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OpenAI Codex is an artificial intelligence model that parses natural language and generates code in response. It powers GitHub Copilot, a programming autocompletion tool, and is based on OpenAI's GPT-3 model, fine-tuned for use in programming applications.
GitHub Copilot is a code completion and automatic programming tool developed by GitHub and OpenAI that assists users of various IDEs by autocompleting code. It uses a deep-learning model trained on public source code and natural language queries, and has faced licensing, privacy, and security controversies.
Learn about the history and features of various programming languages used for AI applications, such as Python, R, Lisp, C++, and Prolog. Compare general-purpose and specialized languages, and their libraries and frameworks.
Bayesian optimization is a strategy for global optimization of black-box functions that does not assume any functional forms. It uses Bayesian methods to construct an acquisition function that determines the next query point and has been applied to various problems in machine learning, robotics, chemistry, and more.
Explainable artificial intelligence (XAI) is the ability to understand and explain the reasoning behind AI decisions or predictions. XAI aims to improve trust, transparency, and accountability of AI systems, and to overcome the "black box" problem of machine learning.
A blackboard system is an artificial intelligence approach that uses a common knowledge base, the "blackboard", to solve complex problems with diverse knowledge sources. Learn about the metaphor, components, language, and implementations of blackboard systems in various domains.
Learn about the attacks and defenses on machine learning algorithms, and how they can be exploited or protected. See examples of adversarial examples, taxonomy of attacks, and applications in spam filtering, computer security, biometric recognition, and more.
Project Jupyter is a nonprofit organization that develops software, standards, and services for interactive data science and scientific computing across multiple programming languages. It supports execution environments (kernels) in Julia, Python, R, and many others, and has a web-based interface called Jupyter Notebook or JupyterLab.