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General game playing – Ability of artificial intelligence to play different games; Generative artificial intelligence – AI system capable of generating content in response to prompts; Human Brain Project – Scientific research project; Intelligence amplification – Use of information technology to augment human intelligence (IA)
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 ...
Artificial intelligence is also starting to be used in video production, with tools and software being developed that utilize generative AI in order to create new video, or alter existing video. Some of the major tools that are being used in these processes currently are DALL-E, Mid-journey, and Runway. [ 248 ]
Generative business intelligence is the application of generative AI techniques, such as large language models, in business intelligence. This combination facilitates data analysis and enables users to interact with data more intuitively, generating actionable insights through natural language queries.
In their Harvard Business Review essay, Collaborative Intelligence: Humans and AI Are Joining Forces – Humans and machines can enhance each other’s strengths, authors H. James Wilson and Paul R. Daugherty report on research involving 1,500 firms in a range of industries, showing that the biggest performance improvements occur when humans ...
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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]
Analogously, a classifier based on a generative model is a generative classifier, while a classifier based on a discriminative model is a discriminative classifier, though this term also refers to classifiers that are not based on a model. Standard examples of each, all of which are linear classifiers, are: generative classifiers:
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