What are Deepfakes?
Deepfakes are computer-generated images that are so realistic that they fool people into thinking they’re real. They are used to create fake recordings of real people talking, which has a much more sinister application.
Deepfakes are becoming increasingly popular on social media and other platforms like YouTube and Instagram. The technology is relatively easy to use, making people better at it every day.
A new feature on Snapchat, known as Cameo, lets you deepfake yourself into a video or GIF. Snapchat users in France who got a test version of the app in 2019 were the first to notice the functionality.
Deepfakes are created using AI algorithms and advanced computer graphics techniques that combine photos, videos, audio recordings, and other data to create a realistic image or video. The software uses machine learning to find patterns in existing images or videos to make them seem more real than they are.
Top 3 Use Cases of Deepfake Videos and Images
Here are the three most common ways businesses can use deepfakes for better productivity and more benefits.
Boost Content Creation Productivity
Deepfakes help businesses in creating better and more engaging content within less time. It allows small businesses to expand their marketing and advertising reach. Small companies and startups with meager marketing budgets can produce equivalent content to their more established rivals.
Theoretically, small businesses can quickly, consistently, and affordably reach customers abroad by using deepfake content.
Helps Teachers Deliver more impactful lessons
Deepfake technology opens up a wide range of opportunities in the field of teaching. For a long time, schools and instructors have used audio, video, and other forms of media in the classroom. An instructor may use deepfakes to give compelling lessons that go beyond the scope of conventional visual and media formats.
Artificial intelligence-generated synthetic media can revive historical figures to create a more engaging and interactive classroom. A voice-over and video of a historical figure or a synthetic video of reenactments may have a more significant impact, engagement, and effectiveness as a teaching tool.
Converts your text into engaging videos
DeepFakes uses AI to convert your text into engaging videos. It can be used by anyone who wants to make the best out of their videos. Many people worldwide have used this technique because it is easy to use and provides excellent results.
The best thing about this technology is that it helps you to get more exposure for your business or business idea. If you have an exciting video, this technology can help you get more exposure for your business or business idea on social media platforms such as YouTube, Facebook, and Twitter.
The Biggest Disadvantage of Deepfakes
The effect that deepfakes and incorrect information, in general, may have on democratic procedures and elections is one of the most prominent worries and possible hazards.
People retain false information more often than accurate information, according to a recent UCC poll. According to the survey, people may create false memories after seeing made-up news items, mainly if such tales support their political convictions. The researchers contend that the results show how voters may be swayed in forthcoming elections, such as the fight for the 2020 US presidency.
How to Distinguish Between Deepfakes and Authentic Content?
Amit Roy Chowdhury’s video computing group (A group of computing enthusiasts at UCR) has created a brand-new technique that is more accurate than state-of-the-art techniques for spotting altered facial expressions in deepfake movies.
The technique uses a deep neural network to split the problem into two halves. The first branch recognizes facial expressions and provides data to a second branch, called an encoder-decoder, regarding the areas of the face that contain the expression, such as the lips, eyes, or forehead. The architecture of the encoder-decoder is in charge of localizing and detecting tampering.
The Expression Manipulation Detection (EMD) framework can identify and pinpoint the precise areas of a picture that have been manipulated.
Studies on two challenging face modification datasets reveal that EMD performs better detecting identity swaps and altered facial expressions. EMD correctly identified 99 percent of the altered videos.
University of California, Riverside Researchers Detect Manipulated Facial Expressions
he video computing group led by Prof. Amit Roy-Chowdhury has recently developed a new method that can detect manipulated facial expressions in deepfake videos with higher accuracy than current state-of-the-art methods.University of Riverside, California
Concluding the Thoughts
Deepfakes are computer-generated visuals so convincingly lifelike that viewers believe they are the actual thing. Additionally, they may be used to make false recordings of actual conversations, which has a far more evil purpose. Since technology is simple, individuals become better at using it daily.