Artificial intelligence at the Ada Lovelace Center

At the ADA Lovelace Center, we conduct research into nine different areas of expertise in AI, as well as incorporating a wide range of scientific partners at the national and international level. The methods range from semantic data models and learning using small annotated datasets (few labels learning) to techniques such as automatic and explainable learning, machine learning, and mathematical optimization. The latter is particularly useful for finding answers to previously unsolvable problems in industry and leveraging efficiency potentials.

At the ADA Lovelace Center, we place particular emphasis on research throughout the data life cycle, which is analogous to the life cycle of products. In the context of AI, the objective is not to collect as much indiscriminate data as possible, but rather to collect the right data and on an appropriate scale. This raises questions such as: How should data be stored, structured, and transmitted? What added value can be derived from data? What happens to data that can’t be used to generate insights? Indeed, with the storage of large volumes of data already leading to considerable CO2 emissions, resource-efficient handling will be essential in the future.

At the ADA Lovelace Center, we focus on applications in production, mobility, logistics, sports, and healthcare. In the context of logistics, for example, we develop AI methods that use publicly available sources of data (for example, infrastructure, market trends, purchasing power, demographic trends, and weather) to generate added value for logistics network planning and related business decisions. In sports such as soccer or hockey, we aim to automate game analysis with the help of a search engine. This would use positioning data to compare game situations with similar situations in the past with a view to evaluating their execution.

The ADA Lovelace Center is a scientific network that brings together local, regional, and national actors as well as engaging in strategic collaborations with international partners such as the Machine Learning Center at the Georgia Institute of Technology or the RIKEN Center for Ad- vanced Intelligence in Tokyo. In this way, we hope to raise our international visibility and boost interest in the ADA Lovelace Center among researchers and students in Germany and abroad.

With a view to developing profitable and practical applications of AI, we also encourage a process of exchange between industry and research. Scientists and employees from companies work together in Joint Labs on specific problems from research and industry in small, agile, and interdisciplinary development teams outside of their day-to-day business for a fixed period of time. These innovative forms of collaboration benefit from the new CoWiS coworking space at our location in Nuremberg, which offers a creativity-enhancing »Work 4.0« environment. »The ADA Lovelace Center sees itself as a multiplier for building up, reinforcing, or further developing a company’s AI expertise,« says Alexander Martin.