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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. GPT-2 - Wikipedia

   en.wikipedia.org/wiki/GPT-2

   t. e. Generative Pre-trained Transformer 2 ( GPT-2) is a large language model by OpenAI and the second in their foundational series of GPT models. GPT-2 was pre-trained on a dataset of 8 million web pages. [2] It was partially released in February 2019, followed by full release of the 1.5-billion-parameter model on November 5, 2019.

4. 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]

5. Upgraded ChatGPT teaches maths and flirts - but still glitches

   www.aol.com/version-chat-gpt-teach-maths...

   OpenAI has unveiled the latest version of the tech which underpins its AI chatbot ChatGPT. It’s called GPT-4o, and it will be rolled out to all users of ChatGPT, including non-subscribers.

6. OpenAI - Wikipedia

   en.wikipedia.org/wiki/OpenAI

   The full version of GPT-2 was not immediately released due to concern about potential misuse, including applications for writing fake news. Some experts expressed skepticism that GPT-2 posed a significant threat. In response to GPT-2, the Allen Institute for Artificial Intelligence responded with a tool to detect "neural fake news".

7. GPT-1 - Wikipedia

   en.wikipedia.org/wiki/GPT-1

   The GPT-1 architecture was a twelve-layer decoder-only transformer, using twelve masked self-attention heads, with 64-dimensional states each (for a total of 768). Rather than simple stochastic gradient descent , the Adam optimization algorithm was used; the learning rate was increased linearly from zero over the first 2,000 updates to a ...