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Examples of artificial intelligence algorithms applied to real-world problems. For technologies used in these applications see: Category:Artificial intelligence; Category:Classification algorithms; Category:Machine learning
An algorithm is fundamentally a set of rules or defined procedures that is typically designed and used to solve a specific problem or a broad set of problems.. Broadly, algorithms define process(es), sets of rules, or methodologies that are to be followed in calculations, data processing, data mining, pattern recognition, automated reasoning or other problem-solving operations.
Lazy evaluation and the list and LogicT monads make it easy to express non-deterministic algorithms, which is often the case. Infinite data structures are useful for search trees. The language's features enable a compositional way to express algorithms. Working with graphs is however a bit harder at first because of functional purity.
International Joint Conferences on Artificial Intelligence; Machine Intelligence Research Institute; Partnership on AI – founded in September 2016 by Amazon, Facebook, Google, IBM, and Microsoft. Apple joined in January 2017. It focuses on establishing best practices for artificial intelligence systems and to educate the public about AI.
[[Category:Artificial intelligence templates]] to the <includeonly> section at the bottom of that page. Otherwise, add <noinclude>[[Category:Artificial intelligence templates]]</noinclude> to the end of the template code, making sure it starts on the same line as the code's last character.
Neural architecture search (NAS) [1] [2] is a technique for automating the design of artificial neural networks (ANN), a widely used model in the field of machine learning.NAS has been used to design networks that are on par with or outperform hand-designed architectures.
Active learning is a special case of machine learning in which a learning algorithm can interactively query a human user (or some other information source), to label new data points with the desired outputs. The human user must possess knowledge/expertise in the problem domain, including the ability to consult/research authoritative sources ...
Generative artificial intelligence (generative AI, GenAI, [1] or GAI) is a subset of artificial intelligence that uses generative models to produce text, images, videos, or other forms of data. [ 2 ] [ 3 ] [ 4 ] These models learn the underlying patterns and structures of their training data and use them to produce new data [ 5 ] [ 6 ] based on ...
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