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  2. Transformer (deep learning architecture) - Wikipedia

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

    Transformer architecture is now used alongside many generative models that contribute to the ongoing AI boom. In language modelling, ELMo (2018) was a bi-directional LSTM that produces contextualized word embeddings , improving upon the line of research from bag of words and word2vec .

  3. 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.

  4. Artificial intelligence in architecture - Wikipedia

    en.wikipedia.org/wiki/Artificial_Intelligence_in...

    Artificial Intelligence is thought to potentially lead to and ensue major changes in architecture. [1] [2] [3] AI's potential in optimization of design, planning and productivity have been noted as accelerators in the field of architectural work. The ability of AI to potentially amplify an architect's design process has also been noted.

  5. Attention Is All You Need - Wikipedia

    en.wikipedia.org/wiki/Attention_Is_All_You_Need

    Already in spring 2017, even before the "Attention is all you need" preprint was published, one of the co-authors applied the "decoder-only" variation of the architecture to generate fictitious Wikipedia articles. [32] Transformer architecture is now used alongside many generative models that contribute to the ongoing AI boom.

  6. 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.

  7. AlexNet - Wikipedia

    en.wikipedia.org/wiki/AlexNet

    AlexNet architecture and a possible modification. On the top is half of the original AlexNet (which is split into two halves, one per GPU). On the bottom is the same architecture but with the last "projection" layer replaced by another one that projects to fewer outputs.

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  9. GPT-1 - Wikipedia

    en.wikipedia.org/wiki/GPT-1

    The GPT-1 architecture was a twelve-layer decoder-only transformer, using twelve masked self-attention heads, with 64-dimensional states each (for a total of 768). Rather than simple stochastic gradient descent , the Adam optimization algorithm was used; the learning rate was increased linearly from zero over the first 2,000 updates to a ...

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