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Investment in innovation: Rhineland-Palatinate funds deep learning at DFKI

| Press release | Machine Learning & Deep Learning

DFKI receives state funding of 605,000 euros for the project "GPU4GenAI - Computing Infrastructure for Increasing Demand through Generative AI". Science Minister Clemens Hoch handed over the funding decision during his visit to DFKI in Kaiserslautern. The approved funds will be used to procure new high-performance computers that will allow data from industry and business to be analyzed and interpreted using deep learning in the future.

Minister Clemens Hoch (center left) presents the funding decision to CFO Helmut Ditzer (center right). Right: Prof. Dr. Antonio Krüger, CEO DFKI, left: Prof. Dr. Andreas Dengel, Managing Director DFKI Kaiserslautern.

"DFKI conducts excellent research in the key technology of artificial intelligence. The research center is one of the most renowned not only nationally but also internationally. The scientists at the Kaiserslautern site produce outstanding research achievements. For consistently good work at the highest level, not only bright minds are crucial, but also an equally efficient infrastructure. I am therefore delighted that new high-performance computers are being purchased for the research center with the help of the state funding for the 'GPU4GenAI' project. This will enable data from industry and business to be analyzed and interpreted quickly and efficiently in the future," emphasized Science Minister Clemens Hoch at the presentation of the funding decision in Kaiserslautern.
 
Prof. Dr. Andreas Dengel, Excecutive Director of DFKI in Kaiserslautern: "A high-performance AI computing infrastructure is the basis for making state-of-the-art AI technologies available to business and industry. The examples from our numerous collaborations show how this not only accelerates machine learning, but also the transfer to industry in the truest sense of the word. With GPU4GenAI, we will further expand our deep learning data center and strengthen it, especially with regard to the increasing demand from generative AI."
 
In recent years, deep learning has established itself as a key technology for solving complex problems. At its core are artificial neural networks that mathematically simulate the structures and information processing of the human brain. In some cases, deep learning approaches achieve higher performance than the human brain. They can generally be used to classify patterns in existing data sets, find correlations, uncover behaviours or detect anomalies in order to support decisions, make predictions or optimize processes.