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Artificial Intelligence; Machine Learning; Natural Language Processing


This subtopic focuses on information technology innovations in the field of artificial intelligence (AI), which refers to intelligence exhibited by machines or software. AI is usually limited or targeted in nature, with general machine-based intelligence remaining an elusive long-term goal.

Included in this subtopic are the technical sub-specialties of machine learning and natural language processing (NLP), both of which are disciplines within the broader field of artificial intelligence. Machine learning refers to processes in which an automated system can learn from data, rather than following a pre-specified set of rules, and in many cases can predict outcomes relating to the learned process. The aim of NLP is to extract information or derive meaning from human language (written or spoken) or to generate human language.

There are many technical approaches to AI, and an even greater diversity of potential applications. Examples of relevant technical fields include (but are not limited to): deep learning; artificial neural networks of various types; supervised, semi-supervised and unsupervised machine learning; machine learning algorithms; pattern recognition; image recognition; machine vision; fuzzy logic; uncertain reasoning using probabilistic methods; named entity recognition; sentiment analysis; natural language understanding; natural language generation; automatic summarization; language translation; analysis of structured or unstructured text; speech recognition; speech analysis; speech processing.

Applications of AI include (but are not limited to): robotics, including in automated manufacturing; industrial controllers; self-driving cars; analysis of online commentary; stock market analysis; optimization of finance operations and stock investments; analysis of medical records; clinical decision support systems for medical diagnosis; automated interpretation of medical test data (e.g. ultrasound scan data); cybersecurity; intrusion detection – in software systems, communications networks and sensor systems; fraud detection; cyber-physical control systems; improvements in human-computer interaction; automated document classification, indexing and retrieval; customer recommendation systems; personalization of customer services; intelligent virtual assistants; search engines, including image-based search; translation services (including speech-to-speech translation).

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