Previous events showcased advancements in AI technologies and their impact on various industries.
Event 1 Description
Event 1 Title
Event 2 description
Event 2 TitleAI is reshaping industries and economies faster than any previous technology, creating unprecedented opportunities for countries that adopt it and leaving behind those that don’t. Nations like the US and China are leading this revolution, while Armenia risks falling behind despite its tech potential.
This keynote will explore why AI is crucial for Armenia’s future and what steps the country must take to harness its power. The message is clear: Armenia needs to act now, or risk missing out on the transformative benefits of AI. It’s time for government, industry, and education to unite and ensure Armenia thrives in the AI-driven world.
Scientific innovations always shape the future of the industry. Here, we present several research breakthroughs from Picsart AI team and show how inhouse scientific contributions can become a basis of a successful product.
The speech explores the evolution of traditional web design and eCommerce creation, highlighting the challenges of manual processes. It examines how AI automates design and content creation, offering faster, more personalized, and scalable solutions for businesses, revolutionizing the digital landscape.
Do you want to learn new skills faster and be more productive? Or teach more engaging, higher quality classes? This talk will introduce the latest AI tools for education that you can start using today, and explore what teaching and learning will look like in the near future.
We’ll cover how 10Web uses AI to automate key processes in people operations, customer care, and documentation. This presentation highlights practical applications of AI-powered automation, showcasing its ability to streamline workflows and scale operations efficiently without human involvement.
With new achievements in AI and machine learning, it has become easier to implement changes that greatly increase the efficiency of systems in fintech. In this talk, we will dive into how Acba Bank solves problems using AI and machine learning, discussing the challenges we faced along the way.
The presentation will be about the state-of-the-art Speech-to-Text and Text-to-Speech technologies for the Armenian language, the use cases of these tools, their advantages and disadvantages, as well as the future development and their integration into bigger systems.
Learn how to grow and protect your business in the AI era. This session will discuss how AI has transformed business management and growth strategies, and provide insights on adapting, staying competitive, and building a resilient business in an ever-evolving landscape.
The presentation will cover the main principles and foundations of the EU AI Act, give an overview on the AI systems classification by risk, and the impact on AI research and industry, including AI companies in Armenia.
This presentation demonstrates how to combine different data sources to create AI clones that autonomously perform tasks, reducing costs by eliminating the need for additional spending on manual efforts and also predict real users behavoir in future.
In this workshop, he will dive into the development of on-device multilingual automatic speech recognition, improving its accuracy with fine-tuned large language models (LLMs) and extracting key points and actionable insights from transcripts to enhance workflow efficiency.
This workshop explores the machine learning (ML) challenge of foreign accent conversion (FAC), a special speech processing problem, within the context of real-time applications. We provide a concise introduction to core ML concepts, highlighting its role in speech processing. A brief overview of digital signal processing (DSP) techniques for audio manipulation is also included.
We then delve into established FAC approaches, analyzing their strengths and weaknesses, particularly regarding their suitability for real-time scenarios. This analysis highlights the critical limitations of high parameter counts and extensive algorithmic lookahead that impede practical implementation.
We propose a novel FAC solution specifically designed to address these limitations,
enabling real-time operation. Our approach prioritizes efficient parameter usage and restricted algorithmic lookahead, making it suitable for resource-constrained environments.
Finally, we establish objective evaluation metrics for FAC tasks and present the performance results achieved by our model.
