Artificial Intelligence
From April 25 to 26 local time, the AI & Big Data Expo Global 2019 was held in Olympia, London. This is a two-day expo showcasing the next generation of technologies and strategies in AI and big data, attracting more than 4,000 relevant practitioners. Dr. Wei Cui, co-founder and chief scientist of Squirrel AI Learning, was invited to give a speech at the Expo and he also shared his insights into AI with senior executives from Darktrace, a UK cyber security company; SAP, the world’s third largest independent software provider; Reddit, one of the largest social platforms in the United States; and Just-Eat, a Danish company equivalent to “Meituan”.
The themes of this expo include: enterprise AI, AI and Internet of Things data analysis, big data business solutions and AI technology solutions.
Dr. Wei Cui from Squirrel AI Learning: How Does AI Provide Economical and Individualized Education for Every Family in China
Dr Wei Cui, chief scientist of Squirrel AI Learning, introduced the AI adaptive learning system independently developed by Squirrel AI Learning. This system can continuously monitor and evaluate students’ individual abilities, find their weaknesses in learning and allow students to progress at their own pace so as to improve their learning. The system provides optimized learning solutions and simultaneous counseling to maximize learning efficiency and improve students’ ability to acquire knowledge and skills.
For years, the lack of senior teachers and geographical problems have adversely affected the popularization of quality education in China. Squirrel AI hopes to train “super teachers” through AI and provide one-on-one tailored education for students.
In his speech, Dr. Wei Cui introduced the basic technologies used to build the system and carry out performance evaluation experiments. Squirrel AI Learning’s adaptive educational engine includes three layers of architecture: ontology layer, algorithm layer and interactive system. Content-focused, the ontology layer incorporates learning maps and knowledge maps. Squirrel AI Learning independently developed the technology to disassemble knowledge points at a super-nano level, making for more accurate determination of the knowledge points students are supposed to master. Take mathematics of junior high school as an example. Squirrel AI Learning can disassemble the 300 knowledge points into 30,000.
The algorithm layer includes content recommendation engine, students’ user portrait engine and target management engine. Based on user status evaluation engine and knowledge recommendation engine, Squirrel AI Learning will build a data model to detect the gaps of knowledge for each student accurately and efficiently and then recommend corresponding learning content according to these gaps.
The interactive system collects interactive data to learn more about students and improve the algorithm. Squirrel AI Learning cooperated with Stanford Research Institute to study the machine-student interactive system. Its self-developed MIBA student behavior data acquisition system won big award at the World Conference on AI.
In addition, the MCM system developed by Squirrel AI Learning can disassemble students’ model of thinking, capabilities and methods of learning and then provide training of these abilities and methods in a single subject according to students’ learning status.
By the beginning of this year, Squirrel AI Learning has set up nearly 2,000 learning centers in more than 300 cities across China with nearly 2 million registered student users. Last year, Squirrel AI donated 1 million free study accounts to underprivileged families to promote education fairness.
Marc Teerlink, SAP’s Global Vice President: How to Realize “Gold Rush” in the Era of AI
Marc Teerlink, SAP’s global vice president, talked about how enterprises adapt to the era of AI. The world is currently on the verge of a “gold rush” with AI. Teerlink’s speech is about how AI and machine learning bring wealth to enterprises as well as experience sharing by current industry leaders.
SAP estimates that by 2030, more than 60% of jobs will face great changes. About 51% of work will be automated but only 5% will be completely done by machine. Therefore, Teerlink prefers to call this era the era of “augmented intelligence” in which technology is used to enhance human’s ability to process information.
Teerlink said that partners using SAP machine learning software have translated algorithms into commercial profits. He cited one example: VALE, a Brazilian-based global mining company, used machine learning to optimize its procurement application process.
The current process is a purely manual one in which scattered information is distributed in multiple files and systems. As a result, 25-40% of the purchase requisitions are rejected every month due to errors, resulting in severe rework.
In the past few years, VALE has started to use SAP Leonardo open innovation framework based on design thinking and technology to define a re-conceived application process that provides an SAP Fiori application accessible from any device to help users complete the end-to-end process without logging into any back-end device systems.
Machine learning for image recognition is the core of this process. Image recognition algorithm is integrated into the application of SAP Leonardo machine learning so that maintenance technicians can recognize the serial number of the materials of any parts that need to be replaced by taking pictures of them. Even without Internet access, technicians can still take pictures of the parts and complete the purchase application process later.
Once the parts are identified, the application will connect to the back-end system and find the correct procurement process for the material, be it contract process or purchase requisition, and then the application will automatically complete the procurement requisition process and check whether the parts have been requested on the previous shift or exist in any nearby deposits.
This procedure streamlines the procurement application process, reduces the delivery cycle of procurement, reduces spare parts inventory, thus reducing working capital and improving labor efficiency.
Enterprises like VALE that have long engaged in AI have already tasted the sweetness. SAP observes that these enterprises generally have the following characteristics: the strategic center of C-level executives, increased competitive differentiation, new income and profitability, and strategies covering the whole field. They all view data as important assets.
Dave Palmer, Technical Director of Darktrace: How Does AI Affect Cybercrime
Darktrace is a British start-up in network security that mainly provides “corporate immune system” that can be deployed in company network to monitor network anomalies. Once suspicious behavior occurs within the network, Darktrace will remind IT managers and, when necessary, automatically trigger protection behavior to mitigate network attacks. Unlike traditional methods that rely on rules or signatures, this automated technology enables security teams to focus on high-value tasks and even to counter fast-moving automated attackers.
Dave Palmer believes that AI will greatly increase the impact of cyber crime on enterprises. Due to the open source environment of computer science and the introduction of various API & SDK by large companies, even people without relevant backgrounds can easily acquire and use AI technology such as face recognition and voice recognition, which greatly lowers the threshold of cyber crime.
Unlike planting a virus or malicious software in the system in the past, network attacks now take many forms and are more and more extensive. For example, stealing your data for blackmail, monitoring important meetings of competing companies, or modifying your data from the bottom to influence the decision-making of your superiors, etc.
Therefore, many companies are deeply engaged in network security protection. For example, Microsoft launched its cloud-based risk security detection tool in 2017 with which developers find bugs and other security vulnerabilities in software to be released or used. The tool is designed to fix bugs before software vulnerabilities occur.
Anand Mariappan, Senior Director of Reddit: Development History of Reddit Machine Learning
Anand Mariappan, senior director of Reddit in charge of search and machine learning engineering, reviewed the history, current projects and future direction of Reddit’s machine learning that covers data platforms, feed rankings, recommendations, user and channel similarities.
Reddit, the US version of “Tianya” and “Baidu Tieba”. According to the data released by Alexa, Reddit is the fifth largest website in the United States, ranking 14th in the world and even surpassing Facebook in traffic. Reddit currently has 330 million active users, nearly 140,000 active communities, 12 million posts and nearly 100 million comments per month. In February this year, Tencent invested $150 million into Reddit. Reddit is currently valued at $3 billion.
Reddit has been building and improving data pipelines over the past few years. Since 2014, it has been using Amazon S3 and Hive to gradually build a multilevel database architecture based on MIDAS, and now the architecture is based on Google’s BigQuery.
Reddit has 140,000 sub-Reddit, which can also be understood as channels. Recommending relevant channels to users is an important way to increase user participation, which was done through manual selection. Now deep learning takes the place of manual selection. Through deep learning, Reddie can directly gather all comments in a channel into a file and then use the end-to-end doc2vec model to train and get semantic information to assist in the matching.
Reddit also optimized the recommendation on the home page. It uses large-scale logistic regression algorithm to make personalized content recommendation based on parameters such as time, channel, user interest, and device.
Mariappan said Reddit is currently developing machine learning programs to optimize personalized models, and has achieved amazing results in the early development phase by using models on TensorFlow to improve the quality of content recommendation.
Ben Dias, Head of Royal Mail: From Zero to Data Science
Ben Dias, head of analysis and data science at Royal Mail, shared his experience of “from zero to data science” and summarized seven key points, hoping to help enterprises accelerate their progress in developing data science by providing practical skills, tools and technologies.
First, be prepared. Enterprises should first understand themselves and be fully prepared in areas of data processing, standard business intelligence analysis, underlying architecture and technology stack.
Second, lay more emphasis on retention of talents than recruitment. Don’t rush to look for talents outside the enterprise. Instead, enterprises should train and retain talents and nurture suitable office culture.
Third, don’t hire “super chicken”. Super chicken refers to highly talented and motivated employees. Margaret Heffernan, an expert in business management consulting, pointed out in a TedTalk that a team of geniuses will not be more efficient, but rather has disastrous performance. Successful teams do not need superstars but collaborative staff working based on consensus.
Fourth: Don’t put all eggs in one basket. Enterprises should comprehensively consider short-term benefits, medium-term considerations and long-term planning.
Fifth, adopt the model of Lean Startup. Lean Startup is a method of developing business and products, aiming to shorten product development cycle and quickly find out whether the proposed business model is feasible. This model is achieved through a combination of business hypothesis-driven experiments, iterative product release and proven learning.
Sixth & Seventh: You must change everyone and everything & apply scientific methods to everything.
Gilles Comau, Head of Just Eat AI: Challenges and Opportunities of Building Personalized Strategies.
Gilles Comau is Just Eat’s director of machine learning and AI. Just Eat, founded in 2001, is a take-out ordering website in Denmark. It provides applications to enable consumers to easily place orders and make payment. Now it has operations in many countries around the world. In 2014, Just Eat was successfully listed on the London Stock Exchange with a market value of $2.4 billion.
Comau’s speech is centered on the challenges and opportunities of building personalized strategies. Delivery services involves millions of similar but greatly different products. Delivery areas also have geographical limitations, which needs to be optimized through algorithms.
Just Eat’s big data analysis helps predict what kind of food users will order at a particular time. For example, big data generated by Just Eat enables analysts to predict which regions are most likely to order healthy food and which regions prefer food collection to delivery.
Results of big data analysis of users’ eating patterns and trends will be provided to restaurants to help them meet various needs and increase menu items. This can help them grow their business.
Just Eat has more than 60 million accounts and at least 7.5 million people have multiple accounts. Therefore, Just Eat needs to use data science to delete repeated accounts and link users with similar attributes.
The match between restaurants and users helps users find delicious food more conveniently. The restaurant’s attributes are mainly based on the food it mainly recommends, including the flavor, attributes, taste, and ingredients of food. User profile is determined by ordering habits, preferences, social attributes, trading habits, contact information, etc.
These attributes will help Just Eat build a two-dimensional and visual vector search space. When searching delicious food through key words, users can get what they want just by judging which vector their key words are the closest to.
Machine learning is also used to deliver orders to customers fast through prediction of driver paths and improvement of communication efficiency so as to deliver food fast, maintain correct delivery order and prevent lost delivery orders.
SOURCE Squirrel AI Learning
Artificial Intelligence
Cognitive Security Market Projected to Reach $134.26 billion by 2030 – Exclusive Report by 360iResearch
PUNE, India, April 26, 2024 /PRNewswire/ — The report titled “Cognitive Security Market by Component (Services, Solutions), Security Type (Application, Cloud, Cybersecurity), Application, Deployment Mode, Enterprise Type, Vertical – Global Forecast 2024-2030” is now available on 360iResearch.com’s offering, presents an analysis indicating that the market projected to grow from a size of $19.50 billion in 2023 to reach $134.26 billion by 2030, at a CAGR of 31.73% over the forecast period.
“The Global Rise of Cognitive Solutions Against Cyber Threats”
The field of cognitive security, leveraging the latest in artificial intelligence (AI), machine learning (ML), and data analytics, is reshaping the way physical and digital assets are protected from cyber threats. This innovative approach learns from user interactions with systems and data, enabling real-time threat detection and a more dynamic defense strategy. Across industries, including finance, healthcare, retail, and government, cognitive security applications, such as fraud detection and cyber defense, are becoming vital in navigating the complex threat landscape. Challenges in integrating with older systems and opportunities include advancements in AI and technology. Globally, the cognitive security market is witnessing rapid growth, driven by high American demand and significant investments in the Asia-Pacific region. In Europe, stringent regulations such as GDPR drive the demand for compliant solutions, while in the Middle East and Africa, the expanding telecom sector highlights the need for robust cybersecurity measures. This global momentum highlights the critical role of cognitive security in an interconnected world, ensuring businesses and governments can overcome cyber threats.
Download Sample Report @ https://www.360iresearch.com/library/intelligence/cognitive-security
“The Essential Role of Cognitive Security in Today’s Digital Age”
As digital transformation reshapes industries, the surge in data generation and intricate data management challenges have outpaced traditional cyber defense mechanisms. Cognitive security adept at processing and analyzing vast arrays of data in real-time, uncovering patterns and anomalies indicative of cybersecurity threats. This advanced approach enables proactive threat detection and swift response measures, significantly mitigating the risks of data breaches and cyber incidents. Cognitive security solutions adeptly handle diverse data types at unparalleled speeds, offering insights typically elusive to manual analysis by harnessing the power of automation. These systems excel at unveiling sophisticated attacks, skillfully hidden within normal network activities, and continuously evolve through machine learning. This perceptual adaptation is vital in a landscape where cyber threats rapidly transform, and digitalization ushers in new vulnerabilities. Cognitive security is a staunch supporter for organizations, ensuring their security policies remain in lockstep with the ever-evolving cyber threat environment and regulatory demands, thus fortifying digital defenses in an increasingly connected world.
“Enhancing Digital Security through Advanced Cognitive Technologies”
In an era where cyber threats are constantly evolving, the importance of robust digital security mechanisms cannot be overstated. The approach encompasses a suite of essential services that ensure the effective operation and continuous improvement of cognitive security systems. These include the meticulous deployment and integration of these systems into existing organizational structures, ensuring they work seamlessly with current technologies and protocols. Ongoing support and maintenance to keep these systems at the forefront of cyber defense, alongside training and consulting to empower staff with the knowledge and skills needed to optimize these advanced security solutions. Cutting-edge technologies include biometric recognition, digital signature authentication, real-time security analytics, and a unified platform managing security logs and data. Each component is vital role in creating a secure digital environment that identifies threats and enables swift, informed responses to protect organizational assets and data.
Request Analyst Support @ https://www.360iresearch.com/library/intelligence/cognitive-security
“International Business Machines Corporation at the Forefront of Cognitive Security Market with a Strong 8.44% Market Share”
The key players in the Cognitive Security Market include Google LLC by Alphabet Inc., Microsoft Corporation, Fortinet, Inc., International Business Machines Corporation, Cisco Systems, Inc., and others. These prominent players focus on strategies such as expansions, acquisitions, joint ventures, and developing new products to strengthen their market positions.
“Introducing ThinkMi: Revolutionizing Market Intelligence with AI-Powered Insights for the Cognitive Security Market”
We proudly unveil ThinkMi, a cutting-edge AI product designed to transform how businesses interact with the Cognitive Security Market. ThinkMi stands out as your premier market intelligence partner, delivering unparalleled insights with the power of artificial intelligence. Whether deciphering market trends or offering actionable intelligence, ThinkMi is engineered to provide precise, relevant answers to your most critical business questions. This revolutionary tool is more than just an information source; it’s a strategic asset that empowers your decision-making with up-to-the-minute data, ensuring you stay ahead in the fiercely competitive Cognitive Security Market. Embrace the future of market analysis with ThinkMi, where informed decisions lead to remarkable growth.
Ask Question to ThinkMi @ https://app.360iresearch.com/library/intelligence/cognitive-security
“Dive into the Cognitive Security Market Landscape: Explore 192 Pages of Insights, 760 Tables, and 28 Figures”
PrefaceResearch MethodologyExecutive SummaryMarket OverviewMarket InsightsCognitive Security Market, by ComponentCognitive Security Market, by Security TypeCognitive Security Market, by ApplicationCognitive Security Market, by Deployment ModeCognitive Security Market, by Enterprise TypeCognitive Security Market, by VerticalAmericas Cognitive Security MarketAsia-Pacific Cognitive Security MarketEurope, Middle East & Africa Cognitive Security MarketCompetitive LandscapeCompetitive PortfolioInquire Before Buying @ https://www.360iresearch.com/library/intelligence/cognitive-security
Related Reports:
Cognitive Radio Market – Global Forecast 2024-2030Cognitive Electronic Warfare System Market – Global Forecast 2024-2030Cognitive Data Management Market – Global Forecast 2024-2030About 360iResearch
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Artificial Intelligence
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]
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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
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
*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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