Marquis’ solution has been used to authenticate more than 10,000 offender identities, according to a company announcement, a use case demanding multi-factor authentication for maximum security
Kramer used several hundred photographs of people wearing zombie makeup and masks so that the neural network could create realistic images of the living dead
The idea is that fans of the brand will be able to “try on” clothes or accessories using avatars, AR and VR technologies, and then buy the product for real. In addition, marketers will have the opportunity to study user preferences and find out which products are most attractive to young audiences
Systems designed to detect deepfakes – videos that manipulate real-life footage using artificial intelligence – can be tricked
With the new feature, if experts are unsure of the accuracy or cannot confirm the accuracy of the data, TikTok will flag such videos as containing “unverified content”
A way to combat fakes for Clubhouse could be to tag the verified account and enable application-level identification that protects against voice forgery using voice biometrics technologies. To obtain such a label, the social network can oblige the user to leave a “voice cast”, and at the level of the application itself create voice biometrics
A white paper published by cybersecurity firm Nisos, sketches five incidents involving deepfake audio attacks
There is also a positive side to the difficulty in recognizing masked people. The problem faced by authentication services is to be solved by facial recognition software
Of course, we sent out a link to Product Hunt to everyone we know. I asked the guys on Mesto social network and Silicon Pravda Telegram chat to support us. But most of the voices came from strangers, which was very encouraging
Editing individual elements in a video requires frame-by-frame changes. This is usually done manually, like in animation, or using special tools that have limited functionality and can only perform certain programmed actions. A development team at Google and Oxford University was able to split each video frame into separate layers and taught AI to recognize people or other moving objects in them