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Berton L: Kubernetes AI

Kubernetes AI

Run LLMs, GPUs, and ML Workloads in Production

JMP Publishing LLC

A Quick Guide to the Printed Circuit Board Industry

PCB Basics for Buyers

A practical guide to navigating AI's transformation of literacy and education, this book combines the long-standing values of writing studies with instruction on how students and teachers can write more effectively with AI. Mirroring the seismic changes on writing brought about by the printing press, the typewriter and the internet, AI's impact on literacy, teaching and writing marks a shift in how we think about knowledge production, intellectual labour and composition. Moving students away from a myopic, transactional, 'vending machine-style' approach, Writing with AI offers techniques on engaging with these new technologies more critically and thoughtfully. With structured, adaptable frameworks based upon relational and conversational models of engagement, this book allows students to better articulate and compose their needs, refine their questions, and engage in an iterative exchange with more meaningful and useful responses from generative learning language models. Introducing a four-part recursive framework - Question, Analyze, Iterate, Compose (QAIC) - that guides students through a deliberate process, Writing with AI gives students the tools for ensuring that AI is integrated thoughtfully and ethically into their work rather than being used as a shortcut. Designed for immediate classroom use, the book features: - Consideration of the ethics of AI - How students can formulate context-aware questions for prompts - Guidance on how students can assess and refine AI-generated content - Explanation on how the use of AI can be a part of a process that expands critical thinking skills - Demonstrations of how AI-assisted insights can be structured into meaningful compositions Offering a structured way to interact meaningfully with AI in the current pedagogical moment, this is an essential resource to exploring the monumental next stage in human development that isn't going away. A readable, accessible alternative to resisting change, Writing with AI reveals that artificial intelligence reinforces the very processes that are essential to good writing, rather than replacing them.

Literacy in the Digital Age

Writing with AI

Navigate leadership transformation when Industrial Age strategies no longer apply In Emergence: How Leaders Break Free from Outdated Thinking, Jennifer Vessels - CEO of Next Step and the change agent who led Adobe's shift from packaged software to cloud subscriptions, from during which its market value grew from $16 billion to $250 billion - delivers a proven approach for leading organizations through rapid, converging disruptions in which traditional planning approaches consistently fail to produce results. The book introduces the P.E.A.C.E. compass - Purpose, Exploration, Action, Collaboration, Empowerment - a structured approach for thriving when predetermined paths disappear. Drawing on transformation work with Adobe, Cisco, Novartis, Schneider Electric, and IKEA, Vessels shows how to integrate AI with human talent, empower multi-generational teams, and build organizations that are ready for continuous change. Readers will also discover: <ul> <li>Strategies for navigating five converging forces - Speed, Confidence, Meaning, Pressure, and Human/AI disruption - reshaping the leadership landscape</li> <li>Practical AI integration approaches used within global enterprises including Van Ameyde, IKEA, and Barloworld</li> <li>How to shift from fear-based decision-making to intuition-driven, experiential leadership that produces measurable organizational results</li> <li>Tiger team structures and empowerment approaches that release collective capability at scale across large organizations</li> <li>The story of Marie, a young woman who navigated wartime Europe on purpose and confidence alone - proof that the P.E.A.C.E. principles are timeless and accessible to anyone, regardless of title or authority</li> <li>Lessons from IKEA's six-year Korean market entry and Novartis's approach to restructuring every six months</li> </ul> Designed for CEOs, executives, managers, and anyone struggling to keep up, Emergence provides the approach leaders need when markets shift faster than traditional planning allows, with tested lessons from engagements with Adobe, Cisco, Google, IKEA, Microsoft, and Novartis. The future is emerging. Take action now - before it moves without you. "Jennifer Vessels has captured the new reality but also powerfully lays out how we can navigate productive ways into the future." Stuart Crainer, cofounder Thinkers50 "Your greatest competitive advantage today is quietly becoming your most dangerous blind spot tomorrow. In this book, Jennifer Vessels distills two decades of experience to provide an approach for leaders ready to trade the comfort of expertise for the courage of navigation."&nbsp; Sunil Gupta, Professor Digital Strategy/Innovation, Harvard &nbsp;

How Leaders Break Free From Outdated Thinking

Emergence

A Practitioner's Guide to Investing in Digital Infrastructure 

Data Centers Unlocked

A Field Guide to Private Equity-Owned Software

Left Holding

Half your newsfeed says you're hopelessly behind on AI. The other half says it's a sham. Both are engineered to make you click - and both lead to the same place: paralysis. Because what passes for AI expertise right now is mostly a temporary information advantage masquerading as expertise. *Fair Game* is the way out. Rob Collie knows that paralysis firsthand. As CEO of a data consulting firm, he watched AI threaten to upend the very business he'd spent a decade building. When fear finally drove him to dig in, what he discovered was unexpected: AI success isn't really about AI. It's about data - and the software around it. Problems he's been solving for thirty years. This book is the distillation of what Collie and his team learned building real AI solutions for real businesses - not theorizing from a stage. *Fair Game* walks you through how AI systems actually work, not at the PhD level, and not at the hand-wavy keynote level, but at the Goldilocks level where real decisions get made. You'll learn: - A five-part recipe for AI success you can apply to any project - Why successful AI is always custom AI - and why "custom" is less scary than it sounds - How to evaluate any AI proposal, hire the right team, and know when you're being sold snake oil You'll understand everything from how LLMs actually work to why your proprietary business knowledge is the one thing AI can't get on its own - all without jargon and using analogies you'll actually remember. Each chapter ends with a practical cheatsheet you can bring to your next meeting. By the time you've finished, the five-part recipe won't feel like a framework. It'll feel like common sense. You don't need to become an engineer. You need to become an architect - someone who knows what to build, what to demand, and what to call BS on. Because AI isn't out of reach. It's fair game.

Customizing AI to Your Business Is Easier Than You Think

Fair Game

Generative AI in Software Development: A Practical Guide for Engineering Leaders explores how large language models and generative tools are fundamentally changing the way software is created, tested, and maintained. This isn't a theoretical or academic deep dive; it's a practical, grounded guide for developers, product teams, and tech leaders who want to understand how generative AI can be embedded into real-world software workflows. From writing and debugging code to generating UI components, managing APIs, and automating deployment tasks, this book shows how AI is becoming a true co-developer.What sets this book apart is its balance: it's not just for hardcore engineers nor is it a high-level overview filled with buzzwords. Instead, it sits at the intersection technical enough to be useful but accessible enough for product managers and decision-makers. The industry is at an inflection point where AI-assisted development is no longer optional; it's become essential. This book fills the gap for those who want to move beyond the hype and see exactly how generative AI can speed up development, improve code quality, and change the economics of software delivery.

A Practical Guide for Engineering Leaders

Generative AI in Software Development

Organizations have been promised that AI will revolutionize them. But what ends up happening is that AI ends up being introduced like standard software. When productivity is the only focus of enterprise AI, the real insights that AI can offer prove elusive. This book shows a better way. Written by leading AI expert and keynote speaker Richard Foster-Fletcher, The AI Gap explains why enterprise AI in most organizations isn't producing the insights that were promised. AI enters as a promise of new intelligence but passes through the procurement, security, legal and compliance systems built for standard software. These systems strip AI of its potential. This book traces how this happens, why it persists and what organization must change to capture the insights AI can deliver. This book will explain why the way AI is implemented keeps restricting its potential and what organization must change to capture the true value of AI. AI works best when it and employees are given the freedom to explore, challenge ideas and use AI in new and create ways. This book is about developing the structures, the environment, and the culture that allows AI to flourish in an organization as a key driver of insights rather than a simple productivity improvement.

How to Fix Enterprise AI and Get Real Insights

The AI Gap

A good TradingView signal can do two things: help you catch trades earlier, and become the product other traders pay to use. Most chartists are on the wrong side of both. They pay for signals instead of owning the logic. They chase 93% backtests without knowing whether the strategy is real. They ask Claude Code for one Pine script, paste errors back ten times, and still end up with an indicator that repaints. Meanwhile, the signal service gets paid every month because it owns the script. Build Trading Signals with Claude Code shows you how to move to the owner side. First, you build Pine v6 TradingView signals you can test, alert, and trade yourself. Then you learn the second path: publish a free version as proof, put stronger versions behind invite-only access, rent scripts for 30, 90, or 365 days, or sell custom indicators to chartists who still cannot get Claude to compile clean Pine. Inside, you build 12 assets that make you a more dangerous chartist: 1. A Pine v6 setup that makes Claude read the manual first. 2. Prompts that turn signal ideas into working scripts. 3. Three TradingView indicators you can put on a chart. 4. Four strategies with sizing, stops, exits, and friction. 5. The breakeven stop-loss fix that prevents fake fills. 6. Alerts that carry real trade context. 7. A webhook loop for Claude trade analysis. 8. A checklist for spotting fake 93% backtests. 9. A faster loop for testing more signal ideas. 10. A 15-row Pine gotchas card. 11. Reusable prompts for the next indicator. &gt;The first money path is your own trading: signals you understand, alerts you control, and backtests you know how to distrust. The second money path is the asset: build a useful signal, prove it in public, publish the free version, rent the stronger version, and sell custom Pine work to people who still think coding indicators is expensive magic. One hundred $50 rentals is $5,000/month. A custom Pine job can pay more than the book, the TradingView plan, and the Claude subscription combined. You build the signal, backtest it with real friction, walk it forward, paper trade it, and only then decide whether it belongs on your chart, in your public library, or behind paid access.

Ship Pine v6 TradingView Indicators, Alerts, Backtests, and Webhooks This Weekend

Build Trading Signals with Claude Code

Turn AI investment into scalable business impact by enabling your workforce to build the solutions they actually need. From AI Users to Solution Builders is a strategic guide for senior AI, technology, and transformation leaders who want to move beyond underperforming, centralized AI initiatives, and unlock real enterprise value. As organizations struggle to translate AI into measurable results, this book shows how shifting from top-down deployment to workforce-led solution building creates faster adoption, stronger ROI, and sustained innovation. Written by experienced AI leader Wei Manfredi, this book combines strategic insight with practical execution. It draws clear parallels between failed digital transformation efforts and current AI adoption challenges, while demonstrating how natural language interfaces are reshaping access to AI. By enabling non-technical professionals to design their own tools, organizations can embed AI directly into workflows, decision-making, and daily operations. You'll learn how to: - Shift from centralized AI models to workforce-driven innovation - Enable employees to build AI solutions for real workflows - Design scalable infrastructure for AI solution development - Apply change management to overcome resistance and drive adoption &gt;Featuring real-world examples from organizations including Lululemon, Google, Oracle, and JPMorgan Chase, this book provides a proven framework for embedding AI into everyday collaboration, accelerating innovation, and future-proofing your organization's competitive advantage. Themes include: AI strategy, AI adoption, workforce transformation, AI governance, enterprise AI, change management

Scaling AI Across Your Organization

From AI Users to Solution Builders

Hart Studies in European Criminal Law

This book offers a comprehensive legal analysis of the urgent challenges posed by deepfakes, focusing on the restrictive measures proposed or introduced to address their related harms. Readers will gain a clear understanding of the harms associated with deepfakes - especially in areas like non-consensual sexualised content and political disinformation - and how criminal and digital regulatory systems are attempting to respond. From a criminal law perspective, the book offers a dual-level critique. On the one hand, criminal law is invoked for its expressive and symbolic function, particularly in response to the discriminatory and gender-based harms often associated with deepfakes, as well as the broader need to prevent systemic risks to democratic society when it comes to electoral manipulation and freedom of thought. Here, criminal law would play a vital role in affirming societal condemnation of such conduct and in acknowledging the serious impact on victims. On the other hand, its use is increasingly entangled with emerging frameworks of digital regulation, taking on a more instrumental role in defining illegal content and reinforcing standards shaped primarily by private platforms and regulatory bodies. This dual function raises fundamental questions about the legitimacy and efficacy of using criminal law-the most coercive form of state power-for purposes that extend beyond its traditional scope. Additionally, the book explores regulatory measures aimed at controlling deepfakes, considered both as AI-generated content and as harmful online material. Discussions around content moderation, transparency duties-such as labelling and watermarking-and safety by design measures are gaining attention globally, with the European Union's Digital Services Act and AI Act leading the way. The book's primary goal is to bridge the two worlds of criminal law and digital regulation through a careful and critical analysis, making it a valuable resource for a broad audience.

Harmful AI-generated Content between Criminal Law and Digital Regulation

Addressing Deepfakes

In a complex business landscape, enterprise architecture can't afford to be a static governance process. Instead, architecture must be adaptive and strategic. This book shows how. Drawing on decades of experiences, Adaptive Enterprise Architecture by Rubi Kaur is a practical guide to enterprise architecture that responds to real business conditions. Explaining why traditional architecture practices are no longer effective, it shows the impact of the pressures of AI, the complexity of modern organizations both in terms of technology and structure as well as the increase of ESG, tech supply chain and geopolitical risks. The book introduces its FLOW model which covers how architecture must operate in the new world. It explains how architect can work across the entire business, build adaptive and evolving architecture, reimagine their roles as orchestrator, create adaptive and agile governance. It equips architects to operate in flow: adapting in real time, orchestrating across business, technology, people and AI. Each chapter will include reflection prompts and practical experiments. The book will feature real-world examples from financial services, telecommunications, the public sector and consulting from the authors' careers and interviews with leading practitioners.

Build Strong Operating Models and Infrastructures for Successful Organizations

Adaptive Enterprise Architecture

Kubernetes AI

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