Generative Ai Text Generation Strategies For Llms

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Generative AI - Text Generation Strategies for LLMs

Author : Anand Vemula
Publisher : Anand Vemula
ISBN 13 :
Total Pages : 72 pages
Book Rating : 4./5 ( download)

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Book Synopsis Generative AI - Text Generation Strategies for LLMs by : Anand Vemula

Download or read book Generative AI - Text Generation Strategies for LLMs written by Anand Vemula and published by Anand Vemula. This book was released on with total page 72 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book delves into the fascinating world of generative AI and explores how Large Language Models (LLMs) are revolutionizing text creation. It equips you with a foundational understanding of these AI models and empowers you to leverage their capabilities for various purposes. Part 1: Foundational Concepts sets the stage by introducing generative AI and its application in text generation. It unveils the inner workings of LLMs, explaining how these AI models are specifically designed to understand and process human language. You'll explore the vast potential of LLM-powered text generation, from crafting poems and scripts to generating product descriptions and social media content. Part 2: Applications and Use Cases dives into the practical applications of LLMs. You'll discover how LLMs can be used to generate different creative text formats like poetry, code, and even movie scripts. Explore techniques for style transfer and textual mashups, allowing you to create unique and innovative writing styles. The chapter on content creation and marketing explores how LLMs can assist with generating product descriptions, blog posts, and social media content, streamlining your content creation process. Part 3: Evaluation and Considerations delves into the process of evaluating LLM-generated text. You'll learn about various metrics used to assess the quality of the generated content, including coherence, fluency, and grammatical correctness. The chapter on challenges and biases in LLM text generation explores the importance of mitigating bias and promoting fairness in AI development. It also addresses safety and security concerns, along with the need for explainability and interpretability of LLM outputs. The final chapter explores the exciting future of generative AI and LLMs. You'll discover emerging trends like more powerful LLMs, multimodal capabilities that integrate text with other formats, and the potential for personalized LLMs that adapt to individual users. The book concludes by discussing the broader impact of generative AI on society, exploring its potential to transform creative industries, education, and communication. By understanding the fundamentals of LLMs and their applications, you can become an active participant in this evolving landscape of AI-powered text generation. This book equips you with the knowledge and tools to leverage the power of LLMs and unlock their potential for creative exploration, informative content creation, and innovative communication.

Master Generative AI with LLMs: A Practical Guide with Exercises

Author : Anand Vemula
Publisher : Anand Vemula
ISBN 13 :
Total Pages : 72 pages
Book Rating : 4./5 ( download)

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Book Synopsis Master Generative AI with LLMs: A Practical Guide with Exercises by : Anand Vemula

Download or read book Master Generative AI with LLMs: A Practical Guide with Exercises written by Anand Vemula and published by Anand Vemula. This book was released on with total page 72 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book equips you with the skills to harness the power of Generative AI, specifically Large Language Models (LLMs), to create various text formats. Get ready to experiment, explore, and unleash your creative potential! Part 1: Unveiling the Power of Generative AI and LLMs We'll begin by demystifying Generative AI and understanding how it transforms text creation. You'll then delve into the capabilities of LLMs, the powerhouse behind this technology. Through interactive exercises, you'll gain firsthand experience with pre-trained LLMs, exploring their strengths and limitations. Part 2: Mastering Text Generation Techniques Now that you're familiar with the tools, let's explore specific techniques for generating different text formats: Text Inpainting: Imagine restoring missing sections of historical documents or poems. We'll use LLMs to fill the gaps and reconstruct the text, putting your detective skills to the test with hands-on exercises. Text Summarization: Information overload is real! Learn how to leverage LLMs to create concise summaries of lengthy texts, like research papers or news articles. You'll practice generating summaries for presentations or reports through engaging exercises. Part 3: Unleashing Your Inner AI Artist Get ready to tap into your creative side! We'll explore how LLMs can assist you in crafting various artistic text formats: Storytelling: Spark your imagination with a starting line and see where the story unfolds! Prompt the LLM and collaborate on creating engaging narratives. Exercises will guide you in co-writing stories with an LLM, taking turns adding sentences. Poetry: Let the AI muse inspire you! We'll experiment with generating poems in different styles, from classic sonnets to modern haikus. Challenge yourself with themed haiku writing exercises using LLMs. Code Generation: Stuck on a coding problem? Discover how LLMs can become your coding assistant! We'll explore using LLMs for code completion and bug detection, putting their capabilities to the test with practical exercises. Part 4: Refining Your Craft - Advanced Techniques Ready to take your skills a step further? We'll delve into advanced techniques for generating more refined and controlled text outputs: Conditional Text Generation: Imagine guiding the LLM to create text that adheres to specific requirements. We'll experiment with specifying genre, style, or even keywords to influence the narrative in your exercises. Sampling Techniques: Discover how to generate diverse outputs from a single prompt! Explore different sampling techniques with LLMs and see how they impact the creativity and unexpectedness of the generated text. You'll compare and analyze outputs generated with different sampling methods. Style and Tone Control: Want your text to sound formal, funny, or even sarcastic? You'll learn how to control the stylistic elements of the generated text, tailoring it to your specific needs. Exercises will guide you in generating product descriptions with different writing styles. By the end of this workshop, you'll be a confident generative AI text creator, equipped with the skills to experiment with LLMs and produce creative, informative, and engaging text formats tailored to your needs

Generative AI and LLMs

Author : S. Balasubramaniam
Publisher : Walter de Gruyter GmbH & Co KG
ISBN 13 : 3111425517
Total Pages : 366 pages
Book Rating : 4.1/5 (114 download)

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Book Synopsis Generative AI and LLMs by : S. Balasubramaniam

Download or read book Generative AI and LLMs written by S. Balasubramaniam and published by Walter de Gruyter GmbH & Co KG. This book was released on 2024-09-23 with total page 366 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Prompt Engineering for Generative AI

Author : James Phoenix
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1098153391
Total Pages : 430 pages
Book Rating : 4.0/5 (981 download)

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Book Synopsis Prompt Engineering for Generative AI by : James Phoenix

Download or read book Prompt Engineering for Generative AI written by James Phoenix and published by "O'Reilly Media, Inc.". This book was released on 2024-05-16 with total page 430 pages. Available in PDF, EPUB and Kindle. Book excerpt: Large language models (LLMs) and diffusion models such as ChatGPT and Stable Diffusion have unprecedented potential. Because they have been trained on all the public text and images on the internet, they can make useful contributions to a wide variety of tasks. And with the barrier to entry greatly reduced today, practically any developer can harness LLMs and diffusion models to tackle problems previously unsuitable for automation. With this book, you'll gain a solid foundation in generative AI, including how to apply these models in practice. When first integrating LLMs and diffusion models into their workflows, most developers struggle to coax reliable enough results from them to use in automated systems. Authors James Phoenix and Mike Taylor show you how a set of principles called prompt engineering can enable you to work effectively with AI. Learn how to empower AI to work for you. This book explains: The structure of the interaction chain of your program's AI model and the fine-grained steps in between How AI model requests arise from transforming the application problem into a document completion problem in the model training domain The influence of LLM and diffusion model architecture—and how to best interact with it How these principles apply in practice in the domains of natural language processing, text and image generation, and code

The Machine Learning Solutions Architect Handbook

Author : David Ping
Publisher : Packt Publishing Ltd
ISBN 13 : 180512482X
Total Pages : 603 pages
Book Rating : 4.8/5 (51 download)

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Book Synopsis The Machine Learning Solutions Architect Handbook by : David Ping

Download or read book The Machine Learning Solutions Architect Handbook written by David Ping and published by Packt Publishing Ltd. This book was released on 2024-04-15 with total page 603 pages. Available in PDF, EPUB and Kindle. Book excerpt: Design, build, and secure scalable machine learning (ML) systems to solve real-world business problems with Python and AWS Purchase of the print or Kindle book includes a free PDF eBook Key Features Go in-depth into the ML lifecycle, from ideation and data management to deployment and scaling Apply risk management techniques in the ML lifecycle and design architectural patterns for various ML platforms and solutions Understand the generative AI lifecycle, its core technologies, and implementation risks Book DescriptionDavid Ping, Head of GenAI and ML Solution Architecture for global industries at AWS, provides expert insights and practical examples to help you become a proficient ML solutions architect, linking technical architecture to business-related skills. You'll learn about ML algorithms, cloud infrastructure, system design, MLOps , and how to apply ML to solve real-world business problems. David explains the generative AI project lifecycle and examines Retrieval Augmented Generation (RAG), an effective architecture pattern for generative AI applications. You’ll also learn about open-source technologies, such as Kubernetes/Kubeflow, for building a data science environment and ML pipelines before building an enterprise ML architecture using AWS. As well as ML risk management and the different stages of AI/ML adoption, the biggest new addition to the handbook is the deep exploration of generative AI. By the end of this book , you’ll have gained a comprehensive understanding of AI/ML across all key aspects, including business use cases, data science, real-world solution architecture, risk management, and governance. You’ll possess the skills to design and construct ML solutions that effectively cater to common use cases and follow established ML architecture patterns, enabling you to excel as a true professional in the field.What you will learn Apply ML methodologies to solve business problems across industries Design a practical enterprise ML platform architecture Gain an understanding of AI risk management frameworks and techniques Build an end-to-end data management architecture using AWS Train large-scale ML models and optimize model inference latency Create a business application using artificial intelligence services and custom models Dive into generative AI with use cases, architecture patterns, and RAG Who this book is for This book is for solutions architects working on ML projects, ML engineers transitioning to ML solution architect roles, and MLOps engineers. Additionally, data scientists and analysts who want to enhance their practical knowledge of ML systems engineering, as well as AI/ML product managers and risk officers who want to gain an understanding of ML solutions and AI risk management, will also find this book useful. A basic knowledge of Python, AWS, linear algebra, probability, and cloud infrastructure is required before you get started with this handbook.

Generative AI for Cloud Solutions

Author : Paul Singh
Publisher : Packt Publishing Ltd
ISBN 13 : 1835080162
Total Pages : 301 pages
Book Rating : 4.8/5 (35 download)

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Book Synopsis Generative AI for Cloud Solutions by : Paul Singh

Download or read book Generative AI for Cloud Solutions written by Paul Singh and published by Packt Publishing Ltd. This book was released on 2024-04-22 with total page 301 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explore Generative AI, the engine behind ChatGPT, and delve into topics like LLM-infused frameworks, autonomous agents, and responsible innovation, to gain valuable insights into the future of AI Key Features Gain foundational GenAI knowledge and understand how to scale GenAI/ChatGPT in the cloud Understand advanced techniques for customizing LLMs for organizations via fine-tuning, prompt engineering, and responsible AI Peek into the future to explore emerging trends like multimodal AI and autonomous agents Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionGenerative artificial intelligence technologies and services, including ChatGPT, are transforming our work, life, and communication landscapes. To thrive in this new era, harnessing the full potential of these technologies is crucial. Generative AI for Cloud Solutions is a comprehensive guide to understanding and using Generative AI within cloud platforms. This book covers the basics of cloud computing and Generative AI/ChatGPT, addressing scaling strategies and security concerns. With its help, you’ll be able to apply responsible AI practices and other methods such as fine-tuning, RAG, autonomous agents, LLMOps, and Assistants APIs. As you progress, you’ll learn how to design and implement secure and scalable ChatGPT solutions on the cloud, while also gaining insights into the foundations of building conversational AI, such as chatbots. This process will help you customize your AI applications to suit your specific requirements. By the end of this book, you’ll have gained a solid understanding of the capabilities of Generative AI and cloud computing, empowering you to develop efficient and ethical AI solutions for a variety of applications and services.What you will learn Get started with the essentials of generative AI, LLMs, and ChatGPT, and understand how they function together Understand how we started applying NLP to concepts like transformers Grasp the process of fine-tuning and developing apps based on RAG Explore effective prompt engineering strategies Acquire insights into the app development frameworks and lifecycles of LLMs, including important aspects of LLMOps, autonomous agents, and Assistants APIs Discover how to scale and secure GenAI systems, while understanding the principles of responsible AI Who this book is for This artificial intelligence book is for aspiring cloud architects, data analysts, cloud developers, data scientists, AI researchers, technical business leaders, and technology evangelists looking to understanding the interplay between GenAI and cloud computing. Some chapters provide a broad overview of GenAI, which are suitable for readers with basic to no prior AI experience, aspiring to harness AI's potential. Other chapters delve into technical concepts that require intermediate data and AI skills. A basic understanding of a cloud ecosystem is required to get the most out of this book.

Generative AI with LangChain

Author : Ben Auffarth
Publisher : Packt Publishing Ltd
ISBN 13 : 1835088368
Total Pages : 369 pages
Book Rating : 4.8/5 (35 download)

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Book Synopsis Generative AI with LangChain by : Ben Auffarth

Download or read book Generative AI with LangChain written by Ben Auffarth and published by Packt Publishing Ltd. This book was released on 2023-12-22 with total page 369 pages. Available in PDF, EPUB and Kindle. Book excerpt: 2024 Edition – Get to grips with the LangChain framework to develop production-ready applications, including agents and personal assistants. The 2024 edition features updated code examples and an improved GitHub repository. Purchase of the print or Kindle book includes a free PDF eBook. Key Features Learn how to leverage LangChain to work around LLMs’ inherent weaknesses Delve into LLMs with LangChain and explore their fundamentals, ethical dimensions, and application challenges Get better at using ChatGPT and GPT models, from heuristics and training to scalable deployment, empowering you to transform ideas into reality Book DescriptionChatGPT and the GPT models by OpenAI have brought about a revolution not only in how we write and research but also in how we can process information. This book discusses the functioning, capabilities, and limitations of LLMs underlying chat systems, including ChatGPT and Gemini. It demonstrates, in a series of practical examples, how to use the LangChain framework to build production-ready and responsive LLM applications for tasks ranging from customer support to software development assistance and data analysis – illustrating the expansive utility of LLMs in real-world applications. Unlock the full potential of LLMs within your projects as you navigate through guidance on fine-tuning, prompt engineering, and best practices for deployment and monitoring in production environments. Whether you're building creative writing tools, developing sophisticated chatbots, or crafting cutting-edge software development aids, this book will be your roadmap to mastering the transformative power of generative AI with confidence and creativity.What you will learn Create LLM apps with LangChain, like question-answering systems and chatbots Understand transformer models and attention mechanisms Automate data analysis and visualization using pandas and Python Grasp prompt engineering to improve performance Fine-tune LLMs and get to know the tools to unleash their power Deploy LLMs as a service with LangChain and apply evaluation strategies Privately interact with documents using open-source LLMs to prevent data leaks Who this book is for The book is for developers, researchers, and anyone interested in learning more about LangChain. Whether you are a beginner or an experienced developer, this book will serve as a valuable resource if you want to get the most out of LLMs using LangChain. Basic knowledge of Python is a prerequisite, while prior exposure to machine learning will help you follow along more easily.

Large Language Models

Author : Anand Vemula
Publisher : Independently Published
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.3/5 (351 download)

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Book Synopsis Large Language Models by : Anand Vemula

Download or read book Large Language Models written by Anand Vemula and published by Independently Published. This book was released on 2024-08-06 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Large Language Models: A Step-by-Step Do It Yourself Guide" is an essential resource for those looking to understand and develop large language models (LLMs) from scratch. This comprehensive guide takes readers through the entire process, from foundational concepts to advanced techniques, ensuring a thorough understanding of both the theory and practical application of LLMs. The book begins with an introduction to LLMs, covering their definitions, historical evolution, and key concepts. It explores various applications, including natural language processing, conversational AI, and text generation. Ethical considerations, such as bias and privacy, are also addressed, setting the stage for responsible AI development. In the next section, readers are guided through the process of building their own LLMs. This includes setting up the development environment, understanding essential machine learning concepts, and collecting and preparing data. Detailed tutorials on model architecture and design follow, including insights into transformers, attention mechanisms, and custom model design. Training strategies and techniques are discussed, with practical examples of fine-tuning and transfer learning. The book then shifts focus to deployment and practical use. It covers various deployment strategies, integrating LLMs with applications and services, and best practices for monitoring and maintaining models. Hands-on projects such as creating chatbots, text summarization tools, and personalized recommendation systems are included, offering readers real-world experience. Advanced topics, including innovative training methods and case studies, round out the guide. Real-world examples, like implementing customer support bots and automating content generation, provide valuable insights into practical applications of LLMs. Overall, this guide equips readers with the knowledge and skills needed to build, deploy, and optimize their own large language models, making it an indispensable resource for AI enthusiasts and professionals alike.

LLMs and Generative AI for Healthcare

Author : Kerrie Holley
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1098160886
Total Pages : 218 pages
Book Rating : 4.0/5 (981 download)

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Book Synopsis LLMs and Generative AI for Healthcare by : Kerrie Holley

Download or read book LLMs and Generative AI for Healthcare written by Kerrie Holley and published by "O'Reilly Media, Inc.". This book was released on 2024-08-20 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: Large language models (LLMs) and generative AI are rapidly changing the healthcare industry. These technologies have the potential to revolutionize healthcare by improving the efficiency, accuracy, and personalization of care. This practical book shows healthcare leaders, researchers, data scientists, and AI engineers the potential of LLMs and generative AI today and in the future, using storytelling and illustrative use cases in healthcare. Authors Kerrie Holley, former Google healthcare professionals, guide you through the transformative potential of large language models (LLMs) and generative AI in healthcare. From personalized patient care and clinical decision support to drug discovery and public health applications, this comprehensive exploration covers real-world uses and future possibilities of LLMs and generative AI in healthcare. With this book, you will: Understand the promise and challenges of LLMs in healthcare Learn the inner workings of LLMs and generative AI Explore automation of healthcare use cases for improved operations and patient care using LLMs Dive into patient experiences and clinical decision-making using generative AI Review future applications in pharmaceutical R&D, public health, and genomics Understand ethical considerations and responsible development of LLMs in healthcare "The authors illustrate generative's impact on drug development, presenting real-world examples of its ability to accelerate processes and improve outcomes across the pharmaceutical industry."--Harsh Pandey, VP, Data Analytics & Business Insights, Medidata-Dassault Kerrie Holley is a retired Google tech executive, IBM Fellow, and VP/CTO at Cisco. Holley's extensive experience includes serving as the first Technology Fellow at United Health Group (UHG), Optum, where he focused on advancing and applying AI, deep learning, and natural language processing in healthcare. Manish Mathur brings over two decades of expertise at the crossroads of healthcare and technology. A former executive at Google and Johnson & Johnson, he now serves as an independent consultant and advisor. He guides payers, providers, and life sciences companies in crafting cutting-edge healthcare solutions.

Adversarial AI Attacks, Mitigations, and Defense Strategies

Author : John Sotiropoulos
Publisher : Packt Publishing Ltd
ISBN 13 : 1835088678
Total Pages : 586 pages
Book Rating : 4.8/5 (35 download)

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Book Synopsis Adversarial AI Attacks, Mitigations, and Defense Strategies by : John Sotiropoulos

Download or read book Adversarial AI Attacks, Mitigations, and Defense Strategies written by John Sotiropoulos and published by Packt Publishing Ltd. This book was released on 2024-07-26 with total page 586 pages. Available in PDF, EPUB and Kindle. Book excerpt: Understand how adversarial attacks work against predictive and generative AI, and learn how to safeguard AI and LLM projects with practical examples leveraging OWASP, MITRE, and NIST Key Features Understand the connection between AI and security by learning about adversarial AI attacks Discover the latest security challenges in adversarial AI by examining GenAI, deepfakes, and LLMs Implement secure-by-design methods and threat modeling, using standards and MLSecOps to safeguard AI systems Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionAdversarial attacks trick AI systems with malicious data, creating new security risks by exploiting how AI learns. This challenges cybersecurity as it forces us to defend against a whole new kind of threat. This book demystifies adversarial attacks and equips cybersecurity professionals with the skills to secure AI technologies, moving beyond research hype or business-as-usual strategies. The strategy-based book is a comprehensive guide to AI security, presenting a structured approach with practical examples to identify and counter adversarial attacks. This book goes beyond a random selection of threats and consolidates recent research and industry standards, incorporating taxonomies from MITRE, NIST, and OWASP. Next, a dedicated section introduces a secure-by-design AI strategy with threat modeling to demonstrate risk-based defenses and strategies, focusing on integrating MLSecOps and LLMOps into security systems. To gain deeper insights, you’ll cover examples of incorporating CI, MLOps, and security controls, including open-access LLMs and ML SBOMs. Based on the classic NIST pillars, the book provides a blueprint for maturing enterprise AI security, discussing the role of AI security in safety and ethics as part of Trustworthy AI. By the end of this book, you’ll be able to develop, deploy, and secure AI systems effectively.What you will learn Understand poisoning, evasion, and privacy attacks and how to mitigate them Discover how GANs can be used for attacks and deepfakes Explore how LLMs change security, prompt injections, and data exposure Master techniques to poison LLMs with RAG, embeddings, and fine-tuning Explore supply-chain threats and the challenges of open-access LLMs Implement MLSecOps with CIs, MLOps, and SBOMs Who this book is for This book tackles AI security from both angles - offense and defense. AI builders (developers and engineers) will learn how to create secure systems, while cybersecurity professionals, such as security architects, analysts, engineers, ethical hackers, penetration testers, and incident responders will discover methods to combat threats and mitigate risks posed by attackers. The book also provides a secure-by-design approach for leaders to build AI with security in mind. To get the most out of this book, you’ll need a basic understanding of security, ML concepts, and Python.

AI-Driven Cybersecurity andThreat Intelligence

Author : Iqbal H. Sarker
Publisher : Springer Nature
ISBN 13 : 3031544978
Total Pages : 207 pages
Book Rating : 4.0/5 (315 download)

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Book Synopsis AI-Driven Cybersecurity andThreat Intelligence by : Iqbal H. Sarker

Download or read book AI-Driven Cybersecurity andThreat Intelligence written by Iqbal H. Sarker and published by Springer Nature. This book was released on with total page 207 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Handbook of Research on Strategic Leadership in the Fourth Industrial Revolution

Author : Zeki Simsek
Publisher : Edward Elgar Publishing
ISBN 13 : 180220881X
Total Pages : 599 pages
Book Rating : 4.8/5 (22 download)

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Book Synopsis Handbook of Research on Strategic Leadership in the Fourth Industrial Revolution by : Zeki Simsek

Download or read book Handbook of Research on Strategic Leadership in the Fourth Industrial Revolution written by Zeki Simsek and published by Edward Elgar Publishing. This book was released on 2024-07-05 with total page 599 pages. Available in PDF, EPUB and Kindle. Book excerpt: This pioneering Handbook surveys the research landscape of strategic leadership in what is referred to as the ‘Fourth Industrial Revolution’: a fusion of technologies and systems which blurs the boundaries between the digital, physical and biological spheres.

Developing Cybersecurity Programs and Policies in an AI-Driven World

Author : Omar Santos
Publisher : Pearson IT Certification
ISBN 13 : 0138074062
Total Pages : 989 pages
Book Rating : 4.1/5 (38 download)

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Book Synopsis Developing Cybersecurity Programs and Policies in an AI-Driven World by : Omar Santos

Download or read book Developing Cybersecurity Programs and Policies in an AI-Driven World written by Omar Santos and published by Pearson IT Certification. This book was released on 2024-07-16 with total page 989 pages. Available in PDF, EPUB and Kindle. Book excerpt: ALL THE KNOWLEDGE YOU NEED TO BUILD CYBERSECURITY PROGRAMS AND POLICIES THAT WORK Clearly presents best practices, governance frameworks, and key standards Includes focused coverage of healthcare, finance, and PCI DSS compliance An essential and invaluable guide for leaders, managers, and technical professionals Today, cyberattacks can place entire organizations at risk. Cybersecurity can no longer be delegated to specialists: Success requires everyone to work together, from leaders on down. Developing Cybersecurity Programs and Policies in an AI-Driven World offers start-to-finish guidance for establishing effective cybersecurity in any organization. Drawing on more than two decades of real-world experience, Omar Santos presents realistic best practices for defining policy and governance, ensuring compliance, and collaborating to harden the entire organization. Santos begins by outlining the process of formulating actionable cybersecurity policies and creating a governance framework to support these policies. He then delves into various aspects of risk management, including strategies for asset management and data loss prevention, illustrating how to integrate various organizational functions—from HR to physical security—to enhance overall protection. This book covers many case studies and best practices for safeguarding communications, operations, and access; alongside strategies for the responsible acquisition, development, and maintenance of technology. It also discusses effective responses to security incidents. Santos provides a detailed examination of compliance requirements in different sectors and the NIST Cybersecurity Framework. LEARN HOW TO Establish cybersecurity policies and governance that serve your organization’s needs Integrate cybersecurity program components into a coherent framework for action Assess, prioritize, and manage security risk throughout the organization Manage assets and prevent data loss Work with HR to address human factors in cybersecurity Harden your facilities and physical environment Design effective policies for securing communications, operations, and access Strengthen security throughout AI-driven deployments Plan for quick, effective incident response and ensure business continuity Comply with rigorous regulations in finance and healthcare Learn about the NIST AI Risk Framework and how to protect AI implementations Explore and apply the guidance provided by the NIST Cybersecurity Framework

Understanding LLM

Author : Anand Vemula
Publisher : Independently Published
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.3/5 (33 download)

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Book Synopsis Understanding LLM by : Anand Vemula

Download or read book Understanding LLM written by Anand Vemula and published by Independently Published. This book was released on 2024-07-13 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Understanding LLM: A Comprehensive Guide to Large Language Models" delves into the intricacies of large language models (LLMs), revolutionizing AI capabilities in understanding and generating human-like text. This comprehensive guide explores the evolution of LLMs from rule-based systems to advanced deep learning architectures, highlighting key milestones and core concepts such as tokens, embeddings, and attention mechanisms. The book navigates through essential topics in LLM implementation, covering neural network fundamentals, transformers architecture, and techniques for pretraining and fine-tuning models. It emphasizes practical strategies for data preparation, managing large datasets, optimizing training performance, and deploying models effectively using frameworks like TensorFlow and PyTorch. Ethical considerations in LLM development are thoroughly examined, focusing on transparency, accountability, bias detection, and fairness. Case studies across healthcare, finance, and entertainment showcase real-world applications, demonstrating how LLMs enhance tasks like text generation, classification, and conversational AI. The future of LLMs is explored in-depth, highlighting emerging trends such as multimodal models, explainable AI, and opportunities for personalized AI applications. Technical challenges like scalability and data privacy are addressed, alongside growth opportunities in interdisciplinary research and AI for social good.

Large Language Models in Cybersecurity

Author : Andrei Kucharavy
Publisher : Springer Nature
ISBN 13 : 3031548272
Total Pages : 249 pages
Book Rating : 4.0/5 (315 download)

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Book Synopsis Large Language Models in Cybersecurity by : Andrei Kucharavy

Download or read book Large Language Models in Cybersecurity written by Andrei Kucharavy and published by Springer Nature. This book was released on 2024 with total page 249 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book provides cybersecurity practitioners with the knowledge needed to understand the risks of the increased availability of powerful large language models (LLMs) and how they can be mitigated. It attempts to outrun the malicious attackers by anticipating what they could do. It also alerts LLM developers to understand their work's risks for cybersecurity and provides them with tools to mitigate those risks. The book starts in Part I with a general introduction to LLMs and their main application areas. Part II collects a description of the most salient threats LLMs represent in cybersecurity, be they as tools for cybercriminals or as novel attack surfaces if integrated into existing software. Part III focuses on attempting to forecast the exposure and the development of technologies and science underpinning LLMs, as well as macro levers available to regulators to further cybersecurity in the age of LLMs. Eventually, in Part IV, mitigation techniques that should allowsafe and secure development and deployment of LLMs are presented. The book concludes with two final chapters in Part V, one speculating what a secure design and integration of LLMs from first principles would look like and the other presenting a summary of the duality of LLMs in cyber-security. This book represents the second in a series published by the Technology Monitoring (TM) team of the Cyber-Defence Campus. The first book entitled "Trends in Data Protection and Encryption Technologies" appeared in 2023. This book series provides technology and trend anticipation for government, industry, and academic decision-makers as well as technical experts.

Generative AI

Author : Martin Musiol
Publisher : John Wiley & Sons
ISBN 13 : 1394205945
Total Pages : 315 pages
Book Rating : 4.3/5 (942 download)

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Book Synopsis Generative AI by : Martin Musiol

Download or read book Generative AI written by Martin Musiol and published by John Wiley & Sons. This book was released on 2023-01-08 with total page 315 pages. Available in PDF, EPUB and Kindle. Book excerpt: An engaging and essential discussion of generative artificial intelligence In Generative AI: Navigating the Course to the Artificial General Intelligence Future, celebrated author Martin Musiol—founder and CEO of generativeAI.net and GenAI Lead for Europe at Infosys—delivers an incisive and one-of-a-kind discussion of the current capabilities, future potential, and inner workings of generative artificial intelligence. In the book, you'll explore the short but eventful history of generative artificial intelligence, what it's achieved so far, and how it's likely to evolve in the future. You'll also get a peek at how emerging technologies are converging to create exciting new possibilities in the GenAI space. Musiol analyzes complex and foundational topics in generative AI, breaking them down into straightforward and easy-to-understand pieces. You'll also find: Bold predictions about the future emergence of Artificial General Intelligence via the merging of current AI models Fascinating explorations of the ethical implications of AI, its potential downsides, and the possible rewards Insightful commentary on Autonomous AI Agents and how AI assistants will become integral to daily life in professional and private contexts Perfect for anyone interested in the intersection of ethics, technology, business, and society—and for entrepreneurs looking to take advantage of this tech revolution—Generative AI offers an intuitive, comprehensive discussion of this fascinating new technology.

Building AI Intensive Python Applications

Author : Rachelle Palmer
Publisher : Packt Publishing Ltd
ISBN 13 : 1836207247
Total Pages : 299 pages
Book Rating : 4.8/5 (362 download)

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Book Synopsis Building AI Intensive Python Applications by : Rachelle Palmer

Download or read book Building AI Intensive Python Applications written by Rachelle Palmer and published by Packt Publishing Ltd. This book was released on 2024-09-06 with total page 299 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master retrieval-augmented generation architecture and fine-tune your AI stack, along with discovering real-world use cases and best practices to create powerful AI apps Key Features Get to grips with the fundamentals of LLMs, vector databases, and Python frameworks Implement effective retrieval-augmented generation strategies with MongoDB Atlas Optimize AI models for performance and accuracy with model compression and deployment optimization Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionThe era of generative AI is upon us, and this book serves as a roadmap to harness its full potential. With its help, you’ll learn the core components of the AI stack: large language models (LLMs), vector databases, and Python frameworks, and see how these technologies work together to create intelligent applications. The chapters will help you discover best practices for data preparation, model selection, and fine-tuning, and teach you advanced techniques such as retrieval-augmented generation (RAG) to overcome common challenges, such as hallucinations and data leakage. You’ll get a solid understanding of vector databases, implement effective vector search strategies, refine models for accuracy, and optimize performance to achieve impactful results. You’ll also identify and address AI failures to ensure your applications deliver reliable and valuable results. By evaluating and improving the output of LLMs, you’ll be able to enhance their performance and relevance. By the end of this book, you’ll be well-equipped to build sophisticated AI applications that deliver real-world value.What you will learn Understand the architecture and components of the generative AI stack Explore the role of vector databases in enhancing AI applications Master Python frameworks for AI development Implement Vector Search in AI applications Find out how to effectively evaluate LLM output Overcome common failures and challenges in AI development Who this book is for This book is for software engineers and developers looking to build intelligent applications using generative AI. While the book is suitable for beginners, a basic understanding of Python programming is required to make the most of it.