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A deepfake is synthetic media, such as video or audio, created using machine learning to mimic real individuals. By training models on genuine footage, deepfakes can produce lifelike content. While deepfakes offer potential in entertainment and education, they also raise ethical concerns, as they can spread misinformation or harm reputations. As they evolve, distinguishing real from fake becomes more challenging, prompting research into detection techniques.
A Reality Anchor is a device that your company can use to ensure that both you and your customers know they are interacting with a real person, anchoring them to reality.
thought it might seam like a odd questoin its one you want to have a clear and definit ansor for. Its Another downstream problem with deepfakes is the lack of tust. buiness is built on trust and how can you trust someone who you dont even know to be real.
We have at least an awser or a way to awser someone should they ever ask.
By working with us you will be able to show your cosomers your a real person. somethings that value is hard to understand untill its gone.
DeepFake Fraud is a real and growing problem. There have been multiple instances where individuals have used deepfakes to steal anywhere from $100,000 to millions of dollars. These incidents have been publicly reported numerous times and have occurred more frequently than one might think.
For financial institutions, safeguarding against this type of fraud is absolutely critical. We offer an additional layer of security that can assist you in this endeavor.
Furthermore, it’s possible for individuals to falsely claim to be victims of deepfakes, even when they were actually involved in legitimate conversations. We can also assist in preventing such false claims. While this may not be a current concern, it’s always better to be prepared than unprepared.
There are various approaches to combatting deepfakes, and many people propose the use of deepfake detectors, which certainly serve a valuable purpose.
However, due to the way deepfakes are constructed using adversarial neural networks, as deepfake detectors improve, deepfakes themselves also become more sophisticated. We believe that eventually, deepfakes may outpace the effectiveness of detectors.
Instead, we advocate for a proactive approach that focuses on directly addressing the image itself, thereby presenting the computer with a problem that is extremely challenging to solve. We primarily employ techniques involving moving lenses, which can significantly enhance the detection of deepfakes. When combined with encryption protocols, this approach can make it exceptionally difficult to commit deepfake fraud, provided that the protocols are followed.”
Bellow you see examples of our product the handheld vertion as well as the headset and screen. The screen being the lowest and the headset being the highest level of security. Along with a graphic going over how the technoligy works;
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