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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.
Hugo (software) Hugo is a static site generator written in Go. Steve Francia [4] originally created Hugo as an open source project in 2013. Since v0.14 in 2015, [5] Hugo has continued development under the lead of Bjørn Erik Pedersen with other contributors. Hugo is licensed under the Apache License 2.0.
Historically, some programming languages have been specifically designed for artificial intelligence (AI) applications. Nowadays, many general-purpose programming languages also have libraries that can be used to develop AI applications.
CodePen. CodePen is an online community for testing and showcasing user-created HTML, CSS and JavaScript code snippets. It functions as an online code editor and open-source learning environment, where developers can create code snippets, called "pens," and test them. It was founded in 2012 by full-stack developers Alex Vazquez and Tim Sabat ...
Text-to-image model. An image conditioned on the prompt "an astronaut riding a horse, by Hiroshige ", generated by Stable Diffusion, a large-scale text-to-image model released in 2022. A text-to-image model is a machine learning model which takes an input natural language description and produces an image matching that description.
References ^ a b "Code Generation Network - Frequently Asked Questions". www.codegeneration.net. Archived from the original on 24 October 2007. Retrieved 15 January 2022. ^ "Open source tools are available that make the task of developing passive code generators all but trivial. One such offering is Velocity from the Apache Software Foundation".
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To do so technically would require a more sophisticated grammar, like a Chomsky Type 1 grammar, also termed a context-sensitive grammar. However, parser generators for context-free grammars often support the ability for user-written code to introduce limited amounts of context-sensitivity. (For example, upon encountering a variable declaration ...