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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] These models learn the underlying patterns and structures of their training data and use them to produce new data [ 3 ] [ 4 ] based on the input ...
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.
Transformer architecture is now used in 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. It was followed by BERT (2018), an encoder-only Transformer model. [35]
The future of generative AI is uncertain, but it's here to stay. There is legal uncertainty around AI and its role in licensing and copyrights. In January 2023, three artists filed a lawsuit ...
Generative AI may not be coming for your job, but it’s certainly coming to your job. Worldwide, 75% of knowledge workers now use gen AI in their work, according to a recent Microsoft/LinkedIn ...
The rapid speed of change in generative AI (GenAI), where significant advances can happen even month-to-month, means that executives must avoid obsessing over perfecting near-term use cases.
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