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Global AI in Computer Vision Market By Offering, By Machine Learning Model, By Function, By Application, By End User, By Regional Outlook, COVID-19 Impact Analysis Report and Forecast, 2021 – 2027

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New York, Aug. 31, 2021 (GLOBE NEWSWIRE) — Reportlinker.com announces the release of the report “Global AI in Computer Vision Market By Offering, By Machine Learning Model, By Function, By Application, By End User, By Regional Outlook, COVID-19 Impact Analysis Report and Forecast, 2021 – 2027” – https://www.reportlinker.com/p06131405/?utm_source=GNW
The AI in a computer or a computer-enabled robotic system makes it capable to manage information and generate results in decision making, learning, and solving problems. The results are produced in such a manner that they are quite similar to the thought process of humans.

Computer vision is one of the domains of computer science. It is focused on reproducing the intricacy of the human vision system. This enables the computers to recognize and process objects from the presented images and videos in a similar manner like humans. As a huge amount of data is generated on daily basis, it is important to have the application of computer vision. Therefore, it is the key catalyst for the growth of computer vision. The precision rates of object detection have been improving with superior and advanced hardware and algorithms in computer vision. The percentage of accuracy reached from 50% to 99%, so computers are responding more quickly to visual inputs as compared to humans.

The increasing need for automation and quality inspection, growing demand for computer vision systems in non-conventional applications are the major factors driving the growth of the AI in computer vision market. Moreover, the increasing need for ASICs is also expected to boost the growth of the market. Similarly, favorable policies and government initiatives to support industrial integration and adoption of AI into the edge devices are likely to create new growth avenues for the market players. However, increasing security concerns associated with cloud-based image processing and analytics are likely to restraint market growth.

COVID-19 Impact

The sudden outbreak of the COVID-19 has impacted various industries. Though, it had a negligible impact on AI in the computer vision market. The outbreak of the COVID-19 has caused a major impediment to the export-oriented economies from a regional point of view. It is due to the temporary closure of manufacturing units. For example, the automotive industry of Germany has been rigorously affected because most of the automobile trade in this region takes place with China and Italy. Apart from the issues related to imports and exports, the manufacturing industry growth in Germany has also been hampered by the shutdown of manufacturing plants and reduces speed in operations in order to curb the spread of COVID-19.

Offering Outlook

Based on Offering, the market is segmented into Software and Hardware. Hardware segment is further bifurcated across Processor, Memory and Storage. The software segment would exhibit highest growth rate during the forecast period. Software tools in combination with a suite of computer vision software help an individual to interface with a camera and a production line. It automatically carries out location analysis, image improvement, flaw detection, character recognition, symbol recognition, character verification, and several other functions.

Machine Learning Model Outlook

Based on Machine Learning Model, the market is segmented into Supervised Learning and Unsupervised Learning & Reinforcement Learning. Supervised learning segment would garner a higher share of the AI in the computer vision market in 2020. The increasing adoption of supervised learning in different healthcare applications mainly medical imaging and their usage in different sensors and devices that includes modern facial recognition algorithms are likely to promote the growth of this segment.

Function Outlook

Based on Function, the market is segmented into Inference and Training. Inspection, measurement, identification, and locating the product are the major applications of computer vision systems in diverse industries. Apart from it, AI-enabled vision systems have methods of developing novel applications like 3D model building, optical character recognition, retail, medical imaging, automobile safety, surveillance & traffic monitoring, morphing, and augmented reality.

Application Outlook

Based on Application, the market is segmented into Non-industrial and Industrial. The non-industrial segment procured the largest share of AI in the computer vision market in 2020. In the non-industrial market, the increasing demand for camera-enabled smartphones in both front and rear ends is boosting the AI in computer vision market, mainly in the consumer segment. Furthermore, the industrial segment is likely to grow at a higher rate due to the adoption of modern technologies.

End User Outlook

Based on End User, the market is segmented into Consumer Electronics, Automotive, Retail, Healthcare, Security & Surveillance, Manufacturing and Others. The Consumer Electronics segment would procure the largest share over the forecast period. There is a growing demand for AI-enabled computer vision systems mainly in consumer electronics like smartphones, laptops, and desktops. This factor is expected to drive the growth of the AI in computer vision market over the forecast period. Healthcare would exhibit the highest CAGR over the forecast period. It is attributed to fact that AI-enabled computer vision technology is finding its applications in radiology and medical imaging.

Regional Outlook

Based on Regions, the market is segmented into North America, Europe, Asia Pacific, and Latin America, Middle East & Africa. Based on region, North America would garner the largest share of the global AI in the computer vision market. The presence of key market players of AI technology including IBM (US), Google (US), Intel (US), Microsoft (US), NVIDIA (US), and Facebook (US) in this region is complementing the growth of the market. In recent years, government interventions have been increased due to rising concerns about the security of crucial infrastructure and sensitive data. This has resulted in the higher adoption of AI in computer vision, especially in security applications.

The major strategies followed by the market participants are Product Launches. Based on the Analysis presented in the Cardinal matrix; Microsoft Corporation, Intel Corporation, Amazon.com, Inc., Facebook, Inc., and Google, Inc. are the forerunners in the AI in Computer Vision Market. Companies such as NVIDIA Corporation, Basler AG, and Xilinx, Inc. are some of the key innovators in the market.

The market research report covers the analysis of key stake holders of the market. Key companies profiled in the report include NVIDIA Corporation, Intel Corporation, Microsoft Corporation, IBM Corporation, Qualcomm, Inc., Amazon.com, Inc., Xilinx, Inc., Google, Inc., Facebook, Inc., and Basler AG.

Recent strategies deployed in AI in Computer Vision Market

Partnerships, Collaborations, and Agreements:

Apr-2021: Intel teamed up with John Deere, an American manufacturing company. The companies announced a pilot program, which depends on AI & computer vision to identify defects in manufacturing regarding the welding process.

Oct-2020: Microsoft partnered with SoftBank, a Japanese multinational conglomerate holding company. This partnership aimed to allow developers to transmit data from Arm-based Internet of Things (IoT) devices to Azure Cloud and also enable developers to easily target a wide variety of Arm-based devices such as intelligent computer-vision-enabled cameras, AI gateways, connected vehicles, and intelligent appliances.

Sep-2020: Basler formed a collaboration with Axiomtek, a leader in designing and manufacturing industrial computer products. This collaboration aimed to provide integrated, all-in-one machine vision solutions for factory & machine automation. In addition, the companies also aimed to help manufacturers & system integrators instantly create their own quality inspection applications to make manufacturing processes effective and competitive.

Sep-2020: NVIDIA collaborated with HCL Technologies, an Indian multinational information technology services and consulting company. Under this collaboration, HCL joined NVIDIA Partner Network (NPN) to utilize the expanded opportunities in the Artificial Intelligence (AI) space. In addition, HCL also unveiled NEXT.ai, HCL’s AI Lab, aimed at upskilling engineers and architects using AI solutions all over the hardware & software technology stacks, which would improve their offerings to develop AI-led solutions for various HCL customers over various industry verticals.

Acquisition and Mergers:

May-2021: Basler announced a merger with Silicon Software, a globally recognized technology leader in the programming of FPGA processors. Basler acquired Silicon Software in 2018 and operated it as an independent company under the group structure. Some functions like logistics, production, sales, and technical support were merged after the acquisition, and now the other functional units are followed step by step.

Sep-2020: NVIDIA came into an agreement to acquire Arm Limited, a British semiconductor, and software design company. Through this acquisition, NVIDIA would integrate its leading AI computing platform with Arm’s vast ecosystem to make the premier computing enterprise for the age of artificial intelligence, fuelling the innovation and also expanding into big, high-growth markets.

Feb-2020: Facebook took over Scape Technologies, a computer vision startup. This acquisition aimed to support the social media site’s interest in next-generation techs like AI and virtual reality.

Product Launches and Product Expansions:

Apr-2021: Basler introduced a new AI machine vision platform. This platform is based on the artificial intelligence (AI) & machine learning (ML) services provided by Amazon Web Services. The platform involves a 5 MPixel Basler ace camera with GigE interface & the NVIDIA Jetson TX2NX module. Additionally, Basler’s pylon Camera Software Suite is integrated with the AWS Panorama Device SDK, allowing customers to implement and operate AI/ML applications on edge gadgets with device management and precision monitoring support.

Apr-2021: Xilinx launched the Kria portfolio of adaptive system-on-modules (SOMs), production-ready small form factor incorporated with boards. Kria adaptive SOMs are the latest way of bringing adaptive computing to AI & software developers, which are coupled with a comprehensive software stack and pre-built, production-grade accelerated applications.

Apr-2021: NVIDIA unveiled the next-generation AI-enabled processor for autonomous vehicles, NVIDIA DRIVE Atlan. This product is the latest addition to NVIDIA’s centralized compute roadmap for autonomous vehicles, and it integrates AI & software with enhancements in networking, computing, and security for extraordinary levels of performance & security.

Apr-202: NVIDIA launched a new class of NVIDIA-Certified System. It brings AI under the reach of companies, which operate their applications on industry-standard enterprise data center infrastructure. In addition, this new class involves high-volume enterprise servers from leading manufacturers, which can operate the NVIDIA AI Enterprise software portfolio and certified for VMware vSphere 7, which is known as the world’s most broadly utilized compute virtualization platform.

Mar- 2021: Facebook introduced SEER, a deep learning solution. This solution aimed to register images on the Internet regardless of curated and labeled data sets. Through the major improvements that are underway in natural language processing (NLP) that includes natural language interference, machine translation, and question answering, SEER utilizes an innovative billion-parameter, self-supervised computer vision model capable of learning from any online image.

Mar-2021: Xilinx expanded its UltraScale+ portfolio for markets with the latest applications, which need ultra-compact & intelligent edge solutions. The latest Artix and Zynq UltraScale+ devices can meet a broad range of applications under the industrial, healthcare, vision, broadcast, automotive, consumer, and networking markets.

Mar-2021: NVIDIA introduced new updates to CUDA-X AI Software. The NVIDIA CUDA-X AI is a deep learning library for all researchers & software developers to develop high-performance GPU-accelerated applications for recommendation systems, interactive AI, and computer vision.

Feb-2021: Xilinx unveiled a set of tools & services for AI-based video analytics, gathered within the Smart World banner. The core of this offering is the Xilinx Video Machine-learning Streaming Server (VMSS) that helps use cases that include virtual fencing, facial recognition, traffic monitoring, crowd statistics, and object detection.

Jan-2021: Intel released a facial recognition feature to its Intel RealSense portfolio. RealSense ID consists of an active depth-sensing camera along with a specified system-on-chip involving Intel’s specialized facial authentication neural network. This product includes the improvements in computer vision & neural networks that made facial recognition & authentication more comprehensive.

Dec-2020: Amazon Web Services released Amazon Lookout for Equipment, Amazon Monitron, the AWS Panorama SDK, the AWS Panorama Appliance, and Amazon Lookout for Vision. These five new machine learning services assist industrial & manufacturing clients to implement the intelligence in their production procedures to enhance operational efficiency, security, quality control, and workplace safety.

Jul-2020: Qualcomm Technologies introduced the Qualcomm QCS610 and Qualcomm QCS410 system-on-chips (SoCs) to the Qualcomm Vision Intelligence Platform. The QCS610 and QCS410 are developed to bring top-quality camera technology that includes robust artificial intelligence & machine learning features earlier only available to high-end devices, into mid-tier camera categories.

Scope of the Study

Market Segments covered in the Report:

By Offering

• Software

• Hardware

o Processor

o Memory

o Storage

By Machine Learning Model

• Supervised Learning

• Unsupervised Learning & Reinforcement Learning

By Function

• Inference

• Training

By Application

• Non-industrial

• Industrial

By End User

• Consumer Electronics

• Automotive

• Retail

• Healthcare

• Security & Surveillance

• Manufacturing

• Others

By Geography

• North America

o US

o Canada

o Mexico

o Rest of North America

• Europe

o Germany

o UK

o France

o Russia

o Spain

o Italy

o Rest of Europe

• Asia Pacific

o China

o Japan

o India

o South Korea

o Singapore

o Malaysia

o Rest of Asia Pacific

• LAMEA

o Brazil

o Argentina

o UAE

o Saudi Arabia

o South Africa

o Nigeria

o Rest of LAMEA

Companies Profiled

• NVIDIA Corporation

• Intel Corporation

• Microsoft Corporation

• IBM Corporation

• Qualcomm, Inc.

• Amazon.com, Inc.

• Xilinx, Inc.

• Google, Inc.

• Facebook, Inc.

• Basler AG

Unique Offerings

• Exhaustive coverage

• Highest number of market tables and figures

• Subscription based model available

• Guaranteed best price

• Assured post sales research support with 10% customization free
Read the full report: https://www.reportlinker.com/p06131405/?utm_source=GNW

About Reportlinker
ReportLinker is an award-winning market research solution. Reportlinker finds and organizes the latest industry data so you get all the market research you need – instantly, in one place.

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Artificial Intelligence

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

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

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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

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

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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.
 

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