Informatyka
AI. Наддержави штучного інтелекту
Кай Фу Лі
Чесно про те, кому загрожує втрата роботи через штучний інтелект та які економічні наслідки тягнуть за собою технологічні прориви. Що буде з людиною, коли штучний інтелект робитиме геть усе? Штучний інтелект змінює світ. Чи буде суперкомпютер правити світом? Що ми можемо зробити для того, щоб не лишитися позаду прогресу?
AI-Assisted Coding. Enhancing Programming with AI Tools and Techniques
Rheinwerk Publishing, Inc, Michael Kofler, Bernd Öggl,...
This book takes programmers through the process of enhancing their workflow using AI tools. It begins by introducing the basics of coding with AI assistants, such as GitHub Copilot and ChatGPT, and shows how these tools can assist in writing and optimizing code. The next section focuses on using AI in debugging, refactoring, and generating software documentation, helping readers master techniques for coding with AI support. Pair programming with AI is explored in detail, with practical examples demonstrating its real-world applications. The book also dives into advanced tools like Ollama and Aider, giving readers the knowledge to build local language models and integrate them into their development workflows. The final chapters highlight how AI can be incorporated into projects, enabling more efficient, innovative coding processes. By the end of the book, readers will have the necessary skills to use AI-powered tools seamlessly, ultimately improving their programming productivity and broadening their AI integration capabilities.
Christoffer Noring, Anjali Jain, Marina Fernandez, Ayşe...
AI-Assisted Programming for Web and Machine Learning shows you how to build applications and machine learning models and automate repetitive tasks.Part 1 focuses on coding, from building a user interface to the backend. You’ll use prompts to create the appearance of an app using HTML, styling with CSS, adding behavior with JavaScript, and working with multiple viewports. Next, you’ll build a web API with Python and Flask and refactor the code to improve code readability. Part 1 ends with using GitHub Copilot to improve the maintainability and performance of existing code. Part 2 provides a prompting toolkit for data science from data checking (inspecting data and creating distribution graphs and correlation matrices) to building and optimizing a neural network. You’ll use different prompt strategies for data preprocessing, feature engineering, model selection, training, hyperparameter optimization, and model evaluation for various machine learning models and use cases. The book closes with chapters on advanced techniques on GitHub Copilot and software agents. There are tips on code generation, debugging, and troubleshooting code. You’ll see how simpler and AI-powered agents work and discover tool calling.
AI-Native LLM Security. Threats, defenses, and best practices for building safe and trustworthy AI
Vaibhav Malik, Ken Huang, Ads Dawson
Adversarial AI attacks present a unique set of security challenges, exploiting the very foundation of how AI learns. This book explores these threats in depth, equipping cybersecurity professionals with the tools needed to secure generative AI and LLM applications. Rather than skimming the surface of emerging risks, it focuses on practical strategies, industry standards, and recent research to build a robust defense framework.Structured around actionable insights, the chapters introduce a secure-by-design methodology, integrating threat modeling and MLSecOps practices to fortify AI systems. You’ll discover how to leverage established taxonomies from OWASP, NIST, and MITRE to identify and mitigate vulnerabilities. Through real-world examples, the book highlights best practices for incorporating security controls into AI development life cycles, covering key areas such as CI/CD, MLOps, and open-access LLMs.Built on the expertise of its co-authors—pioneers in the OWASP Top 10 for LLM applications—this guide also addresses the ethical implications of AI security, contributing to the broader conversation on trustworthy AI. By the end of this book, you’ll be able to develop, deploy, and secure AI technologies with confidence and clarity.*Email sign-up and proof of purchase required
AI-Powered DevOps with LLMs. Applying Large Language Models to Software Delivery and SRE
Gu Huangliang, Zheng Qingzheng, Niu Xiaoling, Che...
If you work in software engineering, DevOps, SRE, or platform teams, this book written by enterprise digital transformation specialists demonstrates how large language models (LLMs) can enhance automation, software delivery, and operational reliability across modern engineering organizations. To build familiarity, the book begins hands-on with the technical underpinnings of LLMs, including Transformers, GPT architectures, and fine-tuning techniques such as LoRA and QLoRA. It then develops these foundations to demonstrate how retrieval-augmented generation (RAG) and agent-based systems can be embedded into real enterprise workflows. Across development, testing, operations, security, and project management scenarios, you will see how LLMs enhance code generation, automate testing, improve log analysis and incident response, support root cause analysis, and assist in risk-based decision-making. By the end of the book, you will be able to move from isolated model experimentation to scalable enterprise practice, designing intelligent DevOps and SRE workflows that are efficient, reliable, and strategically aligned.
Abhijit Dey, Srinivasan Shanmuganathan, David Roldán Martínez
In today’s FinTech landscape, AI is no longer optional, it’s non-negotiable. And it’s not here to replace product managers, but to enhance their skills and amplify their impact. This book is a comprehensive guide for product managers and FinTech innovators looking to harness generative AI and LLMs in financial services. As the industry moves beyond traditional apps into AI-driven platforms, this book offers a practical blueprint for building trust and driving innovation in a rapidly evolving landscape shaped by generative AI.Unlike other FinTech books that lean towards theory, this guide provides actionable, real-world insights. It covers foundational AI-first principles, offers deep dives into key FinTech verticals through success-and-failure case studies, and explores platform scaling and agentic AI. Each chapter centers on real scenarios including a FinTech startup case study to illustrate frameworks and best practices. You’ll learn to integrate AI responsibly, navigate regulatory hurdles, and design customer-centric, data-driven financial products. You’ll equip yourself with the practical tools and templates to confidently innovate within regulatory boundaries.By the end, you’ll be ready to design and scale AI-driven financial products, positioning yourself as a forward-thinking product leader in the AI-first FinTech era.
AI-Ready PostgreSQL 18. Building Intelligent Data Systems with Transactions, Analytics, and Vectors
Vibhor Kumar, Marc Linster, Ed Boyajian
In today’s data-first world, businesses need applications that blend transactions, analytics, and AI to power real-time insights at scale. Mastering PostgreSQL 18 for AI-Powered Enterprise Apps is your essential guide to building intelligent, high-performance systems with the latest features of PostgreSQL 18.Through hands-on examples and expert guidance, you’ll learn to design architectures that unite OLTP and OLAP, embed AI directly into apps, and optimize for speed, scalability, and reliability. Discover how to apply cutting-edge PostgreSQL tools for real-time decisions, predictive analytics, and automation. Go beyond basics with advanced strategies trusted by industry leaders. Whether you’re building data-rich applications, internal analytics platforms, or AI-driven services, this book equips you with the patterns and insights to deliver enterprise-grade innovation.Ideal for developers, architects, and tech leads driving digital transformation, this book empowers you to lead the future of intelligent applications. Harness the power of PostgreSQL 18—and unlock the full potential of your data.
AIX, PowerVM - UNIX, wirtualizacja, bezpieczeństwo. Podręcznik administratora
Sebastian Biedroń
Poznaj system AIX z bliska! Systemy operacyjne z rodziny UNIX znane są z wysokiej niezawodności i wydajności. Właśnie z tego powodu w wielu firmach są one wykorzystywane do zarządzania serwerami kluczowych aplikacji. Jednym z systemów należących do tej grupy jest AIX, który zyskał popularność dzięki bardzo dużym możliwościom wirtualizacji i konfiguracji zabezpieczeń spełniających nawet najsurowsze wymogi bezpieczeństwa. Z niniejszej książki dowiesz się, jak działa ten system operacyjny i jak z nim pracować jako administrator. Nauczysz się wykorzystywać przy tym najlepsze praktyki w branży. Poznasz sposób działania rozwiązania PowerVM, które jest jednym z najbardziej elastycznych, a jednocześnie najbardziej niezawodnych rozwiązań wirtualizacyjnych. Dowiesz się też, jak w praktyce wykorzystać liczne możliwości zapewnienia bezpieczeństwa systemu operacyjnego i aplikacji działających pod jego kontrolą. Platforma IBM Power Podstawy systemu AIX Wirtualizacja elementów systemu Instalacja i utrzymanie systemu Zarządzanie użytkownikami, dyskami i systemem plików Tworzenie kopii bezpieczeństwa i diagnostyka systemu Zarządzanie siecią, bezpieczeństwem i wydajnością Zostań administratorem serwerów Power!