Optimizing Prompt Engineering For Generative Ai

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Optimizing Prompt Engineering For Generative Ai

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Author : ERIK HERMAN
language : en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date : 2025-03-11

Optimizing Prompt Engineering For Generative Ai written by ERIK HERMAN and has been published by Walter de Gruyter GmbH & Co KG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-11 with Computers categories.

In the constantly changing field of artificial intelligence, effective communication and prompt engineering have become essential for developers, researchers, and tech enthusiasts to guide and improve AI. Optimizing Prompt Engineering for Generative AI provides in-depth insight into the techniques and skills needed to create prompts that enhance the performance and relevance of conversational AI systems. Intended for AI practitioners, technology developers, and academics, this book serves as both a foundational text for newcomers and a detailed guide for experienced professionals seeking to refine their skills. This book equips readers with the knowledge to effectively design, test, and refine AI prompts that lead to more accurate, engaging, and ethically aligned AI interactions. From the basics of prompt construction to advanced techniques for specific industries, the content covers a broad spectrum. Each chapter builds on the previous one, starting with an introduction to the fundamental concepts of prompt engineering, moving through detailed discussions on crafting effective prompts, and concluding with insights into future trends and ethical considerations. Through a blend of theoretical explanations, practical applications, case studies, and hands-on exercises, the coverage ensures that readers not only understand the principles of prompt engineering but also know how to apply these principles effectively. By the end of this journey, readers will be equipped to enhance the capabilities of AI systems, making them more responsive, intuitive, and beneficial in a variety of real-world settings. This book is not just a manual; it’s a pathway to mastering the art of conversational AI, designed to foster an innovative approach to AI interactions that are as transformative as they are forward-thinking.

Prompt Engineering For Generative Ai

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Author : James Phoenix
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2024-05-16

Prompt Engineering For Generative Ai written by James Phoenix and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-16 with Computers categories.

Large language models (LLMs) and diffusion models such as ChatGPT and Stable Diffusion have unprecedented potential. Because they have been trained on all the public text and images on the internet, they can make useful contributions to a wide variety of tasks. And with the barrier to entry greatly reduced today, practically any developer can harness LLMs and diffusion models to tackle problems previously unsuitable for automation. With this book, you'll gain a solid foundation in generative AI, including how to apply these models in practice. When first integrating LLMs and diffusion models into their workflows, most developers struggle to coax reliable enough results from them to use in automated systems. Authors James Phoenix and Mike Taylor show you how a set of principles called prompt engineering can enable you to work effectively with AI. Learn how to empower AI to work for you. This book explains: The structure of the interaction chain of your program's AI model and the fine-grained steps in between How AI model requests arise from transforming the application problem into a document completion problem in the model training domain The influence of LLM and diffusion model architecture—and how to best interact with it How these principles apply in practice in the domains of natural language processing, text and image generation, and code

Prompt Engineering And Generative Ai Applications For Teaching And Learning

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Author : ElSayary, Areej
language : en
Publisher: IGI Global
Release Date : 2025-03-13

Prompt Engineering And Generative Ai Applications For Teaching And Learning written by ElSayary, Areej and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-13 with Computers categories.

By creating specific prompts, educators can harness the power of AI models to generate tailored content, provide instant feedback, and simulate real-world scenarios for deeper learning engagement. Whether it's creating personalized lesson plans, generating creative writing prompts, or assisting with problem-solving exercises, generative AI creates an interactive approach to education. As AI evolves, its potential to support both educators and students in more efficient, adaptive, and inclusive ways may transform the future of learning. Prompt Engineering and Generative AI Applications for Teaching and Learning explores generative AI’s impact on education, navigating the complexities of its integration into teaching and learning strategies. It examines the complex dynamics between AI technology and educational methodologies, offering new perspectives on personalized education, the art of prompt engineering skills, and the role of generative AI in research. This book covers topics such as ethics and law, higher education, and personalized learning, and is a useful resource for academicians, researchers, computer engineers, and data scientists.

Optimizing Generative Ai Workloads For Sustainability

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Author : Ishneet Kaur Dua
language : en
Publisher: Springer Nature
Release Date : 2024-11-18

Optimizing Generative Ai Workloads For Sustainability written by Ishneet Kaur Dua and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-18 with Computers categories.

This comprehensive guide provides practical strategies for optimizing Generative AI systems to be more sustainable and responsible. As advances in Generative AI such as large language models accelerate, optimizing these resource-intensive workloads for efficiency and alignment with human values grows increasingly urgent. The book starts with the concept of Generative AI and its wide-ranging applications, while also delving into the environmental impact of AI workloads and the growing importance of adopting sustainable AI practices. It then delves into the fundamentals of efficient AI workload management, providing insights into understanding AI workload characteristics, measuring performance, and identifying bottlenecks and inefficiencies. Hardware optimization strategies are explored in detail, covering the selection of energy-efficient hardware, leveraging specialized AI accelerators, and optimizing hardware utilization and scheduling for sustainable operations. You are also guided through software optimization techniques tailored for Generative AI, including efficient model architecture, compression, and quantization methods, and optimization of software libraries and frameworks. Data management and preprocessing strategies are also addressed, emphasizing efficient data storage, cleaning, preprocessing, and augmentation techniques to enhance sustainability throughout the data life cycle. The book further explores model training and inference optimization, cloud and edge computing strategies for Generative AI, energy-efficient deployment and scaling techniques, and sustainable AI life cycle management practices, and concludes with real-world case studies and best practices By the end of this book, you will take away a toolkit of impactful steps you can implement to minimize the environmental harms and ethical risks of Generative AI. For organizations deploying any type of generative model at scale, this essential guide provides a blueprint for developing responsible AI systems that benefit society. What You Will Learn Understand how Generative AI can be more energy-efficient through improvements such as model compression, efficient architecture, hardware optimization, and carbon footprint tracking Know the techniques to minimize data usage, including evaluation, filtering, synthesis, few-shot learning, and monitoring data demands over time Understand spanning efficiency, data minimization, and alignment for comprehensive responsibility Know the methods for detecting, understanding, and mitigating algorithmic biases, ensuring diversity in data collection, and monitoring model fairness Who This book Is For Professionals seeking to adopt responsible and sustainable practices in their Generative AI work; leaders and practitioners who need actionable strategies and recommendations that can be implemented directly in real-world systems and organizational workflows; ML engineers and data scientists building and deploying Generative AI systems in industry settings; and researchers developing new generative AI techniques, such as at technology companies or universities

Generative Ai And Llms

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Author : S. Balasubramaniam
language : en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date : 2024-09-23

Generative Ai And Llms written by S. Balasubramaniam and has been published by Walter de Gruyter GmbH & Co KG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-23 with Computers categories.

Generative artificial intelligence (GAI) and large language models (LLM) are machine learning algorithms that operate in an unsupervised or semi-supervised manner. These algorithms leverage pre-existing content, such as text, photos, audio, video, and code, to generate novel content. The primary objective is to produce authentic and novel material. In addition, there exists an absence of constraints on the quantity of novel material that they are capable of generating. New material can be generated through the utilization of Application Programming Interfaces (APIs) or natural language interfaces, such as the ChatGPT developed by Open AI and Bard developed by Google. The field of generative artificial intelligence (AI) stands out due to its unique characteristic of undergoing development and maturation in a highly transparent manner, with its progress being observed by the public at large. The current era of artificial intelligence is being influenced by the imperative to effectively utilise its capabilities in order to enhance corporate operations. Specifically, the use of large language model (LLM) capabilities, which fall under the category of Generative AI, holds the potential to redefine the limits of innovation and productivity. However, as firms strive to include new technologies, there is a potential for compromising data privacy, long-term competitiveness, and environmental sustainability. This book delves into the exploration of generative artificial intelligence (GAI) and LLM. It examines the historical and evolutionary development of generative AI models, as well as the challenges and issues that have emerged from these models and LLM. This book also discusses the necessity of generative AI-based systems and explores the various training methods that have been developed for generative AI models, including LLM pretraining, LLM fine-tuning, and reinforcement learning from human feedback. Additionally, it explores the potential use cases, applications, and ethical considerations associated with these models. This book concludes by discussing future directions in generative AI and presenting various case studies that highlight the applications of generative AI and LLM.

Prompt Engineering

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Author : Eric C. Richardson
language : en
Publisher: BPB Publications
Release Date : 2025-05-15

Prompt Engineering written by Eric C. Richardson and has been published by BPB Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-15 with Computers categories.

DESCRIPTION The power of AI and ML can only be harnessed if one knows how to utilize it effectively. This book serves as your accessible guide to understanding the core principles and the exciting world of prompt engineering, a crucial skill in today's AI-driven landscape. Whether you are a curious beginner or a tech enthusiast, this book will illuminate the path to mastering intelligent interactions with AI. Explore the evolution of AI and ML, starting with foundational concepts and historical milestones, progressing to the fascinating realm of generative models and the revolutionary rise of transformer architectures like GPT. Discover the art and science behind crafting effective prompts, exploring various prompt types, understanding the significance of tokens and syntax, and implementing efficiency strategies. You will gain insights into practical tools and platforms, alongside a crucial understanding of the ethical and societal implications and the financial considerations of working with AI. Finally, explore real-world applications through examples of cutting-edge chatbots and AI systems. The book covers ethical practices and best practices that help users achieve efficiency while also considering AI's broader impacts on privacy, security, and fairness. By the end of this book, you will possess a solid understanding of the technological underpinnings of modern AI and the practical expertise to engineer compelling and effective prompts. You will be well-equipped to navigate the evolving world of AI and leverage its capabilities with confidence and competence. WHAT YOU WILL LEARN ● Grasp AI/ML Foundations, historical context, diverse learning paradigms, and core concepts. ● Understand AI, ML Foundations, Transformer-based systems, and the future directions of prompt engineering. ● Explore generative models' development, GAN mechanics, and the shift towards transformers. ● Comprehend transformer architecture, self-attention, and the rise of GPT-like models. ● Master transformer models' pivotal role and application in effective prompt engineering. ● Analyze GPT model architecture, training, language modeling, and diverse applications. ● Define prompt engineering, its objectives, components, and evaluation methodologies. WHO THIS BOOK IS FOR This book is tailored for AI professionals, developers, and enthusiasts aiming to deepen their practical AI interaction skills. It also benefits educators, tech industry workers, and individuals involved in designing or implementing AI solutions in their workflows, requiring a foundational understanding of fundamental technology concepts. TABLE OF CONTENTS 1. A Brief Overview of ML and AI 2. Evolution of Machine Learning 3. Development of Generative Models 4. Rise of GPT and Transformer-Based Models 5. Transformer-based Models in Prompt Engineering 6. Transformer Architecture Concepts 7. The Prompt Ecosystem 8. Prompt Types In-Depth 9. Understanding Tokens 10. Efficiency in Prompt Engineering 11. Critical Role of Syntax 12. Techniques and Strategies for Prompt Engineering 13. Challenges of Quality Prompts 14. Tools and Platforms for Prompt Engineering 15. Ethics in Artificial Intelligence 16. Finances of Prompts and Cost Management 17. Future Directions and Challenges of AI and ML 18. Legal Framework for Artificial Intelligence 19. Practical Examples of Chatbots and AI Systems

Transforming Education With Generative Ai Prompt Engineering And Synthetic Content Creation

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Author : Sharma, Ramesh C.
language : en
Publisher: IGI Global
Release Date : 2024-02-07

Transforming Education With Generative Ai Prompt Engineering And Synthetic Content Creation written by Sharma, Ramesh C. and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-07 with Education categories.

The rise of generative Artificial Intelligence (AI) signifies a momentous stride in the evolution of Large Language Models (LLMs) within the expansive sphere of Natural Language Processing (NLP). This groundbreaking advancement ripples through numerous facets of our existence, with education, AI literacy, and curriculum enhancement emerging as focal points of transformation. Within the pages of Transforming Education With Generative AI: Prompt Engineering and Synthetic Content Creation, readers embark on a journey into the heart of this transformative phenomenon. Generative AI's influence extends deeply into education, touching the lives of educators, administrators, policymakers, and learners alike. Within the pages of this book, we explore the intricate art of prompt engineering, a skill that shapes the quality of AI-generated educational content. As generative AI becomes increasingly accessible, this comprehensive volume empowers its audience, by providing them with the knowledge needed to navigate and harness the potential of this powerful tool.

The Complete Obsolete Guide To Generative Ai

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Author : David Clinton
language : en
Publisher: Simon and Schuster
Release Date : 2024-08-27

The Complete Obsolete Guide To Generative Ai written by David Clinton and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-27 with Computers categories.

The Complete Obsolete Guide to Generative AI is a lighthearted look at programming with AI, as well as a rock-solid resource for getting the best out of these insanely powerful services. Let it be your guide to creating images and presentations, working with data feeds, prompt engineering, and much more.

Generative Ai In Education

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Author : Ilaria Torre
language : en
Publisher: Frontiers Media SA
Release Date : 2024-12-24

Generative Ai In Education written by Ilaria Torre and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-24 with Science categories.

In the field of education, there is a growing interest in the use of Generative Artificial Intelligence to reshape the educational landscape. Led by our esteemed Associate Editors (Dr. Zapata-Rivera & Prof. Torre) and Review Editors (Profs. Lee, Sarasa-Cabezuelo & Libbrecht & Dr. Ghergulescu), this editorial initiative aims to investigate the transformative potential of Generative AI in various aspects of education. By leveraging machine learning models, these intelligent systems extract useful insights from vast amounts of data, making them capable of delivering highly individualized content. They can analyze a learner's proficiency level, learning style, and pace, and then tailor the study material accordingly. Whether a learner prefers visual aids, textual content, or interactive modules, Generative AI can adapt its content generation strategies to meet distinct preferences and learners’ needs. This ensures an elevated engagement level and enhanced comprehension, highlighting its potential to transform traditional teaching methodologies.

Ultimate Generative Ai Solutions On Google Cloud

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Author : Arun Pandey
language : en
Publisher: Orange Education Pvt Ltd
Release Date : 2024-12-29

Ultimate Generative Ai Solutions On Google Cloud written by Arun Pandey and has been published by Orange Education Pvt Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-29 with Computers categories.

TAGLINE Unlock Generative AI's Potential: Transform Ideas into Reality on Google Cloud! KEY FEATURES ● Step-by-step guidance for building Generative AI apps on Google Cloud Platform. ● Pro tips for fine-tuning models to achieve optimal performance. ● Industry-specific use cases for practical, hands-on learning. DESCRIPTION Generative AI, powered by Google Cloud Platform (GCP), is reshaping industries with its advanced capabilities in automating and enhancing complex tasks. The Ultimate Generative AI Solutions on Google Cloud is your comprehensive guide to harnessing this powerful combination to innovate and excel in your job role. It explores foundational machine learning concepts and dives deep into Generative AI, providing the essential knowledge needed to conceptualize, develop, and deploy cutting-edge AI solutions. Within these pages, you'll explore Large Language Models (LLMs), Prompt engineering, Fine-tuning techniques, and the latest advancements in AI, with special emphasis on Parameter-Efficient Fine-Tuning (PEFT) and Reinforcement Learning with Human Feedback (RLHF). You'll also learn about the integration of LangChain and Retrieval-Augmented Generation (RAG) to enhance AI capabilities. By mastering these techniques, you can optimize model performance while conserving resources. The integration of GCP services simplifies the development process, enabling the creation of robust AI applications with ease. By the end of this book, you will not only understand the technical aspects of Generative AI but also gain practical skills that can transform your work to drive innovation and boost operational efficiency with Generative AI on GCP. WHAT WILL YOU LEARN ● Build and deploy cutting-edge generative AI solutions using Google Cloud, LangChain, and RAG. ● Fine-tune large language models (LLMs) with PEFT to meet precise business objectives. ● Master prompt engineering techniques to enhance model performance with GCP tools. ● Optimize production AI for efficiency and scalability using GCP’s Cloud Functions and Cloud Run. ● Apply real-world industry use cases to drive innovation and solve complex problems with LLMOps. ● Manage and streamline AI projects effectively using GCP services like Dataflow, Pub/Sub, and Monitoring. WHO IS THIS BOOK FOR? This book is tailored for AI practitioners, data scientists, and developers with a foundational knowledge of machine learning and experience using Google Cloud services. Familiarity with Python programming and an interest in generative AI applications will enrich your understanding and support practical implementation of the concepts. TABLE OF CONTENTS 1. Generative AI Essentials 2. Google Cloud Basics 3. Getting Started with Large Language Models 4. Prompt Engineering and Contextual Learning 5. Fine-Tuning a Large Language Model 6. Parameter-Efficient Fine-Tuning (PEFT) 7. Reinforcement Learning with Human Feedback 8. Model Optimization 9. LLMOps for Managing and Monitoring AI Projects 10. Harnessing RAG and LangChain 11. Case Studies and Real-World Implementations Index