Das baisakhi (30 resultados)

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PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

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Taschenbuch. Condición: Neu. Proceedings of International Conference on Computational Intelligence, Data Science and Cloud Computing | IEM-ICDC 2025 | Moutushi Singh (u. a.) | Taschenbuch | xx | Englisch | 2026 | Springer | EAN 9789819694938 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. …

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Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book includes selected papers presented in 3rd International Conference on Computational Intelligence, Data Science, and Cloud Computing (IEM-ICDC 2025), organized by the Departmentof Information Technology and Computer Science & Engineering, Institute of Engineering andManagement, Kolkata, India, during April 11 12, 2025.It covers substantial new findings about AI and robotics, image processing and NLP, cloudcomputing and big data analytics as well as in cyber-security, blockchain and IoT, and variousallied fields. The book serves as a reference resource for researchers and practitioners in academiaand industry.…

Hardback. Condición: New.

Paperback. Condición: new. Paperback. The rapid development of generative AI systems, particularly large language models (LLMs), has generated both widespread excitement and growing concern. While these systems exhibit remarkable fluency and reasoning capabilities, they remain prone to a critical limitation known as hallucination, the confident production of inaccurate, unverifiable, or fabricated information. This phenomenon underscores a fundamental challenge in the reliability and trustworthiness of AI technologies. As a result, there is a pressing need for research that examines the theoretical foundations of AI hallucination, as well as approaches for its detection, mitigation, and broader socio-technical implications. Hallucination-Aware AI for Truthful and Aligned Systems examines the corrective measures needed to address the widespread impact of AI hallucinations, drawing on the insights and practices of leading experts to confront one of the most pressing challenges in contemporary AI. Through a multidisciplinary approach, the book advances the conversation around generative AI by exploring methods to improve reliability, alignment, and trustworthiness across diverse application domains. Covering topics such as augmenting clinical expertise, evolution of hallucination, and evaluating and detecting hallucinations, this book is a critical academic resource for graduate and doctoral students, data scientists, machine learning engineers, innovation leads, tech consultants, policymakers, and more. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Paperback. Condición: new. Paperback. The rapid development of generative AI systems, particularly large language models (LLMs), has generated both widespread excitement and growing concern. While these systems exhibit remarkable fluency and reasoning capabilities, they remain prone to a critical limitation known as hallucination, the confident production of inaccurate, unverifiable, or fabricated information. This phenomenon underscores a fundamental challenge in the reliability and trustworthiness of AI technologies. As a result, there is a pressing need for research that examines the theoretical foundations of AI hallucination, as well as approaches for its detection, mitigation, and broader socio-technical implications. Hallucination-Aware AI for Truthful and Aligned Systems examines the corrective measures needed to address the widespread impact of AI hallucinations, drawing on the insights and practices of leading experts to confront one of the most pressing challenges in contemporary AI. Through a multidisciplinary approach, the book advances the conversation around generative AI by exploring methods to improve reliability, alignment, and trustworthiness across diverse application domains. Covering topics such as augmenting clinical expertise, evolution of hallucination, and evaluating and detecting hallucinations, this book is a critical academic resource for graduate and doctoral students, data scientists, machine learning engineers, innovation leads, tech consultants, policymakers, and more. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

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Hardcover. Condición: new. Hardcover. The rapid development of generative AI systems, particularly large language models (LLMs), has generated both widespread excitement and growing concern. While these systems exhibit remarkable fluency and reasoning capabilities, they remain prone to a critical limitation known as hallucination, the confident production of inaccurate, unverifiable, or fabricated information. This phenomenon underscores a fundamental challenge in the reliability and trustworthiness of AI technologies. As a result, there is a pressing need for research that examines the theoretical foundations of AI hallucination, as well as approaches for its detection, mitigation, and broader socio-technical implications. Hallucination-Aware AI for Truthful and Aligned Systems examines the corrective measures needed to address the widespread impact of AI hallucinations, drawing on the insights and practices of leading experts to confront one of the most pressing challenges in contemporary AI. Through a multidisciplinary approach, the book advances the conversation around generative AI by exploring methods to improve reliability, alignment, and trustworthiness across diverse application domains. Covering topics such as augmenting clinical expertise, evolution of hallucination, and evaluating and detecting hallucinations, this book is a critical academic resource for graduate and doctoral students, data scientists, machine learning engineers, innovation leads, tech consultants, policymakers, and more. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Hardcover. Condición: new. Hardcover. The rapid development of generative AI systems, particularly large language models (LLMs), has generated both widespread excitement and growing concern. While these systems exhibit remarkable fluency and reasoning capabilities, they remain prone to a critical limitation known as hallucination, the confident production of inaccurate, unverifiable, or fabricated information. This phenomenon underscores a fundamental challenge in the reliability and trustworthiness of AI technologies. As a result, there is a pressing need for research that examines the theoretical foundations of AI hallucination, as well as approaches for its detection, mitigation, and broader socio-technical implications. Hallucination-Aware AI for Truthful and Aligned Systems examines the corrective measures needed to address the widespread impact of AI hallucinations, drawing on the insights and practices of leading experts to confront one of the most pressing challenges in contemporary AI. Through a multidisciplinary approach, the book advances the conversation around generative AI by exploring methods to improve reliability, alignment, and trustworthiness across diverse application domains. Covering topics such as augmenting clinical expertise, evolution of hallucination, and evaluating and detecting hallucinations, this book is a critical academic resource for graduate and doctoral students, data scientists, machine learning engineers, innovation leads, tech consultants, policymakers, and more. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book includes selected papers presented in 3rd International Conference on Computational Intelligence, Data Science, and Cloud Computing (IEM-ICDC 2025), organized by the Departmentof Information Technology and Computer Science & Engineering, Institute of Engineering andManagement, Kolkata, India, during April 11 12, 2025.It covers substantial new findings about AI and robotics, image processing and NLP, cloudcomputing and big data analytics as well as in cyber-security, blockchain and IoT, and variousallied fields. The book serves as a reference resource for researchers and practitioners in academiaand industry. 629 pp. Englisch.…

Paperback. Condición: new. Paperback. The rapid development of generative AI systems, particularly large language models (LLMs), has generated both widespread excitement and growing concern. While these systems exhibit remarkable fluency and reasoning capabilities, they remain prone to a critical limitation known as hallucination, the confident production of inaccurate, unverifiable, or fabricated information. This phenomenon underscores a fundamental challenge in the reliability and trustworthiness of AI technologies. As a result, there is a pressing need for research that examines the theoretical foundations of AI hallucination, as well as approaches for its detection, mitigation, and broader socio-technical implications. Hallucination-Aware AI for Truthful and Aligned Systems examines the corrective measures needed to address the widespread impact of AI hallucinations, drawing on the insights and practices of leading experts to confront one of the most pressing challenges in contemporary AI. Through a multidisciplinary approach, the book advances the conversation around generative AI by exploring methods to improve reliability, alignment, and trustworthiness across diverse application domains. Covering topics such as augmenting clinical expertise, evolution of hallucination, and evaluating and detecting hallucinations, this book is a critical academic resource for graduate and doctoral students, data scientists, machine learning engineers, innovation leads, tech consultants, policymakers, and more. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…

Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book includes selected papers presented in 3rd International Conference on Computational Intelligence, Data Science, and Cloud Computing (IEM-ICDC 2025), organized by the Department of Information Technology and Computer Science & Engineering, Institute of Engineering and Management, Kolkata, India, during April 11 ? 12, 2025. It covers substantial new findings about AI and robotics, image processing and NLP, cloud computing and big data analytics as well as in cyber-security, blockchain and IoT, and various allied fields. The book serves as a reference resource for researchers and practitioners in academia and industry.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 652 pp. Englisch.…

Taschenbuch. Condición: Neu. Hallucination-Aware AI for Truthful and Aligned Systems | Baisakhi Das (u. a.) | Taschenbuch | Englisch | 2026 | IGI GLOBAL SCIENTIFIC PUBLISHING | EAN 9798337373218 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.…

Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The rapid development of generative AI systems, particularly large language models (LLMs), has generated both widespread excitement and growing concern. While these systems exhibit remarkable fluency and reasoning capabilities, they remain prone to a critical limitation known as hallucination, the confident production of inaccurate, unverifiable, or fabricated information. This phenomenon underscores a fundamental challenge in the reliability and trustworthiness of AI technologies. As a result, there is a pressing need for research that examines the theoretical foundations of AI hallucination, as well as approaches for its detection, mitigation, and broader socio-technical implications. Hallucination-Aware AI for Truthful and Aligned Systems examines the corrective measures needed to address the widespread impact of AI hallucinations, drawing on the insights and practices of leading experts to confront one of the most pressing challenges in contemporary AI. Through a multidisciplinary approach, the book advances the conversation around generative AI by exploring methods to improve reliability, alignment, and trustworthiness across diverse application domains. Covering topics such as augmenting clinical expertise, evolution of hallucination, and evaluating and detecting hallucinations, this book is a critical academic resource for graduate and doctoral students, data scientists, machine learning engineers, innovation leads, tech consultants, policymakers, and more.…

Hardcover. Condición: new. Hardcover. The rapid development of generative AI systems, particularly large language models (LLMs), has generated both widespread excitement and growing concern. While these systems exhibit remarkable fluency and reasoning capabilities, they remain prone to a critical limitation known as hallucination, the confident production of inaccurate, unverifiable, or fabricated information. This phenomenon underscores a fundamental challenge in the reliability and trustworthiness of AI technologies. As a result, there is a pressing need for research that examines the theoretical foundations of AI hallucination, as well as approaches for its detection, mitigation, and broader socio-technical implications. Hallucination-Aware AI for Truthful and Aligned Systems examines the corrective measures needed to address the widespread impact of AI hallucinations, drawing on the insights and practices of leading experts to confront one of the most pressing challenges in contemporary AI. Through a multidisciplinary approach, the book advances the conversation around generative AI by exploring methods to improve reliability, alignment, and trustworthiness across diverse application domains. Covering topics such as augmenting clinical expertise, evolution of hallucination, and evaluating and detecting hallucinations, this book is a critical academic resource for graduate and doctoral students, data scientists, machine learning engineers, innovation leads, tech consultants, policymakers, and more. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…

Buch. Condición: Neu. Hallucination-Aware AI for Truthful and Aligned Systems | Baisakhi Das (u. a.) | Buch | Englisch | 2026 | IGI GLOBAL SCIENTIFIC PUBLISHING | EAN 9798337373201 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand. …

Buch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The rapid development of generative AI systems, particularly large language models (LLMs), has generated both widespread excitement and growing concern. While these systems exhibit remarkable fluency and reasoning capabilities, they remain prone to a critical limitation known as hallucination, the confident production of inaccurate, unverifiable, or fabricated information. This phenomenon underscores a fundamental challenge in the reliability and trustworthiness of AI technologies. As a result, there is a pressing need for research that examines the theoretical foundations of AI hallucination, as well as approaches for its detection, mitigation, and broader socio-technical implications. Hallucination-Aware AI for Truthful and Aligned Systems examines the corrective measures needed to address the widespread impact of AI hallucinations, drawing on the insights and practices of leading experts to confront one of the most pressing challenges in contemporary AI. Through a multidisciplinary approach, the book advances the conversation around generative AI by exploring methods to improve reliability, alignment, and trustworthiness across diverse application domains. Covering topics such as augmenting clinical expertise, evolution of hallucination, and evaluating and detecting hallucinations, this book is a critical academic resource for graduate and doctoral students, data scientists, machine learning engineers, innovation leads, tech consultants, policymakers, and more.…