AI TrustID

The algorithm’s function essentially involves artificial intelligence making decisions about the “liveness” of photos, and our task is to teach AI to accurately distinguish real photos from spoofs. How does this happen? Dozens of individuals specially trained by us gather sets of hundreds of thousands of sorted real and fake photos (datasets). These prepared datasets are then loaded into AI for training. The AI identifies common features among all real photos and common features among all fake photos, as well as features that differentiate real photos from spoofs. It’s worth noting that these features are often completely imperceptible to the human eye. Once the model training is complete, testers take over. These are not the same people who collected the datasets. They are unaware of the fake materials on which the AI was trained and try various methods to deceive the system, attempting to have it accept a fake photo as real or, conversely, reject a real photo as fake. If this occurs, the system continues to be trained specifically on such photos. New datasets are assembled, loaded into the models, and the training process continues.The uniqueness of AI with machine learning lies in the fact that even when operating in real products with real photos and real attempts at deception, the system continues to learn and improve even in the absence of any erroneous triggers.