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  2. Hubert Dreyfus's views on artificial intelligence - Wikipedia

    en.wikipedia.org/wiki/Hubert_Dreyfus's_views_on...

    Book cover of the 1979 paperback edition. Hubert Dreyfus was a critic of artificial intelligence research. In a series of papers and books, including Alchemy and AI, What Computers Can't Do (1972; 1979; 1992) and Mind over Machine, he presented a pessimistic assessment of AI's progress and a critique of the philosophical foundations of the field.

  3. Computing Machinery and Intelligence - Wikipedia

    en.wikipedia.org/wiki/Computing_Machinery_and...

    A machine cannot be the subject of its own thought (or can't be self-aware). A program which can report on its internal states and processes, in the simple sense of a debugger program, can certainly be written. Turing asserts "a machine can undoubtably be its own subject matter." A machine cannot have much diversity of behaviour. He notes that ...

  4. Machine learning - Wikipedia

    en.wikipedia.org/wiki/Machine_learning

    Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn from data and generalize to unseen data, and thus perform tasks without explicit instructions. [1]

  5. Apache SystemDS - Wikipedia

    en.wikipedia.org/wiki/Apache_SystemDS

    SystemDS 2.0.0 is the first major release under the new name. This release contains a major refactoring, a few major features, a large number of improvements and fixes, and some experimental features to better support the end-to-end data science lifecycle.

  6. Explainable artificial intelligence - Wikipedia

    en.wikipedia.org/wiki/Explainable_artificial...

    Explainable AI (XAI), often overlapping with interpretable AI, or explainable machine learning (XML), is a field of research within artificial intelligence (AI) that explores methods that provide humans with the ability of intellectual oversight over AI algorithms.

  7. Automated machine learning - Wikipedia

    en.wikipedia.org/wiki/Automated_machine_learning

    Automated machine learning (AutoML) is the process of automating the tasks of applying machine learning to real-world problems. It is the combination of automation and ML. [1] AutoML potentially includes every stage from beginning with a raw dataset to building a machine learning model ready for deployment.

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    Get AOL Mail for FREE! Manage your email like never before with travel, photo & document views. Personalize your inbox with themes & tabs. You've Got Mail!

  9. Learning classifier system - Wikipedia

    en.wikipedia.org/wiki/Learning_classifier_system

    A step-wise schematic illustrating a generic Michigan-style learning classifier system learning cycle performing supervised learning. Keeping in mind that LCS is a paradigm for genetic-based machine learning rather than a specific method, the following outlines key elements of a generic, modern (i.e. post-XCS) LCS algorithm.