2019' edition

2019' edition

Context and Motivation

The current process of digitisation undertaken in all parts of society, business and technology is transforming industry in all its facets and processes. Data, smart services, Internet of Things, robotics, Artificial Intelligence are changing the way humans and companies work together. There is a strong reshaping of Industry going on.

In this strongly dynamic context, the current data revolution and increasing automation of cognitive tasks are raising challenging issues related to:

  • interoperability of data, things and services in the increasingly open and geographically distributed industrial ecosystems;

  • efficient processing of the big amount of data generated by distributed production and business processes supported by IoT;

  • consistent and coordinated autonomous decisions and activities undertaken by fine-grained (machines, robots, humans) to coarse-grained (workshops, enterprises) entities in decentralized and open ecosystems.

In order to build a trustful intelligent open infrastructure to support this industry of the future, it is important to enhance the set of methods and to increase research in the domain of Artificial Intelligence on the one hand, and to foster education, development and cross-fertilisation efforts with the actors of Industry 4.0 on the other hand.

Considering the challenges previously listed, Artificial Intelligence technologies pertaining to Knowledge Representation and Reasoning, Autonomous Agents and Decentralised Artificial Intelligence, Responsible Artificial Intelligence should be combined to tackle these challenging issues.

In that direction, it is of first importance to share experiences and expertise between academia and industrial partners from France, Germany as well as other European countries with regard to Industry of the future and AI.

Goal of the Summer School

This Summer School is part of a series of coordinated events aiming at investigating how Artificial Intelligence technologies can tackle the challenging issues of the industry of the future with respect to interoperability, data processing and autonomy, thus contributing to a trustful and responsible intelligent infrastructure. The key objective is to prototype and review solution approaches to actual problems.

The goal of this Summer School is to gather young talents and train them on common theoretical and practical basis by experts from industry and academia, inspired by the visions and the experience of keynote speakers.

Participants will also work towards executable proof-of-concept solutions to the problems identified during the first workshop of the series of events, addressing the given requirements stemming from the industry and building on cutting-edge Artificial Intelligence, Autonomous Agents, Linked Data and Big Data Technology.

The main topics of the Summer school will be on the Web of Things, Knowledge Graphs, Decentralized AI, and Responsible AI.

Potential Interest

Participants will benefit from a motivating environment where:

  • This event series is closely aligned with the cutting-edge R&D activities including the Boost4.0 European lighthouse project for big data technology in manufacturing.

  • Excellent young talents draft innovative proof-of-concept solutions to actual problems.

  • A reality check by expert reviewers confirms the further viability of the initial solutions.

  • The events provide their participants with a network of business/project partners for subsequent experimentation and implementation.

Planned Organization

The Summer School will be organized along the 4 main topics mentioned above, each having balanced time dedicated to lecturing and practicing. In addition, students will have several working sessions in groups to draft plausible solutions to the challenges, create prototypes and test their approach as fast and as efficiently as possible.

The main topics of the sessions will enable the following:

  • The Web of Things – exploiting semantic descriptions of things, building mashups of things automatically;

  • Knowledge graphs – knowledge representation at scale, graph-based data management and querying;

  • Decentralized AI – multi-agent systems, coordination;

  • Responsible AI – AI ethics & AI safety

Participants that managed to propose promising ideas will be able to further develop them later in collaboration with companies and academic experts, either during the follow up workshop that will take place in September, or remotely in cooperation with the organisers and interested partners.