DeepAngel

DeepAngel, originally incubated at the MIT Media Lab, represents a sophisticated intersection of generative adversarial networks (GANs) and forensic computer vision. By 2026, it has solidified its position as a critical tool in the 'Post-Truth' digital landscape, offering two-way functionality: the ability to detect AI-generated modifications and the capability to perform 'automated erasure' of objects within images. The technical architecture leverages semantic segmentation to identify specific entities (e.g., people, vehicles, text) and utilizes advanced inpainting algorithms to remove them while maintaining background consistency. Unlike consumer-grade AI editors, DeepAngel's primary market value lies in its transparency and forensic logging, helping journalists, researchers, and legal professionals identify what has been subtracted from digital reality. Its 2026 positioning focuses on 'Media Provenance,' acting as a counter-measure against the proliferation of high-fidelity synthetic media. It serves as both an educational platform for understanding AI capabilities and a technical utility for verifying the integrity of visual assets in high-stakes environments like newsrooms and digital archives.