Artificial Intelligence Mathematical Olympiad Prize.
LONDON, April 26, 2024 /PRNewswire/ — XTX Markets’ newly created Artificial Intelligence Mathematical Olympiad Prize (‘AIMO Prize’) is a $10mn challenge fund designed to spur the creation of a publicly shared AI model capable of winning a gold medal in the International Mathematical Olympiad (IMO).

XTX Markets is delighted to announce the appointment of five further advisory committee members. This group brings great expertise in machine learning, including D. Sculley, the CEO of Kaggle; Lester Mackey, a Principal Researcher at Microsoft Research and a Macarthur Fellow; and Peter J. Liu, a research scientist at Google DeepMind.
Prolific mathematicians Kevin Buzzard, who achieved a perfect score in the International Mathematical Olympiad, and Leo De Moura who is the Chief Architect for Lean, the automated reasoning tool, also join the advisory group.
They join the existing advisory committee members Terence Tao and Timothy Gowers, both winners of the Fields Medal, as well as Dan Roberts, Geoff Smith and Po-Shen Loh.
The AIMO Advisory Committee will support the development of the AIMO Prize, including advising on appropriate protocols and technical aspects, and designing the various competitions and prizes.
Simon Coyle, Head of Philanthropy at XTX Markets, commented:
“We are thrilled to complete the AIMO Advisory Committee with the appointments of D., Kevin, Leo, Lester and Peter. Together, they have enormous experience in machine learning and automated reasoning and are already bringing expertise and wisdom to the AIMO Prize. We look forward to announcing the winners of the AIMO’s first Progress Prize soon, and then publicly sharing the AI models to support the open and collaborative development of AI.”
Further information on the AIMO Prize
There will be a grand prize of $5mn for the first publicly shared AI model to enter an AIMO approved competition and perform at a standard equivalent to a gold medal in the IMO. There will also be a series of progress prizes, totalling up to $5mn, for publicly shared AI models that achieve key milestones towards the grand prize.
The first AIMO approved competition opened to participants in April 2024 on the Kaggle competition platform. The first progress prize focuses on problems pitched at junior and high-school level maths competitions. There is a total prize pot of $1.048m for the first progress prize, of which at least $254k will be awarded in July 2024, There will be a presentation of progress held in Bath, England in July 2024, as part of the 65th IMO.
For more information on the AIMO Prize visit: https://aimoprize.com/ or the competition page on Kaggle: https://www.kaggle.com/competitions/ai-mathematical-olympiad-prize/
Advisory Committee member profiles:
D. Sculley
D. is the CEO at Kaggle. Prior to joining Kaggle, he was a director at Google Brain, leading research teams working on robust, responsible, reliable and efficient ML and AI. In his career in ML, he has worked on nearly every aspect of machine learning, and has led both product and research teams including those on some of the most challenging business problems. Some of his well-known work involves ML technical debt, ML education, ML robustness, production-critical ML, and ML for scientific applications such as protein design.
Kevin Buzzard
Kevin a professor of pure mathematics at Imperial College London, specialising in algebraic number theory. As well as his research and teaching, he has a wide range of interests, including being Deputy Head of Pure Mathematics, Co-Director of a CDT and the department’s outreach champion. He is currently focusing on formal proof verification, including being an active participant in the Lean community. From October 2024, he will be leading a project to formalise a 21st century proof of Fermat’s Last Theorem. Before joining Imperial, some 20 years ago, he was a Junior Research Fellow at the University of Cambridge, where he had previously been named ‘Senior Wrangler’ (the highest scoring undergraduate mathematician). He was also a participant in the International Mathematical Olympiad, winning gold with a perfect score in 1987. He has been a visitor at the IAS in Princeton, a visiting lecturer at Harvard, has won several prizes both for research and teaching, and has given lectures all over the world.
Leo de Moura
Leo is a Senior Principal Applied Scientist in the Automated Reasoning Group at AWS. In his spare time, he dedicates himself to serving as the Chief Architect of the Lean FRO, a non-profit organization that he proudly co-founded alongside Sebastian Ullrich. He is also honoured to hold a position on the Board of Directors at the Lean FRO, where he actively contributes to its growth and development. Before joining AWS in 2023, he was a Senior Principal Researcher in the RiSE group at Microsoft Research, where he worked for 17 years starting in 2006. Prior to that, he worked as a Computer Scientist at SRI International. His research areas are automated reasoning, theorem proving, decision procedures, SAT and SMT. He is the main architect of several automated reasoning tools: Lean, Z3, Yices 1.0 and SAL. Leo’s work in automated reasoning has been acknowledged with a series of prestigious awards, including the CAV, Haifa, and Herbrand awards, as well as the Programming Languages Software Award by the ACM. Leo’s work has also been reported in the New York Times and many popular science magazines such as Wired, Quanta, and Nature News.
Lester Mackey
Lester Mackey is a Principal Researcher at Microsoft Research, where he develops machine learning methods, models, and theory for large-scale learning tasks driven by applications from climate forecasting, healthcare, and the social good. Lester moved to Microsoft from Stanford University, where he was an assistant professor of Statistics and, by courtesy, of Computer Science. He earned his PhD in Computer Science and MA in Statistics from UC Berkeley and his BSE in Computer Science from Princeton University. He co-organized the second place team in the Netflix Prize competition for collaborative filtering; won the Prize4Life ALS disease progression prediction challenge; won prizes for temperature and precipitation forecasting in the yearlong real-time Subseasonal Climate Forecast Rodeo; and received best paper, outstanding paper, and best student paper awards from the ACM Conference on Programming Language Design and Implementation, the Conference on Neural Information Processing Systems, and the International Conference on Machine Learning. He is a 2023 MacArthur Fellow, a Fellow of the Institute of Mathematical Statistics, an elected member of the COPSS Leadership Academy, and the recipient of the 2023 Ethel Newbold Prize.
Peter J. Liu
Peter J. Liu is a Research Scientist at Google DeepMind in the San Francisco Bay area, doing machine learning research with a specialisation in language models since 2015 starting in the Google Brain team. He has published and served as area chair in top machine learning and NLP conferences such as ICLR, ICML, NEURIPS, ACL and EMNLP. He also has extensive production experience, including launching the first deep learning model for Gmail Anti-Spam, and using neural network models to detect financial fraud for top banks. He has degrees in Mathematics and Computer Science from the University of Toronto.
About XTX Markets:
XTX Markets is a leading financial technology firm which partners with counterparties, exchanges and e-trading venues globally to provide liquidity in the Equity, FX, Fixed Income and Commodity markets. XTX has over 200 employees based in London, Paris, New York, Mumbai, Yerevan and Singapore. XTX is consistently a top 5 liquidity provider globally in FX (Euromoney 2018-present) and is also the largest European equities (systematic internaliser) liquidity provider (Rosenblatt FY: 2020-2023).
The company’s corporate philanthropy focuses on STEM education and maximum impact giving (alongside an employee matching programme). Since 2017, XTX has donated over £100mn to charities and good causes, establishing it as a major donor in the UK and globally.
In a changing world XTX Markets is at the forefront of making financial markets fairer and more efficient for all.

View original content:https://www.prnewswire.co.uk/news-releases/10-million-artificial-intelligence-mathematical-olympiad-prize-appoints-further-advisory-committee-members-302128542.html