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Cognitive computer. A cognitive computer is a computer that hardwires artificial intelligence and machine learning algorithms into an integrated circuit that closely reproduces the behavior of the human brain. [1] It generally adopts a neuromorphic engineering approach. Synonyms include neuromorphic chip and cognitive chip. [2][3]
BELBIC (Brain Emotional Learning Based Intelligent Controller) is one such controller which is proposed by Caro Lucas, Danial Shahmirzadi and Nima Sheikholeslami and adopts the network model developed by Moren and Balkenius to mimic those parts of the brain which are known to produce emotion (namely, the amygdala, orbitofrontal cortex, thalamus ...
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.
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.
Rather than relying on raw computing horsepower, it uses an old-school, as-yet-unproven type of "nueromorphic" tech that's modeled after the human brain. Intel unveils an AI chip that mimics the ...
Deep learning is a subset of machine learning methods based on neural networks with representation learning. The field takes inspiration from biological neuroscience and is centered around stacking artificial neurons into layers and "training" them to process data.
Moravec's paradox is the observation in 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 by Hans Moravec, Rodney Brooks, Marvin Minsky and others in the 1980s.
Hopfield network. A Hopfield network (associative memory or Ising–Lenz–Little model or Nakano-Amari-Hopfield network) is a spin glass system used to model neural networks, based on Ernst Ising 's work with Wilhelm Lenz on the Ising model of magnetic materials. [1]