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e. In machine learning, a neural network (also artificial neural network or neural net, abbreviated ANN or NN) is a model inspired by the structure and function of biological neural networks in animal brains. [ 1 ][ 2 ] An ANN consists of connected units or nodes called artificial neurons, which loosely model the neurons in the brain.
In general, the term cognitive computing has been used to refer to new hardware and/or software that mimics the functioning of the human brain [5][6][7][8][9] (2004). In this sense, cognitive computing is a new type of computing with the goal of more accurate models of how the human brain/ mind senses, reasons, and responds to stimulus.
Machine learning and data mining often employ the same methods and overlap significantly, but while machine learning focuses on prediction, based on known properties learned from the training data, data mining focuses on the discovery of (previously) unknown properties in the data (this is the analysis step of knowledge discovery in databases).
Fundamentally, deep learning refers to a class of machine learning algorithms in which a hierarchy of layers is used to transform input data into a slightly more abstract and composite representation. For example, in an image recognition model, the raw input may be an image (represented as a tensor of pixels).
Artificial intelligence in healthcareis the application of artificial intelligence(AI) to copy human cognition in the analysis, presentation, and understanding of complex medical and health care data. It can also augment and exceed human capabilities by providing faster or new ways to diagnose, treat, or prevent disease.
Artificial consciousness, [1] also known as machine consciousness, [2][3] synthetic consciousness, [4] or digital consciousness, [5] is the consciousness hypothesized to be possible in artificial intelligence. [6] It is also the corresponding field of study, which draws insights from philosophy of mind, philosophy of artificial intelligence ...
Moravec's paradox is the observation in the fields of artificial intelligence and robotics that, contrary to traditional assumptions, reasoning requires very little computation, but sensorimotor and perception skills require enormous computational resources. The principle was articulated in the 1980s by Hans Moravec, Rodney Brooks, Marvin ...
Artificial neural networks (ANNs) are models created using machine learning to perform a number of tasks. Their creation was inspired by neural circuitry. [1] [a] While some of the computational implementations ANNs relate to earlier discoveries in mathematics, the first implementation of ANNs was by psychologist Frank Rosenblatt, who developed the perceptron. [1]