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2. 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. GPT-4o is free, but with a usage limit that is 5 times higher for ChatGPT Plus subscribers.

3. 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.

4. ChatGPT maker OpenAI announces new 'flagship' model - AOL

   www.aol.com/finance/chatgpt-maker-openai...

   OpenAI said on Monday it is rolling out a new advanced model, GPT-40, which will be available to users for free. The company provided live demonstrations of GPT-40's capabilities, including a new ...

5. GPT-4 - Wikipedia

   en.wikipedia.org/wiki/GPT-4

   Machine learningand data mining. 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 ...

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. 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]