This is a practical, non-technical guide for business leaders, entrepreneurs, and curious minds. This comprehensive guide on agentic AI cuts through the hype and offers a clear, jargon-free strategic roadmap to understanding and applying this technology. The authors bring a rare perspective, having implemented agentic AI across diverse organizations—from global enterprises to agile startups—witnessing both remarkable successes and sobering failures.

Large language models (LLMs) are not just shaping the trajectory of AI, they're also unveiling a new era of security challenges. This practical book takes you straight to the heart of these threats. Author Steve Wilson, chief product officer at Exabeam, focuses exclusively on LLMs, eschewing generalized AI security to delve into the unique characteristics and vulnerabilities inherent in these models.

When AI expert and investigative journalist Karen Hao first began covering OpenAI in 2019, she thought they were the good guys. Founded as a nonprofit with safety enshrined as its core mission, the organization was meant, its leader Sam Altman told us, to act as a check against more purely mercantile, and potentially dangerous, forces. What could go wrong?

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.

The difference between growing your business and going out of business is your ability to think strategically. The problem is, most leaders are stuck in the operational weeds, struggling to find the time to make better strategic decisions. This challenge is only heightened by the rise of AI. While you know AI is the future, current demands leave you with no time to explore its benefits. Meanwhile, your competition is gaining an edge by integrating AI. The time to act is now.

Superagency offers a roadmap for using AI inclusively and adaptively to improve our lives and create positive change. While acknowledging challenges like disinformation and potential job changes, the book focuses on AI’s immense potential to increase individual agency and create better outcomes for society as a whole. Imagine AI tutors personalizing education for each child, researchers rapidly discovering cures for diseases like Alzheimer's and cancer, and AI advisors empowering people to navigate complex systems and achieve their goals.

If you're looking to make a career move from programmer to AI specialist, this is the ideal place to start. Based on Laurence Moroney's extremely successful AI courses, this introductory book provides a hands-on, code-first approach to help you build confidence while you learn key topics.

Data engineering has grown rapidly in the past decade, leaving many software engineers, data scientists, and analysts looking for a comprehensive view of this practice. With this practical book, you'll learn how to plan and build systems to serve the needs of your organization and customers by evaluating the best technologies available through the framework of the data engineering lifecycle.

Author Martin Kleppmann helps you navigate the diverse data landscape by examining the pros and cons of various technologies for processing and storing data. Software keeps changing, but the fundamental principles remain the same. With this book, software engineers and architects will learn how to apply those ideas in practice, and how to make full use of data in modern applications.

If you read (or listen to) nothing else on artificial intelligence and machine learning, listen to these ten articles. We've combed through hundreds of Harvard Business Review articles and selected the most important ones to help you understand the future direction of AI, bring your AI initiatives to scale, and use AI to transform your organization.

Nvidia is the darling of the age of artificial intelligence: the company’s chips are powering the generative-AI revolution, and demand is insatiable. For all the current interest and attention, however, Nvidia is not of our time. Founded more than three decades ago in a Denny’s in East San Jose, for years it was known primarily in the then-niche world of computer gaming. In fact, the company’s leather-jacketed leader, Jensen Huang, is the longest-serving CEO in an industry marked by near constant turmoil and failure.

In November 2022, a webpage was posted online with a simple text box. It was ChatGPT, and was unlike any app people had used before. It was more human than a customer service agent, more convenient than a Google search. Behind the scenes, battles for control and prestige between the world’s two leading AI firms, OpenAI and DeepMind, who now steers Google's AI efforts, has remained elusive—until now.

Feel like AI is leaving you behind? The ChatGPT Bible is here to help. This comprehensive four-book collection shows how to leverage ChatGPT for productivity, income, and personal growth.

Something new entered our world in November 2022—the first general purpose AI that could pass for a human and do the kinds of creative, innovative work that only humans could do previously. Wharton professor Ethan Mollick immediately understood what ChatGPT meant: after millions of years on our own, humans had developed a kind of co-intelligence that could augment, or even replace, human thinking. Through his writing, speaking, and teaching, Mollick has become one of the most prominent and provocative explainers of AI.

In June of 2024, thirty-one years after its founding in a Denny’s restaurant, Nvidia became the most valuable corporation on Earth. The Thinking Machine is the astonishing story of how a designer of video game equipment conquered the market for AI hardware, and in the process re-invented the computer. Essential to Nvidia’s meteoric success is its visionary CEO Jensen Huang, who more than a decade ago, on the basis of a few promising scientific results, bet his entire company on AI.

This is a practical, non-technical guide for business leaders, entrepreneurs, and curious minds. This comprehensive guide on agentic AI cuts through the hype and offers a clear, jargon-free strategic roadmap to understanding and applying this technology. The authors bring a rare perspective, having implemented agentic AI across diverse organizations—from global enterprises to agile startups—witnessing both remarkable successes and sobering failures.

Unlock the potential of Generative AI with this Large Language Model production-ready playbook for seamless deployment, optimization, and scaling. This hands-on guide takes you beyond theory, offering expert strategies for integrating LLMs into real-world applications using retrieval-augmented generation (RAG), vector databases, PEFT, LoRA, and scalable inference architectures. Whether you're an ML engineer, data scientist, or MLOps practitioner, you’ll gain the technical know-how to operationalize LLMs efficiently, reduce compute costs, and ensure rock-solid reliability in production.

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.

In Build a Large Language Model (from Scratch) bestselling author Sebastian Raschka guides you step by step through creating your own LLM. Each stage is explained with clear text, diagrams, and examples. You’ll go from the initial design and creation, to pretraining on a general corpus, and on to fine-tuning for specific tasks.

If you're looking to make a career move from programmer to AI specialist, this is the ideal place to start. Based on Laurence Moroney's extremely successful AI courses, this introductory book provides a hands-on, code-first approach to help you build confidence while you learn key topics.

Machine learning systems are both complex and unique. Complex because they consist of many different components and involve many different stakeholders. Unique because they're data dependent, with data varying wildly from one use case to the next. In this book, you'll learn a holistic approach to designing ML systems that are reliable, scalable, maintainable, and adaptive to changing environments and business requirements. Author Chip Huyen, cofounder of Claypot AI, considers each design decision in the context of how it can help your system as a whole achieve its objectives.

Want to Implement AI Agents in Your Organization? Heard of Agentic AI & Wonder What It Is About? Need a No-BS Guide to Implementing AI Agents Today? If you answered yes to any of these questions, then keep reading ... Amazon-bestselling author and AI consultant David M. Patel is going to show in this comprehensive hands-on executive guide to AI Agents everything you need to know to implement and harness the full potential of AI Agents & Agentic AI in your organization.

AI Agents: A Complete Guide for the Complete Beginner Welcome to the world of AI agents - a world where machines make decisions, adapt, learn, and act autonomously. "AI Agents: A Complete Guide For The Complete Beginner" is your gateway to understanding this transformative technology without the need for advanced technical knowledge. Whether you’re a professional curious about the AI revolution, a student exploring AI as a career, or just someone fascinated by the digital minds shaping our future, this book offers a clear, accessible path to understanding AI agents. What You’ll Learn: ...

Recent breakthroughs in AI have not only increased demand for AI products, they've also lowered the barriers to entry for those who want to build AI products. The model-as-a-service approach has transformed AI from an esoteric discipline into a powerful development tool that anyone can use. Everyone, including those with minimal or no prior AI experience, can now leverage AI models to build applications. In this book, author Chip Huyen discusses AI engineering: the process of building applications with readily available foundation models.

Tap into the future of wealth creation with the power of ChatGPT and AI-driven automation, and unlock new ways to elevate your financial success beyond imagination…

As tech products become more prevalent today, the demand for machine learning professionals continues to grow. But the responsibilities and skill sets required of ML professionals still vary drastically from company to company, making the interview process difficult to predict. In this guide, data science leader Susan Shu Chang shows you how to tackle the ML hiring process. She'll take you through the highly selective recruitment process by sharing hard-won lessons she learned along the way.

How do some organizations maintain 24-7 internet-scale operations? How can organizations integrate security while deploying new features? How do organizations increase security within their DevOps processes? This practical guide helps you answer those questions. Steve Suehring provides unique content to help practitioners and leadership successfully implement DevOps and DevSecOps. Learning DevSecOps emphasizes prerequisites that lead to success through best practices and then takes you through some of the tools and software used by successful DevSecOps-enabled organizations.

This friendly guide teaches you how to apply common algorithms to the practical problems you face every day as a programmer. You'll start with sorting and searching and, as you build up your skills in thinking algorithmically, you'll tackle more complex concerns such as data compression and artificial intelligence. This accesible introduction is suitable for self-taught programmers, engineers, or anyone who wants to brush up on algorithms. Each carefully presented example includes helpful diagrams and fully annotated code samples in Python.

Large language models (LLMs) are not just shaping the trajectory of AI, they're also unveiling a new era of security challenges. This practical book takes you straight to the heart of these threats. Author Steve Wilson, chief product officer at Exabeam, focuses exclusively on LLMs, eschewing generalized AI security to delve into the unique characteristics and vulnerabilities inherent in these models.

Are you prepared for AI systems that don’t just follow instructions—but create their own goals? Struggling to make sense of the emerging risks posed by increasingly autonomous AI systems? Worried about how to secure, govern, and control agentic AI before it makes decisions that go beyond your intent? Want to protect your organization from reputational, legal, or financial fallout—but don’t know where to start? If so, Agentic AI: Navigating Risks and Security Challenges is for you. In this practical and beginner-friendly guide, cybersecurity expert Taimur Ijlal introduces you to the ...