Name: Hunting for deepfakes
Uploaded: 2023-12-08T14:36:36.896Z
Duration: 2 min 16 s
Description: Deepfakes are becoming better and easier to make thanks to better tools and more computing power. But deepfake hunters are also upgrading. A race for the truth has begun.

Deepfakes are becoming better and easier to make thanks to better tools and more computing power. But deepfake hunters are also upgrading. A race for the truth has begun.

Munich

The release of Open AI's ChatGPT has accelerated the development of artificial intelligence and warnings about its impact on society.

Rise of AI

Hunting for deepfakes

Nikolas Müller warns that deepfakes are getting increasingly easy to create. He's a cyber security expert in Munich and has been looking into different models. So you would look up a politician, for example, which you want to clone. And then you find a video where he is giving a speech. Maybe this video is 30 minutes long. But every second of the video has 20 to 30 frames. So just by taking this single video, you maybe have 10,000 images of the politician. And then you can feed this into the autoencoder, which learns to disentangle the image and then you can manipulate it. An autoencoder is a type of neural network used for making deepfakes. In essence, it works a lot like a good pizza chef. They first learn the ingredients of every pizza on the menu and what it should taste and look like. And then, before long, they can combine those ingredients differently to make entirely new pizzas. The outcomes of deepfake tools that use such AI can be incredibly realistic, as demonstrated here. I am not Morgan Freeman. And what you see is not real. So the tools are much more ready in a way. They are much easier to use. The data that we have in order to train these deepfake generating models has matured a lot. Compute has become much more affordable. And also people have just looked at the technology and seen its value and invested in it heavily. So we just have more compute at our fingertips now than a few years back. Müller helped design a tool that can identify some deepfakes. It works best when the voice in a clip is generated with AI. When someone creates a video with a good human voice actor, for example, the fakes are harder to detect. And so are the newest fakes. Okay, so these deepfake detection models struggle whenever the fakes are newer than the models themselves. So we have to continuously update them. And also it's just very hard to get access to all the fakes and all the good audio out there. While these deepfakes are harder to spot, they are also harder to create. Even so, as deepfake tools get more sophisticated and accessible, the people routing them out will have to adapt too.

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Rise of AI