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Autor(en): 
  • Karol Przystalski
  • Natalia Lipp
  • Dawid Pacholczyk
  • Jan K. Argasi¿ski
  • Building Personality-Driven Language Models: How Neurotic is ChatGPT 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 2 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   i.d.R. innert 7-14 Tagen versandfertig
    Veröffentlichung:  März 2026  
    Genre:  Naturwissensch., Medizin, Technik 
     
    appliedcomputerscienceandpsychology / ArtificialIntelligence / largelanguagemodels / Mensch-Computer-Interaktion / Nachrichtententechnik, Telekommunikation / Personality-DrivenLanguageModels / Psychologyandartificialintelligence
    ISBN:  9783031800894 
    EAN-Code: 
    9783031800894 
    Verlag:  Springer 
    Einband:  Kartoniert  
    Sprache:  English  
    Dimensionen:  H 240 mm / B 168 mm / D 11 mm 
    Gewicht:  339 gr 
    Seiten:  196 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:

    This book provides an innovative exploration into the realm of artificial intelligence (AI) by developing personalities for large language models (LLMs) using psychological principles. Aimed at making AI interactions feel more human-like, the book guides you through the process of applying psychological assessments to AIs, enabling them to exhibit traits such as extraversion, openness, and emotional stability. Perfect for developers, researchers, and entrepreneurs, this work merges psychology, philosophy, business, and cutting-edge computing to enhance how AIs understand and engage with humans across various industries like gaming and healthcare. The book not only unpacks the theoretical aspects of these advancements but also equips you with practical coding exercises and Python code examples, helping you create AI systems that are both innovative and relatable. Whether you're looking to deepen your understanding of AI personalities or integrate them into commercial applications, this book offers the tools and insights needed to pioneer this exciting frontier.

    In addition, this book:

    • Applies human psychological assessments to measure and quantify the behavioral responses of Language Large Models.
    • Outlines methodologies for the training and fine-tuning of LLMs to exhibit distinct and consistent personality traits.
    • Offers a guide on augmenting LLMs to deliver more human-like interactions, substantially elevating the user experience.

      



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