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  2. Deep learning - Wikipedia

    en.wikipedia.org/wiki/Deep_learning

    Deep learning is a subset of machine learning that focuses on utilizing neural networks to perform tasks such as classification, regression, and representation learning. The field takes inspiration from biological neuroscience and is centered around stacking artificial neurons into layers and "training" them to process data.

  3. Transformer (deep learning architecture) - Wikipedia

    en.wikipedia.org/wiki/Transformer_(deep_learning...

    Glossary of artificial intelligence; ... The transformer is a deep learning architecture that was developed by researchers at Google and is based on the multi-head ...

  4. Deep reinforcement learning - Wikipedia

    en.wikipedia.org/wiki/Deep_reinforcement_learning

    Deep learning methods, often using supervised learning with labeled datasets, have been shown to solve tasks that involve handling complex, high-dimensional raw input data (such as images) with less manual feature engineering than prior methods, enabling significant progress in several fields including computer vision and natural language ...

  5. Artificial intelligence - Wikipedia

    en.wikipedia.org/wiki/Artificial_intelligence

    Artificial intelligence (AI), in its broadest sense, is intelligence exhibited by machines, particularly computer systems.It is a field of research in computer science that develops and studies methods and software that enable machines to perceive their environment and use learning and intelligence to take actions that maximize their chances of achieving defined goals. [1]

  6. 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 ...

  7. The most underreported and important story in AI right now is ...

    www.aol.com/finance/most-underreported-important...

    Insiders have long known that one of the biggest problems in AI research is the tests (“benchmarks”) that we use to evaluate AI systems. The well-known Turing Test aimed to measure genuine ...

  8. Neural network (machine learning) - Wikipedia

    en.wikipedia.org/wiki/Neural_network_(machine...

    Topological deep learning, first introduced in 2017, [147] is an emerging approach in machine learning that integrates topology with deep neural networks to address highly intricate and high-order data.

  9. 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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