Machine Learning – AI Engineering- AI for the Good
21-23 June 2021 – 100% online!
This year will mark the 5th edition of this remarkable French-German event, organized jointly by SIEMENS AI Lab, Ecole Normale Supérieure Paris-Saclay and Universität Passau! This year’s Summer-School will take place under the lead of the SIEMENS AI Lab.
Registration is free but mandatory before the event (register here). Once registered, you will receive by mail a link to the live session on the pdf ticket. For technical reasons, only the first 200 registrations will have access to the online session.
Registration is free but mandatory before the event (link to the registration). Once registered, you will receive by mail a link to the live session on the pdf ticket. For technical reason, only the first 200 registrations will have access to the online session.
Accelerate the European future with the 4th Digital French-German Summer School with Industry 2020.The Artificial Intelligence (AI) is spreading everywhere, from mobile apps becoming smarter and smarter, through objects with distributed AI, to data analytics that go far beyond predictive capabilities. Every company in every industry is under pressure to figure out how it will disrupt its business.While AI is widely adopted in Business to Consumer businesses driven by the investments of the GAFAs that are leading the research in this area, the digital revolution in the Business to Business world is starting. It offers a unique opportunity for Europe, and especially for France and Germany to remain in the lead of industrial domains, relying on their strengths in science and engineering. However, the challenges to be addressed to make them leaders in the Industry 4.0 to bring European industry to the forefront are much easier to get solved with a concerted effort.Digital twin is crucial for Industry 4.0 as it is a unique opportunity to shorten the long iterative cycles of industrial products or processes. But, particularly for the initial design phases of a product, device or process, insufficient specific data is available to train such digital models. Transfer Learning is definitely a key field to jump over this issue, offering the ability to start from the data from a similar case.The business and technological potential of AI are so huge that the prospect of machines that are self-operating and have data analysis and context-specific decision-making capacity beyond the level of human performance must be taken seriously, especially regarding its consequences, benefits and risks. The citizens’ well-being has to remain the ultimate rationale for deploying AI technologies.As a leading international IT services company, Atos is pleased to actively support this revolution with actions like, being a founding member of the “IA for Industry” Research Chair leaded by the École Normale Supérieure Paris-Saclay, or promoting the yearly French-German AI summer school since its early days. Both are mixing the strong French and German AI research communities and industrial leadership of the two countries to lead to a brilliant European future.In the difficult actual context, it is great that the 2020’s edition of the French-German AI summer school is reinventing itself and I’m excited by the agenda. It’s a valuable opportunity to move one step ahead to support the European ambitions.Éric Monchalin, Vice-President, Head of Machine Intelligence at Atos
13.00-13.15 Register & join the virtual plenary session
13.15-13.50 Official opening & group photo
Welcome by the organizers – Prof. Mathilde Mougeot, ENS Paris Saclay & ENSIIE, Prof. Harald Kosch & Axelle Cheney, both Passau University, Dr. Ullli Waltinger & Benno Blumoser, both Siemens AI Lab.
Official opening – Dr. Bernd Forster/ Michael HIinterdobler, Bayerische Staatskanzlei, Germany and by Hubert Tardieu, ATOS CEO Adviser, France,
After Chiemsee in 2017, Cachan in 2018, Passau in 2019 we are this year fully Virtual. I do not forget that we should have been in Clermont Ferrand where Michelin has invited us for 2020. I am sure we shall be able to organize a future edition in Clermont Ferrand. AI for Industry has become a real essential topic well recognized by the European Commission in the Public Private Partnership in preparation and we can claim to be among the first to have identified it. The chair created three years ago around ENS Paris Saclay and initially regrouping : Atos, CEA joined by Bertin has been augmented in 2018 by Michelin and SNCF followed last year by Banque de France.Inaugurating the second Summer School in 2018 I was saying: “Anticipating 2020 we are convinced that Industrial Data Platform will be common place in B-to-B in the same way platforms are dominating the B-to-C world today (in 2018)”Not quite yet on Business Data. However the importance of business data has been fully recognized in the European Strategy for Data announced on February 19, 2020 which is strongly promoting data space in a number of domains as manufacturing, energy, farming, finance , transportation, health with the objective that more industrial data be available for training machine learning.As well the GAIA-X project presented earlier by Marco Alexander Breit is a great example of franco-german cooperation on cloud which will facilitate interoperability between cloud and data sharing.On AI the initial program defined in 2017 proves to be the right one with a specific focus on measurable AI for business as a natural next step after Analytics. The great accent put on transfer learning was also the right choice even if it proves more difficult to implement as compared to what we thought in 2017.The progress on measurable AI have been superbly illustrated by the Ile de France AI Challenge which took place at the end of 2019 with the Jury on February 26. Based upon real challenge and industrial data provided by Michelin and SNCF we were able to compare the results provided by 15 start-up’s while protecting the industrial data and executing algorithms proposed by start-up’s on a neutral machine provided by Atos. Interestingly the same company won the two challenges as different as identification of wear indicators on a tire and the forecast of traffic in subways based on past traffic.
We did not fully anticipate the importance of ethics in AI. We have seen many attempts to give good recommendations, but they were more oriented to the consumer market. In industrial markets, we are still waiting for the proper guidance and initiative as AI for Good or Responsible AI are currently studied. As well the importance of edge computing begins to be fully realized with distribution of intelligence between edge and the center.
I am very pleased that Siemens has accepted to organize the 2021 5thedition in Germany and I hope that we shall be able to organize next year an AI Challenge in Germany on the same scheme as the one organized in France in 2020.
The success of this edition with more than 200 participants collected in one week is a great encouragement to the team in charge.
Live presentation by Dr. Francois Deheeger, Michelin Lead Data Scientist, France. Hybrid model in product design. slides.
Live presentation by Dr. Fikri Hafid, Réseau de Transport d’Electricité Head of R&D Studies, France. Machine learning use cases at a transmission system operator. slides.
Live presentation by Prof. Michael Granitzer, Passau University Professor for Data Science, Germany. Machine Learning Engineerging and Sustainability. slides.
Q&A on the 3 presentations and panel discussion.
14.50-15.00 Active Break (Stretching)
15.00-16.15 Session 2 – AI for the Good (chaired by Siemens)
Live presentation by Benno Blumoser, Siemens AI Lab Munich, Germany. AI for the Good – a Corporate View.
Live presentation by Dr. Brian Tervil, CNRS research scientist, Borelli center, ENS Paris-Saclay, France. ONADAP – a visualization and decision support tool for dynamic human and material ressources allocation within hospital facilities in times of sanitary crisis. slides.
Live presentation by Valentin KRUSPEL, Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ),Germany. Data Powered Positive Deviance and Beyond – Using AI for Sustainable International Development.
Live presentation by Julia Gottfriedsen, German Aero-Space Center (DLR) Environmental Data Science Researcher, Germany. Using Data Analytics and Machine Learning to Control Wildfire.
Q&A on the 4 presentations and panel discussion.
16.15-16.20Passive Break (get yourself a coffee before the final part)
16.20 – 17.20Session 3 – AI Engineering (chaired by Passau University)
Live presentation by Prof. Gianluca Bontempi, Université Libre de Bruxelles Professor and Co-Head at Machine Learning Group, Belgium. Causality and big data analytics: risks, challenges and solutions. slides and documents.
Live presentation by Matthias Laporte, Inspector at Banque de France, France. Self organizing maps for anomaly detection in an operational context. slides.
Live presentation by Tobias Bürger, BMW Lead Big Data and AI Platform, Germany. Machine Learning and AI in Practice – Insights into use cases from the BMW Group.
Q&A on the 3 presentations and panel discussion.
17.20 – 17.30 Wrap-up and Closing
ENS Paris-Saclay, France, Prof. M. Mougeot (& ENSIIE) , Dr. A. Kalogeratos, Dr. C. Truong, University of Passau, Germany: A. Cheney, Prof. H. Kosch, Siemens AI Lab, Germany: Dr. U. Walltinger, Dr. B. Blumoser.