According to MIT Technology Review,  Assembler combines several existing techniques in academia for detecting common manipulation techniques, including changing image brightness and pasting copied pixels elsewhere to cover up something while retaining the same visual texture.

It also includes a detector that spots deepfakes of the type created using StyleGAN, an algorithm that can generate realistic imaginary faces.

These detection techniques feed into a master model that tells users how likely it is that an image has been manipulated.

Assembler is a good step in fighting manipulated media -- but it doesn't cover many other existing manipulation techniques, including those used for video, which the team will need to add and update as the ecosystem keeps evolving.

"It also still exists as a separate platform from the channels where doctored images are usually distributed. Experts have recommended that tech giants like Facebook and Google incorporate these types of detection features directly into their platforms. That way such checks can be performed in close to real-time as photos and videos are uploaded and shared."