Fields of mathematics, physics, chemistry, computer science, IT, quantum technology, automatization, digitalization
The greatest challenges of our time include the applications of artificial intelligence, research into networks and the storage, management, processing and application of large databases that are growing exponentially in size. Over the past 15 years, the development of technologies built on artificial intelligence (AI) has been so extensive that this period has often been referred to as the start of a new industrial revolution. Several countries have declared AI research and development to be of strategic importance. Data science and network research, which respond to the challenges posed by ever-growing volumes of data, have also come into focus in recent decades. These three subject fields are closely related, and collectively elevate the concept of digital society to a higher level.
Research into artificial intelligence and related applications is well represented in the research plans of HUN-REN member institutes, including those from the area of social sciences and the humanities – HUN-REN Research Centre for the Humanities (HUN-REN RCH), HUN-REN Research Centre for Economic and Regional Studies (HUN-REN CERS), HUN-REN Hungarian Research Centre for Linguistics (HUN-REN NYTK), HUN-REN Centre for Social Sciences (HUN-REN CSS); of life sciences – HUN-REN Institute of Experimental Medicine (HUN-REN IEM), HUN-REN Biological Research Centre, Szeged (HUN-REN BRC Szeged), HUN-REN Research Centre for Natural Sciences (HUN-REN RCNS); and of mathematics and natural sciences – HUN-REN Research Centre for Astronomy and Earth Sciences (HUN-REN CSFK), HUN-REN Alfréd Rényi Institute of Mathematics (HUN-REN Rényi Institute), HUN-REN Institute for Computer Science and Control (HUN-REN SZTAKI), a part of HUN-REN RCNS and the HUN-REN Wigner Research Centre for Physics (HUN-REN Wigner RCP).
Through its Horizon Europe program, the European Union is placing special emphasis on the Digital Europe program. One of the crucial pillars of this initiative also relies on the artificial intelligence program, which is discussed here in a broad sense and includes digital network research and the science of big data.
The HUN-REN Alfréd Rényi Institute of Mathematics is among the top centres for mathematical research both at the national and European levels. The Institute conducts research in all major fields of mathematics (algebra, analysis, discrete mathematics, geometry, and topology). Research on the relationships between groups and graphs, as well as the growth of groups, is highlighted as an important direction of algebraic research. Researchers carry out noise-sensitivity research based on analytical methods to determine how the outputs of processes depend on tiny changes in the inputs.
The research groups at the Institute focusing on graph theory and combinatorics in the area of discrete mathematics have long been renowned and acknowledged. These subjects are connected to important fields such as large networks, algorithm theory, and artificial intelligence. The work of the traditional discrete and computational geometry groups, as well as later groups studying algebraic geometry and differential topology, should be highlighted as key directions of geometric research.
Research into artificial intelligence includes network science, a discipline Hungary plays a leading role in both on the theoretical and practical level. The methods of network research are applicable when dynamic data clusters that are dispersed or exist in different data sets are to be matched and analyzed. As a result, network science significantly contributes to big data research, and it is also closely related to other fields of science (data visualization, complexity science, artificial intelligence).
Machine learning methods enable computers to learn rules, functions and decisions automatically, without human intervention or help. The deep learning research conducted at the HUN-REN Institute for Computer Science and Control (HUN-REN SZTAKI) aims to explore, among other areas, how robust a system applying the methods of deep learning is, i.e. whether the introduction of a new training point is capable of deteriorating the system’s properties. HUN-REN SZTAKI’s objectives include controlling complex systems using machine learning algorithms, teaching an optimal control signal, and the provision of stability for the controlled system.
One of the most important applications of AI today is the practical use of machine vision. HUN-REN SZTAKI’s research builds on its results in the fields of sensor data analysis, sensor fusion, and model-based control for both ground vehicles and aircraft. Within the frames of European and domestic research projects and in cooperation with industrial market players (Airbus, Bosch, Knorr-Bremse), HUN-REN SZTAKI aims to produce theoretical results that are applicable in practice.
The Institute of Philosophy at the HUN-REN Research Centre for the Humanities (HUN-REN RCH) explores the history of Hungarian philosophy in a European context, and also conducts research in the field of epistemology and metaphysics in a constant dialogue with artificial intelligence research. The HUN-REN RCH Institute for Literary Studies manages and publishes the literary history corpus of the Hungarian national cultural heritage, and also performs research and development aimed at the creation of new methodologies for digital literary history, electronic textology and philology.
Several planned research projects of the HUN-REN Centre for Economic and Regional Studies (HUN-REN CERS) focus on how various AI applications can be used to solve problems of analysis and decision making. These include the prediction of economic data series using neural networks, the identification of outliers in complex administrative databases, and the estimation of real preferences using machine learning methods.
The results of big data research, primarily those associated with algorithm theory, have provided the foundations for significant breakthroughs in artificial intelligence in the fields of robotics, autonomous transportation and natural language processing (NLP). The strategic aim supported by HUN-REN SZTAKI is to build a model for the Hungarian language and enable computer systems to communicate in natural Hungarian. In cooperation with partners of the language and speech technology platform, the HUN-REN Hungarian Research Centre for Linguistics (HUN-REN NYTK) is developing a basic language technology infrastructure for AI purposes that is to contain freely accessible digitized and annotated corpora that are orders of magnitude larger than those available today.
The HUN-REN Centre for Social Sciences (HUN-REN CSS) has been the leading Hungarian centre for applying AI-based big data methods for the purposes of social sciences and text analysis for some time. Its research involves creating and applying data mining and machine learning analysis techniques to satisfy new fields of activity.
The portfolio of the HUN-REN Research Centre for Natural Sciences (HUN-REN RCNS) includes machine learning methods, especially the application of deep learning techniques for imaging and AI-supported data analysis in the field of medical biology. Their results in MRI imaging achieved with the help of AI have been considered outstanding internationally.
Of the research subjects related to big data explored by the HUN-REN Research Centre for Astronomy and Earth Sciences (HUN-REN CSFK), the creation of the Fly’s Eye system, which observes the sky in its entirety, must be highlighted, as well as the HUN-REN CSFK’s participation in large-scale spectroscopic and photometric sky surveys (LSST, WEAVE, Gaia). The scientists working at HUN-REN CSFK aim to get better insights into the physics, dynamics, birth, and development of stars, star systems, and galaxies, as well as to understand the activity of the Sun and other stars and explore their impact on our planet. The HUN-REN Wigner Research Centre for Physics (HUN-REN Wigner RCP), in cooperation with CERN and the Budapest University of Technology and Economics (BME), has developed the Collaboration Spotting Tool to visualize large data sets in a fast and effective manner.
One of the most important missions of the HUN-REN Centre for Ecological Research (HUN-REN CER) is to develop a program based on big data grounds to systematically collect long-term data series, maintain databases, and analyze them statistically and using the methods of bioinformatics, thereby establishing the basis for utilizing such data for social and economic purposes.
HUN-REN SZTAKI and HUN-REN Wigner RCP have jointly established a cloud service for researchers with the primary aim of making the cloud suitable for supporting special artificial intelligence applications. Within the HUN-REN Cloud, a multi-server park environment was created where large AI and big data applications can be run effectively.
New tools and equipment leveraging the potential of the specific laws of quantum mechanics, today's emerging field of quantum technology open new vistas in the area of communications and computing sciences. Key research areas at the HUN-REN Wigner Research Centre for Physics include quantum informatics, the physical basis of quantum bits, and the application of remote access quantum computers.