Search results for "Generative AI System Design"
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R 2,442.00
Generative AI for Software Development
In just a few short years, AI has transformed software development, and snazzy new tools continue to arrive, with no let-up in sight. How, as a software engineer, product builder, or CTO, do you keep up? This practical book is the result of Sergio Pereira's mission to test every AI tool he could find and provide practitioners with much-needed guidance through the commotion.Generative AI for Software Development focuses on AI tool comparisons, practical workflows, and real-world case studies, with each chapter encompassing critical evaluations of the tools, their use cases, and their limitations. While product reviews are always relevant, the book goes further and delivers to readers a coherent framework for evaluating the tools and workflows of the future, which will continue to complicate the work of software development.Learn how code generation and autocompletion assistants are reshaping the developer experienceDiscover a consistent method for rating code-generation tools based on real-world coding challengesExplore the GenAI tools transforming UI/UX design and frontend developmentLearn how AI is streamlining code reviews and bug detectionReview tools that are simplifying software testing and QAExplore AI for documentation and technical writingUnderstand how modern LLMs have redefined what chatbots can do
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Regulating Hate Speech Created by Generative AI
Regulating Hate Speech Created by Generative AI explores the new hybrid space of Human Machine Interaction (HMI) in which hate speech is represented and computed through algorithms and AI generative systems. The book is exploratory because there are still many problem-solving challenges to be faced. It is also innovative because it is not assuming that solutions lie only in technological advancements but on a broader scale. In this sense, large language models can and are being considered from a holistic view (i.e., from the different dimensions and layers of regulatory and legal governance). Highlights of the book include:Generative AI and social engines of hateAn introduction to generative Artificial Intelligence application, trends, and ethicsThe mechanics and validation of generative AI outcomesAn evaluation of Generative AI for hate speech detectionBest practices and key considerations for AI regulationUsing GenAI capabilities for early detection of threats in the digital environment.This book is a hard look at ways to regulate generative AI to reduce online hate and secure justice in a digital environment. Featuring research and offering practical guidelines, the book examines guidelines for regulating generative AI models, so they do not contribute to online hate disinformation and imagery.
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Generative and Open AI in Industry 5.0
This book provides an up-to-date and easy-to-read introduction to Generative AI and its revolutionary contribution to building Industry 5.0. Written for both practitioners and interested readers, it is a clear and compelling overview of the technologies at the heart of the next industrial revolution.Part one introduces the conceptual notions behind generative models, large language models (LLMs), and the neural networks that drive them. It delves into the mathematical and conceptual foundations of Generative AI, transformer architecture, and the practical applications of language and vision models. The second half links the innovations to Industry 5.0, discussing digital twins, predictive maintenance, DevOps, and cybersecurity in intelligent systems. It encompasses real-world applications of AI in areas such as finance, manufacturing, and smart infrastructure. Case studies, like the application of generative models in FinTech and blockchain adoption, underscore how AI is already transforming business and society around the world.The book is perfect for students, researchers, and practitioners of AI, data science, and industrial systems interested in comprehending the theory and practical applications of Generative AI. It also benefits educators and policy makers who wish to lead in cutting-edge technological advancements, with emphasis on responsible, secure, and human-oriented AI applications for a brighter future.
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Generative AI and LLMs
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.
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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 and Creativity
Generative AI and Creativity: From Theory to Practice is an immersive exploration into the revolutionary domain of generative artificial intelligence. It takes a step-by-step journey starting with the fundamentals of generative AI and progressing to advanced applications. The book unravels the complexities of generative models, delving into key techniques such as generative adversarial networks (GANs) and variational autoencoders (VAE)s, providing a solid foundation for readers to understand the underlying principles.FEATURES• Explores the collaboration between humans and AI in creative processes• Examines generative art movements, graphic design applications, and artist-AI collaborations• Defines creativity in AI, by showcasing case studies and discussing ethical considerationsMoving beyond creative content generation in art and music to practical implementations in industries like healthcare and finance, the book showcases the versatility and transformative potential of generative AI across diverse domains. Readers will gain practical skills through coding examples, case studies, and collaborative projects, empowering them to integrate generative AI into their own work.The book is enriched with stories of innovation, featuring pioneers who have leveraged generative AI to push the boundaries of creativity. Ethical considerations and the societal impact of generative AI are also explored to foster a holistic understanding of the technology.
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GPT Meets Game Theory
This book explores a new way to understand and employ neural networks through the lens of game theory. It shows how these systems can be seen as players working together or competing to achieve goals. Focusing on transformers, the engines behind today’s most advanced AI, this book explains key mathematical concepts and strategies in a clear, approachable way.As AI models are growing larger and taking on more data, this book draws from biology, physics, as well as game theory, to help readers understand how we can interpret and guide their behavior. It also looks at how these ideas apply to “mean-field” models and how they can be used in situations like federated learning, where many devices work together to train an AI system. The book shows how choosing the right AI design and training method is like making strategic moves in a game - especially when multiple AI agents are involved.This book is an illuminating read for computer science, engineering, and mathematics researchers who are interested in the mathematical underpinnings of deep learning models, particularly transformers, and those who are curious about how game theory can be applied to training and optimizing these models.
R 2,980.94
Practical Generative AI with ChatGPT
Transform your professional world with ChatGPT and OpenAI—master prompt design to revolutionize development, marketing, research, and enterprise implementationKey FeaturesTurn ChatGPT into your companion for marketing, research, personal productivity, art and codingLearn prompt engineering techniques that deliver consistent, relevant, and ethical AI-powered resultsBuild custom GPTs and assistants tailored to your specific business needs and workflowsPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionPractical Generative AI with ChatGPT is your hands-on guide to unlocking the full potential of ChatGPT. From building AI assistants and mastering prompt engineering to analyzing documents and images and even generating code, this book equips you with the skills to integrate generative AI into your workflow.Written by a technical architect specializing in AI and intelligent applications, this book provides the tools and knowledge you need to streamline tasks, enhance productivity, and create intelligent solutions. You’ll learn how to craft precise prompts, leverage ChatGPT for daily efficiency, and develop custom AI assistants tailored to your needs.The chapters show you how to use ChatGPT’s multimodal capabilities to generate images with DALL·E and even transform images into code. This ChatGPT book goes beyond basic interactions by showing you how to design custom GPTs and integrate OpenAI’s APIs into your applications. You’ll explore how businesses use OpenAI models, from building AI applications, including semantic search, to creating an AI roadmap. Each chapter is packed with practical examples, ensuring you can apply the techniques right away.By the end of this book, you’ll be well equipped to leverage OpenAI's technology for competitive advantage.What you will learnExplore the fundamentals of generative AI and GPT modelsMaster prompt engineering to consistently get relevant and reliable outputs from ChatGPTDevelop marketing strategies and conduct meaningful A/B testing with AI assistanceBoost your coding with code generation, review, and optimizationEnhance research with real-time knowledge miningEnhance your visual creativity with image generation, image understanding, and style transferDesign custom GPTs and assistants tailored to specific business functionsDiscover how enterprises are leveraging large language models for their AI appsWho this book is forThis book is ideal for business professionals, developers, marketers, researchers, and decision-makers who want to leverage AI to enhance productivity. No advanced technical background is required for the foundational sections, making the content accessible to beginners, while later chapters provide depth for technical professionals implementing enterprise solutions. If you’re seeking practical applications of generative AI in business contexts, you’ll find immediate, actionable value in this book.
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Generative AI Application Integration Patterns
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 FeaturesGet familiar with the most important tools and concepts used in real scenarios to design GenAI appsInteract with GenAI models to tailor model behavior to minimize hallucinationsGet acquainted with a variety of strategies and an easy to follow 4 step frameworks for integrating GenAI into applicationsBook DescriptionExplore 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 learnConcepts of GenAI: pre-training, fine-tuning, prompt engineering, and RAGFramework for integrating AI: entry points, prompt pre-processing, inference, post-processing, and presentationPatterns for batch and real-time integrationCode samples for metadata extraction, summarization, intent classification, question-answering with RAG, and moreEthical use: bias mitigation, data privacy, and monitoringDeployment and hosting options for GenAI modelsWho this book is forThis 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 knowledgeSoftware architects seeking best practices and design patternsProfessionals using ML for data science, research, etc., who want a deeper understanding of Generative AITechnical product managers with a software development backgroundThis concise focus ensures practical, actionable insights
R 1,693.00
Information Access in the Era of Generative AI
Generative Artificial Intelligence (GenAI) has emerged as a groundbreaking technology that promises to revolutionize many industries as well as people’s personal and professional lives. This book discusses GenAI and its role in information access - often referred to as Generative Information Retrieval (GenIR) - or more broadly, information interaction.The role of GenAI in information access is complex and dynamic, with many dimensions. To address this, following a brief introduction to GenAI and GenIR, the remainder of the book provides eight chapters, each targeting a different dimension or sub-topic. These cover foundations of GenIR, interactions with GenIR systems, adapting them to users, tasks, and scenarios, improving them based on user feedback, GenIR evaluation, the sociotechnical implications of GenAI for information access, recommendations within GenIR, and the future of information access with GenIR.The book is targeted at graduate students and researchers interested in issues of information retrieval, access, and interactions, as well as applications of GenAI in various informational contexts. While some of the parts assume prior background in IR or AI, most others do not, making this book suitable for adoption in various classes as a primary source or as a supplementary material.
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Critiquing Generative AI in Africa’s Media Ecosystems
This book takes a critical approach to the rise of Artificial Intelligence (AI) within the media and communication landscape.The book argues that as technology is a social construct reflecting existing power dynamics, those in the Global South, and in Africa in particular, are bound to be marginalised and have their knowledge, systems overlooked as the Global North dominates technological developments. The birth of AI has ignited debates about its benefits to lower income countries, with some highlighting its potential to advance businesses and grow economies. However, this book argues that AI tools have been produced to serve Western needs, and that instead there is a need for countries in Africa to have home grown solutions defined by local values. Drawing on case studies and analysis from across the continent, the book seeks to caution, challenge, and proffer solutions to the use and understanding of Generative AI for media and communication in non-western societies.At a time when generative AI is threatening to shape the future of media and communication around the world, this book is a vital and timely contribution to debates within critical data studies and African media studies.
R 9,305.71
Optimizing Generative AI Workloads for Sustainability
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 practicesBy 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 LearnUnderstand how Generative AI can be more energy-efficient through improvements such as model compression, efficient architecture, hardware optimization, and carbon footprint trackingKnow the techniques to minimize data usage, including evaluation, filtering, synthesis, few-shot learning, and monitoring data demands over timeUnderstand spanning efficiency, data minimization, and alignment for comprehensive responsibilityKnow the methods for detecting, understanding, and mitigating algorithmic biases, ensuring diversity in data collection, and monitoring model fairness Who This book Is ForProfessionals 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 set
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Research Perspectives on Software Engineering and Systems Design
This book combines cutting-edge research addressing current challenges and emerging opportunities in computing, artificial intelligence, sustainability, and education. Through interdisciplinary insights, readers will discover novel computational frameworks designed to enhance cybersecurity, optimise energy systems, and advance interactive technologies such as chatbots, virtual reality, and gaming for medical rehabilitation. Each chapter demonstrates innovative methodologies--from advanced AI-driven complex data analyses to sophisticated mathematical models addressing real-world problems. The studies highlight how data science, machine learning, and computational intelligence can boost organisational efficiency, support sustainable development, and significantly enhance human-computer interaction. Ideal for researchers, industry experts, educators, and advanced students, this resource provides valuable perspectives on practical applications and theoretical advancements essential for staying ahead in rapidly evolving technological fields.
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Future-Ready with Generative AI
For the first time in history, the most powerful artificial intelligence (AI) works through language itself: The same medium humans use to think and communicate. Dr Michael Kollo reveals why this makes AI uniquely accessible to everyone, and how to harness this linguistic revolution for work and life.This book thoughtfully explores why language-based AI represents something fundamentally different from previous automation, examining both imagined fears and genuine possibilities for workforce transformation. It explains why institutional change takes time despite impressive capabilities, how AI systems are quietly becoming our digital confidants, and why we may eventually come to resent the very technologies we initially embrace. These concepts are explained with care through real-world examples and practical frameworks, whilst companion fictional stories help different audiences understand the emotional reality of technological change. From a software developer orchestrating AI agents to a postal worker finding unexpected digital companionship, these narratives illuminate what it actually feels like to live through this transformation. The book addresses both the remarkable potential of conversational AI and its capacity for subtle manipulation, providing readers with the understanding needed to engage thoughtfully with systems that speak our language.Future-Ready with Generative AI: Skills, Mindsets and Stories in the Age of AI transforms AI from intimidating complexity into intuitive collaboration. Because these systems work through language, everyone can learn to use them effectively. Readers wil gain practical wisdom for leveraging conversational AI while preserving human creativity, relationships, and independent thinking.
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Building Trust in the Generative Artificial Intelligence Era
In an era where generative artificial intelligence (AI) is reshaping industries and daily life, trust has become a cornerstone for its successful adoption and application. Building Trust in the Generative Artificial Intelligence Era: Technology Challenges and Innovations explores how trust can be built, maintained, and evaluated in a world increasingly reliant on AI technologies. Designed to be accessible to a broad audience, thi book blends theoretical insights with practical approaches, offering readers a comprehensive understanding of the topic.This book is divided into three parts. The first part examines the foundations of trust in generative AI, highlighting trends and ethical challenges such as "greenwashing" and remote work dynamics. The second part provides actionable frameworks and tools for assessing and enhancing trust, focusing on topics like cybersecurity, transparency, and explainability. The final section presents global case studies exploring university students' perceptions of ChatGPT, generative AI's applications in European agriculture, and its transformative impact on financial systems.By addressing both the opportunities and risks of generative AI, this book delivers groundbreaking insights for academics, professionals, and policymakers worldwide. It emphasizes practical solutions, ensuring readers gain the knowledge needed to navigate the evolving technological landscape and foster trust in transformative AI systems.
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Data Lakehouse Revolution
We are racing toward a new kind of AI--faster, smarter, and more connected than ever. At the heart of it is the Data Lakehouse, and Databricks is the engine powering the transformation. Whether you're a data scientist training models, an engineer scaling pipelines, or an architect modernizing your stack, this book gives you what you need to stay ahead. Inside, you'll understand how to unlock the full potential of Machine Learning and Generative AI (GenAI) using Databricks--no fluff, just real tools, real strategies, and real results. From MLFlow and AutoML to Unity Catalog, Retrieval Augment Generation (RAG), and Vector Search, you'll get a complete blueprint for building intelligent systems that actually work in production. With step-by-step labs, industry case studies, and expert tips from someone who's lived through the entire evolution of enterprise AI, this book is your guide to mastering what's next. If you're serious regarding building AI that matters, this is where your journey begins. What You'll Learn Build full-stack ML and GenAI solutions on Databricks Train and track models with MLFlow, AutoML, and tuning strategies Secure and govern data with Unity Catalog Apply explainable, ethical AI techniques Deploy and monitor ML models in real-world pipelines Use RAG and vector search to power GenAI applications Gain confidence with hands-on labs and real enterprise use cases Who This Book Is For Azure administrators, data architects, and data engineers
R 1,368.00
Integrating AI Techniques into the Design and Development of Smart Cyber-Physical Systems
Building on the knowledge of risks, vulnerabilities, and safety measures associated with cyber-physical systems, this book focuses on adapting artificial intelligence (AI) techniques to smart cyber-physical systems application development. The future is going to see cyber-physical systems in almost every aspect of life, so a book that focuses on shedding light on the design, development, and security aspects of cyber-physical systems in more crucial domains such as defense, healthcare, biomedical, smart city applications, is needed.Integrating AI Techniques into the Design and Development of Smart Cyber-Physical Systems: Defense, Biomedical, Infrastructure, and Transportation offers an introductory exploration of the fundamental theories and concepts of AI and machine learning (ML) that are utilized in the building of dependable cyber-physical systems. It brings the ideas of advanced design and development and empowered security measures to cyber-physical systems. By focusing on the application of AI in cyber-physical systems design as well as security aspects, an improvement in reliability and advancements can be explored. Also included are the latest findings and advancements as well as case studies and illustrative examples on the design and development of smart cyber-physical systems.This resource is highly valuable for those employed in educational institutions, research laboratories, enterprises, and government agencies, as well as for students seeking novel ideas in the realm of smart cyber-physical systems design.
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Generative AI in Creative Industries
This book compiles a comprehensive collection of pioneering research that addresses the multifaceted challenges and theoretical aspects of Generative AI in creative industries. Generative AI, a groundbreaking technological development, has been carving a significant niche within the creative industries. This innovative form of AI, exemplified by models like OpenAI's ChatGPT, is not only transforming the landscape of human-like text generation but is also radically reshaping creative fields such as music, literature, and visual arts. In the realm of creative industries, Generative AI serves as a catalyst for artistic innovation, offering tools for artists to push the boundaries of creativity. It assists in composing music, generating unique artworks, and even writing stories or scripts, thereby democratizing the creative process. The integration of Generative AI in these industries promises a synergy between human creativity and machine intelligence, potentially leading to novel genres and forms of art. Despite its transformative potential, the incorporation of Generative AI in creative fields is not devoid of challenges. Ethical considerations, such as authorship rights, originality, and the impact on traditional creative roles, are pivotal. Moreover, the authenticity and emotional depth of AI-generated content compared to human-created art is a subject of ongoing debate. The book aims to feature original manuscripts encompassing a wide array of topics, from the development of new generative technologies and their practical application in creative fields, to critical analysis of the ethical, legal, and cultural implications of these systems. By gathering the latest advancements in this field and spotlighting emerging avenues for research, this book serves as an invaluable resource and guide for researchers, artists, and practitioners operating at the intersection of Generative AI and creative industries.
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Systemic Text Generation as Problem Solving
This study explores an approach to text generation that interprets systemic grammar as a computational representation. Terry Patten demonstrates that systemic grammar can be easily and automatically translated into current AI knowledge representations and efficiently processed by the same knowledge-based techniques currently exploited by expert systems. Thus the fundamental methodological problem of interfacing specialized computational representations with equally specialized linguistic representations can be resolved. The study provides a detailed discussion of a substantial implementation involving a relatively large systemic grammar, and a formal model of the method. It represents a fundamental and productive contribution to the literature on text generation.
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AI Agents with MCP
Since its release in late 2024, Anthropic's Model Context Protocol (MCP) has redefined how developers build and connect AI agents to tools, data, and each other. AI Agents with MCP is the first comprehensive guide to this rapidly emerging standard, helping engineers unlock its full potential with hands-on projects. Whether you're developing agentic workflows, bridging tools across platforms, or creating robust multiagent systems, this book walks you through every layer of MCP--from protocol structure to server and client implementation. Author Kyle Stratis provides the practical expertise needed to build fully functional MCP servers, clients, and more. Unlike high-level overviews or fragmented documentation, this book gives you a deep systems-level understanding of MCP's capabilities--and limitations. With its flexible, model-agnostic design, MCP continues to gain traction across the generative AI community; this book ensures you're ready to build with it confidently and effectively. Understand the structure and core concepts of the Model Context Protocol Build complete MCP servers, clients, and transport layers in Python Consume tools, prompts, and data via MCP-based agent workflows Extend agent capabilities with MCP for large-scale and AI-native systems
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Generative AI on Google Cloud with LangChain
Turn challenges into opportunities by mastering advanced techniques for text generation, summarization, and question answering using LangChain and Google Cloud toolsKey FeaturesSolve real-world business problems with hands-on examples of GenAI applications on Google CloudLearn repeatable design patterns for Gen AI on Google Cloud with a focus on architecture and AI ethicsBuild and implement GenAI agents and workflows, such as RAG and NL2SQL, using LangChain and Vertex AIPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionThe rapid transformation and enterprise adoption of GenAI has created an urgent demand for developers to quickly build and deploy AI applications that deliver real value. Written by three distinguished Google AI engineers and LangChain contributors who have shaped Google Cloud’s integration with LangChain and implemented AI solutions for Fortune 500 companies, this book bridges the gap between concept and implementation, exploring LangChain and Google Cloud’s enterprise-ready tools for scalable AI solutions.You'll start by exploring the fundamentals of large language models (LLMs) and how LangChain simplifies the development of AI workflows by connecting LLMs with external data and services. This book guides you through using essential tools like the Gemini and PaLM 2 APIs, Vertex AI, and Vertex AI Search to create sophisticated, production-ready GenAI applications. You'll also overcome the context limitations of LLMs by mastering advanced techniques like Retrieval-Augmented Generation (RAG) and external memory layers.Through practical patterns and real-world examples, you’ll gain everything you need to harness Google Cloud’s AI ecosystem, reducing the time to market while ensuring enterprise scalability. You’ll have the expertise to build robust GenAI applications that can be tailored to solve real-world business challenges.What you will learnBuild enterprise-ready applications with LangChain and Google CloudNavigate and select the right Google Cloud generative AI toolsApply modern design patterns for generative AI applicationsPlan and execute proof-of-concepts for enterprise AI solutionsGain hands-on experience with LangChain's and Google Cloud's AI productsImplement advanced techniques for text generation and summarizationLeverage Vertex AI Search and other tools for scalable AI solutionsWho this book is forIf you’re an application developer or ML engineer eager to dive into GenAI, this book is for you. Whether you're new to LangChain or Google Cloud, you'll learn how to use these tools to build scalable AI solutions. This book is ideal for developers familiar with Python and machine learning basics looking to apply their skills in GenAI. Professionals who want to explore Google Cloud's powerful suite of enterprise-grade GenAI products and their implementation will also find this book useful.
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