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A large language model (LLM) is a type of machine learning model designed for natural language processing tasks such as language generation. LLMs are language models with many parameters, and are trained with self-supervised learning on a vast amount of text. This page lists notable large language models.
A large language model (LLM) is a type of machine learning model designed for natural language processing tasks such as language generation. LLMs are language models with many parameters, and are trained with self-supervised learning on a vast amount of text.
T5 (Text-to-Text Transfer Transformer) is a series of large language models developed by Google AI introduced in 2019. [1] [2] Like the original Transformer model, [3] T5 models are encoder-decoder Transformers, where the encoder processes the input text, and the decoder generates the output text.
Andrew Yan-Tak Ng (Chinese: 吳恩達; born April 18, 1976 [2]) is a British-American computer scientist and technology entrepreneur focusing on machine learning and artificial intelligence (AI). [3] Ng was a cofounder and head of Google Brain and was the former Chief Scientist at Baidu , building the company's Artificial Intelligence Group ...
Llama (Large Language Model Meta AI, formerly stylized as LLaMA) is a family of large language models (LLMs) released by Meta AI starting in February 2023. [2] [3] The latest version is Llama 3.3, released in December 2024. [4] Llama models are trained at different parameter sizes, ranging between 1B and 405B. [5]
Amazon is adding artificial intelligence visionary Andrew Ng to its board of directors, a move that comes amid intense AI competition among startups and big technology companies. The Seattle ...
Pages in category "Large language models" The following 53 pages are in this category, out of 53 total. This list may not reflect recent changes. ...
A language model is a model of natural language. [1] Language models are useful for a variety of tasks, including speech recognition, [2] machine translation, [3] natural language generation (generating more human-like text), optical character recognition, route optimization, [4] handwriting recognition, [5] grammar induction, [6] and information retrieval.