Generative AI: Retrieval Augmented Generation (RAG) systems

The emergence of large language models and their application in retrieval augmented generation (RAG) text has thrown open a unique window of opportunity for many sectors. This has meant that using natural language processing technologies for search and text generation has never been more accessible.

Against this background, this talk will address the application of LLMs for RAG, exploring how this technology is setting a new standard for human interaction with unstructured knowledge databases. We will show how the application of this technology enables unprecedented access to information, helping to shift towards more accurate and higher quality generative AI systems.

Programa

Introduction to Retrieval Augmented Generation
Retrieval Augmented Generation
Advanced Developments in Retrieval Augmented Generation
A RAG for the legal portal of Catalonia (Use case)

Masterclass taught by Eurecat and the BSC

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Taught by:

Oriol Alas Cercos, Applied Artificial Intelligence Researcher at Eurecat Researcher in the Applied Artificial Intelligence unit at Eurecat. He holds a degree in Computer Engineering and a Master’s degree in Computer Engineering, both from the University of Lleida (UdL). Since joining Eurecat, Oriol has actively participated in projects related to data analytics, data engineering and artificial intelligence. He is currently engaged in deep learning projects to address challenges in computer vision, anomaly detection, time series analysis and natural language processing (NLP). Carlos Rodríguez Penagos, Established Researcher, Language Technologies Unit at the Barcelona Supercomputing Center (BSC).