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OpenAI Codex is an artificial intelligence model developed by OpenAI. It parses natural language and generates code in response. It powers GitHub Copilot, a programming autocompletion tool for select IDEs, like Visual Studio Code and Neovim. [ 1] Codex is a descendant of OpenAI's GPT-3 model, fine-tuned for use in programming applications.
TensorFlow.nn is a module for executing primitive neural network operations on models. [ 38] Some of these operations include variations of convolutions (1/2/3D, Atrous, depthwise), activation functions ( Softmax, RELU, GELU, Sigmoid, etc.) and their variations, and other operations ( max-pooling, bias-add, etc.).
Pythonis a high-level, general-purpose programming languagethat is popular in artificial intelligence.[1] It has a simple, flexible and easily readable syntax.[2] Its popularity results in a vast ecosystem of libraries, including for deep learning, such as PyTorch, TensorFlow, Keras, Google JAX.
GitHub Copilot. GitHub Copilot is a code completion tool developed by GitHub and OpenAI that assists users of Visual Studio Code, Visual Studio, Neovim, and JetBrains integrated development environments (IDEs) by autocompleting code. [ 1] Currently available by subscription to individual developers and to businesses, the generative artificial ...
GPT-3 was used by The Guardian to write an article about AI being harmless to human beings. It was fed some ideas and produced eight different essays, which were ultimately merged into one article. [44] GPT-3 was used in AI Dungeon, which generates text-based adventure games. Later it was replaced by a competing model after OpenAI changed their ...
Business Intelligence - Generative BI. Generative BI [ 67] refers to the application of generative AI techniques, like Large Language Models (LLMs), in business intelligence. This combination accelerates the development of advanced models, automates data analysis, and facilitates the generation of actionable insights.
e. Generative Pre-trained Transformer 2 ( GPT-2) is a large language model by OpenAI and the second in their foundational series of GPT models. 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]
Generative pretraining (GP) was a long-established concept in machine learning applications. [16] [17] [18] 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.