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  2. Andrej Karpathy - Wikipedia

    en.wikipedia.org/wiki/Andrej_Karpathy

    Andrej Karpathy (born 23 October 1986 [2]) is a Slovak-Canadian computer scientist who served as the director of artificial intelligence and Autopilot Vision at Tesla. He co-founded and formerly worked at OpenAI , [ 3 ] [ 4 ] [ 5 ] where he specialized in deep learning and computer vision .

  3. AutoGPT - Wikipedia

    en.wikipedia.org/wiki/AutoGPT

    Performance is reportedly enhanced when using AutoGPT with GPT-4 compared to GPT-3.5. For example, one reviewer who tested it on a task of finding the best laptops on the market with pros and cons found that AutoGPT with GPT-4 created a more comprehensive report than one by GPT 3.5.

  4. AlexNet - Wikipedia

    en.wikipedia.org/wiki/AlexNet

    The original paper said different numbers, but Andrej Karpathy, the former head of computer vision at Tesla, said it should be 227×227×3 (he said Alex didn't describe why he put 224×224×3). The next convolution should be 11×11 with stride 4: 55×55×96 (instead of 54×54×96).

  5. Former OpenAI, Tesla engineer Andrej Karpathy starts AI ... - AOL

    www.aol.com/news/former-openai-tesla-engineer...

    Karpathy - who received a PhD from Stanford University - started posting tutorial videos on how to solve Rubik's cubes and over the years has published content online exploring concepts related to AI.

  6. 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]

  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.

  8. File:Java Programming.pdf - Wikipedia

    en.wikipedia.org/wiki/File:Java_Programming.pdf

    You are free: to share – to copy, distribute and transmit the work; to remix – to adapt the work; Under the following conditions: attribution – You must give appropriate credit, provide a link to the license, and indicate if changes were made.

  9. Generative artificial intelligence - Wikipedia

    en.wikipedia.org/wiki/Generative_artificial...

    Above: An image classifier, an example of a neural network trained with a discriminative objective. Below: A text-to-image model, an example of a network trained with a generative objective. Since its inception, the field of machine learning used both discriminative models and generative models, to model and predict data.