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2. Hallucination (artificial intelligence) - Wikipedia

   en.wikipedia.org/wiki/Hallucination_(artificial...

   (In reality, as a consequence of the no-hair theorem, a black hole without an accretion disk is believed to have no magnetic field.) [39] Fast Company asked ChatGPT to generate a news article on Tesla's last financial quarter; ChatGPT created a coherent article, but made up the financial numbers contained within.

3. Grok (chatbot) - Wikipedia

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

   As with other text-to-image models, Aurora generates images from natural language descriptions, called prompts. [ 64 ] The capacity to generate images using Flux was added in August 2024, with The Verge reporting that the kinds of prompts that would be "immediately blocked" on other services seemed to be permitted by Grok.

4. Sora (text-to-video model) - Wikipedia

   en.wikipedia.org/wiki/Sora_(text-to-video_model)

   Sora is a text-to-video model developed by OpenAI. The model generates short video clips based on user prompts, and can also extend existing short videos. Sora was released publicly for ChatGPT Plus and ChatGPT Pro users in December 2024. [1] [2]

5. OpenAI releases text-to-video model Sora for ChatGPT ... - AOL

   www.aol.com/news/openai-releases-text-video...

   The Microsoft-backed company, which kicked off a generative AI craze with the launch of its ChatGPT chatbot in November 2022, aims to target similar text-to-video tools from Meta and Alphabet's ...

6. List of chatbots - Wikipedia

   en.wikipedia.org/wiki/List_of_chatbots

   A chatbot is a software application or web interface that is designed to mimic human conversation through text or voice interactions. [1] [2] [3] Modern chatbots are typically online and use generative artificial intelligence systems that are capable of maintaining a conversation with a user in natural language and simulating the way a human would behave as a conversational partner.

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.