9798337373218 - hallucination-aware ai for truthful and aligned systems (6 risultati)
- Brossura
Da: PBShop.store UK, Fairford, GLOS, Regno UnitoPBShop.store UK
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 201,00
EUR 6,87 spedizioneSpedito da Regno Unito a U.S.A.Quantità: Più di 20 disponibili
PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.
- Brossura
- Print on Demand
Da: Grand Eagle Retail, Bensenville, IL, U.S.A.Grand Eagle Retail
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 253,59
Spedizione gratuitaSpedito in U.S.A.Quantità: 1 disponibili
Paperback. Condizione: 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 hallucinati…on, 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.
- Brossura
- Print on Demand
Da: CitiRetail, Stevenage, Regno UnitoCitiRetail
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 210,91
EUR 43,30 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 1 disponibili
Paperback. Condizione: 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 hallucinati…on, 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.
- Brossura
- Print on Demand
Da: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 272,74
EUR 32,52 spedizioneSpedito da Australia a U.S.A.Quantità: 1 disponibili
Paperback. Condizione: 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 hallucinati…on, 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.
- Altre immagini
- Brossura
- Print on Demand
Da: preigu, Osnabrück, Germaniapreigu
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 261,10
EUR 70,00 spedizioneSpedito da Germania a U.S.A.Quantità: 5 disponibili
Taschenbuch. Condizione: 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 D…emand.
- Altre immagini
- Brossura
- Print on Demand
Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 317,77
EUR 64,11 spedizioneSpedito da Germania a U.S.A.Quantità: 2 disponibili
Taschenbuch. Condizione: 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 rem…ain 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.
