Meta Acquires Limitless To Propel AI Wearable Innovation

by THEFUTURE.TEAM

December 8, 2025

Overview Of A Strategic Acquisition

Meta has strategically acquired Limitless, the AI startup formerly known as Rewind, marking a significant milestone in the evolution of AI-powered wearables. The company, which pioneered an innovative pendant that records conversations, announced via its website that it will cease selling its hardware devices while providing one year of dedicated support for its existing customer base.

Transitioning Business Models And Product Lines

In a transformative move, Limitless will transition its customers to the Unlimited Plan without the need for an ongoing subscription fee. The tech firm will also wind down additional functionality, including its legacy desktop software, Rewind, which innovatively converted desktop activity into a searchable record. This strategic pivot highlights the evolution from early-stage hardware experimentation to a more integrated software and service-oriented model.

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Leadership And Market Dynamics

Founded by Brett Bejcek and Dan Siroker – the latter of whom previously led Optimizely – Limitless successfully navigated a competitive landscape marked by rising investments and market pressure from tech giants like OpenAI and Meta. As indicated by the company’s founders, the market has transformed from an era where AI and hardware were viewed as a remote possibility to today’s inevitable future of integrated personal superintelligence.

Meta’s Vision For The Future

Meta’s acquisition of Limitless reinforces the company’s commitment to bringing AI-enabled wearables to a broader audience. Currently, Meta is focused on evolving its portfolio with products such as AR/AI glasses, including the notable Ray-Ban Meta and Oakley Meta, as well as in-lens displays in the Meta Ray-Ban Display series. While Limitless will likely act as a support mechanism for existing Meta products, its expertise is a clear indication of Meta’s intent to accelerate innovation in the wearable space.

Data Autonomy And Financial Backing

Existing customers of Limitless are offered robust data options, with capabilities to either export or delete their personal data directly from the app. The startup, backed by over $33 million in funding from prominent investors including a16z, First Round Capital, and NEA, has positioned itself at the intersection of hardware and AI technology.

Conclusion

This acquisition not only underscores Meta’s expanding vision in AI-enabled wearables but also signals a broader industry shift towards integrated personal intelligence devices. As Limitless’ seasoned team merges with Meta’s Reality Labs, the coming years are poised to witness rapid advancements in how technology interweaves with daily life.

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Meta Unveils Muse Wonder Models In A Bid For Frontier AI Leadership

by THEFUTURE.TEAM

October 13, 2026

Meta has introduced two new AI models, Muse Wonder and Muse Wonder Full, signalling a more ambitious move into frontier AI. The releases build on Muse Spark but target more demanding tasks, including coding, while placing greater emphasis on long-term memory and personalised assistance.

Larger Models Target More Demanding Tasks

Unlike Muse Spark, which was designed for low latency and lightweight use, Muse Wonder and Wonder Full are significantly larger and, according to Meta, more capable. The company reports stronger benchmark performance and improvements on demanding workloads, including coding.

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According to Meta’s model card, both models achieved benchmark results comparable to Fable 5.1 and GPT-6 Astra in the company’s internal testing. Meta described the release as “the next step on our scaling ladder and a major leap toward personal superintelligence” in its announcement.

Pricing Reflects Meta’s Frontier Ambitions

The models’ pricing places them in the premium AI segment. Through the Meta Model API, Muse Wonder will cost $4 per million input tokens and $20 per million output tokens, putting it in a similar pricing tier to GPT-6 Sol and Opus 5.5.

Muse Wonder Full, by contrast, will not be offered through the API. Meta says it will be exclusive to Muse Code subscribers, tying access to its most advanced model to a premium product. Both models will also power the Muse agent.

Long-Term Memory Takes Centre Stage

Meta is increasingly positioning its AI strategy around assistants that can support users over time rather than respond only to individual prompts. A central part of that approach is what the company calls “active memory”: the ability to retain, organise and synthesise information provided by users across extended periods.

Meta points to the MemoryBench benchmark, which evaluates systems designed for continual learning and memory construction. The company says Muse Wonder now outperforms Fable, Opus and Astra on this measure.

“We put a tremendous amount of effort into making sure your model can remember what’s important to you over days, weeks, months, and beyond,” research scientist Kavya Kopparapu said in a launch video.

New Models Follow Meta’s AI Reorganisation

The launch is also significant within Meta’s broader AI strategy. It is the company’s first frontier-model release since Scale AI founder Alexandr Wang reorganised its AI operations in August 2025. Meta has since introduced Muse Spark and the Muse agent, while making fewer high-profile model announcements than competitors such as OpenAI and Anthropic.

The new models were trained at Meta’s Prometheus data centre in central Ohio, which came online earlier in 2026, according to the company. The facility highlights the growing importance of infrastructure in the race to develop advanced AI systems, where performance depends not only on algorithms and data but also on computing capacity, data-centre investment and access to capital.

As competition intensifies, Muse Wonder and Wonder Full represent a broader bet on larger models, persistent memory and premium AI products. Their longer-term significance will depend on how their reported capabilities translate into real-world performance and whether users find enough value to pay for access.

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