Scaling Enterprise Solutions With Large Language Models
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Scaling Enterprise Solutions With Large Language Models
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Author : Arindam Ganguly
language : en
Publisher: Apress
Release Date : 2025-06-23
Scaling Enterprise Solutions With Large Language Models written by Arindam Ganguly and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-23 with Computers categories.
Artificial Intelligence (AI) is the bedrock of today's applications, propelling the field towards Artificial General Intelligence (AGI). Despite this advancement, integrating such breakthroughs into large-scale production-grade enterprise applications presents significant challenges. This book addresses these hurdles in the domain of large language models within enterprise solutions. By leveraging Big Data engineering and popular data cataloguing tools, you'll see how to transform challenges into opportunities, emphasizing data reuse for multiple AI models across diverse domains. You'll gain insights into large language model behavior by using tools such as LangChain and LLamaIndex to segment vast datasets intelligently. Practical considerations take precedence, guiding you on effective AI Governance and data security, especially in data-sensitive industries like banking. This enterprise-focused book takes a pragmatic approach, ensuring large language models align with broader enterprise goals. From data gathering to deployment, it emphasizes the use of low code AI workflow tools for efficiency. Addressing the challenges of handling large volumes of data, the book provides insights into constructing robust Big Data pipelines tailored for Generative AI applications. Scaling Enterprise Solutions with Large Language Models will lead you through the Generative AI application lifecycle and provide the practical knowledge to deploy efficient Generative AI solutions for your business. What You Will Learn Examine the various phases of an AI Enterprise Applications implementation. Turn from AI engineer or Data Science to an Intelligent Enterprise Architect. Explore the seamless integration of AI in Big Data Pipelines. Manage pivotal elements surrounding model development, ensuring a comprehensive understanding of the complete application lifecycle. Plan and implement end-to-end large-scale enterprise AI applications with confidence. Who This Book Is For Enterprise Architects, Technical Architects, Project Managers and Senior Developers.
Scaling Enterprise Solutions With Large Language Models
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Author : Arindam Ganguly
language : en
Publisher: Springer Nature
Release Date : 2025-05-20
Scaling Enterprise Solutions With Large Language Models written by Arindam Ganguly and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-20 with Computers categories.
Artificial Intelligence (AI) is the bedrock of today's applications, propelling the field towards Artificial General Intelligence (AGI). Despite this advancement, integrating such breakthroughs into large-scale production-grade enterprise applications presents significant challenges. This book addresses these hurdles in the domain of large language models within enterprise solutions. By leveraging Big Data engineering and popular data cataloguing tools, you’ll see how to transform challenges into opportunities, emphasizing data reuse for multiple AI models across diverse domains. You’ll gain insights into large language model behavior by using tools such as LangChain and LLamaIndex to segment vast datasets intelligently. Practical considerations take precedence, guiding you on effective AI Governance and data security, especially in data-sensitive industries like banking. This enterprise-focused book takes a pragmatic approach, ensuring large language models align with broader enterprise goals. From data gathering to deployment, it emphasizes the use of low code AI workflow tools for efficiency. Addressing the challenges of handling large volumes of data, the book provides insights into constructing robust Big Data pipelines tailored for Generative AI applications. Scaling Enterprise Solutions with Large Language Models will lead you through the Generative AI application lifecycle and provide the practical knowledge to deploy efficient Generative AI solutions for your business. What You Will Learn Examine the various phases of an AI Enterprise Applications implementation. Turn from AI engineer or Data Science to an Intelligent Enterprise Architect. Explore the seamless integration of AI in Big Data Pipelines. Manage pivotal elements surrounding model development, ensuring a comprehensive understanding of the complete application lifecycle. Plan and implement end-to-end large-scale enterprise AI applications with confidence. Who This Book Is For Enterprise Architects, Technical Architects, Project Managers and Senior Developers.
Scaling Big Data Leveraging Llms For Enterprise Success
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Author : Vincent Kanka
language : en
Publisher: Libertatem Media Private Limited
Release Date : 2024-04-29
Scaling Big Data Leveraging Llms For Enterprise Success written by Vincent Kanka and has been published by Libertatem Media Private Limited this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-29 with Business & Economics categories.
As enterprises navigate an increasingly data-driven world, the integration of Large Language Models (LLMs) into big data pipelines offers transformative opportunities. Scaling Big Data: Leveraging LLMs for Enterprise Success serves as a comprehensive guide for IT leaders, data scientists, and executives seeking to harness LLMs for superior analytics and decision-making. This book delves into the intersection of LLMs and big data, exploring how enterprises can scale operations while enhancing agility and insight extraction. Readers will uncover practical strategies for integrating LLMs with traditional tools like Apache Spark and Hadoop, optimizing infrastructure for real-time data processing, and employing RAG-based architectures to refine query systems. From cloud-based deployments to on-premise solutions, this guide provides actionable frameworks for building scalable, secure, and efficient systems tailored to industry-specific needs. Real-world case studies demonstrate how LLMs revolutionize workflows in finance, healthcare, marketing, and more, showcasing their ability to deliver precise, context-rich insights at scale. This book also addresses challenges such as ensuring data privacy, achieving low latency in pipelines, and navigating compliance landscapes. Emerging trends, including multi-modal LLM applications and AI- driven automation, are explored, preparing readers to stay ahead in a rapidly evolving technological landscape. Whether streamlining analytics, enhancing decision-making, or driving innovation, Scaling Big Data equips professionals with the tools to transform their enterprises and thrive in a competitive digital era.
Scaling Enterprise Solutions With Large Language Models
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Author : ARINDAM. GANGULY
language : en
Publisher:
Release Date : 2025
Scaling Enterprise Solutions With Large Language Models written by ARINDAM. GANGULY and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025 with categories.
Cloud Innovation Scaling With Vectors And Llms
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Author : Sayantan Bhattacharyya
language : en
Publisher: Libertatem Media Private Limited
Release Date : 2024-09-11
Cloud Innovation Scaling With Vectors And Llms written by Sayantan Bhattacharyya and has been published by Libertatem Media Private Limited this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-11 with Business & Economics categories.
Cloud-native architectures have become the foundation for modern enterprises seeking agility, scalability, and efficiency. Cloud Innovation: Scaling with Vectors and LLMs is a definitive guide for IT leaders, solution architects, and senior managers aiming to integrate advanced technologies like vector databases and Large Language Models (LLMs) into scalable cloud systems. This book explores the principles of cloud-native systems, providing actionable insights into designing elastic and resilient architectures. Readers will learn how to leverage vector databases for high-dimensional data management and harness the power of LLMs for natural language understanding and generation. From optimizing real-time data ingestion to implementing retrieval-augmented generation (RAG) systems, the book offers practical strategies for building future-ready applications. Key topics include the integration of LLMs with vector databases, techniques for elastic scaling, cost optimization strategies, and designing systems for high availability and disaster recovery. Real-world case studies demonstrate how leading enterprises have successfully deployed these technologies to drive innovation, enhance operational efficiency, and meet evolving customer needs. Packed with insights on security, compliance, and performance optimization, Cloud Innovation also examines emerging trends in cloud computing and AI, preparing professionals to navigate the next wave of digital transformation. Whether you ' re modernizing legacy systems or pioneering AI-driven solutions, this book equips you with the tools to scale efficiently, innovate boldly, and lead in the rapidly evolving cloud ecosystem.
The Adventurous And Practical Journey To A Large Scale Enterprise Solution
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Author : Vahid Hajipour
language : en
Publisher: CRC Press
Release Date : 2023-03-16
The Adventurous And Practical Journey To A Large Scale Enterprise Solution written by Vahid Hajipour and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-16 with Computers categories.
The high failure rate of enterprise resource planning (ERP) projects is a pressing concern for both academic researchers and industrial practitioners. The challenges of an ERP implementation are particularly high when the project involves designing and developing a system from scratch. Organizations often turn to vendors and consultants for handling such projects but, every aspect of an ERP project is opaque for both customers and vendors. Unlocking the mysteries of building a large-scale ERP system, The Adventurous and Practical Journey to a Large-Scale Enterprise Solution tells the story of implementing an applied enterprise solution. The book covers the field of enterprise resource planning by examining state-of-the-art concepts in software project management methodology, design and development integration policy, and deployment framework, including: A hybrid project management methodology using waterfall as well as a customized Scrum-based approach A novel multi-tiered software architecture featuring an enhanced flowable process engine A unique platform for coding business processes efficiently Integration to embed ERP modules in physical devices A heuristic-based framework to successfully step into the Go-live period Written to help ERP project professionals, the book charts the path that they should travel from project ideation to systems implementation. It presents a detailed, real-life case study of implementing a large-scale ERP and uses storytelling to demonstrate incorrect and correct decisions frequently made by vendors and customers. Filled with practical lessons learned, the book explains the ins and outs of adopting project methodologies. It weaves a tale that features both real-world and scholarly aspects of an ERP implementation.
Machine Learning At Scale Efficient Ai Solutions With Big Data
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Author : Anand Vemula
language : en
Publisher: Anand Vemula
Release Date :
Machine Learning At Scale Efficient Ai Solutions With Big Data written by Anand Vemula and has been published by Anand Vemula this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
Machine Learning at Scale: Efficient AI Solutions with Big Data" explores the challenges and techniques of building and deploying machine learning systems capable of handling massive datasets and complex models. It begins by establishing the foundations of scalable ML, covering the evolution from Big Data to AI-first, modern data engineering practices like data lakes and feature stores, and efficient algorithms including distributed training and federated learning. The book then transitions to practical implementation, detailing how to scale data preparation and feature engineering, optimize large model training and evaluation using techniques like AutoML and model compression, and implement MLOps for streamlined deployment and monitoring. It addresses crucial aspects of operationalizing ML, including CI/CD pipelines, model serving strategies, and drift detection. Finally, the book delves into advanced and emerging topics: scaling deep learning architectures like transformers and LLMs, multimodal learning, and graph neural networks. It concludes with a discussion of responsible AI, covering bias mitigation, fairness, privacy, and the ethical implications of large-scale ML. The future of ML at scale is explored through the lens of emerging hardware, the convergence of cloud and edge computing, and the evolving role of ML in shaping society and industry.
Introduction To Large Language Models For Business Leaders
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Author : I. Almeida
language : en
Publisher: Now Next Later AI
Release Date : 2023-09-02
Introduction To Large Language Models For Business Leaders written by I. Almeida and has been published by Now Next Later AI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-02 with Computers categories.
Responsible AI Strategy Beyond Fear and Hype - 2025 Edition Finalist for the 2023 HARVEY CHUTE Book Awards recognizing emerging talent and outstanding works in the genre of Business and Enterprise Non-Fiction. In this comprehensive guide, business leaders will gain a nuanced understanding of large language models (LLMs) and generative AI. The book covers the rapid progress of LLMs, explains technical concepts in non-technical terms, provides business use cases, offers implementation strategies, explores impacts on the workforce, and discusses ethical considerations. Key topics include: - The Evolution of LLMs: From early statistical models to transformer architectures and foundation models. - How LLMS Understand Language: Demystifying key components like self-attention, embeddings, and deep linguistic modeling. - The Art of Inference: Exploring inference parameters for controlling and optimizing LLM outputs. - Appropriate Use Cases: A nuanced look at LLM strengths and limitations across applications like creative writing, conversational agents, search, and coding assistance. - Productivity Gains: Synthesizing the latest research on generative AI's impact on worker efficiency and satisfaction. - The Perils of Automation: Examining risks like automation blindness, deskilling, disrupted teamwork and more if LLMs are deployed without deliberate precautions. - The LLM Value Chain: Analyzing key components, players, trends and strategic considerations. - Computational Power: A deep dive into the staggering compute requirements behind state-of-the-art generative AI. - Open Source vs Big Tech: Exploring the high-stakes battle between open and proprietary approaches to AI development. - The Generative AI Project Lifecycle: A blueprint spanning use case definition, model selection, adaptation, integration and deployment. - Ethical Data Sourcing: Why the training data supply chain proves as crucial as model architecture for responsible development. - Evaluating LLMs: Surveying common benchmarks, their limitations, and holistic alternatives. - Efficient Fine-Tuning: Examining techniques like LoRA and PEFT that adapt LLMs for applications with minimal compute. - Human Feedback: How reinforcement learning incorporating human ratings and demonstrations steers models towards helpfulness. - Ensemble Models and Mixture-of-Experts: Parallels between collaborative intelligence in human teams and AI systems. - Areas of Research and Innovation: Retrieval augmentation, program-aided language models, action-based reasoning and more. - Ethical Deployment: Pragmatic steps for testing, monitoring, seeking feedback, auditing incentives and mitigating risks responsibly. The book offers an impartial narrative aimed at informing readers for thoughtful adoption, maximizing real-world benefits while proactively addressing risks. With this guide, leaders gain integrated perspectives essential to setting sound strategies amidst generative AI's rapid evolution. More Than a Book By purchasing this book, you will also be granted free access to the AI Academy platform. There you can view free course modules, test your knowledge through quizzes, attend webinars, and engage in discussion with other readers. No credit card required. AI Academy by Now Next Later AI We are the most trusted and effective learning platform dedicated to empowering leaders with the knowledge and skills needed to harness the power of AI safely and ethically.
Transactions On Large Scale Data And Knowledge Centered Systems I
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Author : Abdelkader Hameurlain
language : en
Publisher: Springer
Release Date : 2009-08-24
Transactions On Large Scale Data And Knowledge Centered Systems I written by Abdelkader Hameurlain and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-08-24 with Computers categories.
Data management, knowledge discovery, and knowledge processing are core and hot topics in computer science. They are widely accepted as enabling technologies for modern enterprises, enhancing their performance and their decision making processes. Since the 1990s the Internet has been the outstanding driving force for application development in all domains. An increase in the demand for resource sharing (e. g. , computing resources, s- vices, metadata, data sources) across different sites connected through networks has led to an evolvement of data- and knowledge-management systems from centralized systems to decentralized systems enabling large-scale distributed applications prov- ing high scalability. Current decentralized systems still focus on data and knowledge as their main resource characterized by: heterogeneity of nodes, data, and knowledge autonomy of data and knowledge sources and services large-scale data volumes, high numbers of data sources, users, computing resources dynamicity of nodes These characteristics recognize: (i) limitations of methods and techniques developed for centralized systems (ii) requirements to extend or design new approaches and methods enhancing efficiency, dynamicity, and scalability (iii) development of large scale, experimental platforms and relevant benchmarks to evaluate and validate scaling Feasibility of these systems relies basically on P2P (peer-to-peer) techniques and agent systems supporting with scaling and decentralized control. Synergy between Grids, P2P systems and agent technologies is the key to data- and knowledge-centered systems in large-scale environments.
Aws Certified Ai Practitioner A Business Professional S Guide
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Author : Vladimir Provorov
language : en
Publisher: Cloud City Press
Release Date : 2025-04-27
Aws Certified Ai Practitioner A Business Professional S Guide written by Vladimir Provorov and has been published by Cloud City Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-27 with Computers categories.
AWS Certified AI Practitioner: A Business Professional's Guide An exam study guide for AWS exam AIF-C01 Second Edition (April 2025) Unlock the Power of AI on AWS – For Business Professionals Are you a business analyst, project manager, or IT professional looking to harness the potential of AI in your organization? Do you need to understand AI/ML capabilities on AWS without diving deep into the technical implementation? This comprehensive study guide is your key to mastering the AWS Certified AI Practitioner exam (AIF-C01) and advancing your career in the AI-driven business landscape. What You'll Learn: Fundamental concepts of AI, ML, and generative AI in business contexts How to identify and evaluate AI opportunities within your organization Best practices for implementing and managing AI projects on AWS Essential AWS AI services and their business applications Strategies for ensuring responsible and ethical AI development Exam Preparation: All domains and topics of the AWS Certified AI Practitioner exam 70 practice questions and detailed answers for self-assessment and exam readiness Real-world scenarios to test your understanding of AI concepts in business settings Dozens of diagrams, summary tables, and hundreds of links for further reading Perfect for: Business analysts and IT support professionals Marketing and sales professionals Product and project managers Line-of-business and IT managers Written by an experienced AWS Solutions Architect, this unofficial guide translates complex AI concepts into easy-to-understand language for non-technical professionals. With real-world examples, practice questions, and actionable insights, you'll gain the confidence to contribute effectively to AI initiatives and make informed decisions about AI technologies. Prepare for the AWS Certified AI Practitioner exam and position yourself as a valuable asset in the AI revolution. Start your journey to becoming an AI-savvy business professional today!