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.
There are many technical approaches to AI, and an even greater diversity of potential applications. Current fields of use include (but are not limited to): intrusion detection - in software systems, communications networks, and sensor systems; the finance industry - optimizing operations and stock investments; medicine - clinical decision support, computer-aided interpretation of medical images; industry - robotics and automation, process management, quality control; and online/telephone customer service - automated assistants.
This subtopic includes a particular focus on 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. NLP uses machine learning to extract information or derive meaning from human language (written or spoken) or to generate human language.
Examples of relevant technical fields within machine learning include (but are not limited to): supervised machine learning; semi-supervised machine learning; unsupervised machine learning; neural networks; machine learning algorithms - e.g. decision tree learning; robot learning; pattern recognition; image recognition. Examples of technical fields within NLP include (but are not limited to): parsing; named entity recognition; data extraction from text; natural language understanding; natural language generation; automatic summarization; machine translation; analysis of structured or unstructured text; speech recognition; speech analysis; speech processing. Applications across both technical fields include (but are not limited to): improvements in human-computer interaction - e.g. computers anticipating users' needs; automated manufacturing; machine vision; robotic control systems; cyber-physical control systems; sentiment analysis; analysis of online commentary; automated medical diagnosis; stock market analysis; translation services (including speech-to-speech translation).