Cybersecurity for Dummies
Get the know-how you need to safeguard your data against cyber attacks Cybercriminals are constantly updating their strategies and techniques in search of new ways to breach data security--shouldn't you learn how to keep yourself and your loved ones safe? Fully updated with information on AI, hybrid work environments, and more, Cybersecurity For Dummies is the best-selling guide you need to learn how to protect your personal and business information from the latest cyber threats. This book helps you build stronger defenses, with detailed instructions on how to protect your computer, your online data, and your mobile devices. Learn how to set up the right security measures and prevent breaches--as well as what to do if your information or systems are compromised. Learn about the different types of cyberattacks and how to defend against them Beef up your data security for hybrid work environments and cloud storage Keep your family members safe against deepfake and other social engineering attacks Make sure you have a plan to respond quickly and limit damage in the event of a breach Ideal for businesses and individuals who want to be cyber-secure. Cybersecurity For Dummies is also a great primer for anyone interested in pursuing a career in cybersecurity.
Machine Learning Models for Predicting Drug-Target Interactions
Grid, Cloud, and Cluster Computing; Quantum Technologies; And Modeling, Simulation and Visualization Methods
Fault-Tolerant Distributed Consensus in Synchronous Networks
Fault-tolerant distributed consensus is a fundamental concept, both in cryptography as well as distributed computing. Ever since the inception of the problem by Lamport et al in 1982, the problem has been widely studied, both in cryptography as well as distributed computing community and several fundamental results have been obtained regarding the possibility, feasibility and optimality of the consensus protocols in various network models and adversarial settings. The problem has generated revived interest from several other communities over the last few years, after the advent of Blockchain protocols. Traditionally, the consensus protocols are studied either in the synchronous or in the asynchronous communication setting and very often the protocols in the former category serve as the basis for the protocols in the latter category. The focus of this book will be on the synchronous communication setting. The book presents all the seminal possibility and feasibility results in this model ever since the inception of the consensus problem, with formal security proofs. Even though the synchronous corruption model may seem weaker than the more practical asynchronous communication model, designing protocols in the synchronous model turns out to be non-trivial and demands sophisticated and highly advanced techniques. Moreover, understanding protocols in the synchronous setting often constitutes the first stepping stone to understanding the more complex asynchronous consensus protocols. The topic of synchronous consensus protocols in itself is a very vast and important topic to be covered in a single book.
Building Applications with AI Agents
Generative AI has revolutionized how organizations tackle problems, accelerating the journey from concept to prototype to solution. As the models become increasingly capable, we have witnessed a new design pattern emerge: AI agents. By combining tools, knowledge, memory, and learning with advanced foundation models, we can now sequence multiple model inferences together to solve ambiguous and difficult problems. From coding agents to research agents to analyst agents and more, we've already seen agents accelerate teams and organizations. While these agents enhance efficiency, they often require extensive planning, drafting, and revising to complete complex tasks, and deploying them remains a challenge for many organizations, especially as technology and research rapidly develops. This book is your indispensable guide through this intricate and fast-moving landscape. Author Michael Albada provides a practical and research-based approach to designing and implementing single- and multiagent systems. It simplifies the complexities and equips you with the tools to move from concept to solution efficiently. Understand the distinct features of foundation model-enabled AI agents Discover the core components and design principles of AI agents Explore design trade-offs and implement effective multiagent systems Design and deploy tailored AI solutions, enhancing efficiency and innovation in your field
Visualizing Generative AI
Generative AI has the potential to innovate and evolve business processes, but workers are still figuring out how to build with, optimize, and prompt GenAI tools to fit their needs. And of course, there are pitfalls to avoid, like security risks and hallucinations. Getting it right requires an intuitive understanding of the technology's capabilities and limitations. This approachable guidebook helps learners of all levels navigate GenAI--and have fun while doing it. Loaded with insightful diagrams and illustrations, Visualizing Generative AI is the perfect entry point for curious IT professionals, business leaders who want to stay on top of the latest technologies, students exploring careers in cloud computing and AI, and anyone else interested in getting started with GenAI. You'll traverse the generative AI landscape, exploring everything from how this technology works to the ways organizations are already leveraging it to great success. Understand how generative AI has evolved, with a focus on major breakthroughs Get acquainted with the available tools and platforms for GenAI workloads Examine real-world applications, such as chatbots and workflow automation Learn fundamentals that you can build upon as you continue your GenAI journey
AI For Beginners
Feeling overwhelmed by AI jargon and endless resources? Wondering how to get hands-on AI experience in this fast-paced field without losing your mind? Many beginners struggle, but with this step-by-step guide, that can change.Here's what you'll uncover: - A 31-day plan to master AI and reshape your tech perspective - Three beginner-friendly projects to apply AI concepts, such as voice assistants and recommendation systems- Navigating AI's ethical and societal impacts- AI's role in healthcare, finance, and marketing- A guide for integrating AI into your career, especially in marketing and data analysis- Debunking common AI misconceptions- A beginner's guide to AI programming languages like Python- Interactive exercises to elevate you from novice to competent AI practitioner...and more!Do you think you can't handle it because you're not tech-savvy? This book simplifies complex ideas into manageable steps.Unlike rapidly outdated guides, it offers ongoing insights into the latest trends and advancements. This is more than a book; it's a reliable ongoing resource.Whether for career growth, personal development, or curiosity, this guide equips you with the tools to succeed.Ready to tackle AI jargon and gain practical experience? Scroll up and click "Add to Cart" now!
Security and Risk Analysis for Intelligent Cloud Computing
Security Relationship Management
Aligning information security to the goals and strategies of the business is paramount for ensuring risks are addressed, without an abundance of negative impacts to the company. But how does a Chief Information Security Officer (CISO) accomplish effective alignment? A security executive must understand the detailed needs of business leaders and stakeholders from across all corners of the company. We cannot rely on a standard cadence of general security discussions across all of the lines of business, as well as functional areas, and expect our alignment to be maximally effective. Instead, we should promote our security programs in such a way that makes it personal to whomever we are speaking with at any given time.By leveraging already established and tested marketing concepts, slightly altered for information security, the CISO can tailor their message to fit the needs of each stakeholder. This allows for in-depth business alignment, as well as a holistic view of the company's underpinnings for the CISO. Within these pages, the reader will learn how segmentation, the Four P's, and customer relationship management techniques, can help to transform their security program. Additionally, the book introduces a concept called Security Relationship Management (SRM) that optimizes the creation and nurturing of the hundreds of professional relationships (within and outside the company) that a CISO must balance each week. Through structured tracking of interactions and analyzing SRM data, the CISO ensures that relationships are managed effectively, which increases alignment between the business and cybersecurity initiatives. Pick up your copy of Security Relationship Management: Leveraging Marketing Concepts to Advance a Cybersecurity Program, today to begin your SRM journey.Please visit www.novelsecurity.com for more information.
Prodigal's Son Ministry Blog Volume 2
Like this Blog's volume 1, volume 2 are the blog posts from January 2017 through December 2018.
Robotics and Autonomous Systems. Innovations, Challenges, and Future Prospects
Artificial Intelligence & Blockchain in Cyber Physical Systems
Concept Drift in Large Language Models
This book explores the application of the complex relationship between concept drift and cutting-edge large language models to address the problems and opportunities in navigating changing data landscapes. It discusses the theoretical basis of concept drift and its consequences for large language models, particularly the transformative power of cutting-edge models such as GPT-3.5 and GPT-4. It offers real-world case studies to observe firsthand how concept drift influences the performance of language models in a variety of circumstances, delivering valuable lessons learned and actionable takeaways. The book is designed for professionals, AI practitioners, and scholars, focused on natural language processing, machine learning, and artificial intelligence.- Examines concept drift in AI, particularly its impact on large language models- Analyses how concept drift affects large language models and its theoretical and practical consequences- Covers detection methods and practical implementation challenges in language models- Showcases examples of concept drift in GPT models and lessons learned from their performance- Identifies future research avenues and recommendations for practitioners tackling concept drift in large language models
