The University of Donja Gorica, with the support of the Innovation Fund of Montenegro, as part of the program for the organization of education in the areas of smart specialization of Montenegro, organizes a three-month training called “AIFUSION – Artificial intelligence in agriculture, medicine and energy.” The course will be held in the period from the end of September (September 21) to the end of December (December 21) 2024.
The education program is divided into 5 modules: Introduction to artificial intelligence, Computer vision, Natural language processing, Artificial intelligence and S3 in practice and Ethics and responsible use of artificial intelligence and work on the final project.
Apart from the fact that the participants will acquire enough knowledge and skills needed for further research in this very current field, they will have the opportunity to expand their network of acquaintances and meet young people with similar interests.
To apply, you need to fill out the Google form found at the link https://forms.gle/f8Pc8ozu9U3tHKY98. Applications last until September 20 (11:59 p.m.), and the course is scheduled to start on September 21.
In collaboration with the National Competence Center Montenegro (NCC Montenegro), the University of Donja Gorica (UDG), and the University of Montenegro (UCG), the company DigitalSmart has successfully started the development of a new model utilizing advanced High Performance Computing (HPC) technologies. This partnership represents an important step towards applying HPC resources to solve complex problems and enhancing academic and industrial processes in Montenegro.
The new model is designed to optimize data processing, providing faster and more efficient solutions for research and development in the field of generative artificial intelligence. The use of HPC technologies in this context enables greater scalability and precision in the analysis and processing of large datasets.
The experiment has been successfully submitted through the Fortissimo call, paving the way for further validation and application of this model on an international level.
NCC Montenegro is highlighting ongoing FFplus Open Calls to empower SMEs and Startups to develop innovative products and services with the support of HPC and AI.
European SMEs and Startups have the opportunity to shift their innovation potential through the two types of FFplus Open Calls (total budget €24.0 million):
Business experiments addressing the uptake of HPC for specific business challenges of SMEs that have had no prior use of HPC services. The maximum funding request per proposal is € 200,000.
Innovation studies, supporting SMEs and startups already active in the field of generative AI technology, which lack the necessary computational resources to scale up. The maximum funding for each innovation study is € 300,000.
Application deadline: September 4th, 2024!
Find out more about FFplus Open Calls, application details and NCC Montenegro’s support on:
The Montenegrin National Center of Competence in High Performance Computing (NCC Montenegro) invites Montenegrin companies to take advantage of the unique opportunity to improve their business using advanced HPC technologies and artificial intelligence and apply for the FFplus call for business experiments and innovative studies. NCC Montenegro, as a center that coordinates initiatives in the field of HPC at the national level, will provide support in the assessment of the company’s readiness for HPC and AI, but also in the selection of EuroHPC JU resources and in finding partners in accordance with expertise and potential.
FFplus is a European initiative that highlights and promotes the adoption of High Performance Computing (HPC) by SMEs and start-ups across Europe. The scope of targeted actions includes solving business challenges through computer methods (modeling and simulation, data analytics) on HPC systems, as well as the use of supercomputer resources for the development of software solutions and (generative) artificial intelligence (AI) services.
With more than a decade long history and a strong reputation in Europe, the Fortissimo projects (Fortissimo 1 and 2, FF4EuroHPC) received a budget of 42.8 million euros and successfully performed more than 130 experiments involving more than 300 partners. These efforts have resulted in 120 success stories from over 20 EU countries, where SMEs have developed new products and services with the help of high-performing computing (HPC) and artificial intelligence, thereby boosting the EU economy. Building on the methods and achievements of the Fortissimo project series, the FFplus call, with a total budget of EUR 30.0 million, including EUR 24.0 million for SMEs and startups, will continue to support and empower SMEs and startups towards innovations.
SMEs and start-ups now have the opportunity to convey their innovative potential through two types of open calls of the FFPlus project (open until September 4th, 2024):
Business experiments will address HPC adoption by SMEs to address specific business challenges of SMEs that have not previously used or had no experience with HPC services.
The maximum request for financing per proposal is 200,000 euros. Expected duration of the experiments: a maximum of 15 months with a planned start on January 1st, 2025.
Per application, it is possible to have a maximum of five partners in the consortium
The call is intended for experiments involving innovative, agile SMEs, focused on innovations resulting from the use of advanced HPC services.
Innovation studies will support European SMEs and start-ups already active in the field of generative AI technology, which lack the necessary computing resources to scale up.
The maximum total funding for each innovation study is 300,000 euros. Expected duration of the experiments: a maximum of 10 months with a planned start on December 1st, 2024.
A maximum of three partners are allowed per application. There are no indirect costs.
Creating history: the first Montenegrin success story in the Fortisimo project
Within the framework of the five-day Fortissimo call, FF4EuroHPC, the consortium with the support of NCC Montenegro, which included Montenegrin partners DigitalSmart doo (coordinator), Radinović Company, Meso-Promet Franca, University of Donja Gorica, and DunavNET from Serbia, implemented a successful pilot project-experiment AIMHIGH in which partners used HPC, machine learning and IoT technology in agriculture to develop a new solution for monitoring and predicting diseases among poultry.
Are you ready for supercomputing and artificial intelligence?
Montenegrin companies that want to find out if they are ready to use supercomputers and AI technologies in their business can do so by filling out the HPC4SME company assessment tool and find out if and how the organization can benefit from free supercomputer services. Companies that are interested in carrying out the assessment and filling out the questionnaire will be additionally supported by the Montenegrin National Competence Center NCC Montenegro.
For more information about the call, you can visit the website of the FFplus project: https://www.ffplus-project.eu/ or contact the Montenegrin National Competence Center (NCC Montenegro) directly at luka.filipovic@udg.edu.me or sanja.nikolic@udg.edu.me
NCC Montenegro representative Luka Filipovic took an active part as a Teaching Assistant in the Nvidia and EuroCC2 supported bootcamp “AI for Scientific Computing”, successfully organized by NCCs Germany, Sweden, Austria and Montenegro, on June 25–26, 2024.
The Bootcamp offered a comprehensive introduction to deep neural networks, focusing on applications in scientific computing and physical systems defined by differential equations. The curriculum included advanced topics based on NVIDIA Modulus to develop and train the models in various areas. This online Bootcamp features guided instructions and support from cross-NCC teaching assistants to facilitate learning, supporting participants to build and enhance AI/DL models.
Representatives from NCC Montenegro in joint efforts with young researchers from UDG, published two scientific papers at the SymOrg 2024 conference, organized by the Faculty of Organizational Science, University of Belgrade, at Zlatibor, Serbia on June 12-14, 2024. The conference, traditionally envisioned as a platform for knowledge innovation and empirical research, bringing together representatives from the scientific and professional community, was themed: ”Unlocking The Hidden Potential Of Organization Through Merging Of Humans And Digitals”, aiming to address the newfound need for balance in the era of AI.
Image source: SymOrg 2024 website
The scientific paper “Detection of Scoliosis” by Elvis Taruh, Enisa Trubljanin, and Dejan Babić explores the application of a deep learning model integrated with a web application to detect scoliosis using x-ray images. Utilizing a dataset of 198 x-ray images from Roboflow, the initial model performance was unsatisfactory, prompting manual annotation of 245 images, which significantly improved the model’s accuracy. YOLOv8, a state-of-the-art object detection algorithm, was used to train two models, demonstrating improved performance with manual annotations. The web application, built with Flask, HTML, CSS, and JavaScript, provides a user-friendly interface for analyzing scoliosis detection results. The backend uses MySQL for data storage and management, facilitating efficient image processing, result display, and feedback from doctors. Evaluation metrics indicate that the second model, which underwent refined annotation and augmentation, performed better, avoiding overfitting and demonstrating higher precision. This approach enhances early scoliosis diagnosis and offers a scalable solution for other medical detection challenges, supporting healthcare providers with more accurate diagnostic tools and improving patient care.
Click on image to open SymOrg 2024 proceedings
In the paper “LLM Consistent Character Bias”, the authors Igor Culafic and Tomo Popovic investigate the potential of Large Language Models (LLMs) for character imitation in media, education, and entertainment. Traditionally, LLMs have been used for tasks like web search and programming, but this study focuses on their application in mimicking specific characters from books. Using a dataset created from the Ciaphas Cain anthology of Warhammer 40k, the authors trained models using Low-Rank Adaptation (LoRA) methods. Three models of varying sizes (1.1B, 7B, and 10.7B parameters) were tested, with training conducted on a NVIDIA RTX 4090 GPU. The study found that the larger models (7B and 10.7B) performed well in maintaining character consistency, though they occasionally struggled with specific details and displayed unexpected behaviors like excessive emoji usage. The smallest model (1.1B), despite higher LoRA Rank parameters, was less effective and prone to errors such as repetitive responses and long rants. The authors conclude that LLMs can successfully imitate fictional characters given adequate data and training, suggesting future improvements could make them useful in various fields, including education and therapy. These models have the potential to enhance interactive experiences in theme parks, video games, and educational tools by providing authentic character interactions. However, they caution against using these models as replacements for human therapists due to their limitations and tendency for inaccuracies.
Click on image to open SymOrg 2024 proceedings
Both research papers were partly supported by the EuroCC2 project that is funded by the European High-Performance Computing Joint Undertaking (JU) under Grant Agreement No 101101903.
NCC Montenegro successfully submitted the proposal No. EHPC-BEN-2023B12-015 High-Resolution Weather Prediction Model for Montenegro, to the EuroHPC Benchmark Access Call, in cooperation with Institute of Hydrometeorology and Seismology of Montenegro (IHMS) on VEGA CPU for the period 15.01.-15.04.2024. The project aimed to leverage the EuroHPC resources to establish and benchmark precise weather forecast models in the complex topography of Montenegro, utilize these models to refine existing meteorological models, and ultimately enhance the accuracy of weather forecasts, particularly for severe weather events.
Simulations used the Weather Research and Forecasting Non-Hydrostatic Mesoscale Model (WRF-NMM) combining advanced numerical techniques with HPC, for studying atmospheric phenomena with high spatial and temporal resolution and providing accurate and efficient simulations of regional weather patterns. Key activities included installing and fine-tuning the model based on previous verification results, preparing input data, running and fine-tuning the model, and analyzing results in the context of weather prediction and parallel computing performance. WRF model is tested on complex Montenegrin terrain on resolutions 0.5km, 1km, 3km, and 5km. Application scalability was tested on up to 8 nodes, running up to 1024 tasks simultaneously. Simulations were executed for different timespans, but results/overall execution time was scaled to one day period to calculate application speedup and efficiency.
Vega HPC has significantly enhanced research capabilities, allowing to achieve results more quickly and with greater accuracy: scalability was successfully tested on 64-512 CPU cores and the model was successfully downscaled to the resolution of 0.5 km. The final report on granted EUROHPC JU Benchmark Access and effective utilization of the VEGA CPU system assigned is submitted.
