This was AIxIA 2020

Thank you for participating in the second French-German conference on the application of Artificial Intelligence!


AIxIA: AI Conference 2020

Artificial Intelligence meets Intelligence Artificielle

After the first successful French-German AI conference in October 2019, with over 300 participants from France, Germany and the world, we are happy to announce that the second AIxIA will take place on 3rd of December 2020.

AI for the environment

This year’s conference will be held online and focusses on the application of Artificial Intelligence for the benefit of the environment!
Climate Change is the biggest challenge of this century. We believe that Artificial Intelligence is a powerful technology that can contribute to a greener world, while at the same time driving economic growth for the benefit of humanity. For this we will present keynotes and talks that centre around this topic.

Join the AIxIA 2020 to learn more about applications of Artificial Intelligence in manufacturing, agriculture, energy, water and resources.



The AIxIA keynotes, talks, discussions and state-of-the art use cases will cover two topics:

AI & Industries

From predicting malfunctions of machines and finding root causes to next-level process automation for production lines – AI technology has led to major improvements in manufacturing. Besides, we see that close human-robot collaboration is in advance. AI can reinforce the collaboration by “humanizing” the robot behavior. At the conference, we will look into how these innovations massively boost business success AND can have a positive environmental impact – the reduction of waste and energy usage are just two examples.
Another aspect that will be covered is AI within the food industry. According to forecasts, humanity will need around 70 percent more food by 2050, than we produce today. AI solutions can help farmers to grow food more efficiently and at the same time in a more environmentally friendly way.

AI & Sustainability

Sustainability is a hot topic. An industry-wide shift is occurring which leads companies to include environmental sustainability goals in their corporate strategies. Companies must be aware of their footprint and what they can do to reduce it. The AI use cases presented in this session focus on these issues with a focus on energy, water, and resources.

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  • Sessions

    3rd December

  • Michael Klingel: Network state estimation for the renewable energy transition

    The energy transition is taking place - through the expansion of renewable energies and the market ramp-up of electromobility - in the distribution grid. As a result, power generation is increasingly migrating to medium and low voltage. This dynamic is accompanied by new challenges for distribution network operators: they have to deal with bidirectional power flows and enormous peak loads - and all this with huge network areas. This is only possible with innovative approaches and the inclusion of artificial intelligence!

    Dr. Cyrille Waguet: AI for resilient infrastructures

    Timely maintenance of railway tracks is crucial for resilience, comfort and safety in rail traffic. It increases the acceptance of rail transport and its sustainability. developed a smart monitor for rails which identifies and categorises anomalies on railway tracks by analysing sensor data based on daily train operations. Connected to the operator’s business processes, the resulting digital twin of the tracks keeps the maintenance teams up to date about the rail conditions and their expected evolution.

  • Francois Werner

    Grand Est Region: an ambition to lead in terms of innovation, competitiveness, job creation and attractivity. The 2019 adopted regional plan for Artificial Intelligence is built around 5 strategic axes: Boosting business competitiveness through AI Supporting scientific excellence, ensuring its outreach and valorization Energizing AI start-ups. Training AI competences and skills Securing an ethical, transparent and inclusive IA It focuses on 3 sectors : health, industrie and bioeconomy.

  • Stéphane Canu: French Strategy on artificial intelligence

    French-German cooperation and its implementation modalities, in particular via calls for projects already implemented or to be implemented in the future will be presented.

    Lisa Kratochwill: Artificial Intelligence – from Hype to Reality for the Energy Industry

    Looking at artificial intelligence as hyped technology no longer seems to be appropriate - it has already penetrated most sectors as a key technology. Especially in the energy sector the high efficiency potential of AI has been very well received - much faster than expected. In dena’s new AI-analysis the most promising fields of application for AI in the energy industry are classified and an initial assessment is carried out to examine the opportunities and challenges.

  • Prof. Dr.-Ing. Gisela Lanza: Artificial Intelligence - The new production manager

    The possible industrial applications of artificial intelligence (AI) are manifold. There are AI systems that perform quality inspection more reliably than humans as well as systems that support engineers in the design phase. Thus, will entire factories soon be managed by AI? Practical examples demonstrate what AI systems can already do, where they are already applied and what limits prevail. Altogether, the new role of production managers will be projected.

    Korbinian Weiß: Sorting Guide – AI development at TRUMPF

    To tackle the complexity of sheet metal production AI solutions can help make this manageable. The overall efficiency of laser cutting of sheet metal can be greatly improved by new tools to minimize waste an increase speed in production. Learn how a AI solution utilizes computer vision to support the worker on the shop floor.

    Dr. Hannes Sieling: AI-Enabled Price Markdowns for Groceries in Real-Time

    AI allows retailers to translate business decisions at scale with a high degree of automation. As grocery retailers experience intensifying competition, they need to manage pricing processes for expiring products to balance profitability and waste. Learn how AI enables the full utilization of intraday POS data and real-time decision making to manage markdowns. Markdown pricing contributes to sustainability goals by minimising and controlling waste based on the retailer’s business strategy.

    Guillaume Cazenave: Computer Vision for gains in efficiency and cost saving

    There are a growing number of Computer Vision (CV) use cases for increasing efficiency and cost savings of organisations. Prior the Edge AI CV revolution, cameras were used by agents for limited visual monitoring actions. Most of the time, agents could at best see an incident at it was occurring or investigate after it happened. With the implementation of Edge AI CV, a single agent can monitor multiple sites remotely and leverage camera infrastructure and AI to prevent incidents and take proactive decisions. This result in significant improvement in business process and reduction in product loss for an increase in ROI of organisations.

    Sébastien Picardat: The challenges of AI and data in agriculture

    Decision tools used in precision agriculture and integrating AI are designed using useful digital agricultural data. These data come from the many connected objects in place in farms: weather sensors, drones, electronic loops, etc. By relying on reliable data, exchanged with the consent of farmers, AI can make a major contribution to the sustainability of the agricultural sector.

  • Dr.-Ing. Robin Hirt:

    AI will open up remarkable opportunities by learning from our data. However, we need to ensure that this exact data is kept safe during the process.

    Thomas Mann:

    AI is the driver of progress of this century - the automation of processes, enabling opportunities for more sustainable prosperity.

    Katia Hilal:

    The industry desperately lacks historical failure data to train Machine Learning algorithms. Blind failure prediction means we predict equipment failures without historical failure data. Magical? No, we invented scientific methods to generate highly discriminant health indicators from industrial time series.



Gaëlle Pinson

General Manager at Hub France IA

Gaëlle Pinson is General Manager at Hub France IA and as such fully aligned with the Hub’s ambition to develop a European AI model for business and society. She started her career in the Prime Ministers administration DATAR dedicated to spatial planning dealing with clusters and innovation policies. She was then responsible for the digital project of the new metro Grand Paris Express, with Minister Christian Blanc when the law was drafted, later in the implementation phase at Société du Grand Paris, where she initiated the data project. She also created a start-up on long time digital archiving based on glass. She is always keen in strongly promoting European projects, including French-German ones.

Gennadi Schermann

Head of Digital Innovation Center (DIZ)

Gennadi Schermann is running the department of Innovation and Digital Ecosystems at CyberForum e.V. as well as the Digital Innovation Center – a joint initiative of CyberForum and FZI Forschungszentrum Informatik. Digital Innovation Center (DIZ) is a statewide contact point for digitalization, artificial intelligence and cybersecurity. The Digital Hub applied AI/de:hub Karlsruhe ist coordinated by the DIZ. Mr. Schermann studied industrial & business engineering at Karlsruhe Institute of Technology (KIT) and Lappeenranta University of Technology in Finland. He gained his international experience during his professional stations at the South East Research Center in Thessaloniki (Greece), at the Deutsche Postbank in Bonn as well as at the Levono Technology Co. in Shanghai (China).

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