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waifu2x is an image scaling and noise reduction program for anime-style art and other types of photos. [1]waifu2x was inspired by Super-Resolution Convolutional Neural Network (SRCNN).
According to Vedal, a separate AI model controls her in-game actions when she plays video games. [6] In a 2023 interview with Bloomberg News, he said that Neuro-sama was his full-time job. [7] The first iteration of Neuro-sama was created in May 2019 as a neural network trained to play the rhythm game osu!. [8]
[152] [153] [154] Similar techniques have also been used to create improved quality or full-length versions of songs that have been leaked or have yet to be released. [155] Generative AI has also been used to create new digital artist personalities, with some of these receiving enough attention to receive record deals at major labels. [156]
However, deepfake scammers have removed the original audio and dubbed over it with an AI Aniston-alike extolling the virtues of collagen supplements and crediting them for “why my body doesn’t ...
Body Labs is a Manhattan-based software company founded in 2013. Body Labs is a software provider of human-aware artificial intelligence that understands the 3D body shape and motion of people from RGB photos or videos.
[64] [65] Released in 2022 on Hugging Face's Spaces platform, Craiyon (formerly DALL-E Mini until a name change was requested by OpenAI in June 2022) is an AI model based on the original DALL-E that was trained on unfiltered data from the Internet. It attracted substantial media attention in mid-2022, after its release due to its capacity for ...
In artificial intelligence, an embodied agent, also sometimes referred to as an interface agent, [1] is an intelligent agent that interacts with the environment through a physical body within that environment. Agents that are represented graphically with a body, for example a human or a cartoon animal, are also called embodied agents, although ...
Generative pretraining (GP) was a long-established concept in machine learning applications. [16] [17] It was originally used as a form of semi-supervised learning, as the model is trained first on an unlabelled dataset (pretraining step) by learning to generate datapoints in the dataset, and then it is trained to classify a labelled dataset.