Background editors are led by Ahmad Al-Dahle, Meta's lead for artificial intelligence generative. In an announcement post on Threads, Al-Dahle declared that the software will allow users to trigger the creation of new backgrounds for their stories which will allow for new creative possibilities.

"With backdrop, you can alter the look of the background of your photo with one tap and a prompt such as 'chasing dinosaurs' or surrounded with puppies to create a completely new background to use in your Story. Click the button to create a background at the top of your new Story to start,'" the author wrote. Users can also write their prompts.

You can now test the Instagram "Try it" stickers

After being posted to stories, the AI-generated backgrounds will include the "Try it" sticker that allows other users can use the same prompts for text on their photos.

The launch builds on Instagram's expanding array of AI services, which includes creativity tools that are already available on Snapchat and other Meta platforms such as Messenger or WhatsApp. In the last month, Meta rolled out a similar AI generator for images called Imagine as well, and Snapchat unveiled paid features enabling users to create fantasy-themed photos.

As AI technology for image generation advances, social platforms are rushing to build the capability into their apps. Instagram is hoping features like the background editor will make it stand out even though ethical questions about deepfakes persist. AI-powered creative tools.

Generative AI is an artificial intelligence capable of creating new content on its own instead of only analyzing existing content. "Generative AI" is the "generative" part that refers to the fact these AI systems can create new images, text audio, video, and other types of data that have never been seen before.

Generative AI is based on deep learning algorithms, specifically on an aspect of AI techniques known as neural nets. To learn the patterns, concepts, and ideas these neural nets are trained by massive amounts of data, often comprising millions or billions of data points. After the machine-learning AI model is sufficiently trained, it can use its learnings to produce novel innovative creations that are based on the patterns it has observed in its training data.