Meta open sources code to let you make Muse AI gadgets
Short summary
Meta released open-source code so anyone can build their own Muse AI gadgets using ESP32 boards or Raspberry Pis, and is also giving away 5,000 of its own Muse Home Link device to control smart home devices. The company is essentially letting hobbyists turn the AI agent into whatever form factor they want.
- Meta open sourced SDKs for Muse so developers can load it onto off-the-shelf hardware like E Ink displays, HDMI sticks, or touchscreens
- The company manufactured 5,000 Muse Home Link gadgets and opened a waitlist for free units shipping this month
- Muse Home Link can control lights, TVs, printers, and other devices through community-built skills
Full summary
Meta has open-sourced the code for Muse, its AI agent, letting anyone build custom hardware to run it. You can load it onto an ESP32 microcontroller board or a Raspberry Pi, then wire it to whatever displays, buttons, sensors, or other hardware you have available. The company throws out specific examples: an E Ink display showing reminders, an HDMI stick for a big screen, or a small touchscreen that mimics Meta's Muse Charm device. Meta's framing is straightforward—treat it as a DIY project where you're responsible for anything that goes wrong.
Beyond just releasing the code, Meta created a reference device called Muse Home Link and manufactured 5,000 units to give away. This gadget works with community-built skills that let the AI handle practical tasks like switching lights on and off, controlling your TV, or sending files to a printer. The actual capabilities depend on what you've set up in your home, but the idea is clear: it's a hub for voice or text commands tied to your existing devices.
You can sign up for the waitlist now if you want one of the Home Link units. Meta says they'll ship sometime this month. The whole move signals Meta's bet that people will tinker with Muse on custom hardware rather than waiting for the company to manufacture every possible form factor. It's a reasonable strategy—let the hobbyist crowd solve for their own use cases while you focus on the AI engine itself.