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  2. Generative artificial intelligence - Wikipedia

    en.wikipedia.org/wiki/Generative_artificial...

    Generative artificial intelligence (generative AI, GenAI, [1] or GAI) is a subset of artificial intelligence that uses generative models to produce text, images, videos, or other forms of data. [ 2 ] [ 3 ] [ 4 ] These models learn the underlying patterns and structures of their training data and use them to produce new data [ 5 ] [ 6 ] based on ...

  3. Open-source artificial intelligence - Wikipedia

    en.wikipedia.org/wiki/Open-source_artificial...

    The rise of large language models (LLMs) and generative AI, such as OpenAI's GPT-3 (2020), further propelled the demand for open-source AI frameworks. [40] [41] These models have been used in a variety of applications, including chatbots, content creation, and code generation, demonstrating the broad capabilities of AI systems. [42]

  4. Ideogram (text-to-image model) - Wikipedia

    en.wikipedia.org/wiki/Ideogram_(text-to-image_model)

    Ideogram was founded in 2022 by Mohammad Norouzi, William Chan, Chitwan Saharia, and Jonathan Ho to develop a better text-to-image model. [3]It was first released with its 0.1 model on August 22, 2023, [4] after receiving $16.5 million in seed funding, which itself was led by Andreessen Horowitz and Index Ventures.

  5. Your 'friendly AI assistant' has arrived to your search bar ...

    www.aol.com/friendly-ai-assistant-arrived-search...

    AI Chatbots in their own words: ChatGPT: OpenAI - GPT-3.5 (GPT-4 available) "I'm an AI language model created by OpenAI called GPT-3.5, designed to understand and generate human-like text based on ...

  6. Stable Diffusion - Wikipedia

    en.wikipedia.org/wiki/Stable_Diffusion

    Stable Diffusion is a deep learning, text-to-image model released in 2022 based on diffusion techniques. The generative artificial intelligence technology is the premier product of Stability AI and is considered to be a part of the ongoing artificial intelligence boom.

  7. Text-to-image model - Wikipedia

    en.wikipedia.org/wiki/Text-to-image_model

    In 2016, Reed, Akata, Yan et al. became the first to use generative adversarial networks for the text-to-image task. [5] [7] With models trained on narrow, domain-specific datasets, they were able to generate "visually plausible" images of birds and flowers from text captions like "an all black bird with a distinct thick, rounded bill".

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