TUM and LMU launch Munich Center for Machine Learning (MCML)

Computers today can link data and make predictions intelligently thanks to advances in computer power. (Image: tum.de. Credit: A. Heddergott)

The Technical University of Munich (Technische Universität München → TUM) and Ludwig-Maximilians-Universität München (LMU) have launched the Munich Center for Machine Learning (MCML). MCML is funded by Germany’s Federal Ministry of Research.

Artificial intelligence and machine learning are crucial technologies for today’s and tomorrow’s digital economy. TUM says that MCML will be connecting key areas of expertise from computer science, data science, and statistics.

What is AI?

AI or artificial intelligence includes software technologies that make machines and other devices think like humans. They also make them behave like human beings. Artificial intelligence contrasts with natural intelligence, which is what we have.

Many experts believe that we can only call it AI if it performs at least as well as we can. ‘Perform,’ in this case, refers to computational speed, capacity, and accuracy.

A human being can learn as he or she goes along. Artificial intelligence also has this ability. We call it machine learning.

MCML coordinator Daniel Cremers

Gottfried Wilhelm Leibniz Prize (Leibniz Prize) winner Prof. Dr. Daniel Cremers, from TUM, is one of the coordinators of MCML. The Leibniz Prize is a program of the German Research Foundation. It awards prizes “to exceptional scientists and academics for their outstanding achievements in the field of research.”

With new algorithms and advances in computing power, computers can pinpoint relationships and link data intelligently . They can also make predictions and draw conclusions.

This forms the basis for new self-controlling systems in industrial manufacturing and logistics. It also forms the basis for new medical devices.

MCML – fifteen teams

Prof. Dr. Daniel Cremers is a well-known expert in neural networks and deep-learning methods. Specifically in the field of computer vision.

Fifteen teams from the fields of computer science, statistics, and data science from TUM and LMU have joined forces. They aim to advance machine learning and pattern recognition methods further.

Prof. Dr. Thomas Seidl, from LMU, is head of the new facility. He is Chair of Database Systems and Data Mining at LMU.

Processing many different types of data

According to a TUM press release:

“The new Competence Center is dedicated to the processing of various data types. Weather data, stock prices, voice recordings or video sequences, for example, are all what is called a time series. Improving the deep-learning methods for such data series, advances the field of computer vision – an important component of autonomous driving.”

“Social media, modern genome research and the diverse use of sensors today also produce enormous amounts of data, and the MCML teams are researching new methods to analyze this data.”

The Federal Ministry of Education and Research will fund MCML as well as other competence centers for machine learning for four years. By the end of the four years, they will have received €7.5 million ($8.53 m).

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