Questions

DeepFake AI

Deepfakes use deep learning artificial intelligence to replace the likeness of one person with another in video and other digital media. The term, which describes both the technology and the resulting bogus content, is a portmanteau of deep learning and fake. 

The program was firstly intended for operations in movie dubbing, allowing the movie sequence to be modified to sync the actors. But now it could be used for medicine and education systems by creating learning tools and can also be used as an accessibility feature within technology.

DeepFaceLab is the leading name in DeepFake software. The open- source DeepFake software can change faces on videos or in images. Cameras are used to capture high definition photos from different angles. Audio recording devices commonly have multiple microphones as well as a sound adjusting system, that allows for the best possible audio that sounds just like a real person, they can use phrases which are put together to form new sentences and words. The use of high performance Computers are essential for AI deep learning, this would influence the responsiveness speeds, processing speeds, and Graphic quality. 

Impacts of DeepFake AI

DeepFake AI is massively impacted by the technological advancements made through Deep Learning. Deep learning tracks back to 1943 were the first computer generated model which was based on the neural networks of a human brain was invented, deep learning uses algorithms that are designed to teach themselves how to resolve problems that have larger data sets, it is used to swap faces in videos, in images, and in other digital content to make the fake appear real. As this technology evolves Deepfake AI will continue to improve. One of the biggest aspects of DeepFake are Cameras and facial recognition. Cameras allow for a digital image of a person to be uploaded and edited with deep learning. The quality of the digital image will impact the overall looks of the model as well as allow for a sense of realism. Facial recognition is already in use through the ability to unlock iphones as well as changes in appearance developed in camera softwares. Audio in DeepFakes is drastic when it comes to realism and the ability to poach words or phrases together to form new sentences and words, which is done through voice recognition. This was first developed In 1990 by a company called Dragon which revealed the world's first voice recognition system.

social and ethical implications

Deepfake is a real threat to society influencing the sentiments and perceptions of people around us. Popular celebrities, politicians and other personalities are getting badly affected by the misuse of AI-backed such technologies. Any popular or well-reputed person from our society can be targeted by creating altered pornographic clips or shifted faced with unknown persons like politicians contending in choices can be the victim of Deepfakes. Similar fake videos or images circulating on social media and other online channels can impact the followership at the time of state or central government choices in any country.

determining whether a deepfake is ethically problematic would be. whether the DeepFaked person would refuse to the way in which they're demonstrated; whether the DeepFake deceives observers, and the intent with which the deepfake was created. Creating and enhancing fake digital individualities for fraud, spying or infiltration purposes is unethical.


What is Deep Learning

Deep learning is part of a broader family of machine learning methods based on artificial neural networks with representation learning. Learning can be supervised, semi-supervised or unsupervised.