The proposed method, called Sparse Evolutionary Training, also gives full artificial intelligence capability to inexpensive computers, meaning it will be possible to turn any internet device into an intelligent Internet of Things object which can send and receive data. Artificial neural networks are widely used in industry, science and medicine to make sense of vast amounts of data, such as in medical diagnostics and personalised medicine. But ANNs are typically made up of lots of layers and millions of nodes, which means their intelligence is severely limited and requires super-computational power. The team of scientists from the University of Derby, Eindhoven University of Technology in the Netherlands, and the University of Texas, Austin, have joined together to develop a method that could push artificial intelligence well beyond its current boundaries. The new system substantially accelerates machine learning by replacing the typical neuronal networks with sparse layers, enabling the use of artificial intelligence in major problems such as genetic disease diagnostics.