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Autor(en): 
  • Vinod Kumar (CSIR-Central Electronics Engineering
  • AI-Processor Electronics: Basic Technology of Artificial Intelligence 
     

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


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   i.d.R. innert 14-24 Tagen versandfertig
    Veröffentlichung:  Januar 2025  
    Genre:  Naturwissensch., Medizin, Technik 
    ISBN:  9780750362573 
    EAN-Code: 
    9780750362573 
    Verlag:  Institute Of Physics Publishing 
    Einband:  Gebunden  
    Sprache:  English  
    Dimensionen:  H 254 mm / B 178 mm / D 22 mm 
    Gewicht:  905 gr 
    Seiten:  398 
    Illustration:  With figures in colour and black and white 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:

    The revolutionary impact of advances in artificial intelligence on consumer and industrial electronics has significantly increased the demand for specialized processing units for AI workloads. AI-Processor Electronics: Basic Technology of Artificial Intelligence explores the principles and technology behind these processors, which perform fast, energy-efficient data processing and complex computations. The book begins with an overview of AI, machine learning, and deep learning, and a brief introduction to digital computer electronics. It highlights the limitations of traditional CPUs in modern AI, discussing parallel computing and AI-optimized hardware that are specially tailored and adapted to meet AI requirements. The book then covers various AI processors, including graphical, tensor, neural, convolutional neural network, vision, sparse neural network, graph analytics, associative memory, and quantum processing units.

    Key features:

    • Provides a review of the physics of operation of a diverse variety of representative AI processors, and the key concepts and innovations underlying their development
    • Covers the underlying principles, technologies, opportunities and future prospects
    • Highlights the inadequacies of general-purpose processors in meeting the computationally intensive needs of artificial intelligence workloads
    • Elucidates the use of parallel processing architecture in simultaneously performing multiple calculations across data streams
    • Explores the concepts of neuromorphic and quantum computing to address the growing demands of big data in AI

      



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