News

Benchmarking Neural Network Explanations

Neural networks have found their way into many every day applications. During the past years they reached excellent performances on various largescale prediction tasks, ranging from computer vision, language processing or medical diagnosis. Even if in recent years AI research developed various techniques that uncover the decision-making process and detect so called “Clever Hans” predictors – there exists no ground truth-based evaluation framework for such explanation methods. BIFOLD researcher Dr. Wojciech Samek and his colleagues now established an Open Source ground truth framework, that provides a selective, controlled and realistic testbed for the evaluation of neural network explanations. The work will be published in Information Fusion.

Two BIFOLD papers ranked as ESI Highly Cited and Hot Papers

Two machine learning papers by BIFOLD researchers received the “Essential Science indicators” (ESI) “Highly Cited” and “Hot Papers” labels for their impact in the science community.

Learning about population health from Twitter texts

Is it possible to learn about the health status of a population and potential side effect of medicationsby analyzing social media conversations? BIFOLD researchers tackled the challenge of making social media posts of medical laypersons concerning diseases and medications understandable for machines. At the BioCreative VII Challenge Evaluation Workshop 2021, they recently explored how a combination of background knowledge and a language transformer model can increase the precision of medical information extraction from Twitter texts.

BIFOLD researchers honored with BBBAW membership

At the “Einsteintag 2021” event on November 26, which honored Albert Einstein – prominent member of a predecessor institution of the Berlin-Brandenburg Academy of Sciences and Humanities (BBAW) – both BIFOLD Co-Director Volker Markl and BIFOLD Fellow Frank Noé were announced as new BBAW members.

Machine Learning consultation

Machine learning (ML) and artificial intelligence (AI) have permeated the sciences and large parts of working life. Today many people use machine learning techniques without being a proven expert. Consequently, many questions and problems arise while using these techniques. BIFOLD accommodates distinguished machine learning experts from different areas and offers a weekly consultation on machine learning for students, but also for companies and institutions.

BIFOLD colloquium "Scalable and fast cloud data management"

Event date: December 06, 2021

Norbert Ritter (University of Hamburg), Felix Gessert (Baqend), and Wolfram Wingerath (Baqend) will talk about their scalable and fast cloud data management research at University of Hamburg and Software-as-a-Service company Baqend.

Science & Startups launches AI initiative

Science & Startups is the association of the four startup services of Freie Universität Berlin, Humboldt-Universität zu Berlin, Technische Universität Berlin and Charité – Universitätsmedizin Berlin. Now they officially launched their new focus programme: K.I.E.Z. (Künstliche Intelligenz Entrepreneurship Zentrum). K.I.E.Z. will be carried out in close cooperation with the Berlin Institute for the Foundations of Learning and Data (BIFOLD).

United against Cyberattacks

BIFOLD Researchers, together with colleagues from Deutsche Commercial Internet Exchange (DE-CIX) and Brandenburg University of Technology, show that the exchange of information about ongoing cyberattacks has the potential to detect and mitigate substantially more attacks and protect critical parts of the Internet infrastructure.

Scheduling computing tasks can reduce emission

To reduce the carbon footprint of cloud computing, researchers from the Berlin Institute for the Foundation of Learning and Data (BIFOLD) investigated the potential of shifting delay-tolerant compute workloads, such as batch processing and machine learning jobs, to times where energy can be expected to be green. Their publication “Let’s Wait Awhile: How Temporal Workload Shifting Can Reduce Carbon Emissions in the Cloud,” was now accepted at Middleware’21. 

Intelligent machines also need control

Dr. Marina Höhne, BIFOLD Junior Fellow, was awarded two million euros funding by the German Federal Ministry of Education and Research to establish a research group working on explainable artificial intelligence.