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  2. GitHub Copilot - Wikipedia

    en.wikipedia.org/wiki/GitHub_Copilot

    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.

  3. Machine learning - Wikipedia

    en.wikipedia.org/wiki/Machine_learning

    Machine learning (ML) is a field of artificial intelligence that develops and studies algorithms that can learn from data and generalize to unseen data. ML has many applications in various fields, such as natural language processing, computer vision, and medicine, and is related to data mining, statistics, and neural networks.

  4. GitHub - Wikipedia

    en.wikipedia.org/wiki/Github

    GitHub is a website that allows developers to create, store, manage and share their code using Git software. It is owned by Microsoft since 2018 and has over 100 million users and 420 million repositories as of January 2023.

  5. Microsoft and open source - Wikipedia

    en.wikipedia.org/wiki/Microsoft_and_open_source

    Microsoft, a technology company historically known for its opposition to the open source software paradigm, turned to embrace the approach in the 2010s. Learn about Microsoft's history, adoption, and contributions to open source projects, such as Linux, GitHub, .NET Framework, and F#.

  6. Neural Network Intelligence - Wikipedia

    en.wikipedia.org/wiki/Neural_Network_Intelligence

    NNI (Neural Network Intelligence) is a free and open-source AutoML toolkit developed by Microsoft. It is used to automate feature engineering, model compression, neural architecture search, and hyper-parameter tuning. The source code is licensed under MIT License and available on GitHub.

  7. Applications of artificial intelligence - Wikipedia

    en.wikipedia.org/wiki/Applications_of_artificial...

    Learn how AI is used in various fields such as internet and e-commerce, language translation, facial recognition, games, agriculture, and cyber security. Explore the examples, challenges, and benefits of AI applications with Wikipedia.

  8. Symbolic artificial intelligence - Wikipedia

    en.wikipedia.org/wiki/Symbolic_artificial...

    Learn about the history, methods, and applications of symbolic AI, a paradigm of AI research based on high-level symbolic representations and logic. Explore the challenges, successes, and limitations of symbolic AI and its relation to other approaches.

  9. Generative artificial intelligence - Wikipedia

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

    Learn about the history, applications, and challenges of generative AI, which is AI capable of creating text, images, videos, or other data using generative models. Explore examples of generative AI systems, such as chatbots, text-to-image models, and transformer networks.