Cloud Innovation Scaling With Vectors And Llms

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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.

Vector Databases Unleashed Isolating Data In Multi Tenant Llm Systems

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Author : Jawaharbabu Jeyaraman
language : en
Publisher: Libertatem Media Private Limited
Release Date : 2025-01-08

Vector Databases Unleashed Isolating Data In Multi Tenant Llm Systems written by Jawaharbabu Jeyaraman 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 2025-01-08 with Business & Economics categories.

In the era of AI-driven innovation, multi-tenant architectures leveraging Large Language Models (LLMs) and vector databases are redefining scalability and efficiency. Vector Databases Unleashed: Isolating Data in Multi-Tenant LLM Systems is the definitive guide for senior IT professionals and data architects looking to master the intricacies of data isolation, scalability, and security in shared environments. This book delves into the foundational principles of multi-tenant systems, emphasizing robust data isolation techniques to ensure privacy and compliance in shared infrastructures. It explores the power of vector databases, their seamless integration with LLMs, and how they unlock the potential for real-time data retrieval and advanced AI applications. Readers will discover practical strategies for embedding isolation techniques, managing tenant access, and implementing scalable architectures that balance performance with security. Packed with actionable insights, the book offers detailed frameworks for designing and deploying multi- tenant LLM systems, complete with real-world case studies that highlight successful implementations and lessons learned. From physical and logical isolation models to advanced encryption and containerization, it provides a roadmap for navigating complex challenges in data-driven enterprises. Vector Databases Unleashed is essential for IT leaders, data scientists, and engineers aiming to harness the power of AI while maintaining stringent security standards in multi-tenant ecosystems. Prepare to transform your understanding of modern data architecture and drive innovation with confidence in this groundbreaking field.

Economics Of Grids Clouds Systems And Services

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Author : Maurizio Naldi
language : en
Publisher: Springer Nature
Release Date : 2025-02-05

Economics Of Grids Clouds Systems And Services written by Maurizio Naldi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-05 with Computers categories.

This book constitutes the refereed proceedings of the 20th International Conference on Economics of Grids, Clouds, Systems, and Services, GECON 2024, held in Rome, Italy, during September 26–27, 2024. The 12 full papers and 10 short papers presented in this book were carefully reviewed and selected from 37 submissions. They focus on topics such as: Function as a Service: Resource Management and QoS; Cloud Business Models, Pricing, Trading, Network Neutrality; Edge Computing and Energy Awareness; AI/Forecasting/Prediction Sales; and Resource Management in Cloud Applications: Simulation, Streaming Processing and Workflows.

Artificial Intelligence In Education Technologies New Development And Innovative Practices

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Author : Tim Schlippe
language : en
Publisher: Springer Nature
Release Date : 2024-12-31

Artificial Intelligence In Education Technologies New Development And Innovative Practices written by Tim Schlippe and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-31 with Education categories.

This book is a collection of selected research papers presented at the 2024 5th International Conference on Artificial Intelligence in Education Technology (AIET 2024), held in Barcelona, Spain, on July 29 - 31, 2024. AIET establishes a platform for AI in education researchers to present research, exchange innovative ideas, propose new models, as well as demonstrate advanced methodologies and novel systems. It is a timely and up-to-date publication responsive to the rapid development of AI technologies, practices and their increasingly complex interplay with the education domain. It promotes the cross-fertilisation of knowledge and ideas from researchers in various fields to construct the interdisciplinary research area of AI in Education. These subject areas include computer science, cognitive science, education, learning sciences, educational technology, psychology, philosophy, sociology, anthropology and linguistics. The feature of this book will contribute from diverse perspectives to form a dynamic picture of AI in Education. It also includes various domain-specific areas for which AI and other education technology systems have been designed or used in an attempt to address challenges and transform educational practice. Education stands as a cornerstone for societal progress, and ensuring universal access to quality education is integral to achieving Goal 4 of the United Nations' Sustainable Development Goals (SDGs). The goal is to ensure inclusive and equitable quality education for all by 2030. This involves not only expanding access to education but also improving the quality of education to promote lifelong learning opportunities. AI has the potential to significantly contribute to the achievement of Goal 4. It is committed to exploring how AI may play a role in bringing more innovative practices, transforming education, and triggering an exponential leap towards the achievement of the Education 2030 Agenda. Providing broad coverage of recent technology-driven advances and addressing a number of learning-centric themes, the book is an informative and useful resource for researchers, practitioners, education leaders and policy-makers who are involved or interested in AI and education.

Langchain For Life Sciences And Healthcare

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Author : Ivan Reznikov
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2025-07-21

Langchain For Life Sciences And Healthcare written by Ivan Reznikov 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 2025-07-21 with Computers categories.

Feeling overwhelmed by the volume of data in your research? Sifting through massive amounts of data to find useful insights is becoming increasingly difficult in drug discovery, genetics, and healthcare. Enter the era of generative AI with LangChain, whose groundbreaking tools are changing the way life scientists and researchers operate. In this groundbreaking book, Dr. Ivan Reznikov teaches you to harness the power of AI to elevate your research capabilities. Divided into two parts, the first is essential for any specialist, covering the transition from traditional statistics to generative AI, the fundamentals of large language models, and the practical uses of LangChain. The second part is designed for life science professionals who want to create AI applications for biology, chemistry, drug development, and more. By the end, you will: Learn how to easily create and integrate LangChain applications into research Discover how to substantially accelerate your experimental and data analysis operations Explore cutting-edge AI solutions designed to address complex research problems Gain the skills and knowledge to advance your career in AI-enhanced life sciences

Mastering Large Language Models With Python Unleash The Power Of Advanced Natural Language Processing For Enterprise Innovation And Efficiency Using Large Language Models Llms With Python

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Author : Raj Arun
language : en
Publisher: Orange Education Pvt Limited
Release Date : 2024-04-12

Mastering Large Language Models With Python Unleash The Power Of Advanced Natural Language Processing For Enterprise Innovation And Efficiency Using Large Language Models Llms With Python written by Raj Arun and has been published by Orange Education Pvt Limited this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-12 with Computers categories.

A Comprehensive Guide to Leverage Generative AI in the Modern Enterprise Key Features● Gain a comprehensive understanding of LLMs within the framework of Generative AI, from foundational concepts to advanced applications. ● Dive into practical exercises and real-world applications, accompanied by detailed code walkthroughs in Python. ● Explore LLMOps with a dedicated focus on ensuring trustworthy AI and best practices for deploying, managing, and maintaining LLMs in enterprise settings. Book Description “Mastering Large Language Models with Python” is an indispensable resource that offers a comprehensive exploration of Large Language Models (LLMs), providing the essential knowledge to leverage these transformative AI models effectively. From unraveling the intricacies of LLM architecture to practical applications like code generation and AI-driven recommendation systems, readers will gain valuable insights into implementing LLMs in diverse projects. Covering both open-source and proprietary LLMs, the book delves into foundational concepts and advanced techniques, empowering professionals to harness the full potential of these models. Detailed discussions on quantization techniques for efficient deployment, operational strategies with LLMOps, and ethical considerations ensure a well-rounded understanding of LLM implementation. Through real-world case studies, code snippets, and practical examples, readers will navigate the complexities of LLMs with confidence, paving the way for innovative solutions and organizational growth. Whether you seek to deepen your understanding, drive impactful applications, or lead AI-driven initiatives, this book equips you with the tools and insights needed to excel in the dynamic landscape of artificial intelligence. What you will learn ● In-depth study of LLM architecture and its versatile applications across industries. ● Harness open-source and proprietary LLMs to craft innovative solutions. ● Implement LLM APIs for a wide range of tasks spanning natural language processing, audio analysis, and visual recognition. ● Optimize LLM deployment through techniques such as quantization and operational strategies like LLMOps, ensuring efficient and scalable model usage. Table of Contents 1. The Basics of Large Language Models and Their Applications 2. Demystifying Open-Source Large Language Models 3. Closed-Source Large Language Models 4. LLM APIs for Various Large Language Model Tasks 5. Integrating Cohere API in Google Sheets 6. Dynamic Movie Recommendation Engine Using LLMs 7. Document-and Web-based QA Bots with Large Language Models 8. LLM Quantization Techniques and Implementation 9. Fine-tuning and Evaluation of LLMs 10. Recipes for Fine-Tuning and Evaluating LLMs 11. LLMOps - Operationalizing LLMs at Scale 12. Implementing LLMOps in Practice Using MLflow on Databricks 13. Mastering the Art of Prompt Engineering 14. Prompt Engineering Essentials and Design Patterns 15. Ethical Considerations and Regulatory Frameworks for LLMs 16. Towards Trustworthy Generative AI (A Novel Framework Inspired by Symbolic Reasoning) Index

Strategic Blueprint For Enterprise Analytics

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Author : Liang Wang
language : en
Publisher: Springer Nature
Release Date : 2024-04-12

Strategic Blueprint For Enterprise Analytics written by Liang Wang and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-12 with Computers categories.

This book is a comprehensive guide for professionals, leaders, and academics seeking to unlock the power of data and analytics in the modern business landscape. It delves deeply into the strategic, architectural, and managerial aspects of implementing enterprise analytics (EA) systems in large enterprises. The book is meticulously structured into three parts. Part 1 lays the foundation for adaptable architecture in EA. Part 2 explores technical considerations: data, cloud platforms, and AI solutions. The final part focuses on strategy execution, investment, and risk management. Acting as a comprehensive guide, the book enables the creation of robust EA capabilities that foster growth, optimize operations, and keep pace with EA's dynamic world. Whether readers are leaders harnessing data's potential, practitioners navigating analytics, or academics exploring this evolving domain, this book provides insights and knowledge to guide readers toward a thriving, data-driven future.

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

Natural Language Processing On Oracle Cloud Infrastructure

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Author : Hicham Assoudi
language : en
Publisher: Springer Nature
Release Date : 2024-12-18

Natural Language Processing On Oracle Cloud Infrastructure written by Hicham Assoudi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-18 with Computers categories.

This book demonstrates how to use Oracle Cloud Infrastructure (OCI) and Hugging Face technologies to develop advanced NLP solutions. Through a practical case study, it addresses common NLP challenges and offers strategies for creating efficient, cost-effective transformer-based models. By the end of this book, you will have the skills and knowledge to create cutting-edge NLP solutions on OCI, customized to meet the needs of various industries and projects. The book takes you through the complete NLP solution life cycle—covering data preparation, model fine-tuning, deployment, and monitoring—while highlighting key topics such as cost-effectiveness and responsible AI for NLP implementations. Drawing from real-world experience and offering practical insights, it bridges the gap between theory and practice, equipping you to design and deploy scalable, cost-efficient NLP solutions. What You Will Learn Master key NLP concepts and the OCI ecosystem Create high-quality datasets using Hugging Face and OCI Data Labeling Service Fine-tune domain-specific pre-trained models from Hugging Face using OCI Data Science Notebook Sessions Deploy and operationalize your models with OCI Data Science Model Deployments Automate the NLP life cycle with OCI Data Science Pipelines Implement cost-effective strategies throughout the entire NLP life cycle, from dataset preparation to model training and deployment Who This Book Is For A diverse audience interested in implementing NLP solutions on Oracle Cloud Infrastructure: NLP practitioners, data scientists, and machine learning engineers who want to learn how to leverage Oracle AI and Hugging Face to implement an end-to-end NLP solution life cycle, from data preparation to model deployment; Oracle practitioners who want to expand their Oracle expertise by exploring OCI's advanced capabilities for building and scaling cutting-edge NLP solutions in enterprise environments; business decision makers who want to discover the strategic benefits of NLP solutions on OCI, including cost-effectiveness and responsible AI, while driving business value

Deepset Cloud For Intelligent Search And Question Answering

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Author : William Smith
language : en
Publisher: HiTeX Press
Release Date : 2025-07-11

Deepset Cloud For Intelligent Search And Question Answering written by William Smith and has been published by HiTeX Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-11 with Computers categories.

"Deepset Cloud for Intelligent Search and Question Answering" "Deepset Cloud for Intelligent Search and Question Answering" is a comprehensive guide to the architecture, engineering, and deployment of state-of-the-art search and question answering (QA) systems. Beginning with an exploration of the evolution from classical keyword search to advanced semantic and neural paradigms, the book lays a strong foundation in the principles underlying modern QA solutions. Readers gain insight into key system components, benchmarking methodologies, and the unique challenges inherent to multilingual and domain-specific applications, setting the stage for robust and scalable real-world deployments. The book delves deeply into the Deepset Cloud platform, offering a detailed examination of its microservices-driven architecture, modular pipelines, and integration capabilities. With an emphasis on best practices, it covers critical topics such as custom pipeline engineering, advanced data management, model selection and tuning, and seamless API integrations. The text also addresses vital aspects of enterprise operations, including security, governance, observability, and cost optimization—ensuring readers are equipped to manage intelligent search at scale with confidence and compliance. Bridging theory and practice, the final chapters present advanced engineering techniques, DevOps strategies, and solution blueprints tailored for industries with stringent regulatory and operational demands. Real-world use cases highlight conversational AI, federated search, continuous model improvement, and emerging trends like retrieval-augmented generation (RAG) and multimodal pipelines. With its blend of architectural rigor and practical guidance, this book is an essential resource for engineers, architects, and technology leaders seeking to innovate with intelligent search and QA in the cloud era.