((link)): Mondomonger Deepfake

Priya leaned forward. “Then we stop chasing the video. We chase the man.”

In response to this growing crisis, lawmakers are beginning to catch up:

At the core of deepfake creation are Generative Adversarial Networks. Two neural networks—the Generator and the Discriminator—work in a continuous loop. The Generator creates fake images, while the Discriminator attempts to spot the flaws. Over thousands of iterations, the Generator learns to create hyper-realistic faces, expressions, and lighting that easily fool the human eye. 2. Diffusion Models and Voice Cloning mondomonger deepfake

Beyond Telegram, deepfakes spread rapidly across Twitter (now X), Facebook, and other mainstream social media platforms. A disinformation campaign run by the notorious used images of celebrities to spread fake stories, demonstrating how deepfake-like tactics are integrated into broader propaganda operations.

: Automatically addressing parts of a background that are uncovered when a face or object is moved during the deepfake process. Everybody Can Make Deepfakes Now! Priya leaned forward

The potential for any digital name—whether a politician, a media mogul, or an artist like Mondomonger—to be used in deepfake content carries serious implications.

: Advanced detectors look for subtle changes in skin color caused by a heartbeat (photoplethysmography), which AI generation often fails to replicate. damaging their online reputation and brand.

Traditional deepfakes rely heavily on flat 2D image datasets. However, creators who post on platforms like Sketchfab provide high-resolution, multi-angle reference maps, neutral poses, and custom skeletons.

: Creators find their digital signatures or signature avatars weaponized in unauthorized content, damaging their online reputation and brand.