Speaker
Description
Abstract:
In the rapidly evolving world of Artificial Intelligence (AI), Large Language Models (LLMs) have emerged as a powerful tool capable of understanding, interpreting, and generating human-like text. This presentation will delve into the intricacies of state-of-the-art models such as GPT, LLAMA, ALPACA and Orca, highlighting their unique capabilities and their potential in transforming High Energy Physics IT.
The talk will explore the practical aspects of fine-tuning these models on local servers using local data, addressing the technical challenges and considerations, and providing effective solutions. We will discuss the potential benefits and the flexibility that local fine-tuning brings to the table, especially for HEPiX, where data interpretation is of paramount importance.
Furthermore, the presentation will showcase real-world examples and case studies to illuminate the practical applications of these models in the HEPiX field. It aims to demonstrate how these cutting-edge AI models can be utilized to comprehend complex HEP data and generate meaningful insights.
This talk invites all HEPiX participants and stakeholders to consider the potential of LLMs as a robust tool for data interpretation and knowledge generation, and encourages a discussion on further exploration and collaboration in this exciting intersection of AI and High Energy Physics.
In this era where data is the new oil, let us tap into the potential of Large Language Models to refine our data and generate valuable insights for High Energy Physics.
