George  Koelpin

George Koelpin

1599563880

What are deepfakes?

This article is part of Demystifying AI, a series of posts that (try to) disambiguate the jargon and myths surrounding AI.

In 2018, a big fan of Nicholas Cage showed us what _The Fellowship of the Ring _would look like if Cage starred as Frodo, Aragorn, Gimly, and Legolas. The technology he used was deepfake, a type of application that uses artificial intelligence algorithms to manipulate videos.

Deepfakes are mostly known for their capability to swap the faces of actors from one video to another. They first appeared in 2018 and quickly rose to fame after they were used to modify adult videos to feature the faces of Hollywood actors and politicians.

In the past couple of years, deepfakes have caused much concern about the rise of a new wave of AI-doctored videos that can spread fake news and enable forgers and scammers.

The “deep” in deepfake comes from the use of deep learning, the branch of AI that has become very popular in the past decade. Deep learning algorithms roughly mimic the experience-based learning capabilities of humans and animals. If you train them on enough examples of a task, they will be able to replicate it under specific conditions.

The basic idea is to train a set of artificial neural networks, the main component of deep learning algorithms, on multiple examples of the actor and target faces. With enough training, the neural networks will be able to create numerical representations of the features of each face. Then all you need to do is rewire the neural networks to map the face of the actor on to the target.

#artificial intelligence #deep learning #deepfakes #neural networks

What is GEEK

Buddha Community

What are deepfakes?
Edmond  Herzog

Edmond Herzog

1596478860

A Look at Deepfakes in 2020

Deepfakes are synthetic media, usually videos, created with deep learning technology. By manipulating images, videos, and voices of real people, a deepfake can portray someone doing things they never did, or saying things they never said.

By feeding a machine learning model thousands of target images, a deepfake algorithm can learn the details of a person’s face. With enough training data, the algorithm can then predict what that person’s face would look like when mimicking the expressions of someone else. A similar process is used for training deepfake algorithms to mimic the accent, intonation, and tone of a person’s voice.

The Public Response to Deepfakes

The start of 2020 came with an interesting shift in response to deepfake technology, when Facebook announced a ban on manipulated videos and images on their platforms. Facebook said it would remove AI-edited content that was likely to mislead people, but added that the ban doesn’t include parody or satire. Lawmakers, however, are skeptical as to whether the ban goes far enough to address the root problem: the ongoing spread of disinformation.

The speed and ease with which a deepfake can be made and deployed, as shown in this article by Ars Technica, have many worried about misuse in the near future, especially with an election on the horizon for the U.S. Many in America, including military leaders, have also weighed in with worries about the speed and ease with which the tech can be used. These concerns are heightened by the knowledge that deepfake technology is improving and becoming more accessible.

#deepfake-technology #ai #deepfakes #machine-learning #synthetic-media

Jerad  Bailey

Jerad Bailey

1596478020

Deepfake detection is super hard!

Recent advancements in artificial intelligence (AI) and cloud computing technologies have led to rapid development in the sophistication of audio, video, and image manipulation techniques. This synthetic media content is commonly referred to as “deepfakes[1].” AI based tools can manipulate media in increasingly believable ways, for example by creating a copy of a public person’s voice or superimposing one person’s face on another person’s body.

Legislation, policy, media literacy, and technology must work in tandem for an effective remedy for malicious use of deepfakes.

Technical countermeasures used to mitigate the impact of deepfakes fall into three categories: media authentication, media provenance, and deepfake detection.

Media Authentication includes solutions that help prove integrity across the media lifecycle by using watermarking, media verification markers, signatures, and chain-of-custody logging. Authentication is the most effective way to prevent the deceptive manipulation of trusted media because it verifies and tracks integrity throughout the content lifecycle or verify it at the distribution endpoint.

#ai #fb #deepfake-technology #dfdc #deepfakes

Gussie  Hansen

Gussie Hansen

1617444000

Can Deep Nostalgia Turn Into Another Deepfake Fiasco?

Deep Nostalgia has created a lot of buzz in the industry, where people are using the AI-based app to animate their old family pictures into a short fake video. If you thought Deepfake videos could pose dangerous implications, wait until you see what its purported sister ‘Deep Nostalgia’ can do.

Deepfake, deep learning, and now Deep Nostalgia are all the brainchildren of the deep tech class of organisations that use emerging technologies like artificial intelligence, robotics, blockchain, etc., to innovate and come up with innovations

#ai and deep learning #deep fake #deep learning techniques #deepfake trend #deepfakes #myheritage #myheritage deep nostalgia

Anil  Sakhiya

Anil Sakhiya

1595601314

What Is Deepfake | Introduction To Deepfake Technology

This ‘What Is Deepfake?’ video will give you a crisp introduction to Deepfake Technology. You should not believe everything you see, because advancements in software have made it easy to create Deepfake videos, and in this video, we will be explaining some of the questions that you may have like, what is Deepfake, how they are created, and how we can use them in real-life instances in just 5 minutes.

Advances in machine learning and Artificial Intelligence have now made it possible for anyone to swap someone else’s face and voice into a video and make it look like they did or said something anything you want. These videos and photos are called Deep fakes, and due to advancements in technology, they are getting more and more sophisticated by the day. The technology harnesses machine-learning techniques – feeding a computer real data about images so it can create the fake.

The main ingredient in deepfakes is machine learning, which has made it possible to produce deepfakes much faster at a lower cost, and this video will explain everything you need to know about deepfake along with the visuals for better understanding.

#machine-learning #artificial-intelligence #deepfake #developer

George  Koelpin

George Koelpin

1599563880

What are deepfakes?

This article is part of Demystifying AI, a series of posts that (try to) disambiguate the jargon and myths surrounding AI.

In 2018, a big fan of Nicholas Cage showed us what _The Fellowship of the Ring _would look like if Cage starred as Frodo, Aragorn, Gimly, and Legolas. The technology he used was deepfake, a type of application that uses artificial intelligence algorithms to manipulate videos.

Deepfakes are mostly known for their capability to swap the faces of actors from one video to another. They first appeared in 2018 and quickly rose to fame after they were used to modify adult videos to feature the faces of Hollywood actors and politicians.

In the past couple of years, deepfakes have caused much concern about the rise of a new wave of AI-doctored videos that can spread fake news and enable forgers and scammers.

The “deep” in deepfake comes from the use of deep learning, the branch of AI that has become very popular in the past decade. Deep learning algorithms roughly mimic the experience-based learning capabilities of humans and animals. If you train them on enough examples of a task, they will be able to replicate it under specific conditions.

The basic idea is to train a set of artificial neural networks, the main component of deep learning algorithms, on multiple examples of the actor and target faces. With enough training, the neural networks will be able to create numerical representations of the features of each face. Then all you need to do is rewire the neural networks to map the face of the actor on to the target.

#artificial intelligence #deep learning #deepfakes #neural networks