Building & Running AI intermediate

On-Device AI

Also called: edge AI, local AI

Running a model on a phone or laptop instead of sending data to a server.

On-device inference keeps data local, works offline, and has no per-token cost — genuinely attractive for privacy and regulated contexts. The trade is capability: local models are smaller and slower than frontier APIs. Quantization and distillation are what make it viable at all.

In practice: Transcribing a confidential meeting without the audio leaving the laptop.

Where this comes up