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An introduction to Deepfakes

Swapping reality with realism.

Humans have developed technologies not merely to guide machines which can enhance lifestyle. We have raced extra miles to teach these machines how to imitate a human brain and consequently, how to make decisions on their own. But what’s the movie behind it? Is it just the yearning for perfection? Or is it motivated to infuse our normal world with the unseen and unimagined comfort?

With the advent of AI and ML, these questions have come to the limelight. And their answers are still vague and multiple in numbers. One such answer is AI-powered Deepfakes or face-swap technology.

Though being in a fledgling phase, this industry has drawn a lot of attention even with the pros and cons still not thoroughly defined. Then what is the fuss about? Let’s find out.

Take a sneak peek

Deepfakes is nothing but swapping your face in an image or a video with someone else’s. The word was tossed by Reddit which amalgamates two different terms Deep Learning and Fake.

The soul of deepfakes is deep neural networks(DNN), a subdivision of AI. With the help of DNN, not just an image or video is manipulated but even voice and expressions can be mimicked. And that makes these face swaps more photorealistic, contrary to the phrase “fake” in deepfakes.

Curious about the mechanism?

Reinventing yourself with someone else’s face may seem like a business of one-click to us. But it is more complex to make machines learn.

The process of creating swap videos or images feeds upon large training sets and statistics, and then new sets of data are generated. It models non-linear relationships with the help of neural networks. These networks are taught to observe and behave similarly to how our brains do.

To simply put, this transformation includes 3 primary steps.

– Extraction

Thousands of videos or pictures are provided to algorithms and every frame is extracted and faces are aligned.

– Training

After extracting frames, Neural Network restructures the two faces using multiple hidden layers. In this process, it learns the important details and removes the noise using an autoencoder. That makes the output more precise.

– Creation

The last phase merges the converted or recreated faces into original frames. It may appear a simple step but it has a great probability to ruin the details while affixing faces back.

To summarize in crisp, Deepfake technology bring futuristic technologies like AI, ML, Deep Learning on the same board to polish its results.

Impression and impact on the present

The world is still skeptical about the positive outcomes driven by deepfakes. And why shouldn’t they be concerned? Distorting political speeches or facts, or creating malicious adult content has become a matter of seconds. And it has attracted many negative opinions about the deepfake videos.

But are we focusing only on one dimension? What lays on the other surface? Unequivocally, the other surface has more affirmative paths for the entertainment industry.

Our mobile devices are not just being flooded with face swap apps, but they are enabling us to recreate stories and reimagine ourselves with a celebrated persona. It lets you try and live something which you might not have even hoped for otherwise.

Deepfakes soon will overtake the traditional video editing techniques, eliminating the uncanny subjects. It’s not a supernatural thing to dub a whole movie into a different language. The neural networks can be trained to match facial movements and to integrate with voice-over without losing the original look and feel of dialogue delivery and emotions.

Though these examples are limited at this moment, deepfakes are going to become more sophisticated within a few years and are going to create whole new opportunities.

A future awaiting change

The face swap trends can still be considered neophytes with limited research being done in this sphere. But slowly and steadily, new techniques are being invented to create deepfakes, giving them a more natural and real touch.

What the future holds is unknown, but the efforts of humankind to collaborate with technologies like AI is an open book. And the results will always be favorable to us if utilized wisely.