<p>We explore the architectural discipline of knowing when to use Machine Learning and when to stick with deterministic code. We dissect the "AI Everywhere" trap, compare the costs of Code 1.0 vs Code 2.0, and establish the "Certainty Gap".</p>

We explore the architectural discipline of knowing when to use Machine Learning and when to stick with deterministic code. We dissect the "AI Everywhere" trap, compare the costs of Code 1.0 vs Code 2.0, and establish the "Certainty Gap".

Model Selection Strategy: When to Reject AI

Sandboxed is a podcast for iOS developers who want to add AI and machine learning features to their apps—without needing a PhD in ML. Each episode, we take one practical topic—like Vision, Core ML, or Apple Intelligence—and walk through how it works, what you can build with it, and how to ship it.

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Model Selection Strategy: When to Reject AI

Model Selection Strategy: When to Reject AI