Bifold – The Berlin Institute for the Foundations of Learning and Data

Building with Molecules

A cooperation project of FZ Jülich and Prof. Dr. Klaus-Robert Müller on manipulation of molecules through Reinforced Learning was announced as a Falling Walls Science Breakthrough of the Year in the category "Engineering and Technology".

AI robot excels in Olympic sport

A Deep Reinforced Learning framework, developed by BIFOLD Co-director Prof. Dr. Klaus-Robert Müller and his colleagues at Korea University, enabled the robot “Curly” to beat top-level athletes in the Olympic sport of curling.

Latest News

2021-02-232020 Pattern Recognition Best Paper Award

2021-02-05BIFOLD Fellow Dr. Wojciech Samek heads newly established AI research department at Fraunhofer HHI

2021-01-15BIFOLD Co-Director Prof. Volker Markl named 2020 ACM Fellow

2021-01-13BIFOLD Research into Machine Learning for Molecular Simulation is among the Top 10 Most Downloaded Physical Science Articles in the Annual Reviews 2020

2021-01-12Resilient Data Management for the Internet of Moving Things: TU Berlin and DFKI Paper was Accepted at BTW 2021

2021-01-05TU Berlin, DFKI and NUS Paper on Parallelizing Intra-Window Join on Multicores was Accepted at SIGMOD 2021

2020-12-29Researchers at FU Berlin Solve Schroedingers Equation with new Deep Learning Method

2020-12-28The BigEarthNet Archive now Contains Sentinel-1 Satellite Images

Events

Mar2021

“Artificial Intelligence and Competitiveness”The Special Committee on Artificial Intelligence in a Digital Age of the European Parliament (AIDA) will hear Prof. Markl on the question
“How to build a competitive and innovative AI sector?“

09:00 – 12:00 CETVirtual

Mission Statement and Goals

BIFOLD, the Berlin Institute for the Foundations of Learning and Data aims to conduct research into the scientific foundations of Big Data and Machine Learning, to advance AI application development, and greatly increase the impact to society, the economy, and science.

BIFOLD will pursue the following strategic priorities in line with the German National AI Strategy:

Research: Conduct high-impact foundational research in the fields of Big Data, Machine Learning and their intersection, to profoundly advance the state-of-the-art in Big Data and Machine Learning methods and technologies as well as attract the world’s best scientists to Germany.
Innovation: Prototype AI technologies, Big Data systems, Data Science tools, Machine Learning algorithms, and support knowledge and technology exchange, to empower innovation in the sciences, humanities, and companies, particularly, startups.
Education: Prepare the next generation of experts in Big Data and Machine Learning, for future academic or industrial careers.