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Generative Pre-trained Transformer 3 (GPT-3) is a large language model released by OpenAI in 2020.. Like its predecessor, GPT-2, it is a decoder-only [2] transformer model of deep neural network, which supersedes recurrence and convolution-based architectures with a technique known as "attention". [3]
OpenAI o3 is a generative pre-trained transformer (GPT) model developed by OpenAI as a successor to OpenAI o1. It is designed to devote additional deliberation time when addressing questions that require step-by-step logical reasoning. [1] [2]
Other such models include Google's PaLM, a broad foundation model that has been compared to GPT-3 and have been made available to developers via an API, [45] [46] and Together's GPT-JT, which has been reported as the closest-performing open-source alternative to GPT-3 (and is derived from earlier open-source GPTs). [47]
Generative Pre-trained Transformer 2 (GPT-2) is a large language model by OpenAI and the second in their foundational series of GPT models. GPT-2 was pre-trained on a dataset of 8 million web pages. [2] It was partially released in February 2019, followed by full release of the 1.5-billion-parameter model on November 5, 2019. [3] [4] [5]
GPT-J is a GPT-3-like model with 6 billion parameters. [4] Like GPT-3, it is an autoregressive, decoder-only transformer model designed to solve natural language processing (NLP) tasks by predicting how a piece of text will continue. [1] Its architecture differs from GPT-3 in three main ways. [1]
The DeepSeek app now ranks at the top for iPhone downloads in the US, just ahead of OpenAI's ChatGPT. ... That's a staggeringly modest figure, considering OpenAI’s GPT model cost more than $100 ...
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Qwen2.5-VL model claimed to beat OpenAI's GPT-4o, Anthropic's Claude 3.5 Sonnet, and Google's Gemini 2.0 Flash in various video understanding, math, document analysis, and question-answering ...