New hardware offers faster computation for artificial intelligence, with much less energy - MIT News

MIT researchers created protonic programmable resistors — building blocks of analog deep learning systems — that can process data 1 million times faster than synapses in the human brain. These ultrafast, low-energy resistors could enable analog deep learning …

As scientists push the boundaries of machine learning, the amount of time, energy, and money required to train increasingly complex neural network models is skyrocketing. A new area of artificial int… [+9739 chars]

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