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  2. Coursera - Wikipedia

    en.wikipedia.org/wiki/Coursera

    Such courses include courses on Generative AI, Data analytics, IT Support, Digital Marketing & E-commerce, Cybersecurity, and more. Google has a total of 1,172 courses on Coursera. They also offered 100,000 scholarships. [53] Google and its 20+ partners will accept those certificates as 4-year degree equivalent. [54] [55]

  3. 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 ...

  4. Google Chrome will use generative AI to summarize articles - AOL

    www.aol.com/news/google-chrome-generative-ai...

    Google is using AI to create a somewhat unique approach to reading articles online.As outlined in a Tuesday blog post, Google is applying its generative AI efforts towards something called "SGE ...

  5. Generative adversarial network - Wikipedia

    en.wikipedia.org/wiki/Generative_adversarial_network

    A generative adversarial network (GAN) is a class of machine learning frameworks and a prominent framework for approaching generative artificial intelligence. The concept was initially developed by Ian Goodfellow and his colleagues in June 2014. [ 1 ]

  6. Google debuts powerful Gemini generative AI model in strike ...

    www.aol.com/finance/google-debuts-powerful...

    Google (GOOG, GOOGL) on Wednesday debuted its new Gemini generative AI model. The platform serves as Google’s answer to Microsoft-backed OpenAI’s GPT-4, and according to DeepMind CEO Demis ...

  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.

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