Fields of mathematics, physics, chemistry, computer science, IT, automatization and 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 ten 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 together bring the concept of digital society to a higher level.
Research into artificial intelligence and related applications is well represented in the research plans of ELKH member institutes, including those from the area of humanities and social sciences – Research Centre for The Humanities (BTK), Research Centre for Economic and Regional Studies (KRTK), Research Institute for Linguistics (NYTI), Centre for Social Sciences (TK); of life sciences – Institute of Experimental Medicine (KOKI), Biological Research Centre (BRC), Research Centre for Natural Sciences (TTK); and of natural sciences – Research Centre for Astronomy and Earth Sciences (CSFK), Alfréd Rényi Institute of Mathematics (Rényi), Institute for Computer Science and Control (SZTAKI), a part of TTK and the Wigner Research Centre for Physics (Wigner FK).
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 the broad sense, and includes digital network research and the science of big data. At present, Hungary is not among the leading countries in the fields of artificial intelligence or research into neural networks. However, our country is at the forefront owing to the results achieved by Hungarian scientists in theoretical mathematics, the theory of algorithms and network research.
The Alfréd Rényi Institute of Mathematics is among the top centers for mathematical research both at the national and European levels. Research into all major fields of mathematics (algebra, analysis, discrete mathematics, geometry and topology) is conducted at the Institute. Research on the relationships of groups and graphs and the growth of groups should be highlighted as an important direction of algebraic research. Based on analytical methods, researchers carry out noise-sensitivity research 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 discrete mathematics area 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 and 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 contributes to big data research significantly, and it is also closely related to other fields of science (data visualization, complexity science, artificial intelligence).
Machine learning methods enable the computer to learn rules, functions and decisions automatically, without human intervention or help. The deep learning research of the Institute for Computer Science and Control (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. SZTAKI’s objectives include controlling complex systems with machine learning algorithms, the teaching of 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. 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), SZTAKI aims to produce theoretical results that are applicable in practice.
The Institute of Philosophy at the Research Centre for the Humanities (BTK), which 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 BTK 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 Centre for Economic and Regional Studies (KRTK) 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 with neural networks, the identification of outliers in complex administrative databases and the estimation of real preferences with 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 SZTAKI is to build a model for the Hungarian language and to enable computer systems to communicate in natural Hungarian. In cooperation with the partners of the language and speech technology platform, the Research Institute for Linguistics (NYTI) is developing a basic language technology infrastructure for AI purposes that is to contain freely accessible digitized and annotated corpora that are larger by orders of magnitude than those available today.
The Centre for Social Sciences (TK) has been the leading Hungarian center for the application of AI-based big data methods for the purposes of social sciences and text analysis for some time. Its research is creating and applying data mining and machine learning analysis techniques to satisfy new fields of activity.
The portfolio of the Research Centre for Natural Sciences (TTK) 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 with the help of AI have been considered outstanding internationally.
Of the research subjects related to big data explored by the Research Centre for Astronomy and Earth Sciences (CSFK), the creation of the Fly’s Eye system, which observes the sky in its entirity, must be highlighted, as well as the CSFK’s participation in large-scale spectroscopic and photometric sky surveys (LSST, WEAVE, Gaia). The scientists working at the CSFK aim to get better insights into the physics, dynamics, birth and development of stars, star systems and galaxies and to understand the activity of the Sun and other stars and explore their impact on our planet. The Wigner Research Centre for Physics (Wigner FK), in cooperation with CERN and the Budapest University of Technology and Economics (BME), created the Collaboration Spotting Tool to visualize large data sets in a fast and effective manner.
One of the most important missions of the Centre for Ecological Research (ÖK) is to create a program on big data grounds to systematically collect long-term data series, to maintain the databases and to analyze them statistically and with the methods of bioinformatics, thereby establishing the basis for using such data for social and economic purposes.
SZTAKI and Wigner FK have jointly established a cloud service for researchers with the primary aim of making the cloud suitable for supporting special artificial intelligence applications. A multi-server park environment was created within the MTA Cloud where large AI and big data applications can be run effectively.