Author: Halyna Hyryavets

Kategórie
General

Online lecture: AI Responsibility Gaps

Online lecture: AI Responsibility Gaps


AI Accountability Dialogue Series


On 12 February 2026, we are organising the opening online lecture of the AI Accountability Dialogue Series, focusing on the timely topic of “responsibility gaps” in artificial intelligence systems. Our guest speakers will be Daniela Vacek and Jaroslav Kopčan.


Daniela Vacek works at the Institute of Philosophy of the Slovak Academy of Sciences (SAS), the Kempelen Institute of Intelligent Technologies (KinIT), and the Faculty of Arts of Comenius University in Bratislava. She is a laureate of the ESET Science Award 2025 in the category Outstanding Young Scientist in Slovakia under 35. She is a Slovak philosopher specializing in the ethics of artificial intelligence, responsibility, analytic aesthetics, and philosophical logic. She leads an APVV-funded project entitled Philosophical and Methodological Challenges of Intelligent Technologies (TECHNE).

Jaroslav Kopčan works as a research engineer at the Kempelen Institute of Intelligent Technologies (KinIT), where he specializes in natural language processing (NLP) and explainable artificial intelligence (XAI). His research focuses on automated content analysis and explainability techniques for underrepresented languages. He works on the development of interpretable NLP systems and tools, with an emphasis on knowledge distillation.

Date and Time: Thursday, 12 February 2026 | 10:00 CET

Venue: Online | Free participation 

The lecture will be conducted in English.

Registration

There is an extensive debate on responsibility gaps in artificial intelligence. These gaps correspond to situations of normative misalignment: someone ought to be responsible for what has occurred, yet no one actually is. They are traditionally considered to be rooted in a lack of adequate knowledge of how an artificial intelligence system arrived at its output, as well as in a lack of control over that output. Although many individuals involved in the development, production, deployment, and use of an AI system possess some degree of knowledge and control, none of them has the level of knowledge and control required to bear responsibility for the system’s good or bad outputs. To what extent is this lack of knowledge and control at the level of outputs present in contemporary AI systems?

From a technical perspective, relevant knowledge and control are often limited to the general properties of artificial intelligence systems rather than to specific outputs. Actors typically understand the system’s design, training processes, and overall patterns of behaviour, and they can influence system behaviour through design choices, training methods, and deployment constraints. However, they often lack insight into how a particular output is produced in a specific case and do not have reliable means of intervention at that level.

The lecture will offer several insights into these questions. In addition, we will show that the picture is even more complex. There are different forms of responsibility, each associated with distinct conditions that must be met. Accordingly, some forms of responsibility remain unproblematic even in the case of AI system outputs, while others prove to be more challenging.

NEWS
BeeGFS in Practice — Parallel File Systems for HPC, AI and Data-Intensive Workloads 6 Feb - This webinar introduces BeeGFS, a leading parallel file system designed to support demanding HPC, AI, and data-intensive workloads. Experts from ThinkParQ will explain how parallel file systems work, how BeeGFS is architected, and how it is used in practice across academic, research, and industrial environments.
When a production line knows what will happen in 10 minutes 5 Feb - Every disruption on a production line creates stress. Machines stop, people wait, production slows down, and decisions must be made under pressure. In the food industry—especially in the production of filled pasta products, where the process follows a strictly sequential set of technological steps—one unexpected issue at the end of the line can bring the entire production flow to a halt. But what if the production line could warn in advance that a problem will occur in a few minutes? Or help decide, already during a shift, whether it still makes sense to plan packaging later the same day? These were exactly the questions that stood at the beginning of a research collaboration that brought together industrial data, artificial intelligence, and supercomputing power.
Who Owns AI Inside an Organisation? — Operational Responsibility 5 Feb - This webinar focuses on how organisations can define clear operational responsibility and ownership of AI systems in a proportionate and workable way. Drawing on hands-on experience in data protection, AI governance, and compliance, Petra Fernandes will explore governance approaches that work in practice for both SMEs and larger organisations. The session will highlight internal processes that help organisations stay in control of their AI systems over time, without creating unnecessary administrative burden.
Kategórie
Calls-Current General

CURRENT FFPLUS CALL

CURRENT FFPLUS CALL

European startups and small and medium-sized enterprises working with artificial intelligence, data, or computationally intensive models currently have the opportunity to take part in an attractive call aimed at supporting innovative research and development. The call targets companies that want to further advance their technological solutions, validate them in real-world conditions, and harness the potential of cutting-edge European supercomputing infrastructure.

It is an opportunity that combines funding, access to state-of-the-art computing resources, and international collaboration, while allowing companies to focus exclusively on research and innovation without the administrative and financial burden typical of many other grant schemes. The call supports applied research with clear innovation potential and is particularly suitable for enterprises that already have experience in using HPC infrastructure and wish to further build on this expertise.

Grants for startups and SMEs of up to €300,000 for innovations in AI and HPC

Startups and small and medium-sized enterprises can receive a grant of up to €300,000 to implement innovative projects using supercomputers and high-performance computing (HPC).

In brief:

  • funding for innovative research with no requirement for own co-financing and no equity taken,
  • free access to European high-performance computing resources,
  • the possibility to form a consortium with another company or a research institution.

The supported innovation project must last no longer than 10 months and may start no earlier than 1 September 2026. The call targets companies that already have practical experience in using HPC infrastructure.

The call is already open. Applications can be submitted from 3 to 25 February 2026 on a first-come, first-served basis. The maximum number of submitted projects is limited to 250.

More information

BACK
Kategórie
Success-Stories General

AI pomáha zachraňovať ženské životy

Success story: AI Helps Save Women’s Lives

Fear of breast cancer is a silent companion for many women. All it takes is an invitation to a preventive screening, a single phone call from a doctor, or the wait for test results—and the mind fills with questions: “Am I okay?” “What if I’m not?” “Could something be missed?”
Even when screening confirms a negative result, the worries often persist.

That is precisely why it makes sense to seek new ways to detect cancer as early as possible—not to replace doctors, but to help them see more, faster, and with greater confidence. And this is where artificial intelligence enters the story. Not as a sci-fi technology, but as a tool that may one day help protect lives.

A Slovak research team from the University of Žilina has brought together medicine, artificial intelligence, and European supercomputers in a joint project with a clear goal: to improve the accuracy of breast cancer detection and support doctors in the interpretation of mammographic images.

Challenge

Mammography generates enormous volumes of imaging data. A single project may work with hundreds of thousands of images at extremely high resolution. The Slovak team from the University of Žilina worked with more than 434,000 mammograms, representing data on the scale of several terabytes.

At the same time, the team decided to use a foundation model—a massive neural network with nearly a billion parameters, originally developed for general image analysis. Such a model has enormous potential, but it also places extreme demands on computing power, memory, and data processing speed.

It quickly became clear that standard research infrastructure was simply not sufficient for such a volume of computations. Without a supercomputer, the project could not have continued.

Solution

The breakthrough came when the project gained access to the AI Factory VEGA in Slovenia, which is part of the European EuroHPC initiative. For the first time, Slovak medical AI research was able to work on infrastructure with a level of performance it had never had access to before.

On this platform, state-of-the-art NVIDIA H100 graphics accelerators, designed specifically for artificial intelligence, were available. The researchers built a complete technological pipeline there, from processing mammographic images to training the model itself.

First, the data had to be cleaned, optimized, and prepared so it could be loaded efficiently during computation. Then the process of adapting the large AI model began, as it “learned” to understand the subtle details of mammography. This was not a one-off computation—it was an incremental process in which the model improved step by step.

The supercomputer thus became not only a powerful tool but a key partner in research. It made it possible to do what was previously virtually impossible: to train a massive medical AI model at once using an enormous volume of data.

Results

Researchers have shown that artificial intelligence can learn from mammographic images in a way that gradually enables it to distinguish between healthy tissue and changes that may signal a problem. In other words, the system began to learn how to “look” at images in a manner similar to a physician—searching for subtle details and small deviations that can be very difficult for the human eye to notice.

This progress is particularly important because it represents the first step toward enabling artificial intelligence to flag changes that a human might not notice at first glance. It is not about replacing the physician, but about providing a supporting tool that can help clinicians make decisions with greater confidence, especially in borderline and ambiguous cases.

Impact and future potential

If this research continues to be further developed, artificial intelligence could become a silent assistant in preventive screening. It can speed up the evaluation of imaging data, reduce the risk of overlooking subtle changes, and help detect disease at a stage when it is still highly treatable.

Pre ženy to v praxi znamená väčšiu šancu na včasné odhalenie rakoviny a tým aj vyššiu nádej na úplné uzdravenie. Pri negatívnych nálezoch môžu dostať ženy nezávislý a objektívny doplnkový názor a tým si znížia neistotu po skríningu.  Hoci je pred vedcami ešte ďalšia práca, už dnes je jasné, že smer, ktorým sa výskum uberá, má veľký zmysel. Cieľ je jednoduchý, ale silný. Využiť moderné technológie tak, aby pomáhali chrániť zdravie a životy žien. 


Success-Stories
BeeGFS in Practice — Parallel File Systems for HPC, AI and Data-Intensive Workloads 6 Feb - This webinar introduces BeeGFS, a leading parallel file system designed to support demanding HPC, AI, and data-intensive workloads. Experts from ThinkParQ will explain how parallel file systems work, how BeeGFS is architected, and how it is used in practice across academic, research, and industrial environments.
When a production line knows what will happen in 10 minutes 5 Feb - Every disruption on a production line creates stress. Machines stop, people wait, production slows down, and decisions must be made under pressure. In the food industry—especially in the production of filled pasta products, where the process follows a strictly sequential set of technological steps—one unexpected issue at the end of the line can bring the entire production flow to a halt. But what if the production line could warn in advance that a problem will occur in a few minutes? Or help decide, already during a shift, whether it still makes sense to plan packaging later the same day? These were exactly the questions that stood at the beginning of a research collaboration that brought together industrial data, artificial intelligence, and supercomputing power.
Who Owns AI Inside an Organisation? — Operational Responsibility 5 Feb - This webinar focuses on how organisations can define clear operational responsibility and ownership of AI systems in a proportionate and workable way. Drawing on hands-on experience in data protection, AI governance, and compliance, Petra Fernandes will explore governance approaches that work in practice for both SMEs and larger organisations. The session will highlight internal processes that help organisations stay in control of their AI systems over time, without creating unnecessary administrative burden.
Kategórie
General

VICE and the Digital Twin at the Pre-Christmas Hydrogen Infoday

VICE and the Digital Twin at the Pre-Christmas Hydrogen Infoday



Dňa 10. decembra 2025 sme sa zúčastnili podujatia Predvianočný vodíkový Infoday v Bratislave. Súčasťou programu bola prezentácia VICE – Vertical Integrated Cyclic Energy, Hydrogen, vedená Laurie Farmerom.


The presentation was prepared and delivered jointly, with each member of the team presenting their respective expert section:

  • Laurie Farmer vysvetlil technologický koncept ukladania prebytočnej energie do vodíka a jeho význam pre energetické systémy.
  • Lucia Malíčková vysvetlila ako bol Farmerov koncept integrovaný do digitálneho dvojčaťa, ktoré umožňuje simuláciu rôznych scenárov, analýzu prevádzky a optimalizáciu energetických cyklov.

Prezentácia demonštrovala:

  • the potential of hydrogen as a stabilizing element within the energy infrastructure,
  • the possibilities for efficient storage and utilisation of energy surpluses,
  • the advantages of linking energy concepts with HPC simulations through the digital twin,
  • the practical application of modelling for future energy and industrial solutions.

The event brought a wealth of insightful discussions and confirmed the growing importance of connecting hydrogen technologies with digital solutions. We look forward to further collaboration with partners from the energy, research, and industrial sectors, as well as to new opportunities that will allow us to continue advancing innovative approaches to sustainable energy.

NEWS
BeeGFS in Practice — Parallel File Systems for HPC, AI and Data-Intensive Workloads 6 Feb - This webinar introduces BeeGFS, a leading parallel file system designed to support demanding HPC, AI, and data-intensive workloads. Experts from ThinkParQ will explain how parallel file systems work, how BeeGFS is architected, and how it is used in practice across academic, research, and industrial environments.
When a production line knows what will happen in 10 minutes 5 Feb - Every disruption on a production line creates stress. Machines stop, people wait, production slows down, and decisions must be made under pressure. In the food industry—especially in the production of filled pasta products, where the process follows a strictly sequential set of technological steps—one unexpected issue at the end of the line can bring the entire production flow to a halt. But what if the production line could warn in advance that a problem will occur in a few minutes? Or help decide, already during a shift, whether it still makes sense to plan packaging later the same day? These were exactly the questions that stood at the beginning of a research collaboration that brought together industrial data, artificial intelligence, and supercomputing power.
Who Owns AI Inside an Organisation? — Operational Responsibility 5 Feb - This webinar focuses on how organisations can define clear operational responsibility and ownership of AI systems in a proportionate and workable way. Drawing on hands-on experience in data protection, AI governance, and compliance, Petra Fernandes will explore governance approaches that work in practice for both SMEs and larger organisations. The session will highlight internal processes that help organisations stay in control of their AI systems over time, without creating unnecessary administrative burden.
Kategórie
General

Strengthening Slovak–Romanian Cooperation and the Development of Scientific Partnership

Strengthening Slovak–Romanian Cooperation and the Development of Scientific Partnership



Romania’s National Day is a significant historical milestone commemorating the Great Union of 1918, when Transylvania, Bessarabia, and Bukovina united with the Kingdom of Romania. This moment laid the foundations of the modern Romanian state and remains a powerful symbol of national identity and unity to this day.


On this occasion, a ceremonial reception was held, bringing together representatives of diplomacy, public institutions, and the scientific community. The event was also attended by Lucia Malíčková, Representative of the National Supercomputing Centre. During the reception, she met with the President of the Slovak Academy of Sciences, Mgr. Martin Venhart, DrSc., as well as with His Excellency, the Ambassador of Romania, Calin Fabian.

The meeting with Martin Venhart marked an important step toward strengthening cooperation between the National Supercomputing Centre and the Slovak Academy of Sciences. Both institutions expressed interest in closer collaboration, particularly in the areas of promoting science and technology, supporting research, and preparing joint innovative projects. This cooperation holds significant potential to contribute to the development of the Slovak research and innovation ecosystem and to the integration of high-performance computing, artificial intelligence, and academic research.

The event also reaffirmed the importance of international cooperation and the shared ambition to further deepen Slovak–Romanian relations, particularly in the strategically important fields of high-performance computing and artificial intelligence.

The reception thus became not only a celebration of Romania’s national heritage, but also an important platform for professional dialogue, networking, and the creation of future partnerships with the potential to deliver concrete benefits for science, innovation, and technological development in both countries.

Calin Fabian a Lucia Malíčková
Martin Venhart a Lucia Malíčková

NEWS
BeeGFS in Practice — Parallel File Systems for HPC, AI and Data-Intensive Workloads 6 Feb - This webinar introduces BeeGFS, a leading parallel file system designed to support demanding HPC, AI, and data-intensive workloads. Experts from ThinkParQ will explain how parallel file systems work, how BeeGFS is architected, and how it is used in practice across academic, research, and industrial environments.
When a production line knows what will happen in 10 minutes 5 Feb - Every disruption on a production line creates stress. Machines stop, people wait, production slows down, and decisions must be made under pressure. In the food industry—especially in the production of filled pasta products, where the process follows a strictly sequential set of technological steps—one unexpected issue at the end of the line can bring the entire production flow to a halt. But what if the production line could warn in advance that a problem will occur in a few minutes? Or help decide, already during a shift, whether it still makes sense to plan packaging later the same day? These were exactly the questions that stood at the beginning of a research collaboration that brought together industrial data, artificial intelligence, and supercomputing power.
Who Owns AI Inside an Organisation? — Operational Responsibility 5 Feb - This webinar focuses on how organisations can define clear operational responsibility and ownership of AI systems in a proportionate and workable way. Drawing on hands-on experience in data protection, AI governance, and compliance, Petra Fernandes will explore governance approaches that work in practice for both SMEs and larger organisations. The session will highlight internal processes that help organisations stay in control of their AI systems over time, without creating unnecessary administrative burden.
Kategórie
General

We Participated in the High-Level Summit on AI in Bratislava

We Participated in the High-Level Summit on AI in Bratislava



We participated in the prestigious High-Level Summit on AI – BratislavAI Forum 2025, one of the most significant current European contributions to shaping the global architecture of AI governance. Lucia Malíčková represented our expertise in artificial intelligence, data ecosystems, and digital innovation.


The BratislavAI Forum is taking place during a period of profound global transformation. The rapid development of artificial intelligence and digital technologies is reshaping economies, industries, education, science, and everyday life. Yet despite the immense opportunities, one essential question stands before us: Are we, as a society, truly prepared for these changes?

The event builds on the AI Action Summit in Paris (February 2025) and paves the way for the High-Level Global AI Conference in India (2026). In doing so, the Slovak Republic positions itself among the active partners contributing to the development of a unified, responsible, and secure global AI ecosystem.

The summit emphasized the need to connect technological progress with the development of human capabilities, critical thinking, and inclusive approaches. The discussions brought together insights from senior government officials, international organizations, technology leaders, and digital regulation experts.

One of the key themes was the fact that the world still lacks a unified framework for the regulation and governance of artificial intelligence. This gap results in fragmented policies, inconsistent development standards, and increased risks of misuse.

The discussions focused on the implementation of:

  • UN Global Digital Compact,
  • OECD AI Principles,
  • UNESCO Recommendation on AI,
  • as well as other multilateral initiatives aimed at strengthening digital trust, security, and accountability.

It was highlighted that only a coordinated international approach can fully unlock the potential of AI in a way that benefits everyone—regardless of geography or socio-economic conditions.

The second main thematic area focused on the economic impacts of artificial intelligence. Experts from central banks, the technology sector, and the legal field discussed how AI is transforming:

  • productivity,
  • the labor market,
  • investment flows,
  • regulation and public policy,
  • and the trust between citizens, the state, and technologies.

The aim was to identify the right balance between innovation and the protection of public interest, while creating an environment that supports inclusive economic growth.

The participation of Lucia Malíčková strengthened our position in discussions on digital transformation, artificial intelligence, and the safe use of data. Her contributions reaffirmed our commitment to actively shaping modern AI ecosystems and supporting international cooperation in this field.

The High-Level Summit on AI in Bratislava enabled us to build new partnerships, share our expertise, and contribute to the discussion on what responsible, secure, and inclusive AI development should look like in Europe and globally.

NEWS
BeeGFS in Practice — Parallel File Systems for HPC, AI and Data-Intensive Workloads 6 Feb - This webinar introduces BeeGFS, a leading parallel file system designed to support demanding HPC, AI, and data-intensive workloads. Experts from ThinkParQ will explain how parallel file systems work, how BeeGFS is architected, and how it is used in practice across academic, research, and industrial environments.
When a production line knows what will happen in 10 minutes 5 Feb - Every disruption on a production line creates stress. Machines stop, people wait, production slows down, and decisions must be made under pressure. In the food industry—especially in the production of filled pasta products, where the process follows a strictly sequential set of technological steps—one unexpected issue at the end of the line can bring the entire production flow to a halt. But what if the production line could warn in advance that a problem will occur in a few minutes? Or help decide, already during a shift, whether it still makes sense to plan packaging later the same day? These were exactly the questions that stood at the beginning of a research collaboration that brought together industrial data, artificial intelligence, and supercomputing power.
Who Owns AI Inside an Organisation? — Operational Responsibility 5 Feb - This webinar focuses on how organisations can define clear operational responsibility and ownership of AI systems in a proportionate and workable way. Drawing on hands-on experience in data protection, AI governance, and compliance, Petra Fernandes will explore governance approaches that work in practice for both SMEs and larger organisations. The session will highlight internal processes that help organisations stay in control of their AI systems over time, without creating unnecessary administrative burden.
Kategórie
General

Invitation to the Online Lecture: Building Europe’s Sovereign AI – The Bielik.AI Case

Computer scientists brainstorm ways to use AI cognitive computing to extract usable information from complex data. Data center employees implement artificial intelligence to process massive datasets
Invitation to the Online Lecture: Building Europe’s Sovereign AI – The Bielik.AI Case



We invite you to join the online lecture “Building Europe’s Sovereign AI – The Bielik.AI Case”, taking place on 11 December 2025 at 10:00. The event is open to experts, practitioners, and anyone interested in artificial intelligence, European technological sovereignty, and open-source AI initiatives.


Europe can build sovereign artificial intelligence without isolation—by ensuring control, portability, and auditability across compute infrastructure, data, models, and deployment.

A compelling example is Bielik.AI, an open, community-driven family of AI models developed in Poland. Within just 18 months, nine models have been released, focusing on EU languages and embedding safety and transparency through features such as Bielik Guard. The lecture will illustrate practical steps toward a credible European path to AI sovereignty.

Katarzyna Z. Staroslawska
AI and HPC specialist engaged in European-scale initiatives in the fields of artificial intelligence, high-performance computing, and AI governance

11. december 2025
10:00
Online (link will be sent to registered participants!

Registration

NEWS
BeeGFS in Practice — Parallel File Systems for HPC, AI and Data-Intensive Workloads 6 Feb - This webinar introduces BeeGFS, a leading parallel file system designed to support demanding HPC, AI, and data-intensive workloads. Experts from ThinkParQ will explain how parallel file systems work, how BeeGFS is architected, and how it is used in practice across academic, research, and industrial environments.
When a production line knows what will happen in 10 minutes 5 Feb - Every disruption on a production line creates stress. Machines stop, people wait, production slows down, and decisions must be made under pressure. In the food industry—especially in the production of filled pasta products, where the process follows a strictly sequential set of technological steps—one unexpected issue at the end of the line can bring the entire production flow to a halt. But what if the production line could warn in advance that a problem will occur in a few minutes? Or help decide, already during a shift, whether it still makes sense to plan packaging later the same day? These were exactly the questions that stood at the beginning of a research collaboration that brought together industrial data, artificial intelligence, and supercomputing power.
Who Owns AI Inside an Organisation? — Operational Responsibility 5 Feb - This webinar focuses on how organisations can define clear operational responsibility and ownership of AI systems in a proportionate and workable way. Drawing on hands-on experience in data protection, AI governance, and compliance, Petra Fernandes will explore governance approaches that work in practice for both SMEs and larger organisations. The session will highlight internal processes that help organisations stay in control of their AI systems over time, without creating unnecessary administrative burden.
Kategórie
General

How Projects Addressing AI in Industry Are Created 2025

Technology human touch background, modern remake of The Creation of Adam
How Projects Addressing AI in Industry Are Created 2025



Artificial intelligence is becoming an integral part of European industry and research, fundamentally transforming how innovative projects are created. In response, the European Commission is introducing two new AI strategies—one focused on the application of artificial intelligence in key industrial sectors, and the other dedicated to the scientific use of AI. These initiatives bring new investment and project opportunities for Slovak institutions and companies, particularly through the Horizon Europe programme.

On this occasion, the National Horizon Office invites you to the webinar “How Projects Addressing AI in Industry Are Created 2025,” which will take place online on 25 November 2025 from 13:00 to 14:30. The event is intended for representatives of companies, research organisations, universities, clusters, innovation centres, and all those planning to submit project proposals incorporating elements of artificial intelligence in the fields of industry and digitalisation.

During the webinar, participants will learn about the upcoming 2026–2027 Work Programme for Cluster 4 (Industry and Digitalisation), including thematic areas and “destinations” under which the new calls will fall. They will also gain an overview of how to effectively integrate the use of artificial intelligence into industry-oriented project proposals in order to better meet the expectations of the European Commission.

A special part of the event will be an interactive panel discussion with industry experts, who will share their experience with preparing and implementing projects under the Horizon Europe programme. Among the panelists will also be our project manager, Lucia Malíčková (NSCC Slovakia), who will explain how projects focused on AI in industrial environments are developed and how to effectively integrate the capacities of the Slovak supercomputing centre into them.

The webinar offers a unique opportunity to understand new trends in the field of AI, gain insight into upcoming opportunities within the Horizon Europe programme, and ask anything you are interested in—from the initial project idea to consortium building and proposal preparation.

More info and registration

NEWS
BeeGFS in Practice — Parallel File Systems for HPC, AI and Data-Intensive Workloads 6 Feb - This webinar introduces BeeGFS, a leading parallel file system designed to support demanding HPC, AI, and data-intensive workloads. Experts from ThinkParQ will explain how parallel file systems work, how BeeGFS is architected, and how it is used in practice across academic, research, and industrial environments.
When a production line knows what will happen in 10 minutes 5 Feb - Every disruption on a production line creates stress. Machines stop, people wait, production slows down, and decisions must be made under pressure. In the food industry—especially in the production of filled pasta products, where the process follows a strictly sequential set of technological steps—one unexpected issue at the end of the line can bring the entire production flow to a halt. But what if the production line could warn in advance that a problem will occur in a few minutes? Or help decide, already during a shift, whether it still makes sense to plan packaging later the same day? These were exactly the questions that stood at the beginning of a research collaboration that brought together industrial data, artificial intelligence, and supercomputing power.
Who Owns AI Inside an Organisation? — Operational Responsibility 5 Feb - This webinar focuses on how organisations can define clear operational responsibility and ownership of AI systems in a proportionate and workable way. Drawing on hands-on experience in data protection, AI governance, and compliance, Petra Fernandes will explore governance approaches that work in practice for both SMEs and larger organisations. The session will highlight internal processes that help organisations stay in control of their AI systems over time, without creating unnecessary administrative burden.
Kategórie
General

Online Lecture: HPC & AI – Competition or Collaboration?

AI technology microchip background futuristic innovation technology remix
Online Lecture: HPC & AI – Competition or Collaboration?



On 26 November 2025 at 10:00, we are hosting a special online lecture dedicated to the rapidly evolving topic of the interplay between high-performance computing (HPC) and artificial intelligence (AI). Our guest will be Erwin Laure, one of the most prominent figures in the European HPC ecosystem.

Date and Time:
Tuesday, 26 November 2025 | 10:00 CEST
Online | Free Registration

REGISTRATION

Erwin Laure serves as the Director of the Max Planck Computing and Data Facility (MPCDF) within the Max Planck Society in Garching near Munich. He is also an Honorary Professor at the Technical University of Munich. He has extensive experience in high-performance computing (HPC), scientific simulations, and data infrastructures, and in recent years has been deeply involved in artificial intelligence and its applications in research. Under his leadership, MPCDF supports dozens of research institutes and is considered one of Europe’s leading centers for scientific computing.

The webinar will be held in English.

Lecture topic: HPC & AI – Competition or Collaboration
The growing influence of generative artificial intelligence is fundamentally changing the way scientists work with data, model complex phenomena, and develop scientific predictions. AI is no longer merely a tool for image analysis—it is increasingly entering domains traditionally dominated by classical HPC simulations. The lecture will explore whether AI can replace simulations in certain cases, what advantages arise from combining both approaches, and how these trends are shaping scientific research.

You can expect an overview of real-world AI applications within the Max Planck Society, examples of successful AI deployment across various scientific domains, and a discussion on how rapidly the role of AI is changing within the international research landscape. The lecture will also address the significant technological shifts that AI is bringing to the hardware sector. Chip manufacturers are increasingly prioritizing low-precision architectures optimized for training AI models, a trend that has long-term implications for the availability and development of HPC technologies.

Generative AI has become widely adopted thanks to large language models and is increasingly entering scientific workflows. While AI has long been established in image-based data analysis, in many other domains it is still in an experimental phase—yet this is changing rapidly. A recent example is the ECMWF’s decision to use AI in its weather forecasting. AI is also reshaping the HPC hardware market, where the high numerical precision required for scientific simulations is no longer essential, and chip manufacturers are shifting toward architectures optimized for AI. The lecture will highlight how these trends are influencing scientific computing and why the effective use of AI can provide a significant competitive advantage.

REGISTRATION

NEWS
BeeGFS in Practice — Parallel File Systems for HPC, AI and Data-Intensive Workloads 6 Feb - This webinar introduces BeeGFS, a leading parallel file system designed to support demanding HPC, AI, and data-intensive workloads. Experts from ThinkParQ will explain how parallel file systems work, how BeeGFS is architected, and how it is used in practice across academic, research, and industrial environments.
When a production line knows what will happen in 10 minutes 5 Feb - Every disruption on a production line creates stress. Machines stop, people wait, production slows down, and decisions must be made under pressure. In the food industry—especially in the production of filled pasta products, where the process follows a strictly sequential set of technological steps—one unexpected issue at the end of the line can bring the entire production flow to a halt. But what if the production line could warn in advance that a problem will occur in a few minutes? Or help decide, already during a shift, whether it still makes sense to plan packaging later the same day? These were exactly the questions that stood at the beginning of a research collaboration that brought together industrial data, artificial intelligence, and supercomputing power.
Who Owns AI Inside an Organisation? — Operational Responsibility 5 Feb - This webinar focuses on how organisations can define clear operational responsibility and ownership of AI systems in a proportionate and workable way. Drawing on hands-on experience in data protection, AI governance, and compliance, Petra Fernandes will explore governance approaches that work in practice for both SMEs and larger organisations. The session will highlight internal processes that help organisations stay in control of their AI systems over time, without creating unnecessary administrative burden.
Kategórie
Success-Stories General

Budúcnosť pôdy ukrytá v dátach 

Success story: The Future of Soil Hidden in Data 

High-Performance Computing (HPC) offers researchers the ability to process enormous volumes of data and uncover connections that would otherwise remain hidden. Today, it is no longer just a tool for technical disciplines – it is increasingly valuable in social and environmental research as well. A great example is a project that harnessed the power of HPC to gain deeper insight into the relationship between humans, soil, and the landscape.

Challenge

Soil represents one of the most valuable resources we have — not only as a space for cultivation and economic activity, but also as a foundation of cultural identity, social relations, and quality of life. The way we use land is changing faster than ever before. The pressures of climate change, infrastructure development, housing demands, and renewable energy expansion are creating new tensions between economic interests, landscape protection, and the public good. 

The foundation of fair and sustainable decision-making is participation — involving people in the processes that shape the land and environment they live in. However, if such processes are not well designed, they can lead to distrust, conflicts, and short-sighted solutions. 

The research team from the Slovak University of Agriculture in Nitra therefore sought a way to capture, analyse, and connect these diverse perspectives. Their goal was to understand soil as a form of social and cultural capital — a space that brings together economic, environmental, and human values. To achieve this, they needed to process extensive datasets reflecting public discussions, attitudes, and values related to land and soil across the European context. 

Solution

To better understand how different stakeholders perceive soil and its value, the team combined data analytics with participatory approaches. During the testing phase, they processed extensive textual data, expert documents, media outputs, and public statements that reflect societal attitudes toward soil and the landscape. 

The team applied text mining methods to process the data, enabling the identification of recurring themes, linguistic patterns, and emotional attitudes related to land use. This approach opens the door to new insights, allowing researchers to derive from data how opinions are formed, where tensions arise, and what values people associate with the landscapes they inhabit. 

The goal of the research is not merely to collect information, but to transform it into actionable insights that help build consensus among the public, experts, and policymakers. 

Use of HPC Infrastructure 

The analysis of such extensive textual data required computational power beyond the capabilities of standard workstations. Therefore, the research team used the computing infrastructure provided by NSCC Slovakia to carry out the data processing. 

In the testing phase, the computations were performed on a supercomputer using 128 core*h in an R environment, enabling parallel processing of large datasets within a short time. This approach significantly reduced the analysis time while allowing the application of complex methodological frameworks typical for social and environmental data — such as modelling relationships between actors, tracking the occurrence of key concepts, and visualizing linguistic patterns. 

Thanks to HPC computing, it was possible to: 

  • process extensive text files from various sources without capacity limitations, 
  • generate clear and structured data outputs that would take several times longer to produce on standard computers, 
  • test the potential of the supercomputer for social science and interdisciplinary research that connects human behaviour, data, and spatial relationships. 

Results

The test computations confirmed that the use of high-performance computing infrastructure enables efficient processing and analysis of extensive textual data originating from various social, environmental, and cultural sources. By applying text mining methods, the team was able to gain insights into key themes and the relationships between different stakeholders involved in land-use decision-making. 

The analysis revealed significant differences in how various groups perceive soil and the landscape — whether in terms of economic, ecological, or value-based priorities. These insights help identify areas where misunderstandings and conflicts arise, while also highlighting shared values that can serve as a foundation for constructive dialogue. 

The research confirmed that the use of HPC infrastructure significantly improves data processing efficiency and enables complex analyses to be carried out in a timeframe that would be unfeasible with standard computing resources. This established a reliable foundation for the main phase of the project, in which the results of the testing stage will be expanded with new data sources and methodological approaches. 

The obtained results represent the first step toward developing a tool capable of linking quantitative data with social contexts — thereby contributing to a deeper understanding of the relationship between people, the landscape, and decisions regarding its use. 

Impact and future: 

The project confirmed that a high-performance computing environment provides significant benefits for social science and environmental research dealing with complex, unstructured data. The combination of social research and computational analytics has created a new approach that can be used to gain a deeper understanding of the relationship between humans, the landscape, and societal change. 

From a methodological perspective, the project serves as a model example of how HPC can support interdisciplinary research that integrates environmental data, text corpora, legislation, and public discourse. Such an approach holds great potential within European initiatives focused on sustainable land management and landscape planning. 

The results thus create a transferable framework that can be applied in both European and national projects — ranging from public policy research and participatory planning to the assessment of the social impacts of environmental decisions. 

Data today can tell stories that we could not have captured just a few years ago. The research team harnessed the computational power of a supercomputer to analyse vast textual datasets in order to better understand how society perceives soil, landscape, and their value. The project demonstrates that the future of soil is hidden in data — and that high-performance computing can support not only scientists but also communities striving to find balance between development and sustainability. 


Success-Stories
BeeGFS in Practice — Parallel File Systems for HPC, AI and Data-Intensive Workloads 6 Feb - This webinar introduces BeeGFS, a leading parallel file system designed to support demanding HPC, AI, and data-intensive workloads. Experts from ThinkParQ will explain how parallel file systems work, how BeeGFS is architected, and how it is used in practice across academic, research, and industrial environments.
When a production line knows what will happen in 10 minutes 5 Feb - Every disruption on a production line creates stress. Machines stop, people wait, production slows down, and decisions must be made under pressure. In the food industry—especially in the production of filled pasta products, where the process follows a strictly sequential set of technological steps—one unexpected issue at the end of the line can bring the entire production flow to a halt. But what if the production line could warn in advance that a problem will occur in a few minutes? Or help decide, already during a shift, whether it still makes sense to plan packaging later the same day? These were exactly the questions that stood at the beginning of a research collaboration that brought together industrial data, artificial intelligence, and supercomputing power.
Who Owns AI Inside an Organisation? — Operational Responsibility 5 Feb - This webinar focuses on how organisations can define clear operational responsibility and ownership of AI systems in a proportionate and workable way. Drawing on hands-on experience in data protection, AI governance, and compliance, Petra Fernandes will explore governance approaches that work in practice for both SMEs and larger organisations. The session will highlight internal processes that help organisations stay in control of their AI systems over time, without creating unnecessary administrative burden.