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  • Conference Day

  • Workshop day

  • The Challenges of AI at the Edge – Towards a Systematic Discipline for AI Systems Engineering

    Many AI systems that interact with “physical reality” fail or get stuck after initial prototypes and before large-scale deployments. Changing this situation is the goal of the Competence Center KI-Engineering (CC-KING). The talk uses actual industrial AI applications to showcase the challenges commonly encountered for AI at the Edge. The talk concludes with current results to overcome these challenges and to establish the use of AI in complex systems as a systematic and dependable engineering practice.

  • The path from an idea to an AI solution - resource optimization with sensor data

    In our workshop, you will learn the typical procedure from the identification of a use case to the planning and implementation of an AI project based on sensor data from mechanical engineering using an industrial example. We will interactively work out how to analyze the business model, plan and set up the IT infrastructure, gain real added value from the analysis of sensor data with the help of AI and create a data-driven solution from this.

  • How to make tomorrow's agriculture happen thanks to Artificial Intelligence?

    Increasingly digitalized, agriculture is generating a considerable amount of data to feed artificial intelligence models. At the service of farms to ensure their economic performance and enable them to limit their environmental impact, data and AI are now essential subjects for the stakeholders in the agricultural sector. This workshop will be about existing initiatives and the issues surrounding data and AI applied to the agricultural sector.

  • KI-Engineering – Karlsruhe Way of AI Systems Engineering

    This workshop covers the core elements of the emerging discipline of KI Engineering in direct contact and discussion with its authors. KI-Engineering is the Karlsruhe way of AI Systems Engineering and addresses the systematical development and operation of AI-based solutions as part of systems that master complex tasks. One core part of the workshop is to get insight knowledge about PAISE, the Process Model of AI Systems Engineering, and its associated methods and tools. Short tutorials are combined with training exercises of mobility and production use cases.