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Meta is expanding its artificial intelligence strategy by forming new partnerships aimed at capturing more real world conversational data, as original content creation on Facebook and Instagram continues to decline. The move reflects growing concern inside the company that reduced user posting activity could weaken one of Meta’s long standing competitive advantages: access to massive volumes of human generated data.
As engagement on Meta’s platforms increasingly shifts toward passive content consumption, particularly short form video, the company faces a challenge. Fewer personal posts, comments, and discussions mean fewer direct signals about how people think, ask questions, and communicate. That data is critical for training large language models and conversational AI systems.
The importance of conversational data has already reshaped the AI landscape. Platforms such as Reddit have become highly valuable training sources because their discussions revolve around questions and answers that closely resemble chatbot interactions. Similarly, Elon Musk’s xAI benefits from conversational data generated on X, while Meta has attempted to recreate this dynamic through Threads.
To strengthen its data pipeline, Meta recently acquired Limitless, an AI startup best known for an AI powered pendant capable of recording everyday conversations and generating summaries. While Limitless will continue supporting the device for another year, sales of the pendant will stop. Industry observers believe Meta is more interested in integrating the technology into its existing hardware ecosystem, particularly its smart glasses, allowing the company to capture real world conversational insights beyond social media posts.
In parallel, Meta has announced a partnership with ElevenLabs, a company specializing in AI voice generation and translation. The collaboration will initially focus on translating Reels into multiple languages and later expand to immersive environments such as Horizon. These tools will generate additional conversational and linguistic data that can be used to further refine Meta’s AI models.
Together, the deals signal Meta’s push to diversify its AI training sources at a time when traditional social engagement patterns are changing. However, the strategy is likely to reignite debates over privacy, consent, and the legality of recording everyday conversations, particularly as political and regulatory attitudes toward AI data collection continue to evolve in the United States.
Despite these concerns, Meta appears determined to secure long term access to conversational data, viewing it as essential to maintaining competitiveness in the rapidly intensifying global AI race.
