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  2. 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.

  3. Training simulation - Wikipedia

    en.wikipedia.org/wiki/Training_Simulation

    In business, training simulation [aka Simulation Training] is a virtual medium through which various types of skills can be acquired. [1] Training simulations can be used in a variety of genres; however they are most commonly [ 2 ] used in corporate situations to improve business awareness and management skills.

  4. Salesforce - Wikipedia

    en.wikipedia.org/wiki/Salesforce

    Salesforce, Inc. is an American cloud-based software company headquartered in San Francisco, California. It provides applications focused on sales , customer service , marketing automation , e-commerce , analytics , artificial intelligence , and application development.

  5. An interview with AI: What ChatGPT says about itself - AOL

    www.aol.com/finance/interview-ai-chatgpt-says...

    I asked it some questions and made a few requests, from how many jobs it might replace to testing out its songwriting chops. My first question was simple, more of a "get to know you," the way I ...

  6. GPT-1 - Wikipedia

    en.wikipedia.org/wiki/GPT-1

    Generative Pre-trained Transformer 1 (GPT-1) was the first of OpenAI's large language models following Google's invention of the transformer architecture in 2017. [2] In June 2018, OpenAI released a paper entitled "Improving Language Understanding by Generative Pre-Training", [ 3 ] in which they introduced that initial model along with the ...

  7. GPT-2 - Wikipedia

    en.wikipedia.org/wiki/GPT-2

    GPT-2 was pre-trained on a dataset of 8 million web pages. [2] It was partially released in February 2019, followed by full release of the 1.5-billion-parameter model on November 5, 2019. [3] [4] [5] GPT-2 was created as a "direct scale-up" of GPT-1 [6] with a ten-fold increase in both its parameter count and the size of its training dataset. [5]

  8. Self-supervised learning - Wikipedia

    en.wikipedia.org/wiki/Self-supervised_learning

    Training an autoencoder intrinsically constitutes a self-supervised process, because the output pattern needs to become an optimal reconstruction of the input pattern itself. However, in current jargon, the term 'self-supervised' often refers to tasks based on a pretext-task training setup.

  9. GPT-3 - Wikipedia

    en.wikipedia.org/wiki/GPT-3

    Generative Pre-trained Transformer 3 (GPT-3) is a large language model released by OpenAI in 2020.. Like its predecessor, GPT-2, it is a decoder-only [2] transformer model of deep neural network, which supersedes recurrence and convolution-based architectures with a technique known as "attention". [3]