Neural network training made easy with smart hardware
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Wisse Hettinga
TU/e researchers have solved a major problem related to neuromorphic chips …
From the TU/e website
Large-scale neural network models form the basis of many AI-based technologies such as neuromorphic chips, which are inspired by the human brain. Training these networks can be tedious, time-consuming, and energy-inefficient given that the model is often first trained on a computer and then transferred to the chip. This limits the application and efficiency of neuromorphic chips. TU/e researchers have solved this problem by developing a neuromorphic device capable of on-chip training and eliminates the need to transfer trained models to the chip. This could open a route towards efficient and dedicated AI chips in the future …
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