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2. ChatGPT - Wikipedia

   en.wikipedia.org/wiki/ChatGPT

   ChatGPT is a chatbot and virtual assistant developed by OpenAI and launched on November 30, 2022. Based on large language models (LLMs), it enables users to refine and steer a conversation towards a desired length, format, style, level of detail, and language. Successive user prompts and replies are considered at each conversation stage as context.

3. ChatGPT can now respond with spoken words. But what is it ...

   www.aol.com/news/chatgpt-used-exactly-does-heres...

   ChatGPT stands for “Chat Generative Pre-trained Transformer.”. It’s a mouthful, we know, hence most people shortening the name of the tool to “ChatGPT.”. As of September 2023, ChatGPT-3. ...

4. OpenAI - Wikipedia

   en.wikipedia.org/wiki/OpenAI

   They said that GPT-4 could also read, analyze or generate up to 25,000 words of text, and write code in all major programming languages. [190] Observers reported that the iteration of ChatGPT using GPT-4 was an improvement on the previous GPT-3.5-based iteration, with the caveat that GPT-4 retained some of the problems with earlier revisions. [191]

5. ChatGPT: Will the Groundbreaking Platform Start Charging You?

   www.aol.com/finance/chatgpt-groundbreaking...

   First, ChatGPT Plus uses the more advanced and intelligent GPT-4, GPT-4V and GPT-4 Turbo variants, as PC Guide detailed — while the free version uses GPT-3.5, per the Evening Standard (via Yahoo ...

6. OpenAI unveils newest AI model, GPT-4o - AOL

   www.aol.com/openai-unveils-newest-ai-model...

   Free ChatGPT users will have a limited number of interactions with the new GPT-4o model before the tool automatically reverts to relying on the old GPT-3.5 model; paid users will have access to a ...

7. Generative pre-trained transformer - Wikipedia

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

   History Initial developments. Generative pretraining (GP) was a long-established concept in machine learning applications. 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.