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The Government of the Republic of Serbia

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Serbia continues to invest in AI

Novi Sad, 15 July 2024

Prime Minister Miloš Vučević said today, at the opening of the Eastern European Summer School of Machine Learning (EEML) in the Science and Technology Park in Novi Sad, that Serbia will continue to invest in artificial intelligence (AI), taking into account ethical principles.

Vučević pointed out that AI must not be misused and that we should work on its legal definition, taking care not to hinder progress.

We need to free people from fear and show that we are working here for their benefit, the Prime Minister said and added that the development and growth of AI is also connected with the production of electricity.

He told the participants of this meeting that they show that there are no boundaries for science, adding that it is necessary to be focused on science, but not to neglect the issue of ethical application of artificial intelligence.

Acting Director of the Research and Development Institute for AI Dubravko Ćulibrk expressed his satisfaction with the fact that the Eastern European School of Machine Learning is being organised in Novi Sad.

Participation in this year's EEML was confirmed by prominent lecturers from universities such as New York University, ETH Zürich, University of Oxford, University of Cambridge, McGill University, as well as representatives of global technology companies, such as Google DeepMind, Genentech (Roche), Bitdefender, Microsoft, INSAIT, PolyAI, but also our experts from the University of Belgrade and the Institute for AI of Serbia.

The Summer School programme, in which there will be more than 250 participants from 24 countries, lasts until 20 July and consists of six days of intensive training that includes lectures, practical sessions, as well as introductory lectures by representatives of the business sector and presentations of sponsor stands.

Participants will have the opportunity to deepen their knowledge and skills by exploring topics such as machine learning fundamentals, multimodal learning, advanced deep learning architectures, etc.