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Author: Juan Pablo Bustos
Publisher: Packt Publishing Ltd
ISBN: 1835887619
Category : Computers
Languages : en
Pages : 219
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Book Description
Unleash the transformative potential of GenAI with this comprehensive guide that serves as an indispensable roadmap for integrating large language models into real-world applications. Gain invaluable insights into identifying compelling use cases, leveraging state-of-the-art models effectively, deploying these models into your applications at scale, and navigating ethical considerations. Key Features Get familiar with the most important tools and concepts used in real scenarios to design GenAI apps Interact with GenAI models to tailor model behavior to minimize hallucinations Get acquainted with a variety of strategies and an easy to follow 4 step frameworks for integrating GenAI into applications Book Description Explore the transformative potential of GenAI in the application development lifecycle. Through concrete examples, you will go through the process of ideation and integration, understanding the tradeoffs and the decision points when integrating GenAI. With recent advances in models like Google Gemini, Anthropic Claude, DALL-E and GPT-4o, this timely resource will help you harness these technologies through proven design patterns. We then delve into the practical applications of GenAI, identifying common use cases and applying design patterns to address real-world challenges. From summarization and metadata extraction to intent classification and question answering, each chapter offers practical examples and blueprints for leveraging GenAI across diverse domains and tasks. You will learn how to fine-tune models for specific applications, progressing from basic prompting to sophisticated strategies such as retrieval augmented generation (RAG) and chain of thought. Additionally, we provide end-to-end guidance on operationalizing models, including data prep, training, deployment, and monitoring. We also focus on responsible and ethical development techniques for transparency, auditing, and governance as crucial design patterns. What you will learn Concepts of GenAI: pre-training, fine-tuning, prompt engineering, and RAG Framework for integrating AI: entry points, prompt pre-processing, inference, post-processing, and presentation Patterns for batch and real-time integration Code samples for metadata extraction, summarization, intent classification, question-answering with RAG, and more Ethical use: bias mitigation, data privacy, and monitoring Deployment and hosting options for GenAI models Who this book is for This book is not an introduction to AI/ML or Python. It offers practical guides for designing, building, and deploying GenAI applications in production. While all readers are welcome, those who benefit most include: Developer engineers with foundational tech knowledge Software architects seeking best practices and design patterns Professionals using ML for data science, research, etc., who want a deeper understanding of Generative AI Technical product managers with a software development background This concise focus ensures practical, actionable insights for experienced professionals
Author: Juan Pablo Bustos
Publisher: Packt Publishing Ltd
ISBN: 1835887619
Category : Computers
Languages : en
Pages : 219
Get Book Here
Book Description
Unleash the transformative potential of GenAI with this comprehensive guide that serves as an indispensable roadmap for integrating large language models into real-world applications. Gain invaluable insights into identifying compelling use cases, leveraging state-of-the-art models effectively, deploying these models into your applications at scale, and navigating ethical considerations. Key Features Get familiar with the most important tools and concepts used in real scenarios to design GenAI apps Interact with GenAI models to tailor model behavior to minimize hallucinations Get acquainted with a variety of strategies and an easy to follow 4 step frameworks for integrating GenAI into applications Book Description Explore the transformative potential of GenAI in the application development lifecycle. Through concrete examples, you will go through the process of ideation and integration, understanding the tradeoffs and the decision points when integrating GenAI. With recent advances in models like Google Gemini, Anthropic Claude, DALL-E and GPT-4o, this timely resource will help you harness these technologies through proven design patterns. We then delve into the practical applications of GenAI, identifying common use cases and applying design patterns to address real-world challenges. From summarization and metadata extraction to intent classification and question answering, each chapter offers practical examples and blueprints for leveraging GenAI across diverse domains and tasks. You will learn how to fine-tune models for specific applications, progressing from basic prompting to sophisticated strategies such as retrieval augmented generation (RAG) and chain of thought. Additionally, we provide end-to-end guidance on operationalizing models, including data prep, training, deployment, and monitoring. We also focus on responsible and ethical development techniques for transparency, auditing, and governance as crucial design patterns. What you will learn Concepts of GenAI: pre-training, fine-tuning, prompt engineering, and RAG Framework for integrating AI: entry points, prompt pre-processing, inference, post-processing, and presentation Patterns for batch and real-time integration Code samples for metadata extraction, summarization, intent classification, question-answering with RAG, and more Ethical use: bias mitigation, data privacy, and monitoring Deployment and hosting options for GenAI models Who this book is for This book is not an introduction to AI/ML or Python. It offers practical guides for designing, building, and deploying GenAI applications in production. While all readers are welcome, those who benefit most include: Developer engineers with foundational tech knowledge Software architects seeking best practices and design patterns Professionals using ML for data science, research, etc., who want a deeper understanding of Generative AI Technical product managers with a software development background This concise focus ensures practical, actionable insights for experienced professionals
Author: Denis Rothman
Publisher: Packt Publishing Ltd
ISBN: 1836200900
Category : Computers
Languages : en
Pages : 335
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Book Description
Minimize AI hallucinations and build accurate, custom generative AI pipelines with RAG using embedded vector databases and integrated human feedback Purchase of the print or Kindle book includes a free eBook in PDF format Key Features Implement RAG’s traceable outputs, linking each response to its source document to build reliable multimodal conversational agents Deliver accurate generative AI models in pipelines integrating RAG, real-time human feedback improvements, and knowledge graphs Balance cost and performance between dynamic retrieval datasets and fine-tuning static data Book DescriptionRAG-Driven Generative AI provides a roadmap for building effective LLM, computer vision, and generative AI systems that balance performance and costs. This book offers a detailed exploration of RAG and how to design, manage, and control multimodal AI pipelines. By connecting outputs to traceable source documents, RAG improves output accuracy and contextual relevance, offering a dynamic approach to managing large volumes of information. This AI book shows you how to build a RAG framework, providing practical knowledge on vector stores, chunking, indexing, and ranking. You’ll discover techniques to optimize your project’s performance and better understand your data, including using adaptive RAG and human feedback to refine retrieval accuracy, balancing RAG with fine-tuning, implementing dynamic RAG to enhance real-time decision-making, and visualizing complex data with knowledge graphs. You’ll be exposed to a hands-on blend of frameworks like LlamaIndex and Deep Lake, vector databases such as Pinecone and Chroma, and models from Hugging Face and OpenAI. By the end of this book, you will have acquired the skills to implement intelligent solutions, keeping you competitive in fields from production to customer service across any project.What you will learn Scale RAG pipelines to handle large datasets efficiently Employ techniques that minimize hallucinations and ensure accurate responses Implement indexing techniques to improve AI accuracy with traceable and transparent outputs Customize and scale RAG-driven generative AI systems across domains Find out how to use Deep Lake and Pinecone for efficient and fast data retrieval Control and build robust generative AI systems grounded in real-world data Combine text and image data for richer, more informative AI responses Who this book is for This book is ideal for data scientists, AI engineers, machine learning engineers, and MLOps engineers. If you are a solutions architect, software developer, product manager, or project manager looking to enhance the decision-making process of building RAG applications, then you’ll find this book useful.
Author: Gregor Hohpe
Publisher: Addison-Wesley
ISBN: 0133065103
Category : Computers
Languages : en
Pages : 741
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Book Description
Enterprise Integration Patterns provides an invaluable catalog of sixty-five patterns, with real-world solutions that demonstrate the formidable of messaging and help you to design effective messaging solutions for your enterprise. The authors also include examples covering a variety of different integration technologies, such as JMS, MSMQ, TIBCO ActiveEnterprise, Microsoft BizTalk, SOAP, and XSL. A case study describing a bond trading system illustrates the patterns in practice, and the book offers a look at emerging standards, as well as insights into what the future of enterprise integration might hold. This book provides a consistent vocabulary and visual notation framework to describe large-scale integration solutions across many technologies. It also explores in detail the advantages and limitations of asynchronous messaging architectures. The authors present practical advice on designing code that connects an application to a messaging system, and provide extensive information to help you determine when to send a message, how to route it to the proper destination, and how to monitor the health of a messaging system. If you want to know how to manage, monitor, and maintain a messaging system once it is in use, get this book.
Author: Suvoraj Biswas
Publisher: Packt Publishing Ltd
ISBN: 1836202903
Category : Computers
Languages : en
Pages : 114
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Book Description
Elevate your AI projects with our course on Enterprise Generative AI using AWS's Well-Architected Framework, paving the way for innovation and efficiency Key Features Learn to secure AI environments Achieve excellence in AI architecture Implement AI with AWS solutions Book DescriptionThe course begins with an insightful introduction to the burgeoning field of Generative AI, laying down a robust framework for understanding its applications within the AWS ecosystem. The course focuses on meticulously detailing the five pillars of the AWS Well-Architected Framework—Operational Excellence, Security, Compliance, Reliability, and Cost Optimization. Each module is crafted to provide you with a comprehensive understanding of these essential areas, integrating Generative AI technologies. You'll learn how to navigate the complexities of securing AI systems, ensuring they comply with legal and regulatory standards, and designing them for unparalleled reliability. Practical sessions on cost optimization strategies for AI projects will empower you to deliver value without compromising on performance or scalability. Furthermore, the course delves into System Architecture Excellence, emphasizing the importance of robust design principles in creating effective Generative AI solutions. The course wraps up by offering a forward-looking perspective on the Common Architectural Pattern for FM/LLM Integration & Adoption within the AWS framework. You'll gain hands-on experience with AWS solutions specifically tailored for Generative AI applications, including Lambda, API Gateway, and DynamoDB, among others.What you will learn Apply Operational Excellence in AI Secure Generative AI implementations Navigate compliance in AI solutions Ensure reliability in AI systems Optimize costs for AI projects Integrate FM/LLM with AWS solutions Who this book is for This course is designed for IT professionals, solutions architects, and DevOps engineers looking to specialize in Generative AI. A foundational understanding of AWS and cloud computing is beneficial.
Author: Jasbir Singh Dhaliwal
Publisher: Packt Publishing Ltd
ISBN: 1803247630
Category : Computers
Languages : en
Pages : 304
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Book Description
Apply modern architectural patterns and techniques to achieve scalable, resilient, and secure intelligent IoT solutions built for manufacturing, consumer, agriculture, smart cities, and other domains Key Features Get empowered to quickly develop IoT solutions using listed patterns and related guidance Learn the applications of IoT architectural patterns in various domains through real-world case studies Explore sensor and actuator selection, analytics, security, and emerging tools for architecting IoT systems Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionAs the Internet of Things (IoT) expands and moves to new domains, architectural patterns need to enable faster digital transformation and more uniform development. Through numerous use cases and examples, this book helps you conceptualize and implement IoT architectural patterns and use them in diverse contexts in real-world scenarios. The book begins by introducing you to a variety of IoT architectural patterns and then helps you understand how they are used in domains such as retail, smart manufacturing, consumer, smart cities, and smart agriculture. You’ll also find out how cross-cutting concerns such as security require special considerations in the IoT context. As you advance, you’ll discover all the nuances that are inherent in each layer of IoT reference architecture, including considerations related to analytics for edge/constrained devices, data visualizations, and so on. In the concluding chapters, you’ll explore emerging technologies such as blockchain, 3D printing, 5G, generative AI, quantum computing, and large language models (LLMs) that enhance IoT capabilities to realize broader applications. By the end of this book, you’ll have learned to architect scalable, secure, and unique IoT solutions in any domain using the power of IoT architectural patterns, and you will be able to avoid the pitfalls that typically derail IoT projects.What you will learn Get to grips with the essentials of different architectural patterns and anti-patterns Discover the underlying commonalities in diverse IoT applications Combine patterns from physical and virtual realms to develop innovative applications Choose the right set of sensors and actuators for your solution Explore analytics-related tools and techniques such as TinyML and sensor fusion Overcome the challenges faced in securing IoT systems Leverage use cases based on edge computing and emerging technologies such as 3D printing, 5G, generative AI, and LLMs Who this book is forThis book is for IoT systems and solutions architects as well as other IoT practitioners, such as developers and both technical program and pre-sales managers who are interested in understanding how various IoT architectural patterns and techniques can be applied to developing unique and diverse IoT solutions. Prior knowledge of IoT fundamental concepts and its application areas is helpful but not mandatory.
Author: Anh Nguyen-Duc
Publisher: Springer Nature
ISBN: 3031556429
Category :
Languages : en
Pages : 346
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Book Description
Author: Shikhar Kwatra
Publisher: Packt Publishing Ltd
ISBN: 1804618586
Category : Computers
Languages : en
Pages : 384
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Book Description
Become proficient in Amazon Bedrock by taking a hands-on approach to building and scaling generative AI solutions that are robust, secure, and compliant with ethical standards Key Features Learn the foundations of Amazon Bedrock from experienced AWS Machine Learning Specialist Architects Master the core techniques to develop and deploy several AI applications at scale Go beyond writing good prompting techniques and secure scalable frameworks by using advanced tips and tricks Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionThe concept of generative artificial intelligence has garnered widespread interest, with industries looking to leverage it to innovate and solve business problems. Amazon Bedrock, along with LangChain, simplifies the building and scaling of generative AI applications without needing to manage the infrastructure. Generative AI with Amazon Bedrock takes a practical approach to enabling you to accelerate the development and integration of several generative AI use cases in a seamless manner. You’ll explore techniques such as prompt engineering, retrieval augmentation, fine-tuning generative models, and orchestrating tasks using agents. The chapters take you through real-world scenarios and use cases such as text generation and summarization, image and code generation, and the creation of virtual assistants. The latter part of the book shows you how to effectively monitor and ensure security and privacy in Amazon Bedrock. By the end of this book, you’ll have gained a solid understanding of building and scaling generative AI apps using Amazon Bedrock, along with various architecture patterns and security best practices that will help you solve business problems and drive innovation in your organization.What you will learn Explore the generative AI landscape and foundation models in Amazon Bedrock Fine-tune generative models to improve their performance Explore several architecture patterns for different business use cases Gain insights into ethical AI practices, model governance, and risk mitigation strategies Enhance your skills in employing agents to develop intelligence and orchestrate tasks Monitor and understand metrics and Amazon Bedrock model response Explore various industrial use cases and architectures to solve real-world business problems using RAG Stay on top of architectural best practices and industry standards Who this book is for This book is for generalist application engineers, solution engineers and architects, technical managers, ML advocates, data engineers, and data scientists looking to either innovate within their organization or solve business use cases using generative AI. A basic understanding of AWS APIs and core AWS services for machine learning is expected.
Author: Vesa Salminen
Publisher: AHFE Conference
ISBN: 1964867118
Category : Technology & Engineering
Languages : en
Pages : 356
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Book Description
Proceedings of the 15th International Conference on Applied Human Factors and Ergonomics and the Affiliated Conferences, Nice, France, 24-27 July 2024.
Author: Amit Bahree
Publisher: Simon and Schuster
ISBN: 1638355762
Category : Computers
Languages : en
Pages : 0
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Book Description
Generative AI can transform your business by streamlining the process of creating text, images, and code. This book will show you how to get in on the action! Generative AI in Action is the comprehensive and concrete guide to generative AI you’ve been searching for. It introduces both AI’s fundamental principles and its practical applications in an enterprise context—from generating text and images for product catalogs and marketing campaigns, to technical reporting, and even writing software. Inside, author Amit Bahree shares his experience leading Generative AI projects at Microsoft for nearly a decade, starting well before the current GPT revolution. Inside Generative AI in Action you will find: • A practical overview of of generative AI applications • Architectural patterns, integration guidance, and best practices for generative AI • The latest techniques like RAG, prompt engineering, and multi-modality • The challenges and risks of generative AI like hallucinations and jailbreaks • How to integrate generative AI into your business and IT strategy Generative AI in Action is full of real-world use cases for generative AI, showing you where and how to start integrating this powerful technology into your products and workflows. You’ll benefit from tried-and-tested implementation advice, as well as application architectures to deploy GenAI in production at enterprise scale. About the technology In controlled environments, deep learning systems routinely surpass humans in reading comprehension, image recognition, and language understanding. Large Language Models (LLMs) can deliver similar results in text and image generation and predictive reasoning. Outside the lab, though, generative AI can both impress and fail spectacularly. So how do you get the results you want? Keep reading! About the book Generative AI in Action presents concrete examples, insights, and techniques for using LLMs and other modern AI technologies successfully and safely. In it, you’ll find practical approaches for incorporating AI into marketing, software development, business report generation, data storytelling, and other typically-human tasks. You’ll explore the emerging patterns for GenAI apps, master best practices for prompt engineering, and learn how to address hallucination, high operating costs, the rapid pace of change and other common problems. What's inside • Best practices for deploying Generative AI apps • Production-quality RAG • Adapting GenAI models to your specific domain About the reader For enterprise architects, developers, and data scientists interested in upgrading their architectures with generative AI. About the author Amit Bahree is Principal Group Product Manager for the Azure AI engineering team at Microsoft. The technical editor on this book was Wee Hyong Tok. Table of Contents Part 1 1 Introduction to generative AI 2 Introduction to large language models 3 Working through an API: Generating text 4 From pixels to pictures: Generating images 5 What else can AI generate? Part 2 6 Guide to prompt engineering 7 Retrieval-augmented generation: The secret weapon 8 Chatting with your data 9 Tailoring models with model adaptation and fine-tuning Part 3 10 Application architecture for generative AI apps 11 Scaling up: Best practices for production deployment 12 Evaluations and benchmarks 13 Guide to ethical GenAI: Principles, practices, and pitfalls A The book’s GitHub repository B Responsible AI tools
Author: Vishal Anand
Publisher: BPB Publications
ISBN: 9355516975
Category : Computers
Languages : en
Pages : 249
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Book Description
DESCRIPTION Generative AI can streamline technical and business processes, increase efficiency, and free up your resources’ time to focus on more strategic initiatives. This book takes the readers through a series of steps to deepen their understanding of the forces that shape an organization’s implementation of Generative AI at scale and successfully dealing with them. This book starts with GenAI potential uses, challenges and enterprise deployment strategies. You will learn to scale GenAI models along with LLMOps, choose the right LLM, and use prompt engineering and fine-tuning to customize the outputs. This book introduces a GenAI operating system as well as an orchestration platform for workflow automation. It discusses ethical considerations, designing a target operating model, cost optimization, Retrieval-augmented Generation (RAG), Model as a Service (MaaS), and Confidential AI. Finally, it explores the future of multi-modal AI assistants in enterprises. This book makes it easier for readers to debunk myths, and address fallacies and common misconceptions that could harm organizational investment and reputation. There are also practical and enterprise class scenarios and information that could help in improving implementations, within your organization, enabling you to achieve success beyond scaling challenges. KEY FEATURES ● Understand challenges and dimensions of model at scale. ● Understand model selection criteria, deployment patterns, and positioning. ● Design operating system and demarcation of landing zones. ● Understand enterprise application of prompt engineering and fine-tuning. ● Understand operating model, orchestration platform, multi AI assistants and ethical considerations. ● Understand various latency factors for Gen AI solutions. WHAT YOU WILL LEARN ● Strategies for scaling GenAI models and discovering LLMOps for managing them. ● How to leverage GenAI to streamline enterprise class processes, boost efficiency, and explore new possibilities. ● Implementations in the enterprise class deployments, addressing potential issues and connecting with enablers and accurate growth strategy and execution principles. WHO THIS BOOK IS FOR This book is for decision makers like CIOs, CTOs, CAIOs, Enterprise Architects, Chief Engineers, and anyone who wishes to learn how to have a rewarding implementation of Generative AI for their organizations and clients. TABLE OF CONTENTS 1. The Rise of Generative AI in Enterprises 2. Complex Needs of Production 3. Model Selection for Enterprises 4. Model Deployment for Enterprises 5. Operating System for Enterprises 6. Prompt Engineering for Enterprises 7. Fine-tuning for Enterprises 8. Orchestration of Generative AI Workflows 9. Six Ethical Dimensions for Enterprises 10. Designing a Target Operating Model 11. Cost Optimization Strategies 12. Retrieval-augmented Generation for Enterprises 13. Model as a Service for Enterprises 14. Confidential AI 15. Latency in Generative AI Solutions 16. Multi-modal Multi-agentic Assistant Framework for Enterprises
