‘Cheap Fake’ Videos Getting Nabbed Via Generative AI

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‘Cheap Fake’ Videos Getting Nabbed Via Generative AI
Large Language Models LLMGenerative AICheap Fakes
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Dr. Lance B. Eliot is a world-renowned expert on Artificial Intelligence (AI) with over 7.4+ million amassed views of his AI columns. As a CIO/CTO seasoned executive and high-tech entrepreneur, he combines practical industry experience with deep academic research.

Cheap fakes are in the news and on our minds, so let's take a look at how generative AI might helpIn today’s column, I’ll explain what cheap fakes are, including how they contrast to deepfakes, and share with you some of the ways that generative AI and large language models are aiming to help deal with the rapidly expanding scourge of cheap fakes .

That being said, cheap fakes are a bit more sophisticated these days because we have better editing software. You can edit just about any medium such as a photo, an image, a video clip, an entire video, an audio stream, etc. The process at times is laborious. You might have to go frame-by-frame in a video to make the changes you want to have shown. There is a skill level of a sort that is needed to suitably make use of the features in such editing packages.

In that way of thinking, the catchphrase about cheap fakes will technically have a very short shelf life. Notice that I said it will technically have a brief run. I’m sure that people will continue to use the cheap fake moniker despite the lack of technical aptness. The allure of referring to something as a cheap fake is abundantly strong. It won’t matter to some that they have lost the meaning of the catchphrase.

The phrase of something being a cheap fake is a wake-up call. Few realize that cheap fakes as a moniker have been around for several years. Many think the cheap fake notion was just invented or discovered in the last few weeks. It seems utterly new to them.Around 2018 and 2019, the idea of referring to a faked photo or video was starting to stand out. Few editing software packages had much if any AI built in. You had to go to a separate AI component or package to do AI-related work.

They could also be wrong if it turns out that the video is completely unaltered and not touched up beyond whatever the original video consisted of. In other words, if the notion of a fake is that it is dependent upon a true original, you could presumably merely get a true copy of the original, compare it to the claimed-to-be cheap fake, and see if they match.

A cheap fake video might be an edited version of an original video. Someone let’s say uploaded an original video, changed the video to make a person in the video look like they are frozen rather than in motion, and then released the newly edited video into the public sphere. In this instance, two videos are floating around. There is the original unedited video, and we now have an edited version that could be construed as a cheap fake.of the video.

Legitimate claim that something is a deepfake rather than a cheap fake . False claim that something is a deepfake when it is a cheap fake. At first, the labor and skills required to make cheap fakes were something that kept the abundance of cheap fakes partially in check. Meanwhile, the deepfakes made use of AI, and assuming you could afford the cost of using AI, the ease of producing deepfakes in volume was like falling off a log. Automation came to your aid.

I’d suggest that when it comes to detecting cheap fakes, there is a long road yet to go and that along the way we need to keep our wits about us and not let the emergence of AI-based tools that claim to be “surefire cheap fake” detectors do a snow job on society.In the AI field, there is an ongoing grand challenge associated with finding ways to devise AI that will detect cheap fakes.

“While ‘deepfakes’ refer to videos that have been doctored using machine learning or other AI-based methods to create or combine human faces and bodies, ‘cheap fakes’ are a far less costly variant of doctored videos generated through readily available software tools such as Photoshop, Premiere Pro, among others.”

“Visual evidence is not only interpreted in formal courtroom settings. Within journalism, visual evidence plays a key role in the construction of public opinion and the arrangement of political power.”The issue of cheap fakes and deepfakes is a huge one when it comes to trials and our justice system, see my coverage at.

For example, we could opt to alter the format of a video and have a different video on a purely bitwise basis. A human who watches the video might not see any visually discernable difference between the original and the alleged cheap fake. Is the alleged cheap fake an actual cheap fake or can we overlook the fact that the format differs?

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