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2. Would you let AI plan your next holiday?

   www.aol.com/news/let-ai-plan-next-holiday...

   Instead the founder of recruitment company People Movers consulted ChatGPT, Open AI’s generative artificial intelligence tool. ... As well as ChatGPT there are other generative AI tools such as ...

3. Gemini (chatbot) - Wikipedia

   en.wikipedia.org/wiki/Gemini_(chatbot)

   Gemini, formerly known as Bard, is a generative artificial intelligence chatbot developed by Google.Based on the large language model (LLM) of the same name and developed as a direct response to the rise of OpenAI's ChatGPT, it was launched in a limited capacity in March 2023 before expanding to other countries in May.

4. DALL-E - Wikipedia

   en.wikipedia.org/wiki/DALL-E

   The first version of DALL-E was announced in January 2021. In the following year, its successor DALL-E 2 was released. DALL·E 3 was released natively into ChatGPT for ChatGPT Plus and ChatGPT Enterprise customers in October 2023, [1] with availability via OpenAI's API [2] and "Labs" platform provided in early November. [3]

5. 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]

6. Removal of Sam Altman from OpenAI - Wikipedia

   en.wikipedia.org/wiki/Removal_of_Sam_Altman_from...

   The release of ChatGPT created divisions with OpenAI as a for-profit company without considerations for the safety of artificial intelligence and a non-profit cautious of artificial intelligence's capabilities; in a staff email sent in 2019 and obtained by The Atlantic, Altman referred to these divisions as "tribes". [23]

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] [18] 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.