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Intel Unveils The First Ever Real-Time DeepFake Detector



Intel Unveils The First Ever Real-Time DeepFake Detector

(CTN News) – Intel claims it has developed the world’s first real-time deep fake detector, which it claims is the first of its kind in the world today.

Using innovative photolith osmograph (PPG) technology, Fake Catcher is said to have a 96% accuracy rate when analyzing blood flow within video pixels, which comes with a 96% accuracy rate.

The Fake Catcher detector was developed by Demir, a senior staff researcher at Intel Labs. It was also developed by, an assistant professor at the State University of New York at Binghamton, in collaboration with.

As a real-time detector, it is made up of Intel hardware and software, and it runs on a server and can be accessed through a web-based platform that is connected to the Internet.

It is worth mentioning that the Fake Catcher differs from most deep learning-based detectors in the sense that it examines real videos instead of merely analyzing raw data to determine whether there is any indication of inauthenticity.

PPG is the method used by Intel company to measure the amount of light absorbed or reflected by blood vessels in living tissues.

This is depends on how much light is absorbed or reflected by them. As your heart pumps blood, your veins change These signals are picked up by technology that can be used to determine whether a video is real or fake based on the color changes of your veins.

The PPG signals used in Fake Catcher have never been applied to the deep fake problem before, according to Demir, who spoke to VentureBeat.

With the detector, these signals are collected from 32 locations on the face. These signals are then processed into spatiotemporal maps before a decision is made as to whether the video is genuine or not.

Across the globe, fake videos are becoming more and more prevalent. Approximately $188 billion is predicted to be spent by companies on cybersecurity solutions in order to counteract this threat, according to Gartner. As of today, detection apps typically require users to upload videos for analysis, and the process of analyzing those videos can take hours.

The Wall Street Journal reported that the detector could be used by Intel social media platforms to prevent users from uploading harmful deep fakes. In addition, news organizations can use it to avoid publishing videos that have been manipulated.

In recent years, Intel deep fakes have targeted prominent political figures as well as celebrities. There was modified TikTok that is a modified last month. In this altered TikTok, the national anthem was replaced by the children’s song Baby Shark instead of Joe Biden singing the child’s song.

As part of efforts to detect deep fakes, racial bias in the datasets that were used to train the algorithms has also been found to be a problem in detecting them.

The University of Southern California, in a study conducted in 2021, found that some detectors showed as much as a 10.7% difference in error rates based on the racial group they were observing.


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