Essentials of Generative AI

Essentials of Generative AI

Takeshi Okadome

84,43 €
IVA incluido
Consulta disponibilidad
Editorial:
Springer Nature B.V.
Año de edición:
2025
Materia
Inteligencia artificial
ISBN:
9789819600281

Selecciona una librería:

  • Librería Samer Atenea
  • Librería Aciertas (Toledo)
  • Kálamo Books
  • Librería Perelló (Valencia)
  • Librería Elías (Asturias)
  • Donde los libros
  • Librería Kolima (Madrid)
  • Librería Proteo (Málaga)

This book provides a concise yet comprehensive introduction to generative artificial intelligence.The first part explains the foundational technologies and architectures that support the realization of generative models. It covers evolved and deepened elements, word embeddings as a representative example of representation learning, and the Transformer as a network foundation, along with its underlying attention mechanism. Reinforcement learning, which became essential for elevating large-scale language models to language generation models, is also discussed in detail, focusing on essential aspects.The second part deals with language generation. It starts by elucidating language modelsand introduces large-scale language models with broad applications as the foundational architecture of language processing, further discussing language generation models as their evolution. Though not common terminology, in this book, models such as ChatGPT and Llama 2, which are large-scale language models fine-tuned using reinforcement learning, are referred to as generative language models.The third part addresses image generation, discussing variational autoencoders and the remarkable diffusion models. Additionally, it explains Generative Adversarial Networks(GAN). Although GAN poses challenges due to unstable learning, their conceptual framework is widely applicable, especially Wasserstein GAN seems suitable for introducing optimal trans- port distance, which is utilized in various scenarios.This book primarily serves as a companion for researchers or graduate students in machine learning, aiming to help them understand the essence of generative AI and lay the groundwork for advancing their own research.

Artículos relacionados

  • Artificial Cognition Systems
    ...
  • Cross-Disciplinary Applications of Artificial Intelligence and Pattern Recognition
    Vijay Kumar Mago
    The need for intelligent machines in areas such as medical diagnostics, biometric security systems, and image processing motivates researchers to develop and explore new techniques, algorithms, and applications in this evolving field. Cross-Disciplinary Applications of Artificial Intelligence and Pattern Recognition: Advancing Technologies provides a common platform for researc...
  • Emerging Applications of Natural Language Processing
    Over the last few years, the area of Natural Language Processing has drastically grown in recognition, not only within the research and development community, but also with industry professionals. As NLP continues to be discussed and researched, certain areas continue to grow and mature. As a result, the need for advanced research and information is in high demand. Emerging App...
  • Androids, Cyborgs, and Robots in Contemporary Culture and Society
    Steven John Thompson
    Mankind’s dependence on artificial intelligence and robotics is increasing rapidly as technology becomes more advanced. Finding a way to seamlessly intertwine these two worlds will help boost productivity in society and aid in a variety of ways in modern civilization. Androids, Cyborgs, and Robots in Contemporary Culture and Society is an essential scholarly resource that delve...
  • Deep Learning Innovations and Their Convergence With Big Data
    The expansion of digital data has transformed various sectors of business such as healthcare, industrial manufacturing, and transportation. A new way of solving business problems has emerged through the use of machine learning techniques in conjunction with big data analytics. Deep Learning Innovations and Their Convergence With Big Data is a pivotal reference for the latest sc...
  • Computational Psychoanalysis and Formal Bi-Logic Frameworks
    Giuseppe Iurato
    Computational psychoanalysis is a new field stemming from Freudian psychoanalysis. The new area aims to understand the primary formal structures and running mechanisms of the unconscious while implementing them into computer sciences. Computational Psychoanalysis and Formal Bi-Logic Frameworks provides emerging information on this new field which uses psychoanalysis and the unc...