In the Netherlands and abroad we see a digital revolution in retail environments, whilst this has a lot of benefits, there is also a growing need for a human touch. We would like to research the human technology interaction that is created here and find out how we use digital tools in harmony to enhance our services.

In this case study, we explore the inner workings of large language models (LLMs) by breaking down their key components into simplified pseudocode. We examine how LLMs process input data, manipulate tokens, and generate predictions while providing a clear, concise understanding of their complex algorithms, ultimately empowering developers and researchers to better comprehend and utilize LLMs in various applications.

The case proposal aims to develop a recommendation system for designing carbon-neutral/negative buildings. Building construction contributes significantly to carbon emissions, so there is a need to reduce the carbon footprint. Designing carbon-neutral/negative buildings involves multiple disciplines and requires evaluating trade-offs. The recommendation system will use machine learning and AI to optimize the early design stages of buildings, considering criteria like cost and whole-life carbon. Real-world data and design scenarios will be used to evaluate the system's effectiveness and provide insights for architects and designers.

For government agencies, such as the police, having a good understanding of trends are vital to be prepared for the future. Currently, thousands of reports are written with the help of even more experts. But the police alone has over 60.000 people. How can we include their expertise? Human swarm intelligence could potentially allow next level assessments and predictions. We´re looking for a module that adds such functionality to our knowledge-graph based platform for trend analysis and future predictions.

The objective of this case is to create a data catalogue for a hyperspectral satellite mission, with a modular architecture that will allow it to be expanded to future missions. Various infrastructure solutions (such as cloud vs. on-site) and storage strategies should be considered. To define the dataflow between the mission and the data catalogue, the team will interface with OHB Sweden's engineering team and also develop strategies to facilitate integration with future data processing modules.

From 2024, reporting on the sustainability of activities will be mandatory for all corporations in Europe, in compliance with the CSRD and the EU taxonomy. Semmtech wants to offer all the big corporations in Europe the tools to help them report on their sustainability. Therefore, Semmtech is looking to 1) share the taxonomy as Linked Data, 2) configure tooling to map this EU taxonomy to operational-and financial systems, and 3) set up dashboards for periodic reporting.

This case study focuses on keeping employees up to date with emerging technologies. It involves the development of an escape room to understand the metaverse and other emerging technologies in a fun and engaging manner. We aim to communicate the benefits of metaverse and other emerging technologies for education in a business context

Cardiology in its current form is already lifesaving, but many processes are repetitive and require simple interactions. We believe that ChatGPT technology can enhance these interactions, allowing us to focus on providing top-quality patient care. As a first-generation prompt engineer, we challenge students to design a future that incorporates this technology while considering societal and patient factors.