When coffee machines, scent generators, and ball-tracking gadgets all run AI, you know we’ve crossed from “productivity tool” to “everything is a model playground.”
CES this year sounds less like a gadget show and more like an AI carnival.[3] We’re talking coffee machines that use AI to brew your personal perfect espresso, devices that generate a custom scent profile just for you, and even ball‑tracking systems that rely on computer vision and ML.[3] It’s basically the “what if we put a model in this?” meme, except the joke has turned into commercial hardware.
From a developer lens, this is the clearest signal yet that AI is no longer just about chatbots and code assistants. It’s embedding itself into mundane objects: appliances, wearables, even smell generators.[3] That means new surfaces for APIs, on‑device models, and edge inference. If a coffee machine can run a personalized taste model, there’s no reason your next side project can’t ship with a tiny local LLM or a vision model baked right into the firmware.
The practical angle: if you’ve been heads‑down in web stacks only, this might be your wake‑up call to learn a bit about edge ML, embedded hardware, or at least how to talk to these devices via SDKs. We’re moving into a world where “full‑stack” can mean frontend, backend, and a model running on a chip inside someone’s kitchen.
So here’s the question: are you going to wait for big vendors to define what “AI in everything” looks like, or are you going to be the person who builds the weird, delightful AI‑powered thing that steals the show at the next CES?
Source: The Daily Star