Nikon and Sony are solving the Deepfake Problem Using Digital Signatures

In December last year, Vladimir Putin, the current president of Russia spoke at the Annual Press Conference in Moscow. Towards the end of the event, he took questions via video calls from people nationwide.

As he finished answering one of the questions and moved on to the next question, he was greeted by someone special.

Himself.

Sitting in a chair across from Vladimir Putin was Vladimir Putin.

The AI-double then proceeded to ask his question, “Hello, my name is Vladimir Vladimirovich. I am a student at St. Petersburg State University. I want to ask, is it true you have a lot of doubles?”

Almost a year ago, Joe Rogan, one of the most popular podcasters in the world, was seen selling a men’s health supplement on TikTok. He and Dr. Andrew Huberman were seen promoting this random supplement together.

It turns out the video was mostly original, but Joe’s voice was analyzed, deepfaked, and superimposed on the original video to make it look like he was promoting the supplement.

These were just some of the mild examples of deepfakes on the internet. The rabbit hole goes deeper. From fake war announcements to artificial hate speech to explicit content—deepfakes are a much bigger problem.

Let’s dive deeper.

What is a deepfake?

A deepfake is a sophisticated form of artificial intelligence-driven manipulation, specifically involving creating or altering audio-visual content to present a fabricated or manipulated reality.

This technique employs deep learning algorithms, often utilizing neural networks, to seamlessly blend or replace elements within existing media, such as swapping faces in videos or altering voices with unnerving accuracy.

While initially developed for entertainment purposes, deepfakes have raised significant concerns due to their potential for misuse, ranging from spreading misinformation and malicious propaganda to creating convincing forgeries with serious consequences.

How do deepfakes work?

Let us first understand deep learning and neural networks using a simple example.

Alright, imagine you have a super-intelligent robot friend. Now, this friend is learning to recognize different things, like showing the difference between cats and dogs in pictures. Deep learning is like how your friend gets better at this over time.

Now, think of a neural network as your robot friend's brain. It comprises many tiny parts called neurons, just like our brains. Each neuron helps the robot understand a small amount of what it's seeing, like the shape of an ear or the color of fur on an animal.

Deep learning is like teaching your robot friend by showing it many, many pictures of cats and dogs. Each time it makes a mistake, it learns a bit more about what makes a cat a cat and a dog a dog. The more pictures it sees, the smarter it becomes at telling them apart.

So, deep learning is like your robot friend learning from lots of examples to become really good at recognizing things, and a neural network is the brain that helps it do this. Just like you learn from seeing and doing things, the robot learns from lots of pictures and keeps getting better at figuring out what's what.

Now, imagine your smart robot friend has become even more advanced and can not only recognize things but also create new things that look incredibly real—this is where deepfakes come in.

Deepfakes use a special kind of artificial intelligence called deep learning, similar to what your robot friend uses. Instead of just identifying things, deepfakes go a step further by mimicking and generating new content. They use something called neural networks, which are like layers of filters that analyze and understand information.

For example, in a deepfake video, the neural network analyzes a person's face in different images and videos, learning all the details—like how their eyebrows move, their expressions, and how their lips sync when they talk. Once the neural network has learned these patterns, it can generate a new video of that person saying or doing things they've never actually done.

Think of it as your robot friend being so good at understanding faces and voices that it can create a video that looks and sounds exactly like someone else, even though that person never did or said those things. It's like a super advanced form of digital impersonation.

This technology has both creative and concerning applications. While it can be used for fun and entertainment, like putting a friend's face on a movie character, it also raises serious issues about misinformation and the potential misuse of realistic-looking fake content.

Deepfake applications: How it was meant to be

Deepfakes offer a game-changing tool for the entertainment industry. In 2013, the movie Fast and Furious 7 was in the middle of filming when Paul Walker, a prominent actor in the movie franchise, died in a car crash. In such unfortunate events, instead of changing the remaining part of the movie script, filming can continue based on the original script. The face of the original actor can be superimposed on a body double to shoot the rest of the film.

Dangerous and life-threatening stunt scenes can also be shot without physically risking anyone’s life.

Deepfake technology can be harnessed to create realistic language tutorials. Learners can practice with videos of native speakers, improving pronunciation and cultural nuances. This immersive experience can significantly improve language learning and cross-cultural understanding.

Deepfakes can bring history to life by generating realistic depictions of historical figures delivering speeches or engaging in pivotal events. This visual aid can make history more engaging for students, providing a vivid understanding of key moments in time.

Deepfakes allow for highly personalized and targeted advertising. Brands could create ads featuring familiar faces tailored to specific demographics, making their campaigns more relatable and impactful.

Salespeople could use tools like Potion to send personalized video messages to thousands of prospective clients without opening the camera app on their phones.

Deepfake technology can be utilized to make media more inclusive. For example, dubbing classic movies or TV shows into various languages with the original actors' faces and expressions intact can improve accessibility for global audiences.

With limited audio recordings, deepfake technology can recreate the voices of historical figures or loved ones who have passed away. This could allow future generations to hear the words and wisdom of influential individuals.

Multiple reports by reputed forecasters estimate that the gaming and virtual reality market is expected to cross 1.1 trillion dollars (US) in size before the start of the next decade.

Deepfakes will be a big part of it.

Deepfakes could enhance the gaming experience by creating more realistic and personalized avatars. Gamers could see their faces mapped onto in-game characters, leading to a more immersive and customized virtual reality experience.

Famous people like actors could also be a part of the gaming industry. Cyberpunk 2077, a video game released in 2020, stars actor Keanu Reeves in the cut scenes and is available as a playable character.

Restore old or damaged film footage by using deepfake technology to reconstruct missing scenes or enhance the overall visual quality. This can contribute to the preservation of cinematic history.

In cases of loved ones, apps like MyHeritage go one step further. Their deepfake technology can accurately animate deceased people from old photos—literally bringing them back to life.

The biggest hurdle today, when it comes to special effects, is time. It takes a lot of time to build special effects scenes. It’s a careful balancing act between filming using greenscreens and computer-generated graphics.

Film and television productions, in the future, can leverage deepfakes to create mind-blowing special effects in just a matter of hours or just a few days.

This could streamline the process of bringing fantastical creatures or futuristic elements to the screen with unprecedented realism.

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