Session 4: Strategy and Business
Grundlegend neue Technologien ermöglichen auch neue Geschäftsmodelle. Wo liegen hier die Chancen für innovative Unternehmen – auf der „Hardware“-Ebene, aber auch bei intelligenten Dienstleistungen? Die vierte und letzte Session des Hightech-Summit erörtert ökonomische und strategische Fragestellungen.
Folgende Wissenschaftler beschreiben Beispiele und Möglichkeiten für neue Geschäftsmodelle
Dr. Stephan Martin, Principal Business AI Strategist bei SAP, beschreibt das disruptive Potential von generativer KI in Wirtschaft und Industrie.
In Theorie und Wissenschaft ist die Digitalisierung weit vorangeschritten. Jetzt verschmelzen Bits und Atome. Damit entstehen auch neue, wissenschafts- und technikgetriebene Geschäftsmodelle. Marc Carrel-Billiard, Senior Managing Director von Accenture und Leiter der F&E-Organisation Accenture Labs, gibt einen hoch spannenden Einblick in diese Entwicklung.
Dr. Michael Pfeiffer, Head of AI Research beim Bosch Center for Artificial Intelligence (BCAI), Deutschland, skizziert den Weg von der KI-Forschung zu marktreifen Produkten, die aufgrund ihrer Komplexität immer neue Entwicklungs- und Konstruktionsverfahren erfordern.
Diese Entwicklung beantwortet Dr. Sameer Prabhu, Head of Market Development von MathWorks, USA, mit dem ‚Model Based Design‘, das z.B. zur Entwicklung von Chirurgie-Robotern, aber auch für die Planung kompletter smarter Fabriken genutzt werden kann.
Die Speaker und Vorträge dieser Session
Everyone is talking about Generative AI – its A(I)ge has just begun. Applications such as ChatGPT create new content like text, images or even code. But what does this technology bring to the enterprise? Generative AI is emerging as a powerful tool for various business processes and industries. Learn about SAP's thoughts on the future of AI in business.
Dr. Stephan Martin is a Principal Business AI Strategist at SAP. He works on the AI strategy of SAP and its holistic execution. Dr. Martin joined SAP in 2016 and has gathered broad experience in customer business process innovation with AI and Data Science. Prior to his career at SAP, he held various academic positions in applied mathematics. He was a temporary professor at RWTH Aachen in 2014 and a postdoctoral researcher at Imperial College London from 2012-2016.
The disruptive potential of Generative AI for Business and Industries
Everyone is talking about Generative AI – its A(I)ge has just begun. Applications such as ChatGPT create new content like text, images or even code. But what does this technology bring to the enterprise? Generative AI is emerging as a powerful tool for various business processes and industries. Learn about SAP's thoughts on the future of AI in business.
Hightech-Summit Session 4: Strategy and Business
At Accenture we believe that we have arrived at an exciting frontier of technology innovation for businesses, one where we’re not just digitizing but starting to put that digital foundation to work. Fusing digital and physical is not only generating new products and services, it’s the force behind a new era of scientific research. Next to Cloud, AI, and the metaverse, leveraging robotics will be a critical connection to converge between digital and physical realities as exist today, into a shared reality that will bring atoms and bits together.
This talk will give a glimpse into Accenture’s client-facing projects and investments in the underlying science and technology tools and capabilities, from digital engineering and manufacturing as new industry standard, to utilizing digital twins and robotics technologies. Those activities range across our R&D Labs, Open Innovation, Ventures, Liquid Studios and Next Gen Robotics Incubation groups, and are supported by a close cooperation with academia.
Marc Carrel-Billiard is a Senior Managing Director at Accenture. He is the Global Lead of Accenture Technology Innovation. In his role Marc leads:
- Accenture Labs, the dedicated R&D organization of Accenture
- Accenture Ventures, which bridges clients with eco-system partners including incubators, accelerators, corporate venture capitalists, start-ups, academia
- Accenture Technology Incubation Group, which incubates applied R&D into business solutions
- and Accenture Liquid Studios, which prototype and scale incubated solutions at clients all over the world
Each practice of Technology Innovation is a critical component of Accenture Innovation architecture, which helps our clients driving continuous innovation at scale in their organizations.
Marc has been with Accenture for more than 25 years and has worked across all the five industry groups we serve. Before taking on the leadership of Technology Innovation, Marc was the global lead for our Emerging Technology practice. He has held several global leadership roles within Accenture’s technology group, and he has worked across several cutting-edge areas of IT including voice recognition, knowledge-based systems, neural networks, and quantum computing.
Marc is one of a select group of Accenture certified Master Technology Architects. He is also a certified a Solution Architect and Select Quality Assurance director.
Marc has broad software engineering and delivery experience, particularly in areas such as component and object-oriented technologies. Before joining Accenture in 1998, Marc was part of IBM Global Services where he published several Marc holds a MS of Computer Sciences from Institut d’Informatique d’Enterprises / CNAM - France (Minor: Mathematics)
Marc was born and grew up in Savigny s/Orge, France. Marc is married with three grownup kids. After living in various world places (USA, Netherlands, …) Marc now lives in the South of France with his wife.
Before joining Accenture in 1998, Marc was part of IBM Global Services and has published several articles and books from 1985 to 1998.
Robotics @ Accenture – applying leading edge robotics research to solve concrete client problems
At Accenture we believe that we have arrived at an exciting frontier of technology innovation for businesses, one where we’re not just digitizing but starting to put that digital foundation to work. Fusing digital and physical is not only generating new products and services, it’s the force behind a new era of scientific research. Next to Cloud, AI, and the metaverse, leveraging robotics will be a critical connection to converge between digital and physical realities as exist today, into a shared reality that will bring atoms and bits together.
This talk will give a glimpse into Accenture’s client-facing projects and investments in the underlying science and technology tools and capabilities, from digital engineering and manufacturing as new industry standard, to utilizing digital twins and robotics technologies. Those activities range across our R&D Labs, Open Innovation, Ventures, Liquid Studios and Next Gen Robotics Incubation groups, and are supported by a close cooperation with academia.
Hightech-Summit Session 4: Strategy and Business
While the whole world is amazed by the rapid progress and new opportunities through AI, there is still little trust in AI for safety critical applications in the real, physical world. Whether in automated driving, robotics, IoT, manufacturing, or quality control, the key enabling technologies are safe and robust AI methods for perception and planning. In my talk I will present recent research results at Bosch, in which we try closing the gap between innovative AI research on benchmark data, and the demands of the real-world applications. Crucial ingredients are the synthesis of realistic data for corner cases, detection of outliers in the data and of model weaknesses, and finally training and deployment of neural networks that run reliably and with high performance on constrained, embedded hardware platforms. The combination of deep domain knowledge and safety aspects, combined with cutting edge methods research is the key to success for industrial applications of AI.
Michael Pfeiffer is the Head of AI Research at Bosch Research and the Bosch Center for Artificial Intelligence (BCAI) in Rennigen. BCAI is the leading AI research lab in the European industry, and works in fields such as perception for automated driving, reinforcement learning, embedded AI, dynamics modelling, manipulation robotics, neuro-symbolic AI, or natural language processing, targeting real-world applications in the broad product spectrum of Bosch. BCAI is closely collaborating with top academia worldwide, including Carnegie Mellon University, Tsinghua University, Cyber Valley, or the University of Amsterdam. From 2018 to 2021 Dr. Pfeiffer was a senior manager for embedded deep learning at BCAI. Prior to joining Bosch in 2016 he was a group leader at the Institute of Neuroinformatics at the University of Zurich and ETH Zurich. He holds an undergraduate degree in Technical Mathematics and a PhD in Computer Science from Graz University of Technology in Austria. In his research Michael Pfeiffer has combined machine learning and computer vision with insights from computational neuroscience. His research has resulted in novel concepts for training spiking neural networks, allowing fast and efficient applications for event-based vision and neuromorphic engineering. At Bosch his research focus has been on novel deep-learning based concepts for processing automotive radar data, and on developing hardware-aware automated machine learning tools and concepts that allow efficient implementations of powerful deep learning algorithms on embedded hardware.
The opportunities and challenges of AI in the physical world
While the whole world is amazed by the rapid progress and new opportunities through AI, there is still little trust in AI for safety critical applications in the real, physical world. Whether in automated driving, robotics, IoT, manufacturing, or quality control, the key enabling technologies are safe and robust AI methods for perception and planning. In my talk I will present recent research results at Bosch, in which we try closing the gap between innovative AI research on benchmark data, and the demands of the real-world applications. Crucial ingredients are the synthesis of realistic data for corner cases, detection of outliers in the data and of model weaknesses, and finally training and deployment of neural networks that run reliably and with high performance on constrained, embedded hardware platforms. The combination of deep domain knowledge and safety aspects, combined with cutting edge methods research is the key to success for industrial applications of AI.
Hightech-Summit Session 4: Strategy and Business
Robotics and AI are laying the foundation for breakthroughs in the industry and society by realizing smart factories, advancing healthcare, transforming mobility and more. Growing system complexity and expected faster design iterations are concomitants that are best addressed through the systematic use of models and data – known as Model-Based Design. This talk highlights how the same foundational principles of Model-Based Design can be applied across flexible manufacturing, surgical robotics, and autonomous driving. This allows reusing experience and sharing best practices across these different domains resulting in faster realization of the benefits from these transformative technologies.
As the Head of Market Development, Sameer manages a worldwide team of market development managers who lead the effort to foster the adoption of MathWorks products for Technical Computing and Model-Based Design across different market segments.
He has over thirty years of experience applying MathWorks products in various application areas and, prior to joining MathWorks, Sameer has engaged in the research and development of complex control systems through his work at Visteon, Caterpillar, and Tata Motors. His efforts have been documented through United States patents and in global publications.
Sameer has a Bachelor’s Degree in Mechanical Engineering from the University of Mumbai and received his Ph.D. in Mechanical Engineering from Duke University, specializing in robotic controls and artificial intelligence. He also holds an MBA from the University of Michigan.
Realizing Smart Factories, Surgical Robots, and Sustainable Mobility with Model-Based Design
Robotics and AI are laying the foundation for breakthroughs in the industry and society by realizing smart factories, advancing healthcare, transforming mobility and more. Growing system complexity and expected faster design iterations are concomitants that are best addressed through the systematic use of models and data – known as Model-Based Design. This talk highlights how the same foundational principles of Model-Based Design can be applied across flexible manufacturing, surgical robotics, and autonomous driving. This allows reusing experience and sharing best practices across these different domains resulting in faster realization of the benefits from these transformative technologies.
Hightech-Summit Session 4: Strategy and Business
Session-Chair
„Strategy and Business” wird von Prof. Alin Albu-Schäffer, DLR – Deutsches Zentrum für Luft- und Raumfahrt: Institut für Robotik und Mechatronik, als Session Chair moderiert.
Technologien haben das Potenzial, Menschen zu unterstützen und unsere Lebensqualität zu verbessern. Es ist jedoch unerlässlich, Technologien so zu gestalten, dass der Nutzen für die Vielen und nicht für die Wenigen im Vordergrund steht. Fragen der sozialen Gerechtigkeit und Gleichberechtigung müssen in den Mittelpunkt der Technologieentwicklung rücken, insbesondere in Bereichen wie KI und Robotik. Dazu müssen wir die interdisziplinäre Zusammenarbeit zwischen den Sozialwissenschaften und der KI-Forschung fördern und soziale, ethische und politische Fragestellungen bereits bei der Technologieentwicklung integrieren.