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Hugging Face, Inc. is an American company that develops computation tools for building applications using machine learning. It is incorporated under the Delaware General Corporation Law [ 1 ] and based in New York City .
In this edition…a Hugging Face cofounder on the importance of open source…a Nobel Prize for Geoff Hinton and John Hopfield…a movie model from Meta…a Trump ‘Manhattan Project’ for AI?
EleutherAI (/ ə ˈ l uː θ ər / [2]) is a grass-roots non-profit artificial intelligence (AI) research group. The group, considered an open-source version of OpenAI, [3] was formed in a Discord server in July 2020 by Connor Leahy, Sid Black, and Leo Gao [4] to organize a replication of GPT-3.
BigScience Large Open-science Open-access Multilingual Language Model (BLOOM) [1] [2] is a 176-billion-parameter transformer-based autoregressive large language model (LLM). The model, as well as the code base and the data used to train it, are distributed under free licences. [ 3 ]
Its speed and accuracy have led many to note that its generated voices sound near-indistinguishable from "real life", provided that sufficient computational specifications and resources (e.g., a powerful GPU and ample RAM) are available when running it locally and that a high-quality voice model is used.
A voiceover was provided by an actor, and AI trained using video of Tiwari speeches was used to lip-sync the video to the new voiceover. A party staff member described it as a "positive" use of deepfake technology, which allowed them to "convincingly approach the target audience even if the candidate didn't speak the language of the voter."
15.ai was a free non-commercial web application that used artificial intelligence to generate text-to-speech voices of fictional characters from popular media. [1] Created by an artificial intelligence researcher known as 15 during their time at the Massachusetts Institute of Technology, the application allowed users to make characters from video games, television shows, and movies speak ...
Deep learning speech synthesis refers to the application of deep learning models to generate natural-sounding human speech from written text (text-to-speech) or spectrum . Deep neural networks are trained using large amounts of recorded speech and, in the case of a text-to-speech system, the associated labels and/or input text.