Quantum computing

Quantum computing represents a frontier in computational technology, offering unparalleled potential for solving complex problems. However, this revolutionary field is not without its challenges. In this blog post, we will explore the vast potential of quantum optimization, identify the key challenges that lie ahead, and discuss strategies for navigating the path forward in this exciting domain.

Reinforcement learning is often the most suitable AI solution for a range of applications in the sectors of autonomous systems, healthcare, and communication, due to the training method. Nevertheless, the nature of these tasks makes data collection potentially resource intensive or in some cases even unachievable. This is where reinforcement learning could benefit from embedding quantum computing methods since hybrid quantum-classical reinforcement learning was empirically shown to need less training steps to reach convergence. Fraunhofer IKS is researching solutions that are also suitable for use in industry.

AI has paved the way for better and faster diagnostics in the realm of medical imaging. However, challenges specific to the field of medicine, notably the scarcity of data, can impede its performance. This article looks into the enhancement of AI algorithms using quantum technology for the improvement of medical diagnostics, showcasing how quantum computing can tackle existing challenges in AI and offer unique opportunities for healthcare.

As an emerging technology, quantum computing is expected to unleash disruptive potential in numerous industrial application areas. Those are for example in logistics, the pharmaceutical industry and the medical sector, or in all areas where machine learning (ML) is used. In practice, however, it is clear that numerous developments still have to be made in both, the field of quantum hardware as well as the associated software.

Quantum computing promises nothing less than to revolutionize data processing. But what exactly does this mean for a specific company and its business model? Fraunhofer IKS provides answers to this and other questions by working closely together with companies in tailored workshops.

Quantum computing still has a reputation as a very experimental cutting-edge technology. And yet, the Fraunhofer Institute for Cognitive Systems (IKS) is working on harnessing its huge potential for industry. One example of this is the QuaST project.

Neural networks are not robust. The development of reliable predictors requires systematic methods to both assess their quality and to gain confidence in their correctness. Quantum computing can provide assistance here.

The “QuaST” (quantum-enabling services and tools for industrial applications) project, led by Fraunhofer IKS, is now underway. Jeanette Lorenz, Senior Scientist at the Quantum Computing Department of Fraunhofer IKS, heads the project. In this interview, she explains what QuaST is all about.

Even at a young age, Jeanette Lorenz knew she wanted to go into science. Now she works at Fraunhofer IKS researching how to make reliable and robust quantum computing possible. Part 13 of our employee portraits series.

Quantum computing has the potential to train artificial intelligence in medical diagnostics more efficiently. This could make diagnoses more accurate even when there is little data available. In the future, medical professionals expect to see improvements in the screening, diagnosis and progress monitoring of brain tumors, for example.

Fraunhofer IKS is carrying out research into safe software applications for quantum computers. The work is part of the new Bavarian initiative Munich Quantum Valley.