“So far, artificial synapse networks exist as software. We’re trying to build real neural network hardware for portable artificial intelligence systems,” says Jeehwan Kim, associate professor of mechanical engineering at MIT. “Imagine connecting a neuromorphic device to a camera on your car, and having it recognize lights and objects and make a decision immediately, without having to connect to the internet.”

MIT isn’t the only institution working to develop neuromorphic chips. Apple, Google, Microsoft and NVIDIA all have their own versions of machine learning hardware. Intel’s Lohi chip mimics the brain with 1,024 artificial neurons. But most artificial brain synapses (memristors) use silver. Kim’s team realized they could fabricate each memristor with alloys of silver and copper, along with silicon. This allowed them to create a millimeter-square silicon chip with tens of thousands of memristors.

“We’re using artificial synapses to do real inference tests,” Kim said in a press release. “We would like to develop this technology further to have larger-scale arrays to do image recognition tasks. And some day, you might be able to carry around artificial brains to do these kinds of tasks, without connecting to supercomputers, the internet, or the cloud.”