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GPT systems can be directed toward particular fields or domains. Some reported examples of such models and apps are as follows: EinsteinGPT – for sales and marketing domains, to aid with customer relationship management (uses GPT-3.5) [66] [67]
GPT-3, specifically the Codex model, was the basis for GitHub Copilot, a code completion and generation software that can be used in various code editors and IDEs. [38] [39] GPT-3 is used in certain Microsoft products to translate conventional language into formal computer code. [40] [41]
GPT-3 in 2020 went a step further and as of 2024 is available only via API with no offering of downloading the model to execute locally. But it was the 2022 consumer-facing browser-based ChatGPT that captured the imaginations of the general population and caused some media hype and online buzz. [ 15 ]
For example, GPT-3, and its precursor GPT-2, [11] are auto-regressive neural language models that contain billions of parameters, BigGAN [12] and VQ-VAE [13] which are used for image generation that can have hundreds of millions of parameters, and Jukebox is a very large generative model for musical audio that contains billions of parameters. [14]
OpenAI o3 is a reflective 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] OpenAI released a smaller model, o3-mini, on January 31st, 2025. [3]
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Grok 3’s somewhat underwhelming performance should be a wake-up call. ... writing in part that “GPT-4o Pro [which includes access to test time compute] has consistently underperformed,” and ...
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]