Webinar: Leveraging LLMs and RAG for Business Innovation

On-demand webinar

Real-World Insights: Leveraging LLMs and RAG for AI Business Innovation

Practical applications of GenAI tactics for business

Watch this On-demand webinar to discover the practical applications that GenAI tactics can offer modern businesses.

In this session, we will explore Artificial Intelligence’s capabilities and offer practical insights into how Large Language Models (LLM) and Retrieval-Augmented Generation (RAG) can drive business innovation.

Industry expert Jakub Chojnacki, Digital Architect at Billennium, will explain how these cutting-edge technologies can change your company’s data-driven decision-making landscape and how you can leverage these techniques in a real-world environment.

Find out more

  • 01

    GenAI tactics for Business

    What is their role in enhancing data analysis and decision-making process?

  • 02

    LLMs & RAG in Action

    What are their applications in e-commerce, finance, and more?

  • 03

    Implementing LLMs & RAG in Your Company

    What practical steps will enable you to integrate successfully?

Jakub Chojnacki
Digital Architect at Billennium

My journey in the realm of Artificial Intelligence began in 2017. Over the past 7 years, I’ve immersed myself in AI technologies, specializing particularly in reinforcement learning and multi-agent reinforcement learning.

Throughout my career, I’ve had the privilege of sharing my expertise by teaching these cutting-edge technologies at higher education institutions. In recent years, my focus has shifted towards research in large language models (LLM), where I strive to bridge the gap between LLMs and my passion for multi-agent reinforcement learning.

As a recognized expert in the field of AI, my contributions span across various domains, with a keen emphasis on reinforcement learning, multi-agent RL, and LLM. I am driven by the belief that AI has the potential to revolutionize industries and am committed to pushing the boundaries of innovation in this dynamic field.