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Autor(en): 
  • Alessandro Benedetti
  • How Large Language Models Can Help Your Search Project 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Auf Bestellung (Lieferzeit unbekannt)
    Veröffentlichung:  Januar 2026  
    Genre:  EDV / Informatik 
     
    Artificial Intelligence / Data Warehousing / Generative AI / Information Storage and Retrieval / Künstliche Intelligenz / Large Language Models / LLMs / machine learning
    ISBN:  9783032015624 
    EAN-Code: 
    9783032015624 
    Verlag:  Springer International Publishing 
    Einband:  Kartoniert  
    Sprache:  English  
    Dimensionen:  H 235 mm / B 155 mm / D  
    Seiten:  206 
    Illustration:  XIII, 206 p. 
    Zus. Info:  EUDR exemption - product or manufacturing materials placed on the market prior to 31.12.2025. 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:

    The primary scope of this book is to communicate the current state of the art of large language model applications in the domain of information retrieval and search with a pragmatic perspective on industrial adoption via open source software.

    To this end, the book is organised in three parts: "Large Language Models" gives an introduction to artificial intelligence and large language models, including an overview of open source and commercial options. Next, "Large Language Models and Search" describes techniques and strategies to integrate large language models in search projects, including how to choose the right model for a specific use case and how to avoid the classic mistakes that can happen in the process. Eventually, "How to Use Open Source Software to Interact with Large Language Models" gives an overview of open source technologies to interact with large language models and gives a detailed survey of how the most popular open source search engines support them.

    The book lays the foundations, deeply analyses the building blocks and shows examples how to implement the ideas described. It highlights both the positives, negatives and possible mitigations of the limitations. This way, it caters primarily software engineers, data scientists and practitioners in artificial intelligence or information retrieval who are curious to learn about the latest trends, research and industrial applications related to search and large language models.

      



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