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  2. ChatGPT-4 vs. 3.5: Which Version Offers More Money-Making ...

    www.aol.com/chatgpt-4-vs-3-5-170413903.html

    For starters, ChatGPT-4 is multimodal (working with both imagers and text) and more “steerable” than ChatGPT-3.5 in that it can take multiple prompts in greater numbers, which allows it to ...

  3. ChatGPT - Wikipedia

    en.wikipedia.org/wiki/ChatGPT

    Legacy ChatGPT-3.5: November 2022 The first ChatGPT version utilizing the GPT-3.5 model. ChatGPT-3.5 Default: 2023 An improvement over the Legacy version, offering better accuracy in responses while using the same GPT-3.5 model. ChatGPT-4: March 2023 Introduced with the ChatGPT Plus subscription, this version is more accurate, based on the GPT ...

  4. GPT-4 - Wikipedia

    en.wikipedia.org/wiki/GPT-4

    Generative Pre-trained Transformer 4 (GPT-4) is a multimodal large language model created by OpenAI, and the fourth in its series of GPT foundation models. [1] It was launched on March 14, 2023, [ 1 ] and made publicly available via the paid chatbot product ChatGPT Plus , via OpenAI's API , and via the free chatbot Microsoft Copilot . [ 2 ]

  5. GPT-4o - Wikipedia

    en.wikipedia.org/wiki/GPT-4o

    GPT-4o ( GPT-4 Omni) is a multilingual, multimodal generative pre-trained transformer designed by OpenAI. It was announced by OpenAI's CTO Mira Murati during a live-streamed demo on 13 May 2024 and released the same day. [ 1] GPT-4o is free, but with a usage limit that is 5 times higher for ChatGPT Plus subscribers. [ 2]

  6. ChatGPT vs. Copilot: Which Should You Use? - AOL

    www.aol.com/chatgpt-vs-copilot-125700781.html

    GPT-4 is available through the paid ChatGPT Plus and OpenAI’s API. The latest iteration, GPT-4o, released in 2024, further improves these capabilities by offering faster processing, a better ...

  7. GPT-3 - Wikipedia

    en.wikipedia.org/wiki/GPT-3

    v. t. e. 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]

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