Machine intelligence and natural language processing

Artificial intelligence and language processing are key factors for automation, efficiency gains, and innovation in businesses and society. Despite major advances in recent years, significant challenges remain in terms of scalability, domain adaptation, explainability, and the responsible use of AI systems. Our research area develops advanced methods in machine intelligence and natural language processing to support companies in analysis, automation, and decision-making.

The focus is on the development and application of large language models, retrieval-augmented generation, and domain-specific AI solutions that can handle complex language and knowledge processing tasks and be flexibly adapted to different application areas. We support companies in integrating AI-based assistance systems, implementing federated learning, and developing methods for unlearning to ensure data protection, adaptability, and regulatory compliance. Close collaboration with industry partners results in innovative solutions that increase efficiency, enable new business models, and strengthen competitiveness in the long term. Our research places particular emphasis on the explainability and transparency of AI systems in order to gain user trust and increase acceptance in practice.

We develop practical tools and frameworks that help companies use AI responsibly and profitably. Empirical studies and pilot projects demonstrate a significant improvement in precision, adaptability, and efficiency in real-world applications. Our work helps to fully exploit the potential of AI and language processing and prepare companies for the challenges and opportunities of the digital future.

Our research projects are developed in close collaboration with industry partners. They are market- and demand-oriented, with the aim of providing applicable solutions for the cloud edge ecosystem.