Digitalization

Fields of mathematics, physics, chemistry, computer science, IT, automatization and digitalization

The greatest challenges of our time include the applications of artificial intelligence, research of networks and the storage, management, processing and application of large databases size of which is growing exponentially. In the past ten years the development of technologies built on artificial intelligence (AI) has been so large-scale that this time is often 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 the ever-growing amount of data, have also come into the focus of attention in the past decades. These three subject fields are closely related, and together they place the concept of digital society at a higher level.

Research into artificial intelligence and related applications  are 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 (SZBK), Research Centre for Natural Sciences (TTK); or 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).

The European Union through its Horizon Europe program puts a 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, including 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 the research of neural networks. However, our country is at the forefront owing to the results of Hungarian scientists in theoretical mathematics, the theory of algorithms and network research.

The Alfréd Rényi Institute of Mathematics is one of the important centers for mathematical research both at the national and the European level. Research into all major branches of mathematics (algebra, analysis, discrete mathematics, geometry, topology) is conducted in the Institute. Research on the relationships of groups and graphs and the growing of groups should be highlighted out of the algebraic research directions. Based on analytical methods, they carry out noise-sensitivity research to determine how the outputs of processes depend on tiny changes in the input. 

The research groups focusing on graph theory and combinatorics in the discrete mathematics branch of the Institute 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 the later groups studying algebraic geometry and differential topology groups must be highlighted out of the geometric research directions. 

Research into artificial intelligence includes network science, in which discipline Hungary plays a leading role both in the theoretical and the practical branches. 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, decisions automatically, without human intervention or help. The deep learning research of the Institute for Computer Science and Control (SZTAKI) aims to explore among others how robust a system applying the methods of deep learning is, i.e., whether the introduction of a new training point is able to deteriorate the system’s properties. SZTAKI’s goals 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 their results achieved in the fields of sensor data analysis, sensor fusion and model based control both for 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, 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 methodology 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 of algorithm theory, provided the foundation 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 digitized and annotated freely accessible corpora larger by magnitudes than today. 

The Centre for Social Sciences (TK) is the leading Hungarian center for applying AI-based Big Data methods for the purposes of social sciences and text analysis. Their research creates data mining and machine learning analysis techniques for a new field. 

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. 

Out of the research subjects related to Big Data in the Research Centre for Astronomy and Earth Sciences (CSFK), the creation of the Fly’s Eye system, which observes the whole sky 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.