Du würdest gerne hinter die Kulissen von Porsche schauen und Kontakte knüpfen? Dann hast du jetzt die Chance dazu! Am 27.04. veranstalten wir eine Exkursion zu Porsche nach Stuttgart und du kannst dabei sein. Es bietet sich dir die Gelegenheit etwas über Motorsport und dessen Produktstrategie bei einer Werksführung durch die Taycan Produktion und einer Museumsführung zu erfahren. Weiterhin gibt es die Möglichkeit sich mit Fachbereichsvertetern auszutauschen und dich über Einstiegsmöglichkeiten bei Porsche zu informieren. Du willst dich für die Exkursion anmelden oder sehen welche anderen Veranstaltungen wir sonst noch anbieten? Dann kannst du das unter https://events.bonding.de/kaiserslautern machen.

Seminar Series »Machine and Deep Learning«

Public hybrid talk: »ChatGPT: If Scale is the Answer, What is Left to be Asked?« Date: April, 4 2023, 17.00-18.00 h Participation options: a) Live on site in the auditorium of the Fraunhofer ITWM, Fraunhofer-Platz 1, Kaiserslautern (No registration is necessary) b) via Microsoft Teams: https://s.fhg.de/Glavas-ChatGPT Abstract: Large Language Models (LLMs) such as Chat-GPT, GPT-4, Bard, PaLM have recently demonstrated an almost shocking level of language understanding and generation abilities, passing a wide variety of complex tests from GRE and SAT to Bar Examination. Even more impressively, the latest of these models have demonstrated understanding (and ability to manipulate) complex artifacts of other modalities, such as images and code.Despite the fact that, as proprietary models, details of their neural architectures and training objectives are not disclosed, all evidence suggests that it is in fact the sheer scale of these models (e.g. GPT-4 is speculated to have tens of trillions of parameters) and the data on which they were trained the key factor to their unprecedented abilities. In fact, even in controlled experiments with smaller language models, certain abilities have been shown to emerge (hence dubbed »emerging abilities«) only at a certain scale. In this talk, I will first cover the (known) technical details of LLMs and their training procedures. In the second part, I will focus on emerging abilities (at different scales) as well as cases on which LLMs still fail. Finally, I will conclude with a discussion of implications that the observation that »scale is all that matters« has on future AI research, and NLP research in particular. Speaker: Prof. Dr. Goran Glavaš, University of Würzburg, Faculty of Mathematics and Computer Science, Center for Artificial Intelligence and Data Science (CAIDAS) Goran Glavaš is a Full Professor for Natural Language Processing at University of Würzburg, Faculty of Mathematics and Computer Science and the Center for AI and Data Science (CAIDAS). He obtained his PhD. at the Text Analysis and Knowledge Engineering Lab (TakeLab), University of Zagreb. His research is in the areas of natural language processing (NLP) and information retrieval (IR), with focus on lexical and computational semantics, multilingual and cross-lingual NLP and IR, information extraction and NLP applications (for social sciences and humanities). He has (co-)authored over a hundred publications in the areas of NLP and IR, publishing regularly at top-tier NLP and IR venues (ACL, EMNLP, NAACL, EACL, SIGIR, ECIR). He has co-organized the TextGraphs workshop on Graph-Based NLP (2017 to 2019) and the SustaiNLP 2020 Workshop on Simple and Efficient NLP (2020) and given tutorials at ACL 2019, EMNLP 2019, and ACL 2022. He served as an Editor-in-Chief of the ACL Rolling Review (2021-2022) and regularly serves as (Senior) Area Chair and Reviewer for top-tier NLP & IR conferences and journals. He is a member of the Association for Computational Linguistics and German Society for Computational Linguistics (GSCL). The event will be moderated by Prof. Dr.-Ing. Janis Keuper. He is a member of the Division Management »High Performance Computing« at the Fraunhofer Institute for Industrial Mathematics ITWM and Coordinator of the R&D-Lab »Data Analysis and Artificial Intelligence« at the High Performance Center Simulation and Software Based Innovation. Detailed information about the lecture of Prof. Dr. Goran Glavaš can be found on our website www.itwm.fraunhofer.de/chatgbt_presentation . About the Seminar Series The Machine and Deep Learning Seminar is organized by employees of the field Data Analysis and Machine Learning in the division »High Performance Computing«. It is intended to give interested persons an insight into this large field of research and a deeper understanding. Everyone who wants to learn more about Deep Learning, Machine Learning or AI in general is invited - no matter if students, PhD students, professors or software developers. In addition to the employees of our department, interested external speakers can also give a lecture in our seminar series. We also have the opportunity to invite external speakers. We are always open to suggestions, suggestions or requests. The event usually takes place every Thursday (except for holiday shifts and summer break). The topic of a talk should either come directly from or is relevant to Deep Learning, Machine Learning, Data Analysis or AI, no matter whether it is about a paper, an own project on or an interesting topic. The complexity can range from an overview talk to a special topic Technical Notes After you click on the Microsoft Teams link, if you are not using Microsoft Teams yet, a browser window will open and you will be asked How would you like to join your Microsoft Teams meeting? You can use Microsoft Teams via a browser (e.g. Chrome) or you can download the Windows app to your desktop or install the Microsoft Teams app on your smartphone or tablet. Contact; Prof. Dr.-Ing. Janis Keuper Member of the Division Management »High Performance Computing«, Team Lead Machine Learning Fraunhofer Institute for Industrial Mathematics ITWM Fraunhofer-Platz 1 67663 Kaiserslautern www.itwm.fraunhofer,de Coordinator of R&D Lab »Data Analysis and Artificial Intelligence«, High Performance Center Simulation and Software Based Innovation www.leistungszentrum-simulation-software.de Fon +49 631 31600-4715 E-Mail: janis.keuper@itwm.fraunhofer.de

Frau Dr. Katherine A. Muñoz Sepúlveda ist Vertretungsprofessorin in der AG Umwelt- und Bodenchemie am Institut für Umweltwissenschaften des Fachbereichs Natur- und Umweltwissenschaften der RPTU in Landau. Zu Ihren Forschungsthemen gehören Mykotoxine. Das sind Stoffwechselprodukte aus Schimmelpilzen, die für Mensch und Umwelt toxisch sind. Die chemische Diversität, die Risikoeinschätzung und die daraus resultierenden, unendlichen wissenschaftlichen Forschungsfragen faszinieren sie besonders. Warum sie sich für die Chemie entschied und wie sie Ihren Alltag mit Forschung, Familie und Freizeit taktet, erzählt sie uns in Ihrem Videoportrait: https://rptu.de/s/vwmnda Das Videoportrait ist Teil der Kampagne "Wissenschaftlerinnen der RPTU stellen sich vor". Ziel ist es, Frauen in der Wissenschaft, ihren Weg dahin, ihre Erfahrungen, Motivationen und Ziele vorzustellen. Wie ist es möglich, Wissenschaft und Karriere, Forschung und Lehre, Familie und Freizeit miteinander zu vereinbaren? Das Projekt ist ein Gemeinschaftsprojekt der Stabstelle Gleichstellung, Vielfalt und Familie sowie der Zentralen Gleichstellungsbeauftragten des Senats der RPTU Kaiserslautern-Landau. Alle Videoportraits im Überblick: https://rptu.de/s/uxnmgh