Participants gained hands-on experience in training multi-modal machine learning models to identify elements within visual media, similar to technologies used in medical X-rays and satellite cartography.
Using Large Language Models (LLMs) and the Model Context Protocol (MCP) to interpret unstructured customer data and automate inventory decisions. AI enrichment project at SEEBURGER
Beyond theory, students learned to manage the hardware and software infrastructure required for large-scale AI image analysis. Strategic Context at SEEBURGER Strategic Context at SEEBURGER The inaugural project focused
The inaugural project focused on using live stream AI analysis to recognize social distancing (6 feet apart) and correct mask-wearing. It allows young participants to work directly with
The at SEEBURGER refers to a recurring collaborative program designed to bridge the gap between high-level academic theory and practical enterprise technology. Program Overview
The project is part of a partnership with the , an organization supporting highly gifted students in STEM fields. It allows young participants to work directly with SEEBURGER experts on cutting-edge machine learning and AI applications. Key Projects & Outcomes
Implementing automated pipelines to ensure enterprise data is "AI-ready" and reliable over the long term. AI enrichment project at SEEBURGER