Take a moment to unsee the Fake; The outcome of Deepfake technology

You are seeing yourself on internet and doing/saying things that you haven’t done? Seen a politician Making some statements on the television and later the leader announces that it wasn’t him? I am not talking about some comic or mimic videos. It’s Realistic content that is created with the help of AI and Machine Learning technology. The ‘Deepfakes’ which become a hot topic on the internet worldwide.

What is Deepfake Technology?

The term “deepfake” is formed by merging “fake” with “deep learning.” It relies on deep learning technology with the help of extensive datasets, to replace faces in videos, images, and various Digital content, creating deceptively realistic forgeries. The Generative Adversarial Network (GAN), a type of network, is used to attain the realistic media content of a person Generally saying deepfake videos are fake videos that generated with the Help of Artificial Intelligence and deep learning technology. To produce realistic videos of a person which is hard to spot its fake one.

How deepfake gaining attention?

Deepfake was spotted around 2017 on reddit with some face swapping video. Which is clearly for Entertainment purpose. The tables have turned now it’s not just mere entertainment, deepfake shook the world with a video of Russian President Vladimir Putin announcing a full fledged war on a video, which was an AI generated video. The same happens for film actors spreading inappropriate videos on internet which is absolute fake but looks authentically convincing.

How deepfake AI works?

It relies on deep learning technology with the help of extensive datasets, to replace faces in videos, images, and various Digital content, creating deceptively realistic forgeries. The Generative Adversarial Network (GAN), a type of network, is used to attain the realistic media content of a person.

Role of Generative adversarial network (GAN)

A generative adversarial network (GAN) is a machine learning (ML) model in which two neural networks compete each other by using deep learning methods to become more accurate in their predictions. We can take the two neural networks as Generator and Discriminator. We train them with the set of real images and a set of fake images we have a set of real images and a set of fake images by the generator. discriminators try to point out the fake images whenever generator generates a new image. and the generator keeps on improving the images with the backs getting from the discriminator. until the discriminator couldn’t distinguish the fake image. The more we train with the datasets more difficult it becomes to spot fake.


The generator’s function is to create fake data that is so convincing that it successfully deceives the discriminator into perceiving it as genuine or real. by keep on submitting the improved fake datasets. It’s carried out by constantly checking the feedback from the Discriminator and understand the spots to improve the generated the images until it reaches a certain point where the discriminator couldn’t spot a difference between the original one and the generated image set from the generator which is a success.


The data used for training the discriminator originates from two distinct origins:

1. Genuine data instances, like actual images of individuals, serve as positive examples employed by the discriminator during its training phase.

2. Artificial data instances generated by the generator serve as negative examples utilized by the discriminator for training purposes.

The generator’s job is to distinguish between real and generated data sets and return the feedback the Generator when spots a difference between them.

Can Deepfake be detected?

Here comes the interesting scene. You made some technology that almost impossible to spot the original and fake, and you seek help from the technology to spot the same, The power of AI and ability of generative adversarial network (GAN) to create something new based on data sets, makes

the result hard to distinguish with the real one. But still some most common approach to find the fake one’s are below

1. Observe the frequency of blinking. Is the individual blinking adequately or excessively?

2. Watch how the lip movements as some deepfakes are based on lip syncing. Do the lip movements look natural?

3. Unrealistic facial hair and skin smoothness

4. Pay attention to facial moles. Does the mole look real?

Even these techniques might not be efficient to spot the deepfakes. Thats how the technology helped deepfakes.

Applications of deep fake technology

We should be thankful to Artificial intelligence and Machine Learning Technology as its made our Life easier. The deepfake also can be used in several areas such as

Entertainment: where the actors face can be manipulated as the scene requires, the aging can be compromised with the technology

Education: Certainly deepfake videos can be easily used on making realistic videos of scientific experiments, historical scenes with efficient information

Innovations: Have you seen some one reading a news on television who is not a real person, yes that’s how the deepfake can bring innovative ideas.

Major Concerns on Deepfake Technology

1. Law and enforcement: Deepfake videos made people question the media evidence that low possess, criminal activities and harassment cases are faked with the help of deepfake videos

2. Attack on reputation: As the internet spread the videos in quick. its easier to spread deepfake damage famous individuals’ reputation on purpose

3. Manipulation: People with fake videos of political leaders Could be triggered easily as the politics is a hot topic and maybe people won’t look for time to check the genuineness of a fake video. Which can get the government in trouble.


Deepfakes are next level innovations which blurring the lines between fake and real. We are not yet ready to see how far AI can go with its capabilities. Deepfake technology is recreating the original, certainly, a time saving innovation in many ways. We can see the impacts on the misuse of the technology but still we are running in a fast progressive track. We couldn’t deny any of the innovation as it is having some drawbacks. But the hopes are high when some technology holds Hands with Artificial intelligence and machine learning. Let’s the deepfake era bring magics to life. We Nuventure Connect Private Limited a top-iot development company entered the realm of IoT integrating AI possibilities delivering innovative IoT remote monitoring solutions in future.

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