BIFOLD opening with governing mayor Franziska Giffey © BIFOLD/Michael Setzpfandt

11 October 2022

"Berlin is clearly the AI capital: internationally attractive and equipped with a broad ecosystem of AI players."

The Berlin Institute for the Foundations of Learning and Data (BIFOLD) is taking Berlin to the next level as a leading international AI hub: the national AI competence centre hosted an international research symposium and ceremony to celebrate the securing of long-term annual state funding.

BIFOLD conducts top level research in the fields of big data management and machine learning and their interfaces in order to train future talent and create highly effective knowledge sharing. We spoke to its two directors, Prof Dr Volker Markl and Prof Dr Klaus-Robert Müller on projects that have been implemented in recent years and on the institute’s future and goals.


BIFOLD has now officially opened its doors. What exactly does BIFOLD stand for and what is the goal of this ambitious project?

Prof Dr Klaus-Robert Müller (KRM): The Berlin Institute for the Foundations of Learning and Data (BIFOLD) emerged from two forerunner projects – the Berlin Big Data Center (BBDC) and Berlin Center for Machine Learning (BZML). We research big data management (BD) and machine learning (ML) and their interfaces. These two key technologies in particular are considered to be innovation drivers in the field of artificial intelligence (AI). BIFOLD generates genuine new knowledge for science, industry and society. Together with our institutional partner, the Charité - Universitätsmedizin Berlin, BIFOLD makes an important contribution to digitisation in medicine and thus creates substantial added value for Berlin.

What are BIFOLD's main focus areas and which research areas are you personally interested in?

Prof Dr Volker Markl (VM): BIFOLD’s aim is to conduct research on the two essential building blocks for the application of artificial intelligence (AI) - big data management (BD) and machine learning (ML) - as well as to teach and and share knowledge in these areas to network and to advance significantly. In research, we set clear priorities: These include scalable data management as well as learning and inference methods, data mining, data management and data security. Last but not least, we also work on the management of data science processes, such as information integration or information visualisation and visual analytics.

KRM: Another focus is on new AI architectures and systems, such as data analysis infrastructures and information marketplaces, highly scalable systems for the Internet of Things and Industry 4.0, as well as AI applications for science, such as bioinformatics, digital humanities and the quantum chemistry. Several of our scientists conduct research on responsible data management and explainable AI, in terms of comprehensible machine learning methods, computer security, securing informational self-determination and data protection, and the associated technical foundations of responsible, ethical data management.

BIFOLD has been conducting research for several years and has already initiated exciting projects and achieved excellent results. Can you tell us about these projects?

KRM: Under BIFOLD and its predecessors, many important AI applications have developed in industry and sciences such as medicine, physics, chemistry and the humanities. In addition, BIFOLD researchers run joint projects with companies such as Google, Amazon, Bosch, Siemens and Zalando. Around 40 start-ups have also emerged in the BIFOLD environment, including successful start-ups such as dataArtisans, Aignostics and Debatoo, and well over 50 open source tools have been published. BIFOLD also makes a significant contribution to the training of urgently needed AI experts: around 170 candidates have already received their doctorates. Every year around 1,800 students attend the introductory lectures on data management and machine learning. Furthermore, BIFOLD has also developed a data sciences course for non-STEM students.

Long-term funding for the project was secured by the federal and state governments this summer. Is this a sign of the rapidly increasing importance of AI research in Germany?

VM: We certainly see it that way. In the coming decades, AI applications will have a massive impact not only on industry and science, but also on our society. If Europe and Germany want to help shape these developments in order to ensure that European values and standards are also taken into account, the continued funding of AI centres is certainly an important first step in this direction.

How do you see Berlin‘s AI ecosystem in terms of linking science, teaching and industry? What makes the university landscape and the community as a whole here in the city so special for you?

KRM: The Berlin ecosystem offers excellent conditions for a research institute like BIFOLD: Berlin has a number of internationally recognised big data and machine learning research groups that already have many years of experience and with which we cooperate successfully. In addition, many other interdisciplinary research institutions and think tanks are based in Berlin, which can stimulate and complement each other.

VM: Berlin is clearly the AI capital: internationally attractive and equipped with a broad ecosystem of AI players. With BIFOLD, we want to build a research beacon around which an ecosystem of spin-offs and application-oriented research initiatives can develop.

Let's look at the future: What are your further plans for the BIFOLD? What milestones are you working towards?

VM: Scientific knowledge and the potential of new AI technologies are constantly increasing. Our mission is to create a research environment here at BIFOLD that is attractive enough to lure the brightest minds in AI to Berlin and jointly develop innovative, efficient, sustainable and explainable AI systems. In order to achieve this, we need the right environment - a location where BIFOLD scientists can meet, exchange ideas and conduct interdisciplinary research. Another goal would be to install a showroom at this location that bridges the gap between science and society and makes AI research accessible to the public.