We develop technologies for the setting up of protected data spaces. It is not just the business community but society as a whole who can benefit from easier access to Artificial Intelligence (AI) applications, data, resources and infrastructures. Data spaces facilitate a fair, secure and transparent exchange of data.
We are developing technology cores which can be used to package Machine Learning tools into software containers which make using infrastructures such as these as easy and as flexible as possible. The containers can be operated in a variety of computing environments with very little effort and are easily scaled to different application scenarios.
Containerized software means we are also able to use hybrid Machine Learning processes and can link data-based and knowledge-based methods in one joint application package. Our architectures also support the automated deployment, scaling and administration of containers.
We have successfully used this technology in research and development projects, in laboratories for training courses and within experimental environments for our customers and partners. We have set up cooperative networks such as the “Fraunhofer Big Data and Artificial Intelligence Alliance”, the “International Data Spaces Association” and the “Big Data Value Association (BDVA)”.