What we learned from a year of building with LLMs

Ready to build real-world applications with large language models? With the pace of improvements over the past year, LLMs have become good enough for use in real-world applications. LLMs are also broadly accessible, allowing practitioners besides ML engineers and scientists to build intelligence int...

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Hauptverfasser: Yan, Eugene (VerfasserIn), Bischof, Bryan (VerfasserIn), Frye, Charles (VerfasserIn), Husain, Hamel (VerfasserIn), Liu, Jason (VerfasserIn), Shankar, Shreya (VerfasserIn)
Format: Elektronisch E-Book
Sprache:English
Veröffentlicht: Sebastopol, CA O'Reilly Media, Inc. 2024
Ausgabe:First edition.
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spelling Yan, Eugene VerfasserIn aut
What we learned from a year of building with LLMs by Eugene Yan, Bryan Bischof, Charles Frye, Hamel Husain, Jason Liu & Shreya Shankar
First edition.
Sebastopol, CA O'Reilly Media, Inc. 2024
1 online resource (64 pages) illustrations
Text txt rdacontent
Computermedien c rdamedia
Online-Ressource cr rdacarrier
Includes bibliographical references
Ready to build real-world applications with large language models? With the pace of improvements over the past year, LLMs have become good enough for use in real-world applications. LLMs are also broadly accessible, allowing practitioners besides ML engineers and scientists to build intelligence into their products. In this report, six experts in AI and machine learning present crucial, yet often neglected, ML lessons and methodologies essential for developing products based on LLMs. Awareness of these concepts can give you a competitive advantage against most others in the field. Over the past year, authors Eugene Yan, Brian Bischof, Charles Frye, Hamel Husain, Jason Liu, and Shreya Shankar have been busy testing and refining these methodologies by building real-world applications on top of LLMs. In this report, they have distilled these lessons for the benefit of the community.
Natural language generation (Computer science)
Artificial intelligence Computer programs
Génération automatique de texte
Intelligence artificielle ; Logiciels
Bischof, Bryan VerfasserIn aut
Frye, Charles VerfasserIn aut
Husain, Hamel VerfasserIn aut
Liu, Jason VerfasserIn aut
Shankar, Shreya VerfasserIn aut
TUM01 ZDB-30-ORH TUM_PDA_ORH https://learning.oreilly.com/library/view/-/9781098176716/?ar X:ORHE Aggregator lizenzpflichtig Volltext
spellingShingle Yan, Eugene
Bischof, Bryan
Frye, Charles
Husain, Hamel
Liu, Jason
Shankar, Shreya
What we learned from a year of building with LLMs
Natural language generation (Computer science)
Artificial intelligence Computer programs
Génération automatique de texte
Intelligence artificielle ; Logiciels
title What we learned from a year of building with LLMs
title_auth What we learned from a year of building with LLMs
title_exact_search What we learned from a year of building with LLMs
title_full What we learned from a year of building with LLMs by Eugene Yan, Bryan Bischof, Charles Frye, Hamel Husain, Jason Liu & Shreya Shankar
title_fullStr What we learned from a year of building with LLMs by Eugene Yan, Bryan Bischof, Charles Frye, Hamel Husain, Jason Liu & Shreya Shankar
title_full_unstemmed What we learned from a year of building with LLMs by Eugene Yan, Bryan Bischof, Charles Frye, Hamel Husain, Jason Liu & Shreya Shankar
title_short What we learned from a year of building with LLMs
title_sort what we learned from a year of building with llms
topic Natural language generation (Computer science)
Artificial intelligence Computer programs
Génération automatique de texte
Intelligence artificielle ; Logiciels
topic_facet Natural language generation (Computer science)
Artificial intelligence Computer programs
Génération automatique de texte
Intelligence artificielle ; Logiciels
url https://learning.oreilly.com/library/view/-/9781098176716/?ar
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