Introduction to RAG

Series: Exploring the LLM Frontier: From Hugging Face to RAG and Beyond

When

2 – 3 p.m., Oct. 31, 2024

Where

ZOOM & Weaver Science-Engineering Library, Room 212

Retrieval-Augmented Generation (RAG) is a technique that enhances the capabilities of Large Language Models (LLMs) by combining them with external knowledge sources.

Generative AI is a subset of artificial intelligence that focuses on creating new content. Unlike traditional AI models that analyze data, generative AI models learn patterns from existing data and generate new, original content. This can range from text, images, music, and even code.

Why Learn About Generative AI?

Understanding generative AI is crucial for several reasons:

  • Innovation: It's driving groundbreaking advancements in various industries, from art and design to healthcare and science.
  • Career Opportunities: The demand for professionals skilled in generative AI is rapidly growing, presenting exciting career prospects.
  • Problem-Solving: Generative AI offers innovative solutions to complex challenges, from content creation to drug discovery.
  • Ethical Considerations: As generative AI becomes more powerful, it's essential to understand its potential impacts and ethical implications.

Applications of Generative AI

The applications of generative AI are vast and expanding rapidly. Some key areas include:

  • Content Creation: Generating text, images, music, and videos. Drug Discovery: Accelerating the development of new drugs by designing potential molecules.
  • Design: Creating innovative designs for products and architecture.
  • Customer Service: Developing advanced chatbots and virtual assistants.
  • Education: Personalized learning experiences and intelligent tutoring systems.
SERIES: Exploring the LLM Frontier: From Hugging Face to RAG and Beyond

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When: Thursdays, 2-3 pm, Sept. 5 - Oct. 31, 2024
Where: Weaver Science-Engineering Library, Rm 212 and Zoom
Instructors: Carlos Lizárraga and Enrique Noriega Atala
YouTube: See below for video link.

Workshop Materials

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Contacts

Carlos Lizárraga
clizarraga@arizona.edu
Enrique Noriega Atala
enoriega@arizona.edu