Kurs · 4 Kapitel
On-Device & Edge AI
Ship AI where the user is — Apple Foundation Models, Gemini Nano, MLX, distillation, and edge deployment patterns
Das wirst du können
- A 12-minute orientation to the On-Device & Edge AI skill path — the three platforms where your model can run without a cloud round-trip, and how to pick yours.
- Ship a capable ~3B LLM inside your iOS app — guided generation, tool calling, and when to still reach for Claude
- Ship on-device AI to 140M+ Android devices — AICore as a shared system service, ML Kit GenAI APIs, and Gemma 4 agentic intelligence.
- Run arbitrary open models on your Mac — unified memory, quantization that actually preserves quality, and the honest limits of a single-user inference node
Was drin ist
- 1On-Device & Edge AI: Start Here
A 12-minute orientation to the On-Device & Edge AI skill path — the three platforms where your model can run without a cloud round-trip, and how to pick yours.
- 2Apple Foundation Models for Swift Developers
Ship a capable ~3B LLM inside your iOS app — guided generation, tool calling, and when to still reach for Claude
- 3Gemini Nano and AICore on Android
Ship on-device AI to 140M+ Android devices — AICore as a shared system service, ML Kit GenAI APIs, and Gemma 4 agentic intelligence.
- 4MLX in Practice: Local Inference on Apple Silicon
Run arbitrary open models on your Mac — unified memory, quantization that actually preserves quality, and the honest limits of a single-user inference node
Zertifikat erhalten
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