NVIDIA has collaborated with a research team at Stanford University to create the world’s largest artificial neural network built to model how the human brain learns. The network is 6.5 times bigger than the previous record-setting network developed by Google in 2012.

Computer-based neural networks are capable of “learning” how to model the behaviour of the brain – including recognising objects, characters, voices, and audio in the same way that humans do.

Yet creating large-scale neural networks is extremely computationally expensive. For example, Google used approximately 1,000 CPU-based servers, or 16,000 CPU cores, to develop its neural network, which taught itself to recognise cats in a series of YouTube videos. The network included 1.7 billion parameters, the virtual representation of connections between neurons.