A Brief Intro…
Deepfake is a technology used for producing or changing video contents so that the video presents stuff that didn’t occur. The term deep fake was first coined in 2017 by a Reddit user named “deep fake”. Deepfake is a combination of “deep learning” and ”fake “. It is a technique that is used for synthesizing human images using the technology of artificial intelligence.
Deepfake video is created by using two competing AI systems — one is called the generator and the other is called the discriminator. Virtually, the generator creates a fake video clip and then asks the discriminator to deduce whether the clip is real or fake. The generator and discriminator together form the generative adversarial network called the GAN, modern and unique machine learning technique.
Deepfake works by incorporating and superimposing existing images and videos onto source images or videos using the GAN Network.
The GAN network is established by identifying the desired output and creating a training dataset for the generator. Once the generator starts producing enough output, videos are fed to the discriminator.
This technique generates new data while using the same statistics as the training set.
Uses of deepfake
- Celebrity pornographic videos
- Revenge porn
- Fake news
- Malicious hoaxes
Typically the use of deepfakes has been negative. Fake news is of course a large concern, but also a lot of adult content utilizing name and/or likeness has been created. Imagine top mainstream media faces and names being passed off as skip the games escorts or other types of sex workers.
So far deepfakes have been developed largely in two major fields:
- Academic research: academic projects have focused on creating more realistic videos and on making techniques simpler, faster, etc. The “Synthesizing Obama” program, disseminated in 2017, modifies video footage of former President Barack Obama to illustrate him grimacing the words contained in a separate audio track. The earliest landmark project was the Video Rewrite program, published in 1997, which modified existing video footage of a person speaking to depict that person mouthing the words contained in a separate audio track.
- Amateur development: in 2017 Reddit community users created many deepfakes that revolved around celebrities’ faces swapped on the bodies of porn actors. As time passed, the Reddit users made many big fixes in those created deepfake videos which then increased the problem as it became more difficult to distinguish between the original and the fake videos.
Deepfakes have been used to misinterpret the speeches of famous politicians on video portals and chat rooms.
In 2018 an app similar to the deep fake was launched, by the name of FakeApp, which helps users to conveniently swap faces and share fake videos. This app uses the GPU network and at least 3 to 4 GB of storage space for its purpose. The main victims of this app are celebrities, but they can also include common people.
- The manipulation of images and videos using artificial intelligence has become a dangerous mass phenomenon, the motivation behind deepfake pornography is to insult and control women.
- Today it takes no time to corrupt things with new technology. The problem with deepfakes is that it’s hard to tell the difference between truth and deception, and which video content is authentic.
- Many websites promised to delete and block deep fake videos, for example, twitter and gfycat.
As the generator gets better at creating fake video clips, the discriminator gets better at spotting them. Conversely, as the discriminator gets better at spotting fake video, the generator gets better at creating them.
Up until today, video content has been more difficult to alter in any significant way. Deepfakes are created through AI, however, they don’t compel the substantial skill that it would take to create a practical video otherwise. Unfortunately, this means that just about anyone can create a deepfake to facilitate their selected strategy. One threat is that people will take such videos at face value; and that people will stop believing in the certainty of any video content at all.
It’s been feasible to alter video footage for decades, but doing it took time, highly qualified artists, and a lot of wealth. Deepfake technology can change the game. As it formulates and develops, anyone could have the capacity to make a persuading fake video, including some people who might seek to “weaponize” it for political or other violent purposes.
Deep fake makes it just as easy to create a fake video of an imminent emergency alert warning attack, or destroy someone’s marriage with a fake sex video, or disrupt a close election by dropping a fake video or audio recording of one of the nominees days before electing starts.