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  2. Machine learning control - Wikipedia

    en.wikipedia.org/wiki/Machine_learning_control

    Example applications include: spacecraft attitude control, [7] thermal control of buildings, [8] feedback control of turbulence, [2] [9] and remotely operated underwater vehicles. [10] Many more engineering MLC application are summarized in the review article of PJ Fleming & RC Purshouse (2002). [11]

  3. Applications of artificial intelligence - Wikipedia

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

    The use of AI in applications such as online trading and decision-making has changed major economic theories. [66] For example, AI-based buying and selling platforms estimate personalized demand and supply curves, thus enabling individualized pricing. AI systems reduce information asymmetry in the market and thus make markets more efficient. [67]

  4. Machine learning - Wikipedia

    en.wikipedia.org/wiki/Machine_learning

    [5] [42] Generalization in this context is the ability of a learning machine to perform accurately on new, unseen examples/tasks after having experienced a learning data set. The training examples come from some generally unknown probability distribution (considered representative of the space of occurrences) and the learner has to build a ...

  5. AI-assisted reverse engineering - Wikipedia

    en.wikipedia.org/.../AI-assisted_reverse_engineering

    AI-assisted reverse engineering (AIARE) is a branch of computer science that leverages artificial intelligence (AI), notably machine learning (ML) strategies, to augment and automate the process of reverse engineering. The latter involves breaking down a product, system, or process to comprehend its structure, design, and functionality.

  6. Feature engineering - Wikipedia

    en.wikipedia.org/wiki/Feature_engineering

    Feature engineering in machine learning and statistical modeling involves selecting, creating, transforming, and extracting data features. Key components include feature creation from existing data, transforming and imputing missing or invalid features, reducing data dimensionality through methods like Principal Components Analysis (PCA), Independent Component Analysis (ICA), and Linear ...

  7. Foundation model - Wikipedia

    en.wikipedia.org/wiki/Foundation_model

    The Stanford Institute for Human-Centered Artificial Intelligence's (HAI) Center for Research on Foundation Models (CRFM) coined the term "foundation model" in August 2021 [16] to mean "any model that is trained on broad data (generally using self-supervision at scale) that can be adapted (e.g., fine-tuned) to a wide range of downstream tasks". [17]

  8. Artificial intelligence in industry - Wikipedia

    en.wikipedia.org/wiki/Artificial_intelligence_in...

    Industrial artificial intelligence, or industrial AI, usually refers to the application of artificial intelligence to industry and business. Unlike general artificial intelligence which is a frontier research discipline to build computerized systems that perform tasks requiring human intelligence, industrial AI is more concerned with the application of such technologies to address industrial ...

  9. Automated machine learning - Wikipedia

    en.wikipedia.org/wiki/Automated_machine_learning

    In a typical machine learning application, practitioners have a set of input data points to be used for training. The raw data may not be in a form that all algorithms can be applied to. To make the data amenable for machine learning, an expert may have to apply appropriate data pre-processing , feature engineering , feature extraction , and ...