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Machine Learning| June 30, 2022

Facing an inconvenient truth

Jean-Pierre Seifert is professor of security in telecommunications at TU Berlin as well as a researcher at the Berlin Institute for the Foundations of Learning and Data. His research focuses on topics such as hardware security, cryptography technology, and quantum computers. He is also an established specialist for computer and communication security. Along with other experts he has been warning for some time now of the dangers of cyberattacks for private businesses and critical state infrastructures. Even before the start of the war in Ukraine his research demonstrated that almost all hardware solutions used in the commercial sector and even those intended to protect state high security areas do not function adequately.

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Machine Learning| June 29, 2022

The shared scientific identity of Europe

The project Sphere: Knowledge System Evolution and the Shared Scientific Identity of Europe is one of the leading Digital Humanities projects, exploring a large corpus of more than 350 book editions about geocentric cosmology and astronomy from the early days of printing between the 15th and the 17th centuries (Sphaera Corpus) for about 76.000 pages of material. The relatively large size of this humanities dataset presents a challenge to traditional historical approaches, but provides a great opportunity to computationally explore such a large collection of books. In this regard, the Sphere project is an incubator of multiple Digital Humanities (DH) approaches aimed at answering various questions about the corpus, with the ultimate objective to understand the evolution and transmission of knowledge in the early modern period.

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Data Management| June 10, 2022

Flexible adjustment of computing workloads could improve carbon footprint of data centers

To reduce their carbon footprint, more and more computing systems are connected to microgrids to gain direct access to renewable energy sources. However, the local availability of solar and wind energy is highly variable and requires consumers to timely adapt their consumption to the current supply. Researchers from the Berlin Institute for the Foundation of Learning and Data (BIFOLD) have developed a new admission control approach that accepts flexible workloads such as machine learning training jobs only if they can be computed relying solely on renewable excess energy.

Data Management| June 10, 2022

Two demo papers accepted at VLDB 2022

Two demonstration papers of BIFOLD researchers have been accepted at the 48th International Conference on Very Large Databases (VLDB). The VLDB 2022 will take place in Sydney, Australia (and hybrid) in September 05-09, 2022.

Machine Learning| May 12, 2022

Wojciech Samek and Klaus-Robert Mueller Published new book on XAI

To tap the full potential of artificial intelligence, not only do we need to understand the decisions it makes, these insights must also be made applicable. This is the aim of the new book “xxAI – Beyond Explainable AI”, edited by Wojciech Samek, head of the Artificial Intelligence department at the Fraunhofer Heinrich Hertz Institute (HHI) and BIFOLD researcher and Klaus-Robert Mueller, professor of machine learning at the Technical University of Berlin (TUB) and co-director at BIFOLD.

Data Management| May 12, 2022

A framework to efficiently create training data for optimizers

A demo paper co-authored by Robin van de Water, Francesco Ventura, Zoi Kaoudi, Jorge-Arnulfo Quiane-Ruiz, and Volker Markl on “Farming Your ML-based Query Optimizer’s Food” presented at the virtual conference ICDE 2022 has won the best paper award.

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Data Management| May 12, 2022

Nebulastream aims to unify the Cloud, the Edge and the Sensors

NebulaStream, the novel, general-purpose, end-to-end data management system for the IoT and the Cloud, recently announced the release of NebulaStream 0.2.0., the closed-beta release. The System is developed and explored by a team of BIFOLD researchers led by Prof. Dr. Volker Markl. It addresses the unique challenges of the “Internet of Things” (IoT).

Data Management| May 05, 2022

ACM SIGMOD Research Highlight Award

The paper “Efficient Control Flow in Dataflow Systems: When Ease-of-Use Meets High Performance” of six BIFOLD researchers was honored with a 2021 ACM SIGMOD Research Highlights Award. 

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Machine Learning| April 28, 2022

“I want to move beyond purely ‘Explaining’ AI”

BIFOLD researcher Dr. Wojciech Samek has been appointed Professor of Machine Learning and Communications at TU Berlin with effect from 1 May 2022. Professor Samek heads the Department of Artificial Intelligence at the Fraunhofer Heinrich-Hertz-Institute. His goal is to further develop three areas: explainability and trustworthiness of artificial intelligence, the compression of neural networks, and so-called federated leaning. He aims to focus on the practical, methodological, and theoretical aspects of machine learning at the interface to other areas of application.

© BIFOLD
Data Management| March 17, 2022

The Art of Entanglement

The Berlin Institute for the Foundations of Learning and Data (BIFOLD), together with the Science Gallery at Technische Universität Berlin, has announced a new artist in residence program called “Art of Entanglement”. The goal of the program is to combine artistic and scientific perspectives of artificial intelligence.
The program is endowed with a gross total of 30,000 euros. The open call was published on sciencegallery.submittable.com. Applications are open to artists based in Berlin who are interested in working intensively with topics and scientists in the fields of Big Data Management and Machine Learning as well as their intersection.
The selected artist will have the opportunity to realize an artistic project of their choice at BIFOLD, the national Berlin Center of Excellence for Artificial Intelligence at TU Berlin, and the Science Gallery platform.