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On September 23, 2024, to further the International Decade of Indigenous Languages, Hugging Face teamed up with Meta and UNESCO to launch a new online language translator [14] built on Meta's No Language Left Behind open-source AI model, enabling free text translation across 200 languages, including many low-resource languages. [15]
In June 2019, a subreddit named r/SubSimulatorGPT2 was created in which a variety of GPT-2 instances trained on different subreddits made posts and replied to each other's comments, creating a situation where one could observe "an AI personification of r/Bitcoin argue with the machine learning-derived spirit of r/ShittyFoodPorn"; [25] by July ...
Hugging Face, of course, is the world’s leading repository for open-source AI models—the GitHub of AI, if you will. ... Wolf also told me Hugging Face is bucking a trend among AI companies: It ...
Flux is a series of text-to-image models. The models are based on a hybrid architecture that combines multimodal and parallel diffusion transformer blocks scaled to 12 billion parameters. [8]
Generative AI systems trained on words or word tokens include GPT-3, GPT-4, GPT-4o, LaMDA, LLaMA, BLOOM, Gemini and others (see List of large language models). They are capable of natural language processing, machine translation, and natural language generation and can be used as foundation models for other tasks. [62]
Natural language processing (NLP) is a subfield of computer science and especially artificial intelligence.It is primarily concerned with providing computers with the ability to process data encoded in natural language and is thus closely related to information retrieval, knowledge representation and computational linguistics, a subfield of linguistics.
Generative AI has been used in video game production beyond imagery, especially for level design (e.g., for custom maps) and creating new content (e.g., quests or dialogue) or interactive stories in video games. [159] [160] AI has also been used in the literary arts, [161] such as helping with writer's block, inspiration, or rewriting segments.
Margaret Mitchell is a computer scientist who works on algorithmic bias and fairness in machine learning.She is most well known for her work on automatically removing undesired biases concerning demographic groups from machine learning models, [2] as well as more transparent reporting of their intended use.