One of the biggest problems for AI researchers is the increasingly high demands they must make of computers, but a new approach could cut down the computing power needed to train AI models.
Artificial intelligence is growing ever more capable at increasingly complex tasks, but requires vast amounts of computing power to develop. A more efficient technique could save up to half the time, energy and computer power needed to train an AI model.
Deep learning models are typically composed of a huge grid of artificial neurons linked by “weights” – computer code that takes an input and passes on a changed output – that represent the synapses linking real neurons. By …App + Web
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