Own Your AI: When to Run Models Locally and When to Trust the Cloud

Every technology adoption curve reaches a moment where the default choice stops being the obvious one. For years, AI meant one thing: you sent your data to a server somewhere, and the server sent back an answer. But that simplicity came with a price you may not have realized you were paying.

This book helps you make intentional choices about AI deployment rather than default ones. You'll understand the real tradeoffs between privacy and capability, cost and convenience, and control and complexity. You'll learn to build systems that use local and cloud AI where each genuinely excels.

Inside, you'll discover:
• The fundamental differences between local and cloud AI architectures
• How to evaluate the true economics of each deployment model
• What hardware you actually need for local inference
• How to set up your first local AI system
• When only cloud AI will meet your needs
• Customizing open-weight models for your specific use cases
• Building hybrid architectures that use the best of both worlds

You don't need to abandon the cloud to benefit from local AI. You need to understand both options well enough to choose intentionally for every task. This book gives you that understanding.