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Real-World AI: From Vision to Value

eBook: How to Effectively Integrate AI into Product Development

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eBook: AI in Product Development

The electronics industry is at a pivotal moment: AI has moved from a distant promise to a real competitive asset. But how do you apply it effectively in product development? This eBook not only answers that question—it equips you with hands-on strategies and valuable know-how.

Knowledge That Drives You Forward

This guide isn’t just an AI primer. It delves into the core topics you need, offering both broad insights and deep, actionable details. You’ll learn how to:

  • Deploy AI in cloud and on-premises environments
  • Perform precise probability calculations within simulations
  • Train AI models quickly and effectively
Part 1

Technology

Technology Beyond Magic, It’s Mathematics

AI can seem like magic, but at its core it’s advanced mathematics and data-driven algorithms. In this first section, we demystify what AI can and cannot do within product development. You’ll learn how quickly modern AI systems actually learn, what determines their accuracy, and how machine learning and neural networks fit into the picture. We also cover essential system requirements and critical training considerations so you can set up your infrastructure correctly from day one.
Part 2

Data

More Isn’t Always Better! The Truth About Data.

Data is the lifeblood of AI, but throwing more data at the problem isn’t always the answer. In Part 2, we explain how to identify the optimal data volume for training robust models, how to keep your datasets fresh and well-organized, and how to elevate data quality to improve overall outcomes. You’ll see how to integrate AI into existing data streams seamlessly, avoid common pitfalls, and prepare your data so that every model you train delivers maximum value.
Part 3

Business Cases

Sounds Great, But Does It Work? AI Applications in Simulation!
It’s one thing to understand AI’s potential; it’s another to see it in action. This section brings you concrete examples of AI-driven simulation in product development. We walk through diverse case studies that showcase the impact of AI on real projects, outline the criteria for determining whether AI is the right solution for your challenges, and offer practical advice for launching your first AI initiative. You’ll finish with a clear roadmap for translating AI concepts into measurable results.
Part 4

Implementation

Making AI Part of the Team!
Integrating AI into your product lifecycle requires more than technology—it demands a strategic approach to people, processes, and governance. In Part 4, we detail how to prepare your teams, adapt existing workflows, and leverage automation to scale your AI efforts. We also address vital legal and compliance considerations such as data security and liability, ensuring that your AI projects start on a foundation that’s as robust as the simulations themselves.
Part 5

Humans & AI

Competitors or Partners?
Will AI replace engineers, or become their most powerful tool? In the final section, we explore how human expertise and AI capabilities can complement each other to drive innovation. You’ll learn what skills engineers need in an AI-powered environment, how roles are evolving, and which ethical guidelines should govern your use of AI. This future-focused perspective helps you strike the right balance between human judgment and machine intelligence.
Overview

When Are The Chapters Expected to Be Released?

  • Part 1: Published
  • Part 2: Published
  • Part 3: Published
  • Part 4: September
  • Part 5: November

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