Cybersecurity

Semantic and Perceptual Captions

Yesterday, Deepseek released the “Janus-Pro”, which is a multimodal embedding and text-to-image generation model. The abstract reminded me of a talk I gave in 2016, where I mentioned that “data, compute and algorithm” are the three driving forces of AI. This was a common understanding at that time. The tech report starts with “In this work, we introduce Janus-Pro, an advanced version of the previous work Janus. Specifically, Janus-Pro incorporates, (1) an optimised training strategy, (2) expanded training data, and (3) scaling to larger model size”.
The three driving forces still remain unbeaten and play crucial roles in AI advancement.

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The Anatomy of Deepfake Fraud: Technology and Countermeasures

In 2017, a video of the actress Gal Gadot appeared on social media wherein the lady was engaged in explicit scenes. An anonymous Reddit user named “deepfakes” claimed to be the creator of that video in which the face of Gal Gadot was superimposed on pornographic content. The origin of deepfakes can be traced back to this identity fraud, where deepfake porn impersonates a real individual. Curiously, Reddit users’ actions in revealing deepfakes proved that the real threat of deepfake videos comes not from technology but from people’s natural inclination to believe what they see.

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Must-have features for deepfake detection in 2024: What should the enterprise look for?

As per Ofcom research, a survey in the UK revealed that Two in Five people have seen at least one deepfake in the last six months – including depictions of sexual content, politicians, and scam adverts. Only one in ten are confident in their ability to spot them. Deepfake detection tools are the only solution to tackle this situation. Let’s have a look at the must-have features in deepfake detection tools of 2024.

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