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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.
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. For the training cost column, 1 petaFLOP-day = 1 petaFLOP/sec × 1 day = 8.64E19 FLOP. Also, only the largest model's cost is written.
Its training cost is reported to be significantly lower than other LLMs. The company claims that it trained V3, a predecessor of R1, for US$6 million compared to $100 million for OpenAI's GPT-4 in 2023, [7] and approximately one tenth of the computing power used for Meta's comparable model, LLaMA 3.1. [7] [8] [71] [10]
DeepSeek is an artificial intelligence (AI) research lab based in China. The DeepSeek team found a way to develop powerful large language models (LLMs) for a tiny fraction of the money being spent ...
An arms race to build the best large language model (LLM). OpenAI with #11, Google with Gemini, Microsoft with Copilot, character.ai, and so on. Established tech giants putting everything into AI. Billions of dollars and thousands of people working on LLMs. The U.S. president investing $500 billion in AI.
Silicon Valley’s initial advantage in LLMs evaporated quickly despite export controls, writes AI expert Gary Marcus.
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