Hagenberg. The RISC Institute of the Johannes Kepler University Linz and the resulting RISC Software GmbH are working closely together to develop a new generation of artificial intelligence: symbolic AI.
The currently dominant AI is based on machine learning and large amounts of data. Symbolic AI, on the other hand, uses mathematical rules, logical and algebraic structures and formal models. This makes it explainable, independent of specific data models and resistant to change. This is precisely what is crucial when AI is used in medicine, industry or research. It is also important to note that the two approaches do not contradict each other, but complement each other.
f.l.t.r. Wolfgang Freiseisen, Bruno Buchberger, Carsten Schneider – © RISC Software GmbH, Reprint free of charge
“Symbolic computing is not a niche tool, but a central foundation of modern artificial intelligence – and its importance will grow rapidly in the coming years.”
– Wolfgang Freiseisen, CEO of RISC Software GmbH
One example of this close cooperation is the InProSSA project. Here, symbolic and data-based methods are combined to develop safe and comprehensible AI systems. At the same time, symbolic AI also plays an important role in international research. For example, the RISC Institute is working with the Deutsches Elektronen-Synchrotron (DESY) to analyze data from the Large Hadron Collider at CERN
“Symbolic methods make it possible to model complex systems in science and technology with structural precision and to gain important insights and properties from them – from particle physics to software verification. Together, we are bringing these technologies from research into application.”
– Prof. Dr. Carsten Schneider, Director of the RISC Institute
RISC Software GmbH uses symbolic AI in areas such as medical diagnostics and simulation-based decision-making. In these applications, it is particularly important that AI systems work comprehensibly and reliably.
The RISC Institute is leading a new initiative to create a publishing forum in which, for the first time, the two fields of Symbolic Computation (SC) and Machine Learning (ML) are consciously linked as the two complementary and cooperative approaches to AI: The SCML: A Publishing Forum for Symbolic Computation and Machine Learning. The forum is part of the “Journal of Symbolic Computation” (Elservier Publishing Company), which was founded by RISC in 1985.
An important pioneer of this development is Prof. Dr. Bruno Buchberger, founder of the RISC Institute and initiator of the Hagenberg Software Park. Today, he continues to contribute his experience and ideas to the strategic development of the institute and GmbH.
“When RISC and the Journal of Symbolic Computation were founded in 1965, I already formulated the field of “automatic programming” – which even then some people liked to see as “artificial intelligence” – as an essential part and important application of symbolic computation in the editorial of the journal, and I am pleased that the RISC Institute and the company will jointly advance the tool of SC together with ML in research, development and application in the new phase of AI.”
-University Professor Dr. Bruno Buchberger
(C)OÖN/Weihbold
“Symbolic AI is not an alternative – it is the necessary further development of classic AI. We are shaping this future together.”
– Prof. Dr. Carsten Schneider, Director of the RISC Institute & Wolfgang Freiseisen, CEO of RISC Software GmbH
Das Forschungsinstitut für Symbolisches Rechnen (RISC) wurde 1987 von Bruno Buchberger gegründet und ist ein Institut der Johannes Kepler Universität (JKU) in Linz. Es gehört zum Institut für Mathematik der Technisch-Naturwissenschaftlichen Fakultät und ist Teil des Softwareparks Hagenberg.
Aus dem RISC Institut ging 1992 die RISC Software GmbH hervor. Sie ist seit über 30 Jahren führend in der angewandten Forschung und Produktentwicklung. Als außeruniversitäre Forschungseinrichtung entwickelt das Unternehmen innovative Softwarelösungen in Bereichen wie KI, digitale Zwillinge, Simulation und Optimierung – von der Grundlagenforschung bis zur praxisnahen Anwendung. RISC Software begleitet Organisationen in Industrie und Medizin erfolgreich auf ihrem digitalen Weg.
Ein besonderer Fokus liegt auf der kontinuierlichen Weiterentwicklung der Mitarbeiter*innen – durch gezielte Weiterbildung, interdisziplinären Austausch und enge Kooperationen mit der Wissenschaft.
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