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2. You can now use ChatGPT for free without a login - AOL

   www.aol.com/lifestyle/now-chatgpt-free-without...

   This version of ChatGPT is an earlier generation of the software called GPT 3.5, originally released in early 2022. And this open-access version does have a few caveats: For one, you can’t save ...

3. ChatGPT - Wikipedia

   en.wikipedia.org/wiki/ChatGPT

   ChatGPT is a generative artificial intelligence chatbot [2] [3] developed by OpenAI and launched in 2022. It is currently based on the GPT-4o large language model (LLM). ChatGPT can generate human-like conversational responses and enables users to refine and steer a conversation towards a desired length, format, style, level of detail, and language. [4]

4. GPT-3 - Wikipedia

   en.wikipedia.org/wiki/GPT-3

   Generative Pre-trained Transformer 3.5 (GPT-3.5) is a sub class of GPT-3 Models created by OpenAI in 2022. On March 15, 2022, OpenAI made available new versions of GPT-3 and Codex in its API with edit and insert capabilities under the names "text-davinci-002" and "code-davinci-002". [ 28 ]

5. GPT-4o - Wikipedia

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

   GPT-4o ("o" for "omni") is a multilingual, multimodal generative pre-trained transformer developed by OpenAI and released in May 2024. [1] GPT-4o is free, but with a usage limit that is five times higher for ChatGPT Plus subscribers. [2] It can process and generate text, images and audio. [3]

6. Understanding images is just one way Chat GPT-4 goes ... - AOL

   www.aol.com/news/understanding-images-just-one...

   One of the most apparent changes with GPT-4, compared to the GPT-3.5 that was powering ChatGPT when it hit the public market in November, is that it accepts visual inputs alongside text.

7. Generative pre-trained transformer - Wikipedia

   en.wikipedia.org/wiki/Generative_pre-trained...

   Generative pretraining (GP) was a long-established concept in machine learning applications. [16] [17] It was originally used as a form of semi-supervised learning, as the model is trained first on an unlabelled dataset (pretraining step) by learning to generate datapoints in the dataset, and then it is trained to classify a labelled dataset.