How to make a RAG app

• Titel: How to make a RAG app
• Mitwirkende: Stewart, Blaize [MitwirkendeR]
• Institutionen: O'Reilly (Firm), [Verlag]
• Ausgabe: [First edition].
• Verlagsort: [Sebastopol, California]
• Verlag: O'Reilly Media, Inc.
• E-Jahr: 2024
• Jahr: [2024]
• Umfang: 1 online resource (1 video file (16 min.))
• Illustrationen: sound, color.
• Gesamttitel/Reihe: Shortcuts
• Fussnoten: Online resource; title from title details screen (O’Reilly, viewed July 1, 2024)
• Datenträger: Online-Ressource
• Sprache: eng
• Sach-SW: Génération automatique de texte
• Sach-SW: Intelligence artificielle ; Logiciels
• Sach-SW: Instructional films
• Sach-SW: Nonfiction films
• Sach-SW: Internet videos
• Sach-SW: Films de formation
• Sach-SW: Films autres que de fiction
• Sach-SW: Vidéos sur Internet
• K10plus-PPN: 1899109188
• K10plus-PPN:
  Universitätsbibliothek
• Lokale URL UB: Zum Volltext
• Lokale URL UB: Bibliothek der Medizinischen Fakultät Mannheim der Universität Heidelberg
• Bibliothek/Idn: UW / m4568072999
• Lokale URL Inst.: Zum Volltext

Abstract

In this video shortcuts collection, you will learn how Vector databases and the vectorization of data are essential components that enable the retrieval-augmented generation (RAG) approach, allowing AI models to access and leverage relevant external information to improve the accuracy, reliability, and transparency of their outputs. Data engineers and software developers working with generative AI should have a strong grasp of vector databases, text embeddings, the RAG architecture, and the integration of these components to build reliable, accurate, and scalable AI-powered applications. Leverage practical, hands-on approaches to data to effectively harness the power of Retrieval-Augmented Generation and vector databases to build reliable, accurate, and scalable AI-powered applications that deliver tangible value to your users.