AI Hardware and On-Device AI
Tracking AI moving from the cloud onto devices: dedicated inference silicon, pocket-sized AI hardware, on-device models in phones and PCs, and what offline inference buys in privacy and latency.
As models shrink, hardware competes for new territory. At one end, pocket devices try to move the conversational entry point off the phone. At the other, on-device inference in phones, PCs and robots uses dedicated silicon to cut latency to tens of milliseconds and keep data local. Thermals, battery and bandwidth decide how large a model can really run, so on-device claims get oversold. What ships and what offline inference saves matter.
