Optimizing Generative Ai Workloads For Sustainability

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Optimizing Generative Ai Workloads For Sustainability

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

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

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

Sustainable Cloud Development

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Author : Parth Girish Patel
language : en
Publisher: Packt Publishing Ltd
Release Date : 2025-03-28

Sustainable Cloud Development written by Parth Girish Patel and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-28 with Computers categories.

Reduce cloud costs and carbon footprint with sustainable design, GenAI, and green architecture principles Key Features Discover sustainable cloud practices, including carbon footprint analysis, optimization, and security Explore best practices, insights, and case studies for implementing sustainable solutions like generative AI workloads Learn cost-saving strategies through efficient resource use and business alignment Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionWritten by three seasoned AWS solution architects, sustainability mentors, and thought leaders, Sustainable Cloud Development equips cloud professionals with actionable strategies to design, build, and optimize workloads that minimize environmental impact, while maintaining performance and scalability. This book combines practical insights, best practices, and case studies to help you align your cloud operations with global sustainability goals. From foundational concepts such as carbon footprint measurement to advanced techniques such as sustainable software architecture, generative AI lifecycle optimization, and cost-efficient cloud practices, this book covers every aspect of sustainable cloud development. You’ll get to grips with key tools, including AWS Cost Explorer, for analyzing costs and usage over time to right-size deployments; auto scaling for automatically scaling compute resources dynamically based on demand; Amazon Trusted Advisor for reviewing optimization recommendations across critical areas such as cost, performance, and security; and Amazon CloudWatch for detailed monitoring and threshold-based alerting around all resources and applications. This book serves as a practical blueprint for optimizing your cloud workloads for both high performance and a minimal environmental footprint.What you will learn Explore the principles of sustainable cloud computing and application performance analysis Discover best practices for data lifecycle management, storage optimization, and networking efficiency Understand and analyze the carbon footprint of cloud applications Implement sustainable software architecture and coding patterns Optimize the lifecycle and consumption of generative AI models Align cloud services with sustainability goals and global regulations Explore eco-friendly generative AI practices, including efficient model deployment Who this book is for This book is for cloud architects, engineers, DevOps professionals, and IT sustainability specialists who want to align their cloud practices with environmental goals. It also caters to software developers eager to build green, efficient solutions. A basic understanding of cloud services and IT infrastructure is necessary.

Kubernetes For Generative Ai Solutions

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Author : Ashok Srirama
language : en
Publisher: Packt Publishing Ltd
Release Date : 2025-06-06

Kubernetes For Generative Ai Solutions written by Ashok Srirama and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-06 with Computers categories.

Master the complete Generative AI project lifecycle on Kubernetes (K8s) from design and optimization to deployment using best practices, cost-effective strategies, and real-world examples. Key Features Build and deploy your first Generative AI workload on Kubernetes with confidence Learn to optimize costly resources such as GPUs using fractional allocation, Spot Instances, and automation Gain hands-on insights into observability, infrastructure automation, and scaling Generative AI workloads Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionGenerative AI (GenAI) is revolutionizing industries, from chatbots to recommendation engines to content creation, but deploying these systems at scale poses significant challenges in infrastructure, scalability, security, and cost management. This book is your practical guide to designing, optimizing, and deploying GenAI workloads with Kubernetes (K8s) the leading container orchestration platform trusted by AI pioneers. Whether you're working with large language models, transformer systems, or other GenAI applications, this book helps you confidently take projects from concept to production. You’ll get to grips with foundational concepts in machine learning and GenAI, understanding how to align projects with business goals and KPIs. From there, you'll set up Kubernetes clusters in the cloud, deploy your first workload, and build a solid infrastructure. But your learning doesn't stop at deployment. The chapters highlight essential strategies for scaling GenAI workloads in production, covering model optimization, workflow automation, scaling, GPU efficiency, observability, security, and resilience. By the end of this book, you’ll be fully equipped to confidently design and deploy scalable, secure, resilient, and cost-effective GenAI solutions on Kubernetes.What you will learn Explore GenAI deployment stack, agents, RAG, and model fine-tuning Implement HPA, VPA, and Karpenter for efficient autoscaling Optimize GPU usage with fractional allocation, MIG, and MPS setups Reduce cloud costs and monitor spending with Kubecost tools Secure GenAI workloads with RBAC, encryption, and service meshes Monitor system health and performance using Prometheus and Grafana Ensure high availability and disaster recovery for GenAI systems Automate GenAI pipelines for continuous integration and delivery Who this book is for This book is for solutions architects, product managers, engineering leads, DevOps teams, GenAI developers, and AI engineers. It's also suitable for students and academics learning about GenAI, Kubernetes, and cloud-native technologies. A basic understanding of cloud computing and AI concepts is needed, but no prior knowledge of Kubernetes is required.

Generative Ai And Ml Algorithms For Maximizing Sustainability And Reducing Carbon Footprints In Smart Residential Energy Systems

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Author : Venkata Narasareddy Annapareddy
language : en
Publisher: JEC PUBLICATION
Release Date :

Generative Ai And Ml Algorithms For Maximizing Sustainability And Reducing Carbon Footprints In Smart Residential Energy Systems written by Venkata Narasareddy Annapareddy and has been published by JEC PUBLICATION this book supported file pdf, txt, epub, kindle and other format this book has been release on with Fiction categories.

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Ai Leadership Handbook

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Author : Andreas Welsch
language : en
Publisher: Andreas Welsch
Release Date : 2024-09-10

Ai Leadership Handbook written by Andreas Welsch and has been published by Andreas Welsch this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-10 with Business & Economics categories.

The pressure on leaders to incorporate AI into their business has never been higher. Despite their best efforts, 85 percent of AI projects fail. But that is rarely just because of technology. Between unrealistic expectations of what AI can do, isolated science projects turned into money pits, and employees looking for clarity on how AI influences their jobs, learning how to successfully introduce AI into your organization can be difficult. Getting it right on the second or third attempt is not an option. In order for your AI program to be successful, you need to be aware of all the facets involved, not just the technology—a daunting task. The AI Leadership Handbookprepares you to master the nine most important facets with ease. Andreas Welsch uses real-world knowledge and examples from interviews with over 60 leaders and experts in AI to help you both introduce and incorporate AI into your organization, from aligning it with your business strategy to turning new-to-AI employees into passionate multipliers to making sure humans stay at the center of your AI use. After reading this book, you will be able to confidently implement AI in your business, no matter your industry. IN THE AI LEADERSHIP HANDBOOK, YOU WILL DISCOVER HOW TO: - Leverage the full scope of an AI leadership role - Win (enthusiastic) buy-in from employees - Take a product-centric approach to building AI applications - Build a pipeline of high-value AI capabilities - Utilize AI ethically, safely, and sustainably Spanning strategy, stakeholder management, collaboration, culture, ethics, data privacy, risk management, and technology, Andreas covers everything you need to know to become a confident and successful AI leader—and get it right on the first try.

Artificial Intelligence Valuation

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Author : Roberto Moro-Visconti
language : en
Publisher: Springer Nature
Release Date : 2024-06-01

Artificial Intelligence Valuation written by Roberto Moro-Visconti and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-06-01 with Business & Economics categories.

The book discusses the main valuation methodologies of artificial intelligence (AI). Company valuation goes hand in hand with estimating intangible assets like AI, which are linked to higher risk and lower collateral value. Their accounting is controversial, and the most widely used valuation approaches are based on market, income, or cost-related metrics.The volume discusses in detail the valuation approaches such as the discounted cash flows (remembering that “cash is king”) or the empirical market multipliers and comparables. The approaches are complemented by several models, including advanced business planning that incorporates machine learning, digital scalability networks, or validating blockchains. The book, with a tailor-made theoretical background backed by empirical cases, shows how to evaluate AI products, such as chatbots or virtual assistants, for AI established producers, startups, or traditional “brick-and-mortar” AI users. The comprehensive set of techniques and methodologies will interest researchers, students, and practitioners in corporate finance, intellectual property valuation, and financial technology.

Solutions Architect S Handbook

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Author : Saurabh Shrivastava
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-03-29

Solutions Architect S Handbook written by Saurabh Shrivastava and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03-29 with Computers categories.

From fundamentals and design patterns to the latest techniques such as generative AI, machine learning and cloud native architecture, gain all you need to be a pro Solutions Architect crafting secure and reliable AWS architecture. Get With Your Book: PDF Copy, AI Assistant, and Next-Gen Reader Free Key Features Hits all the key areas -Rajesh Sheth, VP, Elastic Block Store, AWS Offers the knowledge you need to succeed in the evolving landscape of tech architecture - Luis Lopez Soria, Senior Specialist Solutions Architect, Google A valuable resource for enterprise strategists looking to build resilient applications - Cher Simon, Principal Solutions Architect, AWS Book DescriptionBuild a strong foundation in solution architecture and excel in your career with the Solutions Architect’s Handbook. Authored by seasoned AWS technology leaders Saurabh Shrivastav and Neelanjali Srivastav, this book goes beyond traditional certification guides, offering in-depth insights and advanced techniques to meet the specific needs and challenges of solutions architects today. This edition introduces exciting new features that keep you at the forefront of this evolving field. From large language models and generative AI to deep learning innovations, these cutting-edge advancements are shaping the future of technology. Key topics such as cloud-native architecture, data engineering architecture, cloud optimization, mainframe modernization, and building cost-efficient, secure architectures remain essential today. This book covers both emerging and foundational technologies, guiding you through solution architecture design with key principles and providing the knowledge you need to succeed as a Solutions Architect. It also sharpens your soft skills, providing career-accelerating techniques to stay ahead. By the end of this book, you will be able to harness cutting-edge technologies, apply practical insights from real-world scenarios, and enhance your solution architecture skills with the Solutions Architect's Handbook.What you will learn Explore various roles of a solutions architect in the enterprise Apply design principles for high-performance, cost-effective solutions Choose the best strategies to secure your architectures and boost availability Develop a DevOps and CloudOps mindset for collaboration, operational efficiency, and streamlined production Apply machine learning, data engineering, LLMs, and generative AI for improved security and performance Modernize legacy systems into cloud-native architectures with proven real-world strategies Master key solutions architect soft skills Who this book is for This book is for software developers, system engineers, DevOps engineers, architects, and team leaders who already work in the IT industry and aspire to become solutions architect professionals. Solutions architects who want to expand their skillset or get a better understanding of new technologies will also learn valuable new skills. To get started, you'll need a good understanding of the real-world software development process and some awareness of cloud technology.

Serverless Development On Aws

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Author : Sheen Brisals
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2024-01-23

Serverless Development On Aws written by Sheen Brisals and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-01-23 with Computers categories.

The adoption of serverless is on the rise, but until now, little guidance has been available for development teams that want to apply this technology on AWS. This definitive guide is packed with architectural, security, and data best practices and patterns for architects and engineers who want to build reliable enterprise-scale serverless solutions. Sheen Brisals, an AWS Serverless Hero, and Luke Hedger, an AWS Community Builder, outline the serverless adoption requirements for an enterprise, examine the development tools your team needs, and explain in depth the nuances of testing event-driven and distributed serverless services. You'll gain practical guidance for keeping up with change and learn how to build serverless solutions with sustainability in mind. Examine the serverless technology ecosystem and AWS services needed to develop serverless applications Learn the approach and preparation required for a successful serverless adoption in an enterprise Learn serverless architectures and implementation patterns Design, develop, and test distributed serverless microservices on AWS cloud Apply security best practices while building serverless solutions Identify and adapt the implementation patterns for your particular use case Incorporate the necessary measures for observable serverless applications Implement sustainable serverless applications in the cloud

Advancements In Cloud Based Intelligent Informative Engineering

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Author : Kishor, Kaushal
language : en
Publisher: IGI Global
Release Date : 2025-04-17

Advancements In Cloud Based Intelligent Informative Engineering written by Kishor, Kaushal and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-17 with Technology & Engineering categories.

In this ever-changing world, the rapid evolution of cloud computing and AI has paved the way for advancements in cloud-based intelligent engineering. This emerging field integrates cloud computing, big data, and AI to enhance the efficiency and automation of engineering processes. By leveraging cloud-based intelligent systems, industries can optimize data management, improve real-time collaboration, and drive innovation across various engineering domains. Advancements in Cloud-Based Intelligent Informative Engineering explores technological advancements and devices in cloud technology. It examines cloud-based intelligent system approaches and developments in informative engineering. This book covers topics such as IoT, machine learning, and blockchain, and is a useful resource for researchers, engineers, business owners, academicians, and scientists.

Hands On Genetic Algorithms With Python

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Author : Eyal Wirsansky
language : en
Publisher: Packt Publishing Ltd
Release Date : 2020-01-31

Hands On Genetic Algorithms With Python written by Eyal Wirsansky and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-31 with Computers categories.

Explore the ever-growing world of genetic algorithms to solve search, optimization, and AI-related tasks, and improve machine learning models using Python libraries such as DEAP, scikit-learn, and NumPy Key Features Explore the ins and outs of genetic algorithms with this fast-paced guide Implement tasks such as feature selection, search optimization, and cluster analysis using Python Solve combinatorial problems, optimize functions, and enhance the performance of artificial intelligence applications Book DescriptionGenetic algorithms are a family of search, optimization, and learning algorithms inspired by the principles of natural evolution. By imitating the evolutionary process, genetic algorithms can overcome hurdles encountered in traditional search algorithms and provide high-quality solutions for a variety of problems. This book will help you get to grips with a powerful yet simple approach to applying genetic algorithms to a wide range of tasks using Python, covering the latest developments in artificial intelligence. After introducing you to genetic algorithms and their principles of operation, you'll understand how they differ from traditional algorithms and what types of problems they can solve. You'll then discover how they can be applied to search and optimization problems, such as planning, scheduling, gaming, and analytics. As you advance, you'll also learn how to use genetic algorithms to improve your machine learning and deep learning models, solve reinforcement learning tasks, and perform image reconstruction. Finally, you'll cover several related technologies that can open up new possibilities for future applications. By the end of this book, you'll have hands-on experience of applying genetic algorithms in artificial intelligence as well as in numerous other domains.What you will learn Understand how to use state-of-the-art Python tools to create genetic algorithm-based applications Use genetic algorithms to optimize functions and solve planning and scheduling problems Enhance the performance of machine learning models and optimize deep learning network architecture Apply genetic algorithms to reinforcement learning tasks using OpenAI Gym Explore how images can be reconstructed using a set of semi-transparent shapes Discover other bio-inspired techniques, such as genetic programming and particle swarm optimization Who this book is for This book is for software developers, data scientists, and AI enthusiasts who want to use genetic algorithms to carry out intelligent tasks in their applications. Working knowledge of Python and basic knowledge of mathematics and computer science will help you get the most out of this book.