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“Generative AI Intelligent Process Automation Platform” project on Leonardo HPC

Uhura Solutions is developing AI platform for document-driven process automation in financial services. The “Generative AI Intelligent Process Automation Platform – GAIPAP” project is a transformative initiative aimed at revolutionizing the financial industry through the integration of advanced AI-driven automation solutions that combine capabilities of Large Language Model (LLM), low-code development, and process automation workflows. This unique fusion of technologies holds the potential to significantly enhance operational efficiency, cost reduction, and customer experience within the financial sector.

An exceptional aspect of the platform is the incorporation of fine-tuned Large language models (LLMs), which sets it apart from generic AI solutions. These LLMs, refined for the financial industry’s unique language, context, and patterns, promise to deliver more precise and relevant insights. The platform’s value proposition is further strengthened by its ability to streamline workflows, offer scalability, real-time data insights, and elevate customer experiences. The integration of a low-code development framework and process automation workflows enables swift prototyping and deployment of AI-driven models, thereby accelerating time-to-market and capitalizing on market opportunities effectively.

The project involves the use of open-source Python libraries and pre-trained Large language models which are fine-tuned on a custom-made private dataset created by the team, allowing for specialized tasks within the financial sector. Leonardo supercomputer enabled us to make a leap with GPU training experiments from 1B to 7B and higher Large language models. We are focusing on various LLM research and optimization methods in this phase of the project, which include hyperparameter tuning, model quantization and pruning, and parameter efficient fine-tuning (PEFT). Special attention is put on dataset preprocessing including quality filtering, deduplication and privacy redacting.

This project, developed and managed by Uhura Solutions, was awarded with 4,500 node hours of GPU resources (8x64GB) on the Leonardo Buster HPC for a duration of 12 months.

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HPC/AI Workshop and Student Conference

On Saturday, December 21st, the University of Donja Gorica will host an HPC/AI Workshop and Student Conference, where participants from the AIFusion and HPC4S3ME projects will present their results.

HPC/AI Workshop and student conference are organized in context of HPC4S3ME and AI Fusion projects

The event will include:

  • Presentation of key results and achievements of both projects,
  • NCC Montenegro and EuroCC2/EuroCC4SEE presentation,
  • Presentation of student projects,
  • Panel discussion,
  • Coctail and networking.

Location: AP Amphitheatre, University of Donja Gorica
Time: 10:00am – 16:00pm

The full agenda:

After the program, the socializing will continue with a cocktail.
Join us to celebrate the results and exchange ideas in the field of HPC and AI

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Industry workshop with ICT Cortex: “Supercomputing Opportunities for Industry Leaders”

NCC Montenegro is co-organizing industry-focused workshops and networking events to inspire innovative companies, SMEs and startups to learn how to improve their business processes and accelerate innovations with supercomputing HPC/AI opportunities. NCC experts provide HPC and AI technical expertise and infrastructure access, adjusted to the business environment and industry domains.

In cooperation with ICT Cortex (ICT Cluster for Information Technologies, Innovation, Education, Design and Technology Development in Montenegro)-gathering more than 40 founding members and 1800 IT experts, NCC Montenegro is organizing workshop “Supercomputing Opportunities for Industry Leaders” on 18th of Dec, to present HPC/AI systems and benefits, NCC services and activities, as well as EuroHPC infrastructure opportunities.

Montenegro’s ICT sector has been recognized as the catalyst for the development of an innovative economy and for strengthening the competitiveness and multiple industries. ICT industry is one of the fastest growing sectors in Montenegro accumulating more than €600 in 2022 (vs €124mn in 2012), achieving almost 10% of GDP (vs 4% in 2012) and 21% of country’s total exports (vs 3% in 2017), according to ICT Cortex /CEED Consulting analyses.

We believe that this workshop will increase awareness on HPC&AI opportunities, provide valuable insights and inspirational use cases to the members and partners of ICT Cortex, enabling them to discover supercomputing power to enhance their innovative business and industry competitiveness.

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New training course offering: Prompt Engineering

Course Description: Prompt Engineering

During the Fall 2024, the NCC team at UDG developed a new training offering aimed at the the use of generative AI, mos specifically at real-life LLM applications and digital transformation. The training was developed based on the communications with students and industry representatives. The initial enrollment in November was over 40 students, where most of them are expected to finish the training by 20 December.

The study of Prompt Engineering represents a cornerstone technique for effective interaction with advanced language models such as GPT-4, LLama and beyond. This course equips students with the knowledge and skills necessary to harness the transformative potential of AI technologies, emphasizing innovative, responsible, and industry-specific applications. In an era of digital transformation, where real-time decision-making and intelligent automation shape industries, the demand for high-performance computing (HPC) is critical. By exploring advanced natural language processing (NLP) models, students will not only develop effective querying techniques but also understand the computational requirements and infrastructure needed to implement these solutions at scale.

Unlocking the Power of AI: The Role of High-Performance Computing in Real-Life LLM Applications and Digital Transformation

As large language models become more sophisticated, their computational demands grow exponentially. Applications such as real-time customer interactions, predictive analytics, and decision support in fields like healthcare and education require HPC infrastructure to ensure performance and scalability. This course bridges the gap between theoretical understanding and practical implementation, highlighting how HPC enables the deployment of robust AI solutions, thus driving innovation in the digital age. Whether you’re preparing to lead AI projects in academia or industry, this course provides the essential knowledge to leverage AI technologies responsibly and effectively, positioning you at the forefront of digital transformation.

Course Content Overview (12 Modules)

  1. Introduction to Prompt Engineering – Fundamentals, significance, and applications of prompt structuring.
  2. Understanding AI Models – Overview of how language models process inputs and generate outputs.
  3. Contextual Importance – Strategies to define and provide context for optimal AI performance.
  4. Crafting Effective Prompts – Techniques for prompt structuring, tone control, and style customization.
  5. Advanced Prompting Techniques – Multi-step prompts, variable integration, and scenario-specific tasks.
  6. Experimentation and Iterative Improvement – Testing, analyzing, and refining prompts for enhanced outcomes.
  7. Industry-Specific Applications – Practical use cases in medicine, education, marketing, and law.
  8. Integrative Techniques – Combining chain-of-thought and meta-prompting for adaptability.
  9. Ethics in Prompt Engineering – Addressing bias, preventing misuse, and upholding ethical AI standards.
  10. Technical Foundations of NLP and Transformers – Key principles of NLP and the mechanics of transformers with a focus on HPC for scaling AI solutions.
  11. Real-life LLM applications, digital transformation, and the need for computing resources.
  12. Introduction ot high-performance computing and uptake to HPC considerations

Learning Outcomes

By the end of this course, students will be able to:

  • Design and structure effective prompts tailored to diverse tasks.
  • Apply advanced techniques such as chain-of-thought and meta-prompting to complex scenarios.
  • Evaluate and optimize AI model responses through iterative feedback loops.
  • Customize prompts for specific industrial needs while adhering to ethical standards.
  • Comprehend technical aspects of transformer-based NLP models.
  • LLMs and digital transformation, the need for computing resources for real-life applications
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EuroCC2 workshop “Establishing Business Relations between SMEs and Academia,”

As part of the EuroCC2 cross-NCC knowledge-sharing online events, which provide a platform for exchanging experiences on best practices, collaboration models, and impactful results, NCC Montenegro participated in the workshop “Establishing Business Relations between SMEs and Academia” on November 7th.

NCC Montenegro highlighted its outreach and onboarding activities for SMEs, featuring collaborations between academia and industry through: HPC/AI workshops and training events; development/research/innovation activities, and collaborative projects/grant schemes. A notable success story from the FinTech sector detailed how ML/HPC supported solutions addressed business challenges, including implementation steps and achieved benefits.

NCC Bulgaria emphasizes collaboration with various industry sectors and academia to foster partnerships with SMEs in addressing industry specific challenges through scientific research, training events, algorithm development, HPC solutions, and efficiency and scalability studies. Examples of successful HPC collaborations include improving precision in furniture design and analyzing advertising channel efficiency.

NCC Norway shared insights into Norway’s power market and collaboration with SINTEF Energy. By transitioning power models to HPC, they reduced simulation times from two hours to two minutes, enabling enhanced scenario testing and platform scalability.
This collaborative workshop demonstrated practical approaches across NCCs, emphasizing the shared goal of bridging the gap between academia and industry through HPC innovations.

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Lecture by prof Kezunovic from Texas A&M on AI/HPC supported risk management in energy sector

As planned, the invited lecture “Risk Management of Future Large-Scale Electrification” by prof. Mladen Kezunovic took place on 25 October 2024 in Enterpreneurial nest at UDG. Threre was over 60 attendees including students, academics from Montenegrin universities and representatives from the industry. This workshop was organized in the context of HPC4S3ME project and supported by EUROCC NCC Montenegro team.

What are the risks? Methodology for risk management and mitigation? What data do we have and how do we manage all that data? How can AI/ML supported by HPC help?

Dr. Mladen Kezunovic is a University Distinguished Professor at Texas A&M with over 35 years of expertise in power engineering. Renowned globally, Dr. Kezunovic has authored over 600 papers and consulted for 50+ companies worldwide. His extensive research and industry contributions, notably in fault modeling, data analytics, and smart grids, have earned him IEEE Life Fellow status and recognition from the US National Academy of Engineering.

prof. Kezunovic from Texas A&M gave presentation on a nove approach to Risk managemement in energy sector
The workshop took place on 25 october at UDG
Over 60 people attended
How AI/ML supported by HPC can help mitigate risk in energy sector?
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Master thesis: HPC/AI for breast cancer detection

Ms. Tamara Pavlovic defended her MSc thesis on the use of HPC/AI for creating prediction models for breast cancer detection on 23.10.2024. With the support from NCC Montenegro, Ms Pavlovic did her research in the context of the HPC4S3ME project and the focus was on AI and computer vision applications in medicine. From the motivational point of view, we congratulate Tamara for finalizing and defending her thesis during the Breast Cancer Awareness Month (‘Pink October’) as people around the world adopt the pink colour and display a pink ribbon to raise awareness about breast health.

ABSTRACT – Artificial Intelligence (AI) is revolutionizing numerous sectors, including medicine, by offering innovative methods for diagnosing, treating, and researching diseases. This master’s thesis focuses on the application of AI in the diagnosis of breast cancer, using computer vision algorithms to analyze mammographic images. Through a combination of convolutional neural networks (CNNs) and deep learning, models have been developed that identify malignant changes, potentially contributing to earlier and more precise disease detection. The thesis examines in detail how AI can improve the efficiency of screening processes, reduce the time required for diagnosis, and enable a more personalized approach to treatment. In addition to technological progress, ethical issues such as patient safety and the transparency of AI systems are also considered. The results of this study confirm that the application of AI in breast cancer diagnostics can significantly enhance medical procedures. The models tested, ResNet152 and DenseNet121, demonstrated quite good performance in classifying breast cancer. Their AUC scores, which exceed the threshold of 0.9, indicate their potential for use in clinical practice. These findings not only contribute to the improvement of diagnostic processes but also open up opportunities for further research and development of AI technologies in medicine.

This research was done in th context of HPC4S3ME and with the support from EUROCC NCC Montenegro
Ms Pavlovic finalized her thesis during the Breast Cancer Awareness Month (‘Pink October’)
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