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Artificial intelligence (AI), in its broadest sense, is intelligence exhibited by machines, particularly computer systems.It is a field of research in computer science that develops and studies methods and software that enable machines to perceive their environment and use learning and intelligence to take actions that maximize their chances of achieving defined goals. [1]
This phenomenon has occurred in relation to every AI application produced, so far, throughout the history of development of AI. AI winter – a period of disappointment and funding reductions occurring after a wave of high expectations and funding in AI. Such funding cuts occurred in the 1970s, for instance.
AI in architecture has created a way for architects to create things beyond human understanding. AI implementation of machine learning text-to-render technologies, like DALL-E and stable Diffusion, gives power to visualization complex. [380] AI allows designers to demonstrate their creativity and even invent new ideas while designing.
Data is typically distinguished in spatial data and time-series data, the former can be things like images, maps, graphs, etc. the latter can be e.g. stock-price or a voice recording. Document AI combines text data, which has a time dimension, with other types of data, such as the position of an address in a business letter, which is spatial.
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.
Automated planning and scheduling, sometimes denoted as simply AI planning, [1] is a branch of artificial intelligence that concerns the realization of strategies or action sequences, typically for execution by intelligent agents, autonomous robots and unmanned vehicles.
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In North America, AI researchers such as Ed Feigenbaum and Frederick Hayes-Roth advocated the representation of domain-specific knowledge rather than general-purpose reasoning. [ 5 ] These efforts led to the cognitive revolution in psychology and to the phase of AI focused on knowledge representation that resulted in expert systems in the 1970s ...
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