March 17, 2025. In the joint project AutoQML, the Fraunhofer Institutes IAO and IPA have developed application software of the same name together with seven industrial partners. The open source software AutoQML combines quantum computing and machine learning. This makes quantum machine learning algorithms usable without in-depth specialist knowledge.
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How do companies manage to exploit the potential of digitalization and remain competitive? The use of technologies such as artificial intelligence can help companies to benefit as much as possible from the digital transformation. Machine learning (ML) in particular already plays a major role in the digitalization strategy of many companies and enables more efficient processes and new business models, among other things. However, there is often a lack of specialists. As a result, the implementation of ML solutions is still often associated with a high workload. From data acquisition and the selection of suitable algorithms to the optimization of training, detailed ML expertise is required.
The approach of automated machine learning (AutoML) counteracts these challenges and facilitates the use of artificial intelligence. In particular, the choice of specific ML algorithms is automated. Users therefore need to be less familiar with ML and can concentrate more on their actual processes.
In this context, the innovation of quantum computing promises to establish new solutions that significantly improve the AutoML approach. In addition, quantum computing offers the computing power that is often required for AutoML.
The joint project “AutoQML” addressed this innovation and achieved two key objectives: firstly, the new AutoQML approach was developed. This extends the AutoML principle with newly developed quantum ML algorithms. Secondly, quantum computing takes the AutoML approach to a new level, as certain problems can be solved more efficiently and sustainably with quantum computing than with conventional algorithms.
Under the leadership of the Fraunhofer Institute for Industrial Engineering IAO, the AutoQML open source software developed now provides developers with simplified access to conventional and quantum ML algorithms. The quantum ML components and methods developed have been brought together in the form of a toolbox and made available to the development teams. This enables users to use machine learning and quantum machine learning and to develop automated hybrid overall solutions.
In addition to the Fraunhofer Institute for Manufacturing Engineering and Automation IPA, the companies GFT Integrated Systems, USU GmbH, IAV GmbH Ingenieursgesellschaft Auto und Verkehr, KEB Automation KG, Trumpf and Zeppelin GmbH participated in the project. The solutions developed were tested using specific use cases from the automotive and production sectors.
In the final benchmarking study, the project consortium compared its open source software AutoQML with the best known, classic and quantitative methods. A key result of the study: the automated solutions of the AutoQML software perform at least as well as the best manually found classical and quantitative methods. This gives developers the opportunity to experiment with their own use cases.
The open source software represents an important step towards a broader application of quantum machine learning in industry, which can sustainably increase the competitiveness and innovative strength of companies.
The further market dissemination by the company partners promotes the transfer of research-related high technology to a broad industrial environment and aims to significantly strengthen Germany as an industrial location. The scientific findings from the project have been presented in several publications. The project was funded by the Federal Ministry for Economic Affairs and Climate Protection (BMWK) for a period of three years.
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Photo: Trumpf Group
