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Meta releases Muse Gadgets SDK to put screens, buttons and home connections on Muse

Meta has released the Muse Gadgets SDK, giving developers a way to build custom hardware around its Muse AI with screens, buttons and connections to other devices in the home. The move extends Muse from a software assistant toward a third-party hardware ecosystem.

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Meta 发布 Muse Gadgets SDK:给 Muse 接上屏幕、按键和家里的设备
Image source: meta.com

Meta has released the Muse Gadgets SDK, a toolkit aimed at developers who want to build custom hardware around its Muse AI. According to the announcement, the SDK lets devices add screens and buttons and connect to other devices in the home, effectively pushing Muse out of the app and onto physical gadgets.

The SDK acts as a link between Muse and hardware: screens present information, buttons handle local interaction, and home connectivity lets a device reach and coordinate with other appliances. For developers, that means they do not have to build an AI stack from scratch to give a device a capable brain.

For Meta, opening the SDK matters because it recasts Muse from an assistant inside its own products into a platform that third-party hardware makers and independent developers can build on. When a hardware ecosystem forms around an AI assistant, users tend to stick to the devices, not just the app.

The announcement did not spell out which device categories, hardware specifications or manufacturing partners the SDK supports; the core claim so far is that Muse can be wired to screens, buttons and home devices through it.

What to watch next is how many hardware makers and developers actually adopt the SDK, and whether Meta follows up with clearer rules on safety, privacy and device compatibility. Whether Muse Gadgets SDK produces recognisable third-party hardware will decide if Muse stays an assistant or becomes a cross-device AI entry point.

Why it matters

Muse Gadgets SDK pushes Meta's assistant into third-party hardware, a step toward making Muse a device ecosystem rather than a single app. For hardware developers, it lowers the bar to building on a mature AI stack.

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