Meta Open Sources Muse AI to Let You Build Custom Smart Devices

Meta is making a bold bet on ubiquitous AI by open sourcing the code behind Muse, its new AI agent platform, and actively encouraging developers and hardware makers to build custom devices powered by the system. The company's strategy is to make Muse the foundational layer for a new generation of smart home devices, wearables, and consumer electronics. Rather than competing with Apple and Amazon by building its own hardware ecosystem, Meta is essentially handing the tools to everyone and betting that scale and adoption will benefit its AI business.

The move is significant because it signals a shift in how Meta views AI competition. Instead of controlling both the software and hardware (like Apple does with Siri and iPhones), Meta is embracing an open approach where third-party manufacturers can license Muse and build it into their products. Meta has suggested specific product categories: smart displays, E Ink colour screens, kitchen appliances, televisions, and even toasters. The vision is that within a few years, Muse becomes the agent you interact with across dozens of devices in your home and on your person.

This is a calculated departure from Meta's earlier hardware strategy. The company spent billions developing Portal devices, Ray-Ban glasses, and other hardware products that largely failed to gain consumer traction. By open sourcing Muse, Meta avoids the capital and manufacturing complexity of building hardware while still capturing the value of having Muse agents everywhere. Every time a user interacts with Muse on a third-party device, they're essentially using Meta's AI infrastructure and data collection capabilities.

How Open Sourcing Benefits Meta

On the surface, giving away your AI code seems counterintuitive. But Meta's business model isn't primarily about selling software licenses. It's about data, advertising reach, and user engagement. The more devices Muse runs on, the more touchpoints Meta has with users, the more data it collects about behaviour and preferences, and the more opportunities it has to serve personalised advertising or recommendations.

There's also a platform effect at work. If Muse becomes the dominant agent platform on consumer devices, developers will optimise for it, third-party companies will build integrations, and a whole ecosystem of complementary services will emerge. Meta benefits from being the central platform without bearing the full cost of hardware development and distribution.

The open source release also builds goodwill with developers and manufacturers at a time when Meta's public image has been battered by privacy concerns, content moderation failures, and accusations of market abuse. By positioning Muse as a collaborative, developer-friendly platform, Meta is trying to position itself as the good actor in AI democratisation.

Technical and Competitive Implications

Muse is designed to be relatively lightweight compared to larger AI models, which makes it feasible to run on consumer devices without requiring constant cloud connectivity or high-end processors. This is a practical advantage over systems that require powerful GPUs or always-on internet. However, the Muse agent will still be trained on Meta's infrastructure and will ultimately funnel data back to Meta's servers for learning and improvement.

Competitors will respond. OpenAI has released Dot, its own agent platform positioned at enterprise users and businesses, though it's clearly eyeing consumer applications. Google is expected to release or expand its own agent offerings. Amazon already has Alexa, though Alexa has remained fairly limited compared to the latest generation of AI agents. Samsung, LG, and other appliance manufacturers will have to decide whether to embrace Muse, build their own agents, or wait to see which platform wins.

The real competition isn't between individual tech companies anymore, it's between competing visions of how AI should be integrated into consumer life. Meta's vision is horizontal and distributed: Muse on every device. Apple's approach is vertical and controlled: deep integration between hardware, software, and services. Amazon and Google are somewhere in the middle, trying to leverage their existing install bases and retail relationships.

What Developers Should Know

For hardware makers, the appeal is obvious: you get sophisticated AI capabilities without building them from scratch. For software developers, building for Muse means tapping into a potentially massive user base. Meta will likely provide APIs, documentation, and support to make integration relatively straightforward.

The catch is that you're betting on Muse becoming the dominant platform. If a different agent architecture wins, your investment in Muse integration becomes a sunk cost. But given Meta's resources and distribution power, the bet is probably reasonable for most manufacturers.