Search results for "generative ki"
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300 Keywords Generative KI
Von A wie Alignment bis Z wie Zensur: Dieses Nachschlagewerk bietet in mehr als 300 Einträgen einen Überblick über das Thema der generativen KI. Es klärt zahlreiche Fachbegriffe, stellt Anwendungsbereiche vor und diskutiert aktuelle Fragestellungen. Dabei spielen neben technischen und wirtschaftlichen Fragen insbesondere ethische und ästhetische eine Rolle. So wird nach der Schönheit von Artefakten gefragt, es wird die Stellung von Bildern zwischen Kunst und Kitsch ausgeleuchtet, und es wird eine Bias-Diskussion zu Text- und Bildgeneratoren geführt. Insgesamt steht der Nutzen der generativen KI im Vordergrund, und die Freude und Lust, sie zu benutzen. Das Buch richtet sich an ein breites Publikum, etwa Journalisten, Politiker und Bürger, aber auch an Wissenschaftler aller Bereiche.
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Generative KI für Dummies
Die Möglichkeiten generativer KI optimal nutzen Mithilfe von generativer Künstlicher Intelligenz lassen sich Texte, Bilder, Videos, Sprache, Musik, Softwarecodes und auch Kunst und Design erschaffen. Doch wie können Sie die Möglichkeiten generativer KI individuell am besten nutzen? KI-Expertin Pam Baker gibt Ihnen einen guten Überblick und führt Sie in die bekanntesten Tools ein. Das Buch erklärt Ihnen, wie Sie geeignete Plattformen finden, gute Prompts schreiben, KI in Ihren Workflow einbinden und gezielt einsetzen – und entscheiden, wann doch ein wenig Human Touch gebraucht wird. Gut verständlich und praxisnah: der ideale Einstieg in ein Thema, das unsere Arbeitswelt rasant verändert. Sie erfahren Welche Plattformen sich für welche Zwecke eignenWie Sie KI-generierte Texte, Bilder, Videos und Audios erstellenWie Sie KI in Ihren Workflow integrierenWie es Ihnen gelingt, KI-Inhalte »menschlicher« zu machen
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Generative KI als neues Teammitglied im Marketing
Generative Künstliche Intelligenz bringt die digitale Transformation im Marketing auf eine neue Ebene und stellt Marketingverantwortliche vor unbekannte Herausforderungen. Erfahren Sie, wie sich die Rolle von Marketingmanager:innen in Zeiten von Generativer KI verändert und welche neuen Kompetenzen gefragt sind. Darüber hinaus gibt das Buch einen Überblick über die Auswirkungen von Generativer KI auf Marketingorganisationen und einen konkreten Leitfaden zu den Handlungsfeldern. .
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Wachstum durch den Einsatz von Generativer KI
Dieses Buch bietet einen fundierten Einblick in die Relevanz von Generativer Künstlicher Intelligenz (KI) im Marketing. Neben einer kompakten Darstellung der Funktionsweise und Grenzen von Generativer KI wird ein umfassender Überblick über KI-basierte Medienformate gegeben.Anhand von Praxisbeispielen und konkreten Auswahlkriterien erfahren Sie, wie Sie geeignete Anwendungsfälle für Generative KI identifizieren und in Ihre Marketingstrategie integrieren können. .
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Generative Engine Optimization: Sichtbar in KI-Systemen
Dieses Essential erklärt, wie Unternehmen in der neuen Ära der KI-Systeme online sichtbar bleiben. Denn: ChatGPT, AI Mode oder Microsoft Copilot verändern die Art und Weise, wie Menschen nach Informationen suchen - und stellen Unternehmen vor einen grundlegenden Wandel. Wer nicht in KI-Antworten auftaucht, verliert Reichweite und Relevanz.Die Autoren führen in die neue Disziplin Generative Engine Optimization (GEO) ein - die die klassische Suchmaschinenoptimierung (SEO) ersetzen wird. Sie zeigen, wie Marken in KI-Antworten auftauchen, welche Faktoren die Sichtbarkeit beeinflussen und wie sich Erfolge messen lassen.Ein kompaktes Fachbuch für Marketingverantwortliche und Entscheider*innen, die verstehen wollen, wie ihr Unternehmen in KI-Systemen präsent bleibt.
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Generative Artificial Intelligence in Knowledge Management Systems
This book looks at Generative Artificial Intelligence (GAI) and Knowledge Management Systems (KMS). It explains the design considerations to implement Generative AI in practice.The book looks at the evolving digital environment and discusses how organizations may effectively manage knowledge through emerging technologies. Chapters cover theory, design and implementation, and case studies from industry players. These case studies will focus on organization implementation experiences to draw out applicable frameworks, principles and best practices. This provides readers with essential insights into future technology development trends.Providing a methodological approach to designing and deploying GAI-based KMS in business, this book will appeal to academic researchers, industrial practitioners, students, and anyone interested in GAI-based KMS.
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Essentials of Generative AI
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.
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KI 2001: Advances in Artificial Intelligence
This volume contains the contributions to the Joint German/Austrian Con- rence on Arti?cial Intelligence, KI 2001, which comprises the 24th German and the 9th Austrian Conference on Arti?cial Intelligence. They are divided into the following categories: – 2 contributions by invited speakers of the conference; – 29 accepted technical papers, of which 5 where submitted as application papers and 24 as papers on foundations of AI; – 4 contributions by participants of the industrial day, during which companies working in the ?eld presented their AI applications. After a long period of separate meetings, the German and Austrian Societies ¨ for Arti?cial Intelligence, KI and OGAI, decided to hold a joint conference in Vienna in 2001. The two societies had previously held one joint conference. This took place in Ottstein, a small town in Lower Austria, in 1986. At that time, the rise of expert system technology had also renewed interest in AI in general, with quite some expectations for future advances regarding the use of AI techniques in applications pervading many areas of our daily life. Since then ?fteen years have passed, and we may want to comment, at the beginning of a newcentury, on the progress that has been made in this direction.
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KI 2019: Advances in Artificial Intelligence
This book constitutes the refereed proceedings of the 42nd German Conference on Artificial Intelligence, KI 2019, held in Kassel, Germany, in September 2019.The 16 full and 10 short papers presented together with 3 extended abstracts in this volume were carefully reviewed and selected from 82 submissions. KI 2019 has a special focus theme on "AI methods for Argumentation" and especially invited contributions that use methods from all areas of AI to understand, formalize or generate argument structures in natural language.
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Learn Generative AI with PyTorch
Learn how generative AI works by building your very own models that can write coherent text, create realistic images, and even make lifelike music. Learn Generative AI with PyTorch teaches the underlying mechanics of generative AI by building working AI models from scratch. Throughout, you'll use the intuitive PyTorch framework that's instantly familiar to anyone who's worked with Python data tools. Along the way, you'll master the fundamentals of General Adversarial Networks (GANs), Transformers, Large Language Models (LLMs), variational autoencoders, diffusion models, LangChain, and more! In Learn Generative AI with PyTorch you'll build these amazing models: A simple English-to-French translatorA text-generating model as powerful as GPT-2A diffusion model that produces realistic flower imagesMusic generators using GANs and TransformersAn image style transfer modelA zero-shot know-it-all agent The generative AI projects you create use the same underlying techniques and technologies as full-scale models like GPT-4 and Stable Diffusion. You don't need to be a machine learning expert—you can get started with just some basic Python programming skills. About the technology: Transformers, Generative Adversarial Networks (GANs), diffusion models, LLMs, and other powerful deep learning patterns have radically changed the way we manipulate text, images, and sound. Generative AI may seem like magic at first, but with a little Python, the PyTorch framework, and some practice, you can build interesting and useful models that will train and run on your laptop. This book shows you how.
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Learning with Generative Artificial Intelligence
This book delves into the core of education’s digital transformation, presenting a thorough and empirical examination of generative artificial intelligence (GenAI)’s impact beyond the theoretical and fragmented insights prevalent in current discourse.Drawing from peer-reviewed and extensive empirical studies, the contributors aim to unveil the multifaceted effects of GenAI (particularly ChatGPT) on learning. They navigate through topics of interaction, assessment, emotion, effect and efficiency, meta-cognition, and ethics, offering a comprehensive exploration of GenAI’s educational implications. This book presents a closed loop of learning theory, multimodal data, and learning analytics technology. Furthermore, this book builds and proposes core conceptual models for future learning and identifies potential research directions.This book will serve as a foundational reference for educators seeking innovative learning and teaching methods and for researchers and technologists who seek to push the boundaries of educational technology and related areas.
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Generative Artificial Intelligence
This book explains the field of Generative Artificial Intelligence (AI), focusing on its potential and applications, and aims to provide you with an understanding of the underlying principles, techniques, and practical use cases of Generative AI models.The book begins with an introduction to the foundations of Generative AI, including an overview of the field, its evolution, and its significance in today’s AI landscape. It focuses on generative visual models, exploring the exciting field of transforming text into images and videos. A chapter covering text-to-video generation provides insights into synthesizing videos from textual descriptions, opening up new possibilities for creative content generation. A chapter covers generative audio models and prompt-to-audio synthesis using Text-to-Speech (TTS) techniques. Then the book switch gears to dive into generative text models, exploring the concepts of Large Language Models (LLMs), natural language generation (NLG), fine-tuning, prompt tuning, and reinforcement learning. The book explores techniques for fixing LLMs and making them grounded and indestructible, along with practical applications in enterprise-grade applications such as question answering, summarization, and knowledge-based generation.By the end of this book, you will understand Generative text, and audio and visual models, and have the knowledge and tools necessary to harness the creative and transformative capabilities of Generative AI. What You Will LearnWhat is Generative Artificial Intelligence?What are text-to-image synthesis techniques and conditional image generation?What is prompt-to-audio synthesis using Text-to-Speech (TTS) techniques?What are text-to-video models and how do you tune them?What are large language models, and how do you tune them? Who This Book Is ForThose with intermediate to advanced technical knowledge in artificial intelligence and machine learning
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Generative AI for Connected and Autonomous Vehicles
Harness generative AI for connected and autonomous vehicle systems As generative AI reshapes intelligent transportation, engineers and researchers need rigorous frameworks for deploying these technologies in safety-critical systems. This book offers a comprehensive treatment of the models, protocols, and adaptation techniques required to bring large language models, vision-language models, diffusion models, and agentic systems into modern CAV architectures. The book progresses from generative foundations through multimodal representation, language-based interaction, agentic coordination, communication protocols, model adaptation, and validation and safety. Mathematical, probabilistic, and reinforcement-learning prerequisites are consolidated into dedicated appendices, allowing the main chapters to focus on system design and CAV-specific applications. Written by an award-winning researcher with more than 100 patents across connected vehicles and AI, readers will also find: Practical treatment of prompt engineering, retrieval-augmented generation, function calling, and tool use for grounding GenAI in vehicular contextChapters on agent architectures, multi-agent systems, orchestration frameworks, and MCP and A2A protocols for collaborative CAV intelligenceAdaptation and deployment techniques including supervised fine-tuning, reinforcement learning fine-tuning, and knowledge distillation for resource-constrained edge platformsDedicated chapters on simulation platforms, evaluation methodologies, and ethical and safety considerations for deploying generative AI in autonomous vehicles Automotive engineers, AI researchers, and graduate students at the intersection of machine learning and intelligent transportation will find this book indispensable. Readers from OEMs, mobility startups, or academic labs gain the foundations and practices needed to design, adapt, and validate generative AI in connected mobility.
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, by sungano kanjere South Africa school team narrowly beaten by Australia in thrilling Kids Literacy Quiz Final
Rugby is not the only sport where South Africa and Australia have clashed recently. On 13 August, the two proud nations faced each other down in...
