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Snap Adds AI Song, Photo, and Sticker Remix Tools to Lens+

Snap is rolling out four AI creative tools to Lens+, including a feature that turns chat messages into short original songs for Snapchat+ subscribers.

Snap app on two phones: a camera screen with an Add a Sound button and a chat menu listing Generate Song
Lens+ · Credit: Snap

Snap is adding four AI-powered creative tools to Lens+, the premium tier of Snapchat+ that launched last year, giving Snapchat subscribers new ways to remix chats, Snaps, Stickers, and captions. The features, detailed in a newsroom post, roll out now in every market where Lens+ sells, though Snap says regional availability may vary in the coming weeks.

The headline addition, Create Song, turns a Snapchat chat message into a short original track. A subscriber presses and holds a message in Chat, taps Create Song, picks a genre, and previews the song before sending it into the conversation. Snap calls Create Song a way to make a text exchange "memorable," but the company named no AI model or music-generation partner behind it.

Three companion tools round out the Lens+ update: AI Photoshoot, AI Remix, and new caption fonts. AI Photoshoot cleans up an almost-good photo, fixing a blink or bad lighting so a subscriber can share the Snap they meant to take. AI Remix lets a subscriber reimagine a friend's incoming Snap in a new visual style before replying. The caption fonts, spanning bubble letters, spray paint, and foam textures, restyle captions, saved Stickers, and received Stickers.

Snap says Snapchat+, the base tier under Lens+, has passed 25 million subscribers worldwide. Create Song, AI Photoshoot, AI Remix, and the new fonts are Lens+-exclusive; Snap gave no launch date for individual markets or for Android versus iOS, and did not say whether any of the four tools will later reach free Snapchat users.

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Kenji Sato

Kenji Sato edits techshooked's coverage of artificial intelligence and emerging technology, following the path from research to production systems. His standard is anti-hype: ask what a model actually does, what data trained it, how it fails in practice, and whether a benchmark measures what the marketing says it does.