AI & Emerging Technology
Most of the AI features you’ve used probably run somewhere far away — in a data center, over an internet connection, with your request bouncing to a server and back. That’s starting to change. A new class of smaller, more efficient AI models is being built to run directly on your phone or laptop, no connection required.
Why smaller is suddenly a selling point
For a long time, “bigger model, better results” was the assumption driving AI development. But bigger models need more computing power, which usually means a remote server. Smaller models trade some raw capability for something valuable in everyday use: they can run locally, instantly, and privately, without sending your data anywhere.
Chipmakers have leaned into this by building dedicated AI processing units directly into phone and laptop chips. Combined with more efficient model designs, that hardware means a device can now handle tasks — like transcribing a voice memo, suggesting a reply, or editing a photo — without a round trip to the cloud.
What actually improves
- Speed. No network round-trip means near-instant responses, even with spotty connectivity.
- Privacy. Data that never leaves the device is data that can’t be intercepted or logged elsewhere.
- Reliability. Features keep working on a plane, in a basement, or anywhere signal drops out.
- Cost. Running a task locally doesn’t consume server capacity, which matters at scale.
The honest tradeoffs
Smaller on-device models generally can’t match the reasoning depth of the largest cloud-based systems. For quick, well-defined tasks — summarizing a paragraph, cleaning up a photo, transcribing speech — the gap barely matters. For open-ended research or complex multi-step reasoning, cloud models still tend to have the edge, at least for now.
The most practical products increasingly blend both: simple, private, instant tasks handled on-device, with harder problems routed to the cloud only when needed. As a shopper, that hybrid approach is worth understanding, because “has AI features” no longer tells you much about how a device actually behaves — where the processing happens changes what you can expect from it.
What to look for when buying a device
If on-device AI matters to you, look past the marketing term itself and check for a dedicated neural processing unit, recent chip generation, and whether the manufacturer is explicit about which features work offline. That’s a better signal than a logo or a buzzword on the box.
