Alexandra Wins

This work aims to develop an adapter solution that builds on existing routing algorithms and uses Large Language Models (LLMs) to further personalize travel planning. The adapter should intelligently plan stopovers and take into account the context of the journey (e.g. purpose of travel, preferences, time constraints) to improve the user experience. The work will analyze existing routing solutions and add a flexible, contextual component that uses LLMs to suggest recommendations and adjustments.

From November 27th to 29th, all the advertised theses will be presented in cooperation with Mercedes-Benz Tech Innovation. Get to know the topics and exchange ideas directly with developers and project managers. We look forward to meeting you! More info here