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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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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 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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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 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 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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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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Introduction to Generative AI
Introduction to Generative AI: Theoretical Foundations, Analysis and Practical Use CasesGenerative Artificial Intelligence is reshaping how we create, learn, and imagine. This book offers a clear and complete journey through the science and art behind this revolution — from how machines learn to produce text, images, and music, to how they are being built, tested, and applied in the real world.The first part of the book lays out the ideas that make generative AI possible — neural networks, transformers, diffusion models, and the mysterious “latent spaces” where creativity meets computation. The middle chapters explore how today’s AI systems reason, plan, and use tools, drawing on powerful frameworks such as LangChain, LangGraph, and AutoGen. The final section moves beyond algorithms, discussing how to build safe, fair, and energy-conscious AI that serves human goals rather than replacing them.Throughout, real-world examples bring the technology to life — from language models that write poetry, to multimodal systems that can paint or compose music, to intelligent agents that collaborate with humans in research, education, and design. Written in accessible language and supported by visual explanations, this book bridges deep technical ideas with human-centered understanding.HighlightsExplains the core principles of how generative models think and createShows how AI systems combine text, vision, and sound in unified waysConnects theory with hands-on applications and real-world use casesDiscusses ethics, creativity, and sustainability in the age of intelligent machinesWritten for learners, researchers, and professionals who want both clarity and depthIntroduction to Generative AI: Theoretical Foundations, Analysis and Practical Use Cases is an essential guide for anyone curious about how artificial intelligence is shaping the next chapter of human innovation.
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Modern Generative AI with ChatGPT and OpenAI Models
Harness the power of AI with innovative, real-world applications, and unprecedented productivity boosts, powered by the latest advancements in AI technology like ChatGPT and OpenAIPurchase of the print or Kindle book includes a free PDF eBookKey FeaturesExplore the theory behind generative AI models and the road to GPT3 and GPT4Become familiar with ChatGPT's applications to boost everyday productivityLearn to embed OpenAI models into applications using lightweight frameworks like LangChainBook DescriptionGenerative AI models and AI language models are becoming increasingly popular due to their unparalleled capabilities. This book will provide you with insights into the inner workings of the LLMs and guide you through creating your own language models. You'll start with an introduction to the field of generative AI, helping you understand how these models are trained to generate new data. Next, you'll explore use cases where ChatGPT can boost productivity and enhance creativity. You'll learn how to get the best from your ChatGPT interactions by improving your prompt design and leveraging zero, one, and few-shots learning capabilities. The use cases are divided into clusters of marketers, researchers, and developers, which will help you apply what you learn in this book to your own challenges faster. You'll also discover enterprise-level scenarios that leverage OpenAI models' APIs available on Azure infrastructure; both generative models like GPT-3 and embedding models like Ada. For each scenario, you'll find an end-to-end implementation with Python, using Streamlit as the frontend and the LangChain SDK to facilitate models' integration into your applications. By the end of this book, you'll be well equipped to use the generative AI field and start using ChatGPT and OpenAI models' APIs in your own projects.What you will learnUnderstand generative AI concepts from basic to intermediate levelFocus on the GPT architecture for generative AI modelsMaximize ChatGPT's value with an effective prompt designExplore applications and use cases of ChatGPTUse OpenAI models and features via API callsBuild and deploy generative AI systems with PythonLeverage Azure infrastructure for enterprise-level use casesEnsure responsible AI and ethics in generative AI systemsWho this book is forThis book is for individuals interested in boosting their daily productivity; businesspersons looking to dive deeper into real-world applications to empower their organizations; data scientists and developers trying to identify ways to boost ML models and code; marketers and researchers seeking to leverage use cases in their domain – all by using Chat GPT and OpenAI Models.A basic understanding of Python is required; however, the book provides theoretical descriptions alongside sections with code so that the reader can learn the concrete use case application without running the scripts.
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Exploring Generative AI with Computational Intelligence
This book demystifies the concept of AI-driven creativity with an in-depth understanding of the underlying principles, algorithms, and applications of generative AI. It begins with a coverage of AI fundamentals, followed by a technical discussion including detailed explanations of model architectures, training processes, and optimisation techniques. It explores case studies showcasing how generative AI is reshaping industries such as entertainment, marketing, design, and healthcare. The book also tackles ethical considerations, addressing issues related to bias, transparency, and responsible AI development.Features:Provides deep understanding of generative AI, including in-depth coverage of various generative models such as GANs, VAEs, and RNNs.Includes practical, real-world examples of how generative AI is applied in different industries.Dedicates significant attention to ethical considerations.Equips readers with the knowledge and tools to build, train, and deploy their own generative AI systems.Offers thorough explanations of AI algorithms, neural network architectures, and training processes.This book is aimed at graduate students and researchers in computer engineering, AI and ML.
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Generative AI Foundations in Python
Begin your generative AI journey with Python as you explore large language models, understand responsible generative AI practices, and apply your knowledge to real-world applications through guided tutorialsKey FeaturesGain expertise in prompt engineering, LLM fine-tuning, and domain adaptationUse transformers-based LLMs and diffusion models to implement AI applicationsDiscover strategies to optimize model performance, address ethical considerations, and build trust in AI systemsPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionThe intricacies and breadth of generative AI (GenAI) and large language models can sometimes eclipse their practical application. It is pivotal to understand the foundational concepts needed to implement generative AI. This guide explains the core concepts behind -of-the-art generative models by combining theory and hands-on application.Generative AI Foundations in Python begins by laying a foundational understanding, presenting the fundamentals of generative LLMs and their historical evolution, while also setting the stage for deeper exploration. You’ll also understand how to apply generative LLMs in real-world applications. The book cuts through the complexity and offers actionable guidance on deploying and fine-tuning pre-trained language models with Python. Later, you’ll delve into topics such as task-specific fine-tuning, domain adaptation, prompt engineering, quantitative evaluation, and responsible AI, focusing on how to effectively and responsibly use generative LLMs.By the end of this book, you’ll be well-versed in applying generative AI capabilities to real-world problems, confidently navigating its enormous potential ethically and responsibly.What you will learnDiscover the fundamentals of GenAI and its foundations in NLPDissect foundational generative architectures including GANs, transformers, and diffusion modelsFind out how to fine-tune LLMs for specific NLP tasksUnderstand transfer learning and fine-tuning to facilitate domain adaptation, including fields such as financeExplore prompt engineering, including in-context learning, templatization, and rationalization through chain-of-thought and RAGImplement responsible practices with generative LLMs to minimize bias, toxicity, and other harmful outputsWho this book is forThis book is for developers, data scientists, and machine learning engineers embarking on projects driven by generative AI. A general understanding of machine learning and deep learning, as well as some proficiency with Python, is expected.
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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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Exploring Generative AI with Computational Intelligence
This book demystifies the concept of AI-driven creativity with an in-depth understanding of the underlying principles, algorithms, and applications of generative AI. It begins with a coverage of AI fundamentals, followed by a technical discussion including detailed explanations of model architectures, training processes, and optimisation techniques. It explores case studies showcasing how generative AI is reshaping industries such as entertainment, marketing, design, and healthcare. The book also tackles ethical considerations, addressing issues related to bias, transparency, and responsible AI development.Features:Provides deep understanding of generative AI, including in-depth coverage of various generative models such as GANs, VAEs, and RNNs.Includes practical, real-world examples of how generative AI is applied in different industries.Dedicates significant attention to ethical considerations.Equips readers with the knowledge and tools to build, train, and deploy their own generative AI systems.Offers thorough explanations of AI algorithms, neural network architectures, and training processes.This book is aimed at graduate students and researchers in computer engineering, AI and ML.
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Generative AI Unleashed
Today's generative AI has been marked by the advent of neural networks, inspired by the human brain, which are trained to recognize patterns in a dataset. Once the network is trained, it can make decisions or predictions without being programmed to perform tasks. Generative AI learns from a set of data without explicit instructions and can create and generate new digital content such as text, audio and art. Recent models are beginning to overcome challenges such as computational power, data quality and training stability. This edited book on generative AI presents novel perspectives, approaches and methodologies, as well as security, ethical and legal considerations, and future trends. Topics and technologies covered include generative transformers and text generation models, generative models for human-like speech synthesis, generative AI for image synthesis, data synthesis for privacy protection, and exploration of the impact of generative AI in fields including industry 4.0, astronomy, and brain tumour detection. Two chapters offer perspectives on ethics and legality. Generative AI Unleashed: Advancements, transformative applications and future frontiers will serve as a valuable resource for researchers, engineers, advanced students and lecturers operating in the domains that are significantly impacted by generative AI.
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Generative Artificial Intelligence and Explainable Artificial Intelligence for Real-world Applications
This book integrates the concepts of explainable artificial intelligence, and generative explainable artificial intelligence, showcasing how explainability can be incorporated into generative models. It highlights the importance of making generative models transparent, offering strategies to achieve this through interpretability techniques.Focuses on the principles and methodologies of explainable artificial intelligence, providing readers with a thorough understanding of how artificial intelligence models can be made transparent and interpretable.Explores explainable artificial intelligence techniques, including feature importance, SHAP values, LIME, and counterfactual explanations.Offers an in-depth examination of generative artificial intelligence, covering cutting-edge advancements in generative models like GANs, VAEs, and transformer-based architectures.Bridges the gap between theoretical concepts and their practical applications, making advanced artificial intelligence technologies accessible to the readers.Includes numerous case studies and real-world examples that demonstrate the successful application of generative artificial intelligence, and explainable artificial intelligence.The text is primarily written for graduate students and academic researchers in electrical engineering, electronics, and communication engineering, computer science and engineering, biomedical engineering, and information technology.
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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...
