Threads tests a Meta AI integration that works similarly to Grok

Threads is currently piloting an innovative integration of Meta AI, which functions similarly to the Grok feature found on X. This new capability allows users with public accounts to mention Meta AI in their posts or responses, enabling them to gain deeper insights into trending topics and breaking news. At present, this feature is in its beta phase, being tested in countries such as Malaysia, Saudi Arabia, Mexico, Argentina, and Singapore. According to a statement from Meta to TechCrunch, this functionality aims to provide users with real-time context and tailored recommendations during their conversations. Users can engage with Meta AI by posing questions such as, "What’s the buzz about the World Cup this month?" or "Which Met Gala outfits are currently trending?" and even inquire about the Knicks' performance in the playoffs. The AI will generate responses as public replies from the @meta.ai account, responding in the same language as the initial query. Through this integration, Threads is evolving into more than just a platform for discussing news and trends; it is becoming a source of information and recommendations without requiring users to navigate away from the app. This approach mirrors the functionality of Grok on X, where users frequently interact with the AI chatbot for clarifications and insights. However, incorporating an AI chatbot into a social platform comes with inherent challenges. For instance, Grok has faced scrutiny for generating controversial content, including posts that glorify historical figures like Hitler. Nonetheless, Meta claims that its AI possesses stronger safeguards compared to Grok, though its ability to avoid similar pitfalls remains to be seen. For those wishing to limit the presence of Meta AI in their feeds, users have the option to mute @meta.ai, select the “Not interested” feature on any Meta AI-generated posts, or hide specific replies from Meta AI that appear on their posts. Meta has expressed its commitment to refining this feature based on initial feedback before rolling it out to a broader audience.