Managing and Understanding Artificial Intelligence: From Classical to Generative AI
portes grátis
Managing and Understanding Artificial Intelligence: From Classical to Generative AI
A Practice Guide for Decision-makers, Developers and Regulators in the Age of the EU AI Act
Holoyad, Taras; Hildesheim, Wolfgang; Schmid, Thomas
Springer Nature Switzerland AG
05/2026
356
Dura
Inglês
9783032005328
Pré-lançamento - envio 15 a 20 dias após a sua edição
Descrição não disponível.
About the Authors.- Acknowledgments.- About the Guest Authors.- Foreword.- Preface.- How to read this book?- Part I. Basics.- 1. Artificial Intelligence - yesterday, today, tomorrow.- 2. Models and modeling - the essence of AI development.- 3. Non-stop models - data-driven AI at industrial scale.- 4. Foundation Models - A Disruptive AI Paradigm.- 5. Success with AI business models - 5 factors for data-driven AI.- Part II. 6. The three-dimensional taxonomy for AI systems "AI=MC (2)".- 7. Taxonomy of AI methods.- 8. Taxonomy of AI capabilities.- 9. AI characteristics of regulatory relevance.- 10. Analyzing and comparing with the AI=MC (2) taxonomy.- 11. Designing Modular AI Systems with the AI=MC (2) Taxonomy.- Part III. AI in practice.- 12. Combining different AI's for intelligent crew planning in shipping.- 13. AI-based customer service - the HUK24 virtual assistant.- 14. AI-based object recognition in remote sensing.- 15. Luminous - a European large language model.- 16. AI-based mobile data capture.- 17. Generative Artificial Intelligence as a Tool for IP Experts.- Part IV. Trustworthiness, standardization and regulation.- 18. Trustworthiness of Artificial Intelligence.- 19. Standardization of Artificial Intelligence.- 20. The AI Act - Europe's law on AI.- 21. AI-based medical devices: Example of conformity assessment.- 22. Quicker to market - The benefits from DIN standards.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
AI-based Data Acquisition;AI Factory;AI Regulation;AI Standardization;European AI Policy;Generative AI;Large Language Models;Luminous;Object Recognition;Symbolic AI;Transformer Architecture;Trustworthy AI;Virtual Assistants
About the Authors.- Acknowledgments.- About the Guest Authors.- Foreword.- Preface.- How to read this book?- Part I. Basics.- 1. Artificial Intelligence - yesterday, today, tomorrow.- 2. Models and modeling - the essence of AI development.- 3. Non-stop models - data-driven AI at industrial scale.- 4. Foundation Models - A Disruptive AI Paradigm.- 5. Success with AI business models - 5 factors for data-driven AI.- Part II. 6. The three-dimensional taxonomy for AI systems "AI=MC (2)".- 7. Taxonomy of AI methods.- 8. Taxonomy of AI capabilities.- 9. AI characteristics of regulatory relevance.- 10. Analyzing and comparing with the AI=MC (2) taxonomy.- 11. Designing Modular AI Systems with the AI=MC (2) Taxonomy.- Part III. AI in practice.- 12. Combining different AI's for intelligent crew planning in shipping.- 13. AI-based customer service - the HUK24 virtual assistant.- 14. AI-based object recognition in remote sensing.- 15. Luminous - a European large language model.- 16. AI-based mobile data capture.- 17. Generative Artificial Intelligence as a Tool for IP Experts.- Part IV. Trustworthiness, standardization and regulation.- 18. Trustworthiness of Artificial Intelligence.- 19. Standardization of Artificial Intelligence.- 20. The AI Act - Europe's law on AI.- 21. AI-based medical devices: Example of conformity assessment.- 22. Quicker to market - The benefits from DIN standards.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
