AI that runs directly on a phone, laptop, or other device instead of sending data to remote cloud servers for processing.
On-device AI uses models small and efficient enough to run on local hardware, often helped by neural processing units built into modern chips. Because data does not need to leave the device, it can improve privacy, reduce latency, and keep features working offline.
Examples include phone cameras that recognize scenes and adjust settings instantly, keyboards that suggest replies, live transcription without an internet connection, and photo apps that search pictures by content. A field technician might use an on-device model to read equipment labels and look up manuals in a basement with no signal. The trade-offs include limited model size, battery use, and inconsistent performance across older devices. Many products combine on-device processing for simple tasks with cloud models for harder ones.
Processing data close to where it is generated, such as on devices or local servers, instead of sending everything to a distant data center.
Neural Processing UnitA specialized processor designed to run AI and machine learning tasks efficiently, often built into phones and laptops.
Small Language ModelA compact language model, typically with a few hundred million to around ten billion parameters, built to run efficiently on modest hardware.
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