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Artificial intelligence-enhanced technology is being used as an aid in the screening of eye disease and prevention of blindness. [90] In 2018, the U.S. Food and Drug Administration authorized the marketing of the first medical device to diagnose a specific type of eye disease, diabetic retinopathy using an artificial intelligence algorithm. [91]
AIMA gives detailed information about the working of algorithms in AI. The book's chapters span from classical AI topics like searching algorithms and first-order logic, propositional logic and probabilistic reasoning to advanced topics such as multi-agent systems, constraint satisfaction problems, optimization problems, artificial neural networks, deep learning, reinforcement learning, and ...
UNESCO recognizes the future of AI in education as an instrument to reach Sustainable Development Goal 4, called "Inclusive and Equitable Quality Education.” [57] The World Economic Forum also stresses AI's contribution to students' overall improvement and transforming teaching into a more enjoyable process.
Artificial intelligence in education (AIEd) is another vague term, [4] and an interdisciplinary collection of fields which are bundled together, [5] inter alia anthropomorphism, generative artificial intelligence, data-driven decision-making, ai ethics, classroom surveillance, data-privacy and Ai Literacy. [6]
Holmes a new AI created by Wipro. [36] Microsoft Cortana, an intelligent personal assistant with a voice interface in Microsoft's various Windows 10 editions. [37] Mycin, an early medical expert system. [38] Open Mind Common Sense, a project based at the MIT Media Lab to build a large common sense knowledge base from online contributions. [39]
The book is intended to explain how computers reason and perceive, and introduce the field of artificial intelligence. It describes the field, both as a branch of engineering and as a science, providing a computational perspective. Ideas for representing knowledge, using knowledge, and building practical systems are provided.
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This field deals with utilization of machine-learning algorithms and artificial intelligence, to emulate human cognition in the analysis, interpretation, and comprehension of complicated medical and healthcare data. Specifically, AI is the ability of computer algorithms to approximate conclusions based solely on input data.