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Synthetic media (also known as AI-generated media, [1] [2] media produced by generative AI, [3] personalized media, personalized content, [4] and colloquially as deepfakes [5]) is a catch-all term for the artificial production, manipulation, and modification of data and media by automated means, especially through the use of artificial intelligence algorithms, such as for the purpose of ...
The winning model of the Deepfake Detection Challenge was 65% accurate on the holdout set of 4,000 videos. [175] A team at Massachusetts Institute of Technology published a paper in December 2021 demonstrating that ordinary humans are 69–72% accurate at identifying a random sample of 50 of these videos.
The Viola–Jones object detection framework is a machine learning object detection framework proposed in 2001 by Paul Viola and Michael Jones. [1] [2] It was motivated primarily by the problem of face detection, although it can be adapted to the detection of other object classes. In short, it consists of a sequence of classifiers.
Kaggle is a data science competition platform and online community for data scientists and machine learning practitioners under Google LLC.Kaggle enables users to find and publish datasets, explore and build models in a web-based data science environment, work with other data scientists and machine learning engineers, and enter competitions to solve data science challenges.
Audio deepfake technology, also referred to as voice cloning or deepfake audio, is an application of artificial intelligence designed to generate speech that convincingly mimics specific individuals, often synthesizing phrases or sentences they have never spoken.
Deep learning is a subset of machine learning that focuses on utilizing neural networks to perform tasks such as classification, regression, and representation learning.The field takes inspiration from biological neuroscience and is centered around stacking artificial neurons into layers and "training" them to process data.
Concretely, the conditional GAN game is just the GAN game with class labels provided: (,):=, [ (,)] +, [ ((,))] where is a probability distribution over classes, () is the probability distribution of real images of class , and () the probability distribution of images generated by the generator when given class label .
These deep generative models were the first to output not only class labels for images but also entire images. In 2017, the Transformer network enabled advancements in generative models compared to older Long-Short Term Memory models, [ 38 ] leading to the first generative pre-trained transformer (GPT), known as GPT-1 , in 2018. [ 39 ]