German Research Center for Artificial Intelligencenews 012021 Download this issue 7 4 e u s s i I K F D 1 2 0 2 © / 1 5 2 2 - 6 9 1 2 - n s s i Ten Years of INDUSTRIE 4.0 AI in Medicine and Medical Technology AI Ecosystem for Agriculture DFKI Talk with Prof. Wolfgang Wahlster New DFKI Branch Office in Lübeck Agri-Gaia Brings Smart Tech to the Fields

03 L A I R O T I D E 1 2 0 2 / 1 S W E N I K F D INDUSTRIAL AI, NATIONAL INITIATIVES, AND INTERNATIONAL COOPERATION The first article to use the term INDUSTRIE 4.0 was co-authored by Prof. Kagermann, Prof. Lukas, and Prof. Wahlster and was published on April 1, 2011. The concept spread rapidly and was taken up by major industry players and by small and medium-sized enterprises. New, flexible "Smart Factories" have been built and existing plants have been retrofitted to make them compatible with INDUSTRIE 4.0 concepts. Essential in all of this was the application of industrial AI. The semantic product memory, the virtual representation of products and manufacturing environments – keyword: digital twins – ensure that the production of even the smallest lots is economically viable (p. 6). In the second wave of the 4th Industrial Revolution, AI systems use digital data to create new value chains and innovative business models. Flexible manufacturing systems are moving forward with hybrid teams and the advances in collaboration among people and machines (p. 16). DFKI presents projects, software, and research prototypes to demonstrate how this all works at the Hannover Messe Digital Edition 2021 (p. 12). The ray-tracing system, which originated at Saarland University and further developed at DFKI, won the "Technology Oscar" from the Academy of Motion Picture Arts and Sciences. Based on simulated beams of light, the system makes it possible to correctly depict surfaces with all their shades and re- flections (p. 35). DFKI continues to expand in northern Germany with a focus on research on AI in medicine. The state of Schleswig-Holstein established a branch office with three new research departments in the city of Lübeck, and provided a funding amount of three million euros (p. 20). Medicine is also one of the fields of application being studied at a new research unit in the city of Oldenburg. The main subject of re- search is the interaction of people with AI systems (p. 18). Additional initiatives and collaborations have emerged on a national and international level. The Eu- ropean Space Agency ESA and DFKI have founded a joint research laboratory at DFKI-Kaiserslautern with the aim of developing new AI technologies and applications for use in commercial space travel (p. 27). The Federal Office of Criminal Investigation (BKA), Rhineland-Palatinate's state Office of Crim- inal Investigation (LKA), and DFKI have launched a transfer lab to develop AI technologies for use in police matters (p. 30). DFKI is also making plans to set up a branch in Japan. Osaka Prefecture University (OPU), which has links with DFKI, has agreed to the procedure for opening a DFKI research laboratory (p. 29). Another suc- cess in the internationalization of INDUSTRIE 4.0 in Japan is the founding of the Flexible Factory Partner Alliance – FFPA – organized with the aim of promoting standardization of the coordination and control systems for wireless technologies in manufacturing (p. 28). Prof. Dr. Antonio Krüger Prof. Dr. Antonio Krüger Prof. Dr. Prof. h.c. Andreas Dengel Prof. Dr. Dr. h.c. Frank Kirchner Prof. Dr. Dr. h.c. Frank Kirchner Prof. Dr. Philipp Slusallek

05 T N E T N O C 1 2 0 2 / 1 S W E N I K F D 34 Innovative Learning Environment for Psychomotor Skills – Project MILKI-PSY Started 35 Prestigious „Sci-Tech Oscar“ Goes to Three Former Computer Science PhD Students from Saarbrücken 36 New Technologies to Support Post-Editing of Machine Translations Imprint Issue 47, April 2021, ISSN 2196-2251 Published by German Research Center for Artificial Intelligence GmbH (DFKI) Editorial staff Heike Leonhard, Christof Burgard, Reinhard Karger, Armindo Ribeiro, Stephan Lehberger Editorial address Saarland Informatics Campus D3 2, Stuhlsatzenhausweg 3, 66123 Saarbrücken, Germany E-Mail news@dfki.de Phone +49 681 85775 5390 Translation team Glenn Peach, Armindo Ribeiro, Sylvia Krüger, Heike Leonhard Photos DFKI, unless otherwise noted Layout, Graphics Christof Burgard Production One Vision Design Responsible Heike Leonhard, M.A. Frequency of publication Semi-annual News online www.dfki.de/en/dfki-news 37 CEF AT Tools and Services – Translation Tools from and for Europe 38 Transfer of Control Among Autonomous Agents – TRACTAT Project Ends Successfully 39 DFKI Staff Interview with Dr. Tim Schwartz 40 News in brief 42 Company Profile 31Content

07 1 2 0 2 / 1 S W E N I K F D Prof. Wahlster, please review for us the evolution of the concept and designation of the word mark “INDUSTRIE 4.0.” As a member of the German government‘s Industry-Sci- ence Research Alliance from 2006-2013, my job was to support Germany‘s High-Tech Strategy and develop specific future projects. Together with my colleagues Henning Kagermann and Johannes Helbig in the Com- munication Promoters Group, we were responsible for innovation in the Information and Communication Tech- nologies (ICT). Under the motto “Ignite Ideas,” Annette Schavan, Germany‘s former Minister for Education and Research, asked us to define ambitious, forward-looking projects with high economic and social potential that would bring German research strengths to bear for the practical benefit of major industries. In September 2010, the Promoters Group decided to define a future project based on scientific trends like the Internet of Things, Internet of Services, and Cy- ber-Physical Systems (CPS). We positioned the pro- ject in the area of cyber-physical production systems, since at that time every second job in Germany de- pended directly or indirectly on the manufacturing of physical products. By December 2010, at a meet- ing at the German Academy of Science and Engineer- ing (acatech) in Berlin with my colleagues Kagermann and Lukas, we were of the opinion that the term “cy- ber-physical production systems” was too unwieldy a name for the future project, so I suggested the intui- tively understood “Industrie 4.0.” The designator “4.0” represents the 4th Industrial Revolution, while simul- taneously indicating the essential role software plays (in the manner of naming versions in the IT branch). When did the planning for the future project officially begin and when was the first use of the term at a major trade event? In January 2011, the Research Alliance determined that a future project titled “INDUSTRIE 4.0: Germany as the lead provider of cyber-physical systems by 2020” should be developed. Although the acatech study at the time, directed by our colleague Manfred Broy, identified many important application areas, Mr. Kagermann, Mr. Lukas, and I chose to focus on applications in the manufac- turing industry – a good decision, as evidenced by the success of INDUSTRIE 4.0. The opening event of the Hannover Messe on April 3, 2011 was attended by the Chancellor Angela Merkel, numerous politicians, and approximately 3,000 industry leaders, and © Deutsche Messe I was able to introduce the term “Industrie 4.0” for the first time to important decision-makers in my speech regarding the work of the Hermes Award jury. “…To remain a center of manufacturing today implies becoming fit for the 4th Industrial Revolution which is powered by the Internet. The Internet of Things establishes a bridge be- tween the virtual and tangible worlds. For indus- trial manufacturing, this approach represents a paradigm shift. An unfinished product controls its own production processes, monitors the rel- evant environmental parameters using embed- ded sensors, and initiates the appropriate cor- rective actions in the event of a malfunction – all simultaneously as an observer and an actor…” Wolfgang Wahlster The Chancellor spontaneously picked up on the term in her subsequent opening remarks. This opened the flood gates and the future project was the topic of discussion at the evening dinner, with intense interest and some in- itial skepticism by traditional equipment manufacturers. For a strategy meeting at acatech in June 2011, I asked DFKI graphic specialist Renato Orsini to prepare a graph- ic according to my conception of the four stages of the Industrial Revolution. Today, it is used in thousands of variations, even in textbooks and, unfortunately, more often than not, plagiarized. Together with this catchy graphic, the word mark “INDUSTRIE 4.0” became the catalyst for the exponential spread of the concept.

09 1 2 0 2 / 1 S W E N I K F D for each physical object and used for control impuls- es. New factories today are always designed as flexible factories. The days of having a factory designed for only one specific product line are truly over. For example, with the volatility of the mobility revolution, every factory for vehicle engines must be convertible to alternative power trains at minimum time and financial expense. The traditional automation pyramid has been eliminat- ed in favor of heterarchical service-oriented architec- tures that support distributed production. Today, quite a few recently built “smart factories” are already implementing many of the basic principles of INDUSTRIE 4.0: Plug & Produce, cycle independent ma- trix-production architectures with configurable produc- tion units and fast changeover times even for the smallest lot sizes with a high degree of product individualization, variable intra-logistics in combination with real-time production planning as well as location-based services for all workers, production equipment, and products in production. Factory floor positioning systems have been vastly improved using AI-based visual SLAM (Simulta- neous Localization and Mapping) methods for mobile systems like autonomous forklifts. The highly parallel execution of neural processes on very powerful graph- ics cards (GPU computing) has significantly improved landmarks recognition, necessary to give mobile robots the freedom to navigate. You often speak of “industrial AI” as a primary research focus in Germany. What are the areas of application and how does Germany compare interna- tionally on the topic of industrial AI? AI is spearheading a second wave of digital manufactur- ing because the mass data generated in manufacturing can only be exploited and monetized with AI in new value creation processes. The American and Chinese Internet companies are leading the way in the application of AI as hyperscalers in the area of B2C. Germany also has outstanding R&D capabilities in industrial AI, as well as in actual practice. Industrial AI is not about ad place- ment or product recommendations, but rather about innovative production, processes, and business models. Consider the systems from global suppliers like Bosch, ZF, Continental, or the SMEs like Harting, Claas, and Sar- torius as well as SAP and Software AG, primarily built to provide the neural pathways of a company, but are actually making corporate knowledge digitally availa- ble and accessible for business development. Let's not forget that German OEMs like VW, BMW, and Daimler, are also driving industrial AI as they make greater use of AI systems and convert their factories worldwide to INDUSTRIE 4.0 step by step. The four stages of the Industrial Revolution. © DFKI, 2011 Was it possible for Germany to achieve the goal of becoming the leading supplier of components for the implementation of cyber-physical production systems by the year 2020 as announced in 2011? Yes, our traditional factory suppliers like Siemens, Bosch-Rexroth, and ABB, but even more so, our many hidden champions among the SMEs have contributed the first solutions and still maintain a lead of one or two years. You will not find a smart factory anywhere in the world not equipped with German companies’ software and hardware components. The challenge by American companies with the “Indus- trial Internet” was too short-sighted. Although upgrad- ing the networking and communication infrastructure is a prerequisite, this in itself is by no means the answer for INDUSTRIE 4.0. Also, an IoT platform does not pro- vide a viable solution for disruptive plant models if they lack the semantic coding of domain knowledge by ex- cellent engineers and skilled workers, intelligent con- trols, and digital twins. Perhaps more important are the solutions for retrofit- ting existing factories with networked IoT boxes, dis- tributed sensor technology, and intelligent control sta- tions based on digital twins. Specializing in the digital enhancement of high precision, robust classic produc- tion plants has made German medium-sized compa- nies highly sought-after suppliers, especially in China. Mobile tablets, smartphones, smartwatches, and data glasses have also enabled a new generation of work- er-specific cognitive assistants, resulting in significant increases in productivity, product quality, job satisfaction, safety, and transparency. People remain at the center, continue to learn throughout their lives, feel no loss of control, and gain more enjoyment from their work.

11 1 2 0 2 / 1 S W E N I K F D G A E S V © The semantic factory memory developed in the SmartF-IT project (2013-2016) forms the basis for intelligent worker support in INDUSTRIE 4.0 factories. The pandemic experience has taught us that we must de- velop solutions to avoid breaks in supply chains or produc- tion stoppages due to short-term staff shortages. The latest “home office” technologies are little help here; rather, “home workbenches” are required: software solutions with remote access to cyber-physical systems, including teleoperation with physical avatars to allow the mobile control, mainte- nance, and repair of factories. In addition to these technological innovations, the next decade still requires the support of governments and trade unions. Successful value creation still requires cooperation at the platform level in the next legislative period if we are to reap the lasting economic and social benefits of the 4th industrial revolution started in Germany. The use of digital training data for machine learning systems means that AI systems will be used not only for predictive maintenance, which is already widespread, but increasingly for incremental quality control, mostly in combination with optical sensors. The goal of the next phase of INDUSTRIE 4.0 is AI-based, zero-defect production. The new generation of smart factories will have a self-learning capability and mod- ular long-term autonomy, in addition to extreme flexibility. These characteristics will guarantee highly robust production, occupational safety, and a high level of resource efficiency. Capability-based production architecture will ensure ex- pandability and flexibility in the next stage of INDUSTRIE 4.0. Edge devices with high bandwidth and the guaranteed low latency of 5G will be interconnected with private 5G-cam- pus networks to a local edge cloud, which then meets re- al-time factory requirements. Hybrid teams of workers and collaborative robots with vari- ous capabilities will create a new type of team robotics, with human-machine interaction guided by human specialists at the center working with robots in tandem, hand-in-hand to solve complex manufacturing tasks. Data infrastructures will take into account industry require- ments and data sovereignty, distributed /multi-cloud and edge support, as well as the provision of services. For exam- ple, for the medium-sized agricultural and food industry, the Agri-Gaia consortium managed by DFKI is developing an AI ecosystem for food production within the concept of INDUS- TRIE 4.0 based on the reference architecture of GAIA-X. The automotive industry, in contrast, has completely different requirements for a data infrastructure based on GAIA-X to implement INDUSTRIE 4.0 in a manufacturing plant. What are the most important success factors for INDUSTRIE 4.0 in the second half or, the next ten years? Research and innovation must not let up in the next phase of this 4th industrial revolution. Investments must continue, particularly in industrial AI as the second wave of the digital transformation. The enormous potential of INDUSTRIE 4.0 is far from exhausted. Interoperability in terms of software and hardware components will play a decisive role, espe- cially to ensure international market access for German SMEs and start-ups. Standards, norms, and certifications are essential drivers for interoperable solutions. Germany must take on a pioneering role in this, while also focusing on the resilience and secu- rity of the solutions offered. Ultimately, we must strive for the right balance between greater digital sovereignty and providing reliable and resilient solutions as a leading indus- trial supplier for global markets.

13 1 2 0 2 / 1 S W E N I K F D AdEPT BIONIC Augmented Reality and AI-based Learning, Teaching, and Collaborating Intelligent Sensor Networks Reduce Physical Stress CHIM CLAIRE Innovation Network Chatbots at the Museum AI Made in Europe CoMem AI to Assist Daily Work in Companies Cyber-Physical Systems Verification and Virtual Prototyping for RISC-V-Systems Franco-German Cooperation in AI DFKI4planet Inria (Institut national de recherche en informatique et en automatique) and DFKI AI for Environment and Sustainability European Language Grid (ELG) EVAREST Scalable Cloud Platform for Multilingual Europe Development and Utilization of Data Products in Food Industry IIP-Extrem InGewA Individualized Implants and Prosthetics for the Lower Extremities The Integrated Trade Tax Wizard (available in German only) Innovative Retail Laboratory (IRL) KI-Campus Application-Oriented Research for the Retail of the Future The Learning Platform for Artificial Intelligence Production Level 4-Demonstrator Robotics Innovation Center The World's First Production Level 4 Demonstrator Intelligent Robotics - for the Earth, the Space and the Human Smart Construction SPAICER Artificial Intelligence in Construction Smart Resilience Services in the Manufacturing Industry TexaS TRACTAT, CAMELOT, RICAIP Construction Kit for Multifunctional Textile-adapted Electronic Systems Transfer of Control in Distributed INDUSTRIE 4.0 Use Cases Xaines Explaining AI with Narratives

DFKI’S CPS DEPARTMENT IN BREMEN DFKI’S CPS DEPARTMENT IN BREMEN DEVELOPS VERIFICATION MEASURES DEVELOPS VERIFICATION MEASURES AND EARLY TESTING OF SOFTWARE AND EARLY TESTING OF SOFTWARE FOR RISC-V-BASED SYSTEMS FOR RISC-V-BASED SYSTEMS k c o t S e b o d A © 15 1 2 0 2 / 1 S W E N I K F D that simulate software representing the physical chip so that software can be created for the hardware that does not yet exist. However, such a prototype is not yet de- veloped for RISC-V. Project VerSys (short for “Consistent verification platform for early stage software develop- ment of RISC-V-based systems”) is designed to remedy this problem. The goal is an open-source RISC-V platform implemented in SystemC that is scalable, modular, and correct. The platform is easily adapted to user requirements and can be used to test software on a virtual RISC-V chip. Future development of the platform with the help of industry partners will make it applicable for industry use. The need for a verification platform for early soft- ware testing is apparent, as evidenced by the strong in- terest in the planned platform on the part of the industry. More information https://riscv.org Contact Prof. Dr. Christoph Lüth Research Department Cyber-Physical Systems christoph.lueth@dfki.de +49 421 218 59830 Whether smart homes, smartphones, autonomous ve- hicles, or the manufacturing of tomorrow – controls for future systems require powerful computer chips. The sys- tems that run on these computer chips are mostly the product of closed-source development and marketed under the “System on Chip (SoC).” However, the trend is moving in a different direction: In addition to open- source software like the Linux operating system, open- source architecture for hardware is also enjoying increasing popu- larity. Today, RISC-V processors (Reduced Instruction Set Computer) are leading the way and, under an open-source license, these can be free- ly designed, manufactured, and distributed. The RISC-V hardware architecture was developed at the Universi- ty of California Berkeley in 2010 and has been met with growing interest in all manufacturing sectors ever since. The functional range of application for these chips and software includes not only Smart Homes and the Inter- net of Things, but also the automotive, communica- tions, and production branches. The open instruction set architecture provides many advantages: The lack of patent fees makes RISC-V attractive, but it is its stand- ardization, expandability, and manufacturer independ- ence that make it so impressive. These characteristics make the processors particularly future-proof. Early de- tection of security gaps is possible thanks to the open architecture and suitable verification measures can be implemented along the entire value-adding chain. To- gether with other consortia partners from industry and research in the joint HEP project, DFKI’s Cyber-Physical Systems (CPS) department, under the direction of Prof. Dr. Rolf Drechsler, is studying what these measures must look like and is implementing a development process – a hardware security module – using a case study from the automotive environment. Another important question for the acceptance of the new architecture is how software can be written now for the chips of the future without having to wait for their pro- duction. This question is answered by virtual prototypes

However, there is still a long way to go before this pro- jected revenue is reached. The operating speed and cost of the collaborative robot arms are major factors. But several questions stand out above all else: How do we guarantee that humans and robots can interact safely? How can we avoid crush injuries, impact injuries, and haz- ards from sharp-edged materials? The research team of Dennis Mronga is working on the answers to these ques- tions at the Human-Robot-Collaboration (HRC) Labs of DFKI-Bremen. One obvious consideration for safe interaction is the de- sign of the robot: An angular design increases the risk of injury and a heavyweight may lead to crushing and im- pact injury. Ideally, a rounded and lightweight robot arm can be designed. But, the role played by humans must also be considered: adequate training of staff is impor- tant to counter the fear and uncertainty in dealing with a robot colleague if we are to ensure safe cooperation in a hybrid team. Robot arms will still be equipped with programmed com- pliance, which ensures the system can react to external influences. Similarly, the arm will interrupt its motion if it encounters resistance – something like a human hand. But, a collaborative robot can react to humans even without physical contact: motion sensors allow it to avoid colli- sions and to reliably detect humans even from a distance. “Probably the safest solution would be a skin of proximity sensors for the robot arm, which provides absolute con- tact avoidance – but, in many situations, the human must be able to control the arm,” explained Dennis Mronga. 17 1 2 0 2 / 1 S W E N I K F D brain waves can detect fatigue or overwork, for exam- ple, triggering the implementation of an increased level of safety. The method is to be released as a cloud-based service for cognitive occupational safety. However, a few more steps are necessary before the wide use of robots in hybrid teams becomes a reality: Un- like segregated assembly-line robots that are equipped with a few sensors and can only adapt their activities in a limited way, the collaborative systems require a lot of environmental information, which is processed at high speeds and incorporated in their planned movements. And, unlike in the classic “Sense-Plan-Act-Methodology,” the robot has to adapt in real-time to operate alongside humans in a dynamic environment. The two-armed KUKA system at the HRC Lab is used in assembly scenarios such as in handling tools. While the safety issue affects most systems and manu- facturing plants, the collaborative robots of the future will have an attribute that promises a key advantage when working in hybrid teams, i.e., the ability to respond in- telligently to their surroundings and make autonomous decisions. Artificial intelligence enables control meth- ods that intuitively respond to humans and reduce risk through real-time processing of sensor data. Contrary to common beliefs, autonomous systems can be taught not to act against humans but rather to actively protect them by moving away. Several AI technologies already exist for this purpose. Nevertheless, hybrid teams make sense if the complex- ity of the tasks is already manageable for the robot: For example, if instead of a gripper arm – which is one of the most complicated actions for robot arms – a screw- ing function is sufficient, more capacity can be used for safety. The safer and more flexible the systems become, the greater the potential away from the assembly lines – whether as a spontaneous helper in the small business, or for ergonomic relief with a contorted assembly. “A robot arm does not need to be able to do everything before it starts to relieve people ergonomically or to support them with monotonous tasks,” said Dennis Mronga. In addition to considerate movements, collaborative ro- bots can use other means to increase safety in the hybrid team. For example, light signals indicate how or where the system will move next. But things are more complex for the research team of Dr. Elsa Kirchner: Project KAMeri aims to measure the cognitive state of the human using an EEG headset and then use this data to adjust the be- havior of the collaborating robotic systems. The captured More information www.dfki.de/ric Contact Dennis Mronga Research Deptartment Robotics Innovation Center dennis.mronga@dfki.de +49 421 17845 6560

19 1 2 0 2 / 1 S W E N I K F D z r a B l e a h c M © i CT scan (left) and a so-called “ground-glass opacity” (center) are used to detect SARS-CoV-2 infections as well as other acute and chronic illnesses – the AI process marks the area on which the diagnosis was based on a so-called “heatmap” (right). Together with the Competence Center AI for Environment and Sustainability (DFKI4planet) founded in 2020, several projects for the European data infrastructure GAIA-X, and a series of successful ventures with regional business and science, this latest expansion strengthens confidence in the belief that the lab will become a full-fledged DFKI site in its own right within a few years. “I am very pleased that Daniel Sonntag, an accomplished AI researcher with many years of experience and a home-grown DFKI talent, is taking over as director. DFKI has an excellent partner for forward-looking AI research in the state of Lower Saxony: the state and its inhabit- ants create the ideal cooperative work environ- ment, true to our motto “Human-Centric AI.” Prof. Dr. Antonio Krüger, CEO, DFKI More information dfki.de/iml Contact Prof. Dr. Daniel Sonntag Head of Research Department Interactive Machine Learning daniel.sonntag@dfki.de +49 681 85775 5263 In addition to the pAItient and Ophthalmo-AI projects, which consolidate the research from DFKI-Saarbrücken, the latest success of Professor Sonntag’s research team relies on image recognition systems for the medical field. The new research department IML recently published a paper dealing with computer tomography scans and im- age-based diagnosis of SARS-CoV-2. Professor Sonntag and DFKI researcher Duy Nguyen, in cooperation with sci- entists at Dublin City University (Ireland), the University of California, Berkeley (USA), VNUHCM-University of Sci- ence (Vietnam), and Max Planck Institute for Informatics, succeeded in developing a prototype that automatically recognizes coronavirus infections in CT-scans. DFK I NE WS 1/2021 New AI systems not only effectively filter CT scans for Cov- id-19 cases from a set of data, which significantly increases the sensitivity of PCR tests, but also assess which areas on an image are particularly conspicuous. Scientists from the international research cooperation presented a joint paper explaining the new approach that improves diag- nosis by merging different data sources and minimizing errors. Using test research data, the method achieves a hit rate of 92 percent – currently, one of the world’s best results in the automatic image recognition of the SARS- CoV-2 virus on a CT scan data set. The paper titled “An attention mechanism using multiple knowledge sources for COVID-19 detection from CT images” was presented as part of the “Trustworthy AI for Healthcare” workshop at the 35th AAAI Conference on Artificial Intelligence in early February 2021. The method is special because it provides a visual representation of the diagnosis to the physician. The aim of the assistance system is to make the basis for a diagnosis more comprehensible and to provide important insights into the AI component’s im- age processing capabilities. Prof. Sonntag is developing the new research area with- in the context of the endowed professorship “Applied Artificial Intelligence” in the Department of Computer Science at Carl von Ossietzky University in Oldenburg, which he has held since November 2020. The professor- ship is funded for five years by a donor group composed of CEWE, EWE, BÜFA, the OLB Foundation, Dr. Caroline Neumüller, Alexander Neumüller, the business associa- tion DER KLEINE KREIS, and the Foundation of North-West Metal Industries (German: Stiftung der Metallindustrie im Nord-Westen). The establishment of this fourth research area repre- sents a new milestone for DFKI-Labs Niedersachsen, which maintains branches in Osnabrück and Oldenburg.

21 1 2 0 2 / 1 S W E N I K F D “The initiative to establish the DFKI field office at Lübeck came about after intensive discussions following a meeting of the German Bundestag’s AI Commission of Inquiry. AI and health is a mega topic with social relevance and Lübeck is the ideal site for this subject.” Prof. Dr. Antonio Krüger, CEO, DFKI ing the SARS-CoV-2 and diagnosing the disease Covid-19 was significantly accelerated with the help of big data and AI. Learning systems have also been helpful in identi- fying risk groups and even in predicting the spread. DFKI and the University of Lübeck are co-authoring a suc- cess story of AI in personalized medicine. Together with the strong, supportive environment of excellent health services and outstanding medical technologies, they can develop a large sector of future medicine. This partnership can propel Lübeck into the Champions League of AI research in Germany.” Contact Prof. Dr. Heinz Handels Head of Research Department AI in Medical Imaging (AIMedI) heinz.handels@dfki.de +49 451 3101 5600 Contact Prof. Dr. Alfred Mertins Head of Research Department AI in Biomedical Signal Processing alfred.mertins@dfki.de +49 451 3101 5800 Contact Prof. Dr. Ralf Möller Head of Research Department Stochastic Relational AI in Healthcare ralf.moeller@dfki.de +49 451 3101 5700 e Stock b o d © A staff, while the University of Lübeck provides office space and the working hours of the professors. An assessment will be carried out after three years to determine whether the approach is successful and whether the location will be made permanent. Prof. Dr. Ralf Möller. “Artificial intelligence is ena- bling major advances in busi- ness, science, education, and society. This new DFKI office is a major milestone in raising the visibility and positioning of Schleswig-Holstein when it comes to the use and application of artificial intelligence technologies, in particular, in the field of healthcare and medicine. This will be a boost to the entire north – Lübeck will have even more international appeal in the future as a strong center of AI research as it develops into a Ger- man-wide powerhouse for AI in the healthcare and medi- cine sectors,” said Dirk Schrödter, State Secretary and Head of the State Chancellery. “The new DFKI field location is a key component of an ‘AI in Healthcare’ ecosystem now being created in Lübeck,” said Prof. Dr. Stefan Fischer, University Vice President for Transfer and Digitalization. The Lübeck campus facilitates close co- operation with various institutions at the University Hospi- tal Schleswig-Holstein, for example, with the Department of Radiology and Nuclear Medicine (Prof. Dr. Jörg Barkhausen) and with the Center for Artificial Intelligence Lübeck (ZKIL) at the University of Lübeck. Prof. Dr. Claudia Schmidtke, member of the German Bundestag representing Lübeck and patient ombudsman of the German government, was instrumental in establishing the contact between DFKI and the University of Lübeck and stressed the importance of the field office – especially in times of a pan- demic: “The revolutionary potential of artificial intelligence in medicine was demonstrated in the corona pandemic, but this is true not only in times of crisis. The work of sequenc- © Universität zu Lübeck

The potential of GAIA-X for agriculture will be demonstrat- ed through the development of use cases. A diverse group of players is necessary to develop smart applications for the industry and put them into practice: from farmers and agricultural systems manufacturers to AI companies and agribusiness software providers. Project partners are implementing an innovative B2B platform that will provide industry-specific, adapted AI components in the form of easy-to-use modules and bring the developers of AI algorithms together with the users. The aim is to close the loop from sensor data recordings by farm machines, to the algorithms’ training on the appropriate servers, to the continuous update and optimization of these algorithms. To achieve this aim, Agri-Gaia develops the appropriate in- terfaces and standards to create a manufacturer-independ- ent infrastructure. “We hit a nerve with Agri-Gaia. The need for a secure, networked data infrastructure as proposed in GAIA-X is huge, especially for developments in AI. Numerous companies along the entire agri- business value chain have already approached us with plans to support the project and become part of the Agri-Gaia ecosystem.” Prof. Dr. Joachim Hertzberg, Director of DFKI Labs in Lower Saxony The project results will clearly benefit the entire agricultural sector and enable innovative business models, in particu- lar, for start-ups and small enterprises whose data and algo- rithm-based services will be able to reach a broader market. Agri-Gaia is expected to work as a catalyst for AI and ensure that smart technologies are used throughout the operations of agribusiness – for more efficient and more sustainable agricultural practices. Contact Dr. Stefan Stiene Research Department Plan-based Robot Control stefan.stiene@dfki.de +49 541 386050 2252 i W M B © Future smart systems will be used to support farmworkers in the field. Innovative agricultural technologies are the subject of Agri-Gaia’s research into the use of AI in agriculture. 23 1 2 0 2 / 1 S W E N I K F D k c ü r b a n s O e l u h c s h c o H ©

k c o t S e b o d A © this problem, the World Bank is cooperating with national governments to launch several projects with the goal of im- proving waste management in these countries and reducing the amount of pollution in rivers, canals, and on beaches. As part of the World Bank projects, DFKI researchers are developing a machine learning algorithm called APLAS- TIC-Q (“aquatic plastic litter detector and quantifier sys- tem”). The initial training basis for this algorithm consists of high-resolution RGB spatial images taken by aerial surveys over Cambodia. Based on so-called Convolutional Neural Networks, APLASTIC-Q consists of two different machine learning components – the plastic waste detector and the plastic waste quantifier – which analyze images in sequence. The detector has 83 percent accuracy in differentiating be- tween plastic waste, water, sand, and vegetation. And, in a second step, for imaged areas where plastic is detected, APLASTIC-Q provides an estimate of the trash density: the plastic waste quantifier analyzes those areas classified as plastic waste and divides the objects into further sub-cat- egories – to include plastic bottles, plastic bags, styrofoam, canisters, and polystyrene packaging – and determines how much of each. The results are quite encouraging. When it comes to analyzing images containing a great deal of trash, especially plastic waste floating in rivers and washed ashore, APLASTIC-Q is way ahead of comparable systems. The algo- rithm is also adaptable for various applications, whether for images recorded with a smartphone or for satellite-based surveillance images. The machine-learning algorithm developed by the scien- tists is proving to be a valuable environmental monitoring tool that provides scientific and evidence-based informa- tion in addition to the knowledge gained from litter collec- tion studies, dragnet fishing, and cleanup operations. For special interest groups and policymakers, this knowledge is essential in choosing effective actions to combat pollution. Making marine plastic visible – innovative monitoring tecnology detects plastic pollution on the seabed Of the eight million tons of trash that get dumped into the sea, only a fraction remains visible floating on the surface. Most of it sinks into deeper waters or to the seafloor. It has not been possible to detect large concentrations of plastic at the bottom of the ocean – until now. A more efficient solu- tion is being developed by DFKI Robotics Innovation Center and its partners Planblue, Kurt Synowzik Tool and Equipment Manufacturing, and the Institute for Biomaterials and Bio- molecular Systems at the University of Stuttgart. The aim of the MarinePlastics project is to develop an inno- vative monitoring system that can automatically detect and identify plastic waste of various kinds on a large scale on the 25 1 2 0 2 / 1 S W E N I K F D a s s a l a h T - y e P s i x e l A © k c o t S e b o d A © ocean floor. The new system will also record the condition of the plastic and link the results with georeferencing data. In this way, it will not only be possible to assess the degree of pollution but also to track changes in plastic waste over any period of time and to implement cleanup measures. The future system envisions not only use by divers, but also by underwater robots that can cover wide areas and reach depths hostile to humans. No expert knowledge is required to understand the information obtained from the dives, thanks to the automatically generated color-coded maps. This makes it useful for diverse purposes in the fight against plastic pollution – for example, in strategic planning for policy- makers and NGOs, in drawing up guidelines and new legislation, and for raising public awareness. To realize the project goals, pro- ject partners rely on a combina- tion of hyper-spectral imaging and innovative AI-based algorithms. The algorithms are trained using characteristic reflectance spectra to accurately detect and classi- fy objects on the seabed, in this case, plastic debris. The role of the Robotics Innovation Center in the project is to develop innovative mission and path planning methods. The com- ponents developed in this project will undergo testing un- der laboratory conditions as well as outside the lab at the bottom of a lake. The MarinePlastics project is funded as part of “Plastic Monitoring in European Waters – PlaMoWa Europa,” a ZIM cooperation network program (ZIM, Zentrale Innovationsprogramm Mittelstand), by the German Federal Ministry for Economic Affairs and Energy (BMWi). A diver scans the seabed using a new type of monitoring technology. More information www.dfki.de/dfki4planet Contact DFKI4planet Prof. Dr. Oliver Zielinski Marine Perception oliver.zielinski@dfki.de +49 421 17845 4710 APLASTIC-Q Mattis Wolf, M. Sc. Marine Perception mattis.wolf@dfki.de +49 421 17845 4714 MarinePlastics Dr. Marc Hildebrandt Robotics Innovation Center marc.hildebrandt@dfki.de +49 421 17845 4127

AI FOR SPACEFLIGHT – AI FOR SPACEFLIGHT – ESA AND DFKI LAUNCH ESA AND DFKI LAUNCH JOINT TRANSFER LAB JOINT TRANSFER LAB 27 1 2 0 2 / 1 S W E N I K F D ESA's OPS-SAT, a mini satellite launched in 2019, allows European industry and academic experts to test innovative new software that could facilitate pattern recognition, autonomous scheduling, deep learning and automated maneuvering in orbit. The European Space Agency (ESA) and the German Research Center for Artificial Intelligence (DFKI) are establishing a joint research laboratory to develop new AI technologies and systems for use in commercial spaceflight – the ESA_Lab@DFKI. The Transfer Lab at DFKI-Kaiserslautern creates a framework for scientists from both research organizations to study AI systems for use in the interpretation of complex, extensive earth observation data and collision avoidance systems for satellites. “The potential for beneficial AI applications in space in the face of a world undergoing technological and climatic change is huge. In this regard, Machine and Deep Learning methods, for example, are ideal for analyzing and interpreting the extensive and complex data recorded by Earth observation systems, whether for climate monitoring, disaster control, or agriculture. The new transfer lab provides a creative space for the joint development of tailored space applications and the identification of sustainable cutting-edge and future needs AI solutions in ESA projects.” Prof. Andreas Dengel, Executive Director at DFKI in Kaiserslautern and head of the Smart Data and Knowledge Services research department Artificial intelligence for Earth observation Satellites send large amounts of data back to Earth every day. AI methods can help generate valuable knowledge from this raw data. Special machine learning methods are used, for example, to make dispersion and dam- age forecasts for environmental protection and disas- ter management in areas affected by natural disasters. Commercial value-added services range from financial risk assessment of such events to monitoring industrial infrastructures on Earth. Another application scenario targets security of supply through agricultural products: yield forecasts are made after the analysis of growth conditions and soil qualities of cultivated areas. Artificial intelligence for the safe operation of satellites Another potential field of application for AI is collision avoidance systems for spacecraft threatened by more and more orbiting objects above Earth. In the past, large, single, highly specialized satellites were in operation. Today, the trend in international spaceflight is toward constellations of hundreds or even thousands of small satellites. This poses new challenges for the operators of space-based infrastructure because, as the number of satellites increases, so does the risk of collision and the creation of even more space debris. AI methods accurately calculate the orbits of active and passive satellites as well as pieces of space debris, helping to prevent collisions by initiating evasive maneuvers. Successful transfer from the research ecosystem The partnership between ESA and DFKI in form of the ESA_Lab@DFKI will support these and other basic research developments and promises to expand the range and scope of innovations transferred from academic research to advanced industrial applications. More information www.dfki.de/sds www.esa.int/Space_in_Member_States/Germany Contact Dr. Mateus Dias Ribeiro Research Department Smart Data & Knowledge Services mateus.dias_ribeiro@dfki.de +49 631 20575 1017

29 1 2 0 2 / 1 S W E N I K F D NEW LAB IN JAPAN NEW LAB IN JAPAN DFKI AND OSAKA PREFECTURE UNIVERSITY PLANNING A NEW LAB IN JAPAN k c o t S e b o d A © DFKI is planning to establish its first research lab in Asia at Osaka Prefecture University. The procedures for opening a DFKI research unit has been agreed with the Osaka Prefectural University (OPU), which is currently merging with Osaka City University to form the largest public university in Japan. “We are strengthening our ties with the German Research Center for Artificial Intelligence (DFKI): we celebrated the 20th anniver- sary of our academic exchange and welcomed Professor Den- gel as a Distinguished Honorary Professor in 2017. The opening of a new DFKI Lab Japan, the first branch outside Germany, is very significant and marks the start of a promising development effort in AI research.” Prof. Masahiro Tatsumisago, President of the Osaka Prefecture University “The planned strategic expan- sion of DFKI in Japan is based on many years of good partnership and a common philosophy. We share with Japan the goal of us- ing AI for the benefit of people and society. As high-tech coun- tries facing intense internation- al competition, we are pleased to expand our existing cooperation with like-mind- ed partners and to jointly pursue promising research topics like Learning Assistance and Smart Cities.” Prof. Dr. Antonio Krüger, CEO DFKI DFKI and OPU have collaborated successfully for many years. For example, a learning lab was set up in Osaka similar to the Immersive Quantified Learning Lab (iQL) at DFKI-Kaiserslautern. The labs explore using AI and sensor technologies for new learning and teaching methods, also with regard to learning cultural differences. “The opening of the DFKI Lab Japan, deepens the existing good relationship and joint pro- jects with Japanese universi- ties, research institutes, and companies, while enhancing the DFKI brand in Japan. Prof. Dr. Koichi Kise has known DFKI very well for decades and we are very excited about having an established Japa- nese researcher as the potential director of the lab.” Prof. Andreas Dengel, Executive Director DFKI Kaisers- lautern and Distinguished Honorary Professor at Osaka Prefecture University “Our collaboration with Profes- sor Dengel of the German Re- search Center for Artificial Intel- ligence (DFKI) goes back more than 20 years, during which time we have promoted joint research and staff exchanges. The open- ing of the first laboratory out- side of Germany at our univer- sity will serve to make our exchange more active than in the past. We also hope to impact the internation- al community by jointly developing human-centered artificial intelligence systems as envisioned at DFKI.” Koichi Kise, Professor of Computer Science and Intelli- gent Systems at OPU and designated director of the lab Contact Christian Heyer Head of Corporate Communications DFKI Kaiserslautern christian.heyer@dfki.de +49 631 20575 1710 More information www.osakafu-u.ac.jp/en

31 1 2 0 2 / 1 S W E N I K F D k c o t S e b o d A © ARTIFICIAL INTELLIGENCE TO CLEAN-UP SPORTS PROJECT EPO-PREDICT II Almost all endurance sports – cycling, athletics, swimming, winter sports, football are doping – with Erythropoietin, EPO for short. The hormone-based preparation is used to increase the number of red blood cells. This is known to improve the transfer of oxygen to the muscles, which improves the per- formance of the entire organism. The use of EPO is forbidden in sports, and the price can be high when it is used to win: If the level of EPO in the blood is too high, it leads to a deteri- oration of the flow characteristics and may cause thrombo- ses, embolisms, heart attack, and stroke. is developing a method for WADA that uses artificial intelligence to detect EPO abuse based on blood samples from ath- letes. Machine learning techniques are being used at DFKI Saarbrücken to train algorithms to detect EPO abuse us- ing sample data provided by the University of Copenhagen. The researchers use statistical methods to track the dynam- ics of several blood parameters in their effort to find the best indicators for detecting the presence of EPO in the body of the athlete. In principle, EPO is easily detected because it gives rise to characteristic changes in the blood count. The international anti-doping organization WADA (World Anti-Doping Agency) created a program called “Athlete Biological Passport (ABP)” to test blood samples from athletes. DFK I NE WS 1/2021 The goal is to develop an algorithm capable of distinguishing between samples from clean and drug-abusing athletes. To achieve this, different classes of machine learning models were trained with hematological profiles. The cost of implementing the process is not insignificant and administering the program depends on the availability of medical professionals. The use of AI-driven strategies to automate the process can contribute decisively to improv- ing the success rate of these doping controls. The collection of health-related data is time consuming and expensive, not to mention highly confidential. To expand the data base, generative-based approaches were used, i.e., syn- thetic data was created to simulate the behavior of various blood parameters. As part of the EPO-Predict II project, DFKI‘s Smart Service Engineering (SSE) group, managed by Prof. Dr. Wolfgang Maaß, The project results will assist WADA to automate and opti- mize the detection of EPO abuse in sports. More information www.dfki.de/sse Contact Dr. Sabine Janzen Research Department Smart Service Engineering sabine.janzen@dfki.de +49681 85775 5269 G n u K y t M o o P , o t o h P k c o t S e b o d A © k c o t S e b o d A ©

33 1 2 0 2 / 1 S W E N I K F D The Agents and Simulated Reality research department, led by Prof. Philipp Slusallek, develops smart simulation tech- nologies for the control of physically plausible virtual char- acters. To generate high-quality animated content, signals from multiple individuals are interpreted in real-time to achieve a seamless and engaging visual experience during the dance. The integration of sensor data in a game engine enables visualizations of the user avatars. A character-con- troller is generated from a user analysis and the current scene to animate the virtual character. Special machine learning models are used to train the different types of movements found in the different dances. The realism is increased when the characters can work intrinsically and learn from their own experience. In the special case of a training scenario, visual and haptic feedback is integrated with an agent-controller. Contact Noshaba Cheema Research Department Agents and Simulated Reality noshaba.cheema@dfki.de +49 681 85775 3834 PROJECT SUMMARY European Union (EU) CAROUSEL+ Sponsor Research department Agents and Simulated Reality Partners Term Grassroots Arts and Research, Edinburgh Napier University, Aalto University, VIVITnet January 1, 2021 - December 31, 2025 CAROUSEL+ is part of a new branch of research called “Real-World Social and Physical AI” that investigates application scenarios in the areas of social, entertainment, health care, education, autonomous driving, and safety and disaster management. © Adobe Stock © Hochschule Osnabrück

35 1 2 0 2 / 1 S W E N I K F D PROJEKT XAINES ZUR PRESTIGIOUS “SCI-TECH OSCAR” GOES ERKLÄRBARKEIT VON KI GESTARTET TO THREE FORMER COMPUTER SCIENCE PHD STUDENTS FROM SAARBRÜCKEN The Academy of Motion Picture Arts and Sciences awards the distinction known as the “Oscar” also for technical merit. 2021 the basic research and technological development of the “Intel Embree Ray Tracing Library” will be honored with the Technical Achievement Award. Three award winners earned their doctorates under Philipp Slusallek at Saarland University. The university professor and DFKI researcher has significantly advanced the award-winning ray tracing tech- nology over the past two decades. Today, this technology provides many Hollywood movies and computer games with the perfect images and can also recently be found in almost all graphics processors. At the virtual award ceremony on February 13, Sven Woop, Carsten Benthin, and Ingo Wald received the Sci-Tech Oscar. All three earned their doctorates more than a decade ago at Saarland University on the topic of ray tracing. Together with Attila T. Áfra and Manfred Ernst, they are honored for co-developing or doing preparatory research on the “Intel Embree Ray Tracing Library.” This software library was de- veloped by Intel mainly for its own processors (CPUs). It is also freely available worldwide to all film producers and other applications as an open-source platform. In particular, the software library has been used to make animated films and virtual game worlds look as realistic as possible. It has been employed, for example, in international hit movies such as Lego Batman, Spider Man, and The Grinch, as well as in the computer game Cyberpunk 2077. “In animated films or virtual role-playing games, it is im- portant to correctly depict surfaces with all their shades and reflections. In each scene, it is also necessary to recal- culate which objects are visible to the viewer and how the incidence of light changes during a movement,” explains Philipp Slusallek. As a computer graphics professor at Saar University, Philipp Slusallek and his team were instrumental in developing the basic ray tracing technology. L.t.r. Ingo Wald, Carsten Benthin and Sven Woop. As early as 2003, the current Oscar winners, together with Professor Slusallek, founded the company “inTrace,” which initially marketed the ray tracing process for the automotive industry. The car manufacturers could use it to simulate the different variants of a vehicle’s body or interior in a photo- realistic way. The high computing power that the ray trac- ing process demands of computers attracted the attention of chip manufacturer Intel to the Saarbrücken researchers. In 2009, the company funded the establishment of an Intel Visual Computing Institute at Saarland University with 12 million dollars - and recruited the three young researchers Carsten Benthin, Sven Woop, and Ingo Wald. Philipp Slusallek now uses the method for a wide range of applications at the DFKI in Saarbrücken, where he is now also managing director. “Among other things, we use real-time ray tracing today to generate synthetic sensor data very quickly, which can be used to train and validate AI systems. The technique is also used for radar simulation, which plays an important role in autonomous driving. In addition, day- lighting systems in architecture can be optimized with it,” explains Professor Slusallek. „I think you can already say that we have advanced the computer world a little bit from Saarbrücken.“ Prof. Dr.-Ing. Philipp Slusallek More information www.oscars.org/sci-tech/ceremonies https://graphics.cg.uni-saarland.de www.dfki.de/asr Contact Prof. Dr.-Ing. Philipp Slusallek Head of Research Department Agents and Simulated Reality philipp.slusallek@dfki.de +49 681 85775 5377

CEF AT TOOLS AND SERVICES TRANSLATION TOOLS FROM AND FOR EUROPE 37 1 2 0 2 / 1 S W E N I K F D The European Union firmly anchored the principle of multilingualism, reflecting its linguistic diversity, in its Charter of Fundamental Rights. Modern language techno- logies help to realize this promise in everyday activities. The aim of “CEF AT Tools and Services” (Connecting Europe Facility – Automated Translation) is to identify and provide multilingual tools and services in support of the ministries, public services, and SMEs in overcoming language barri- ers. This project was initiated by the EC in 2017, with a term ending in April 2021. As the lead manager, DFKI's Multilin- guality and Language Technology research unit partnered with CrossLang, ELDA, IDC, ILSP, and Tilde to develop the multilingual tools, concepts, and analyses required for a multilingual Europe. “CEF AT Tools and Services significantly raised the profile of European language technology vendors and demonstrated the broad spectrum and potential of language technolo- gy 'made in Europe.'” In the process, it became clear that continuing support of EU companies is essential. The re- search conducted in the project provides the basis for ac- tively shaping the future of the European translation service called eTranslation," said Dr. Andrea Lösch, project leader. DFKI and its partners organized conferences, language tech- nology workshops, and meetings with public service pro- fessionals, while also conducting several detailed surveys with stakeholders from all EU member states, plus Norway and Iceland. The purpose was to provide comprehensive information to European authorities about the possibilities and promise inherent in the use of language technologies and to create a forum for mutual exchange. A comprehensive requirements study was conducted to determine the needs of Europe's SMEs and public servic- es and to identify ways to expand the existing machine translation tool, eTranslation. The study revealed that users wanted a wider choice of languages (e.g., Arabic) and subject areas (e.g., business and finance, or technology and science). There was also interest expressed in the intro- duction of new features, like translation of text in images and automatic summarization. The first engines for non- EU languages (Russian, Chinese, and Turkish) were quickly released in 2020. According to a CEF marketing study for language technol- ogies, an annual growth rate of 10% is expected in the EU. However, the study also warned that with more than 500 European language technology firms, there is a danger of market fragmentation – a problem for the development of the European language technology market. The project also produced a “Catalog of CEF eTranslation Services.” It lists more than 670 tools and technologies from European service providers that support the work of public services and SMEs in Europe, including speech recognition and tools for anonymization and computer- aided translation. More information https://cef-at-service-catalogue.eu https://ec.europa.eu/cefdigital/wiki/display/ CEFDIGITAL/eTranslation Contact Dr. Andrea Lösch Research department Multilinguality and Language Technology andrea.loesch@dfki.de +49 681 85775 5285

DFKI STAFF INTERVIEW With Dr. Tim Schwartz i e z t e D r e v i l O / D A A D © Senior researcher Dr. Tim Schwartz has been head of the Human-Robot-Communication team at DFKI-Saarbrücken since 2016. 39 T I A R T R O P - R E T I E B R A T I M 1 2 0 2 / 1 S W E N I K F D What do you see as potential applications for your research? My research area is human-robot interaction, where the central issue is how humans and robots can work together in so-called hybrid teams within the context of INDUSTRIE 4.0. One particularly exciting aspect is how we design the communication between humans and robots, especially in light of the increasing autonomous capabilities of the robots. The social aspects are of great importance here in addition to the technological challenges: What fears exist on the part of humans, and what can be done to alleviate those fears? When did your interest in artificial intelligence begin and how have AI processes changed since that time? I learned of AI at the end of my computer science studies from the book “Artificial Intelligence – A Modern Approach” by Russel and Norvig. The subject was so fascinating to me that I stayed for another semester and later earned my doctorate under Prof. Dr. Wolfgang Wahlster. As I started my scientific career, the term AI was often scoffed at in everyday conversations and I had to defend it in the public debate. In the meantime, almost the opposite is the case, so that I now find myself having to refute the exaggerated claims as well as, of course, the natural fear. What are the greatest challenges and opportunities today for AI systems? The current AI buzz is driven by advances in deep neural networks, i.e., sub-symbolic models. Many novel approaches have been developed even for old problems like image recognition, speech synthesis, and automatic text translation. I view these approaches as analogous to the human intuitive recognition of objects. In contrast, symbolic AI models reflect more logical thinking. This also raises questions of how and why our biologic neural networks are able to achieve both forms, so to speak, in one architecture. What are we still missing in the artificial networks? What are your favorite interests outside of your work as a research scientist? I don‘t understand your question! Joking aside, I do like to do things in my free time where I can use my hands. For example, I play the guitar, restore instruments, tinker with electronics, but I also bake bread or pizza and try to make hand-pulled noodles like the Chinese do (although I haven‘t had much success with that yet). Do you see any parallels to your professional work? Generally, whenever I perform manual work, I am always aware of how far we still have to go before we can start to compare the capabilities of an artificially intelligent robot with those of a human being. Meshing sensors and actuators with experiential and imitation learning networks with the ability to reason; abstraction, problem solving, adaptation, creativity, and dreaming are quite fantastic. The world still has many surprises to offer. What are your current work projects? I am working on Project CAMELOT, which deals with transfer-of-control situations and continuous adaptive learning where an autonomous system needs assistance at the Research and Innovation Center on Advanced Industrial Production (RICAIP). Together with our partners in the Czech Republic and Saarland, we are investigating opportunities for spatially distributed production arising from concepts such as INDUSTRIE 4.0 and Production Level 4 concepts, collaborative robotics, and augmented reality systems. Contact Dr. Tim Schwartz Research Department Cognitive Assistants tim.schwartz@dfki.de +49 681 85775 5306

41 F E I R B N I S W E N 1 2 0 2 / 1 S W E N I K F D Robotics Innovation Center (RIC) presents EU project funding program for robotics in industry and maintenance Robots can prove their potential value where humans are at risk, precision is required, and fast action is needed – for example, for inspection and main- tenance tasks. As a component of the EU-sponsored RIMA project, DFKI cooperates with small and medium-sized companies that are interested in robotics to maintain and service their plants. In addition to project funding, DFKI‘s RIC also offers training, administrative services, and the use of its test facilities. The RIC manages one of the 13 Digital Innovation Hubs (DIH) funded by the EU over four years, which promotes the exchange of ideas be- tween research and industry. Prof. Robert Wille receives coveted ERC Consolidator Grant Best Paper Awards to DFKI‘s Cyber- Physical Systems research department For his work in the field of quantum computing, Prof. Dr. Robert Wille received the prestigious Consolida- tor Grant awarded by the European Research Council. Prof. Wille, from the Johannes Kepler University Linz and the Software Competence Center Hagenberg, is also associat- ed with the DFKI Cyber-Phys- ical Systems department. His expertise is in develop- ing methods for improving the performance of quan- tum computers. The research project explores methods for the simulation and proof of correctness of corresponding quantum programs and is funded by the ERC with two million euros. The Best Paper Award at “Euromicro Conference on Digital System Design” (DSD), held in August 2020, was awarded to only one research team. The team members were Prof. Dr. Rolf Drechsler and Dr. Philipp Niemann, both from the University of Bremen and DFKI‘s Cyber-Physical Systems department, Alexandre Almeida from Sao Paulo State Uni- versity in Brazil, and Prof. Gerhard Dueck from the Univer- sity of New Brunswick in Canada. The prize was awarded for their publication “Design Space Exploration in the Map- ping of Reversible Circuits to IBM Quantum Computers.” In September 2020, another team led by Prof. Drechsler was honored with Best Paper Award at the “Forum on Specifi- cation & Design Languages (FDL).” Scientists Dr. Vladimir Herdt (DFKI), Prof. Dr. Daniel Große (Johannes Kepler Univer- sity Linz and DFKI), Eyck Jentzsch (MINRES® Technologies), and Rolf Drechsler received the prize for their publication “Efficient Cross-Level Testing for Processor Verification: A RISC-V Case-Study,” in which they presented a new test approach for processor verification. Book tips for young fans of robotics “Alles über Roboter” (Everything about Robots) is the recently published title of Volume 47 in the Ravensburger children‘s books series “Why? For what? What for?” Author Andrea Erne and illustrator Markus Humbach chose to feature, among others, the systems at the DFKI Robotics In- novation Center. In the book, readers will find the six-legged MANTIS, the space robot SherpaTT, the ape-like Charlie and the Coyote III Rover. “Finja forscht – Der rätselhafte Roboter” (Finja investigates – The curi- ous robot) by author Isabell Harder and illustrator Lea Fröhlich, is a fic- tional video chat with Prof. Dr. Rolf Drechsler, Chair of the Computer Architecture Working Group at the University of Bremen and Head of DFKI‘s Cyber-Physical Systems research, in which he answers questions about “Artificial Intelligence” posed by Finja and Malik, the two charac- ters in the children‘s book.

Intelligent Solutions for the Knowledge Society Bremen Site Prof. Dr. Rolf Drechsler Cyber-Physical Systems Prof. Dr. Dr. h.c. Frank Kirchner Robotics Innovation Center Lübeck Oldenburg Bremen Osnabrück Laboratory Niedersachsen Osnabrück Prof. Dr. Joachim Hertzberg Plan-Based Robot Control Prof. Dr. Oliver Thomas Smart Enterprise Engineering Oldenburg Prof. Dr. Daniel Sonntag Interactive Machine Learning Prof. Dr. Oliver Zielinski Marine Perception Kaiserslautern Saarbrücken Saarbrücken Site Prof. Dr. Josef van Genabith Multilinguality and Language Technology Prof. Dr. Jana Koehler Algorithmic Business and Production Prof. Dr. Antonio Krüger Cognitive Assistants Prof. Dr. Peter Loos Institute for Information Systems Prof. Dr. Wolfgang Maaß Smart Service Engineering Prof. Dr. Philipp Slusallek Agents and Simulated Reality Branch Office Lübeck Prof. Dr. Heinz Handels AI in Medical Imaging Prof. Dr. Alfred Mertins AI in Biomedical Signal Processing Prof. Dr. Sebastian Möller Stochastic Relational AI in Healthcare Berlin Project Office Berlin Prof. Dr. Gesche Joost Interactive Textiles Prof. Dr. Volker Markl Intelligent Analytics for Massive Data Prof. Dr. Sebastian Möller Speech and Language Technology Prof. Dr. Niels Pinkwart Educational Technology Lab Kaiserslautern Site Prof. Dr. Prof. h.c. Andreas Dengel Smart Data & Knowledge Services Prof. Dr. Paul Lukowicz Embedded Intelligence Prof. Dr. Martin Ruskowski Innovative Factory Systems Prof. Dr. Hans Schotten Intelligent Networks Prof. Dr. Didier Stricker Augmented Vision Living Labs Testing, evaluation, and demonstration of innovative technologies in comprehensive application scenarios Advanced Driver Assistance Systems Living Lab, Bremen Ambient Assisted Living Lab, Immersive Quantified Learning Lab (IQL), Innovative Retail Lab, Robotics Exploration Lab, Smart City Living Lab, SmartFactory-KL, Smart Office Space Living Lab Competence Centers Coordination of research activities in particular areas Ambient Assisted Living, Autonomous Driving, Deep Learning, Emergency Response and Recovery Management, AI for Environment and Sustainability, Semantic Web, Safe and Secure Systems, Smart Agriculture Technologies, Wearable AI © Harryarts /vecteezy © Freepik