AI project aims to mimic processes of the human brain

This project will see physicists, biologists, chemists, neuroscientists and artificial intelligence (AI) specialists working to create human-like ‘thinking' hardware.

Experts from the School of Science have received a £965,568 grant from the EPSRC to fund the project which aims to understand how to replicate biological neural networks with electronic chips and create human-like machines.

According to Loughborough, it will be the first system of its kind and will be capable of reproducing the brain's ability to distinguish between fast moving objects, animals and people, as well as express short statements of recognition.

Principal investigator Professor Sergey Saveliev, of the School of Science, said: "Although modern computers significantly outperform the human brain when it comes to numeracy, they still cannot handle tasks requiring guesswork and intuition.

"But using circuits with memristors will allow computers to learn things just as we do.

"It will also help us understand whether the brain can be completely reduced to a biologically-wired electric circuit, or whether our brains have something beyond simple electric and chemical functionalities."

The research is being carried out in collaboration with the University of Massachusetts, the Salk Institute for Biological Sciences, A&M Texas University, and Cambridge-headquartered ARM.

The team will develop a prototype chip made of memristors, which are electrical components that control the flow of a current in a circuit but remember charges which pass through. The design is expected to the system the ability to learn and recognise in a faster, cheaper and more energy efficient way than traditional software-driven AI systems.

Prof Saveliev said: “Most of the computer hardware we use is made up of a CPU and memory, and so computation takes place in two separate places inside a machine – that's very different to our brain.

"We should have a system which is much more like the brain, where processing and storage are in exactly the same place.

"Using Loughborough's expertise in solid state physics, functional materials, thin films, modelling, and AI, we intend to develop a prototype of a memristive neuromorphic chipset able to analyse image-streams and to make decisions and choices in the same place – mimicking neural process in a brain cortex.”

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