On January 15, 2020 the Berlin Institute for the Foundations of Learning and Data (BIFOLD) was officially announced at Forum Digital Technologies in Berlin. Please also see the Technische Universität Berlin (in German).
MESSAGE FROM THE DIRECTORS
As you know, data has become an enormously important production factor. Together with intelligent algorithms, they form the cornerstone of Artificial Intelligence. It is only through the combination of Big Data and Machine Learning that the great successes of AI have become possible, which we have seen in recent years and will continue to see in the future.
In Berlin, too, with the two competence centers BBDC and BZML, we have already achieved internationally highly regarded successes, from basic research and open source software development to very successful spin-offs.
With BIFOLD, Berlin now has a technological research beacon around which an entire ecosystem of spin-offs and application-oriented research labs can develop. This will enable us to attract top international talent to Berlin and make AI a relevant economic factor for Berlin.
The special thing about BIFOLD is that we are avoiding the mistake that unfortunately is commonly made in science, namely, to consider partial aspects of AI in isolation. For example, the best algorithms will not help us, if we do not simultaneously research and develop the underlying technologies and systems in which real data is efficiently provided and processed jointly with analysis algorithms.
With respect to data – i.e., my research area in BIFOLD – important challenges lie, for example, in the processing of widely geographically distributed data, i.e., in some cases globally distributed data, which cannot always be physically combined on an infrastructure for analysis due to data protection laws as well as for technical reasons.
Think, for example, of the globally distributed vehicle data of an automobile manufacturer or patient data that is collected across hospitals. Thus, we need new data processing architectures, that on the one hand handle the growing data streams efficiently, and on the other hand reliably protect the privacy and rights of data producers.
An additional challenge is the exponential growth of sensor data, the complete capture of which would quickly exceed the capacities of our global cloud infrastructures and is neither necessary nor sensible.
We are therefore developing new approaches to preprocess data at the source, at the so-called edge, in such a way that we only transfer and store data that is relevant for a particular analysis. This is not only economically more efficient, but also ecologically more sensible and less questionable in terms of data protection.
The systems that we develop should make ideal use of the growing variety of memory and chip technologies and at the same time be so easy to operate, i.e., function in a largely automated manner, that would not require users to hold a five-year computer science degree, in order to work with them.
Because computer scientists, as you all know, are currently a painful bottleneck in the job market.
You see, especially for the commercialization and economic success of basic research, it is extremely important to look at the entire stack of hardware, software, data, algorithms, and the broad ecosystem of applications holistically, and preferably together in a research institute of critical size.
And that’s why I am particularly pleased as a database researcher and thank the German Federal Ministry of Education and Research (BMBF) and the State of Berlin, that with BIFOLD we are now creating the conditions to be able to do exactly this in Berlin.
As you know, data has become an enormously important production factor. Together with intelligent algorithms, they form the cornerstone of Artificial Intelligence. It is only through the combination of Big Data and Machine Learning that the great successes of AI have become possible, which we have seen in recent years and will continue to see in the future.
In Berlin, too, with the two competence centers BBDC and BZML, we have already achieved internationally highly regarded successes, from basic research and open source software development to very successful spin-offs.
With BIFOLD, Berlin now has a technological research beacon around which an entire ecosystem of spin-offs and application-oriented research labs can develop. This will enable us to attract top international talent to Berlin and make AI a relevant economic factor for Berlin.
The special thing about BIFOLD is that we are avoiding the mistake that unfortunately is commonly made in science, namely, to consider partial aspects of AI in isolation. For example, the best algorithms will not help us, if we do not simultaneously research and develop the underlying technologies and systems in which real data is efficiently provided and processed jointly with analysis algorithms.
With respect to data – i.e., my research area in BIFOLD – important challenges lie, for example, in the processing of widely geographically distributed data, i.e., in some cases globally distributed data, which cannot always be physically combined on an infrastructure for analysis due to data protection laws as well as for technical reasons.
Think, for example, of the globally distributed vehicle data of an automobile manufacturer or patient data that is collected across hospitals. Thus, we need new data processing architectures, that on the one hand handle the growing data streams efficiently, and on the other hand reliably protect the privacy and rights of data producers.
An additional challenge is the exponential growth of sensor data, the complete capture of which would quickly exceed the capacities of our global cloud infrastructures and is neither necessary nor sensible.
We are therefore developing new approaches to preprocess data at the source, at the so-called edge, in such a way that we only transfer and store data that is relevant for a particular analysis. This is not only economically more efficient, but also ecologically more sensible and less questionable in terms of data protection.
The systems that we develop should make ideal use of the growing variety of memory and chip technologies and at the same time be so easy to operate, i.e., function in a largely automated manner, that would not require users to hold a five-year computer science degree, in order to work with them.
Because computer scientists, as you all know, are currently a painful bottleneck in the job market.
You see, especially for the commercialization and economic success of basic research, it is extremely important to look at the entire stack of hardware, software, data, algorithms, and the broad ecosystem of applications holistically, and preferably together in a research institute of critical size.
And that’s why I am particularly pleased as a database researcher and thank the German Federal Ministry of Education and Research (BMBF) and the State of Berlin, that with BIFOLD we are now creating the conditions to be able to do exactly this in Berlin.
We would like to thank you very much for the confidence you have placed in us to establish our BIFOLD AI Center! And I would like to assure you that the money is in good hands, because Berlin has always been a stronghold of AI research and has been so for a quarter of a century. From my ranks alone, 33 professors have emerged and I am not the only one in this center who has produced successful young scientists! My esteemed namesake has already spoken about the many spin-offs.
What is it all about: the technical foundations of AI are machine learning and big data. This is exactly what we are researching here and, as you have already heard, this is a unique combination. We want to advance the basics of AI. Why? In engineering disciplines, for example, in the automotive sector, it sometimes takes a decade for a clever invention to find its way into our new car. AI is different: progress in the fundamentals translates very quickly into a new product or service, and fast can mean just a few weeks. Fortunately, for someone as well versed in mathematics as I am, this means that the saying really applies here: there is nothing more practical than a good theory.
I would like to give an example of our research. Until about 4 years ago, everyone was always complaining that machine learning methods like deep learning are black boxes, one doesn‘t know what happens in them – a real absurdity for an application (just imagine a medical diagnosis without transparency)! We could change that here in our centre, establishing explainable AI (made in Germany/Berlin) as we were able to finally solve a complicated mathematical problem. Now everyone can use our new technique to understand, improve and make their AI methods safe and trustworthy. Another important task of the center is the broad application of AI in the sciences of physics, chemistry, medicine and the digital humanities – something particularly new all with very strong partners in Berlin — researchers of international top standing only a subway ride away.
Our country urgently needs AI professionals. There are still very few of them, so we have to train far more than ever before – a great challenge for our center, where we will happily include the new professorships to be created. Only 5 years ago I had about 50 students in my special lecture on machine learning, now 637 are registered. With this exponential increase, soon half of Berlin will be sitting in my class …
If we want to create many new jobs, where will all the applicants come from? From all over the world and of course from Germany and Berlin. Everyone wants to go to Berlin, that’s our incredible location advantage and everyone loves this city (me too) and this city inspires us all to create new ideas.
We would like to thank you very much for the confidence you have placed in us to establish our BIFOLD AI Center! And I would like to assure you that the money is in good hands, because Berlin has always been a stronghold of AI research and has been so for a quarter of a century. From my ranks alone, 33 professors have emerged and I am not the only one in this center who has produced successful young scientists! My esteemed namesake has already spoken about the many spin-offs.
What is it all about: the technical foundations of AI are machine learning and big data. This is exactly what we are researching here and, as you have already heard, this is a unique combination. We want to advance the basics of AI. Why? In engineering disciplines, for example, in the automotive sector, it sometimes takes a decade for a clever invention to find its way into our new car. AI is different: progress in the fundamentals translates very quickly into a new product or service, and fast can mean just a few weeks. Fortunately, for someone as well versed in mathematics as I am, this means that the saying really applies here: there is nothing more practical than a good theory.
I would like to give an example of our research. Until about 4 years ago, everyone was always complaining that machine learning methods like deep learning are black boxes, one doesn‘t know what happens in them – a real absurdity for an application (just imagine a medical diagnosis without transparency)! We could change that here in our centre, establishing explainable AI (made in Germany/Berlin) as we were able to finally solve a complicated mathematical problem. Now everyone can use our new technique to understand, improve and make their AI methods safe and trustworthy. Another important task of the center is the broad application of AI in the sciences of physics, chemistry, medicine and the digital humanities – something particularly new all with very strong partners in Berlin — researchers of international top standing only a subway ride away.
Our country urgently needs AI professionals. There are still very few of them, so we have to train far more than ever before – a great challenge for our center, where we will happily include the new professorships to be created. Only 5 years ago I had about 50 students in my special lecture on machine learning, now 637 are registered. With this exponential increase, soon half of Berlin will be sitting in my class …
If we want to create many new jobs, where will all the applicants come from? From all over the world and of course from Germany and Berlin. Everyone wants to go to Berlin, that’s our incredible location advantage and everyone loves this city (me too) and this city inspires us all to create new ideas.