Mark Zuckerberg Flaunts Gold Chain Gifted By Rapper T-Pain: "That's Awesome''

He also demonstrated a special feature of Meta's new AI research model.

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T-Pain also reacted to the video through a comment

Mark Zuckerberg, CEO of Meta, recently shared a video on Instagram showcasing a gold chain gifted by American singer and rapper T-Pain. The gold chain features the Meta logo and a distinctive triangle pendant, a hallmark of T-Pain's design. Through the post, Mr. Zuckerberg also demonstrated a special feature of Meta's new AI research model. 

As he wears the chain, the video seamlessly transitions to highlight the AI model's features, including object selection. With a few taps, he selects various objects in the video, such as the gold chain, his shirt, and even his face, demonstrating the AI's precision and versatility. 

''Thanks @tpain for the epic new chain. This is a perfect opportunity to show how the new Segment Anything AI research model we're releasing today can track different objects in the same video. Lots of fun video effects will be possible with this,'' he wrote on Instagram while posting the video. 

Watch the video here:

T-Pain also reacted to the video through a comment that read, ''Looks great on you, buddy. Thanks for being a great friend,'' to which Mr. Zuckerberg replied, “It's a great chain! Looking forward to more adventures ahead.''

The video has amassed several reactions and comments. One user wrote, ''New chain ..awesome.'' Another commented, ''We have Zuck with drip before GTA VI.'' A third said, ''Zuck really leaning into the chain fashion , I like it.''

A fourth added, ''Sometimes I feel Zuck's heart so pure as a child .That's why we love Zuck's style. Zuck is an example of a great winner.''

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According to the Meta blog, the Segment Anything Model 2 (SAM 2) can segment any object in any video or image—even for objects and visual domains it has not seen previously, enabling a diverse range of use cases without custom adaptation. SAM 2 has many potential real-world applications. It could also aid in faster annotation tools for visual data to build better computer vision systems.

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