Posted in | Machine-Vision

Researchers Aim to Create New Generation of AI that Mimics Neural Processes of the Human Brain

An international team of researchers is creating a new generation of artificial intelligence that imitates the neural processes of the human brain.

This project, headed by Loughborough University, will integrate the skills of biologists, chemists, physicists, artificial intelligence (AI) experts, and neuroscientists and is aimed at developing human-like “thinking” hardware.

Specialists from the School of Science have obtained a £965,568 grant from the EPSRC to fund the project, which intends to understand how to replicate biological neural networks with electronic chips.

It will be the first system of its kind and will be able to reproduce the brain’s ability to differentiate between rapidly moving objects, people, and animals, and also put across short statements of recognition, for instance, “it was a car moving left not right.”

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.

Professor Sergey Saveliev, Principal Investigator, School of Science, Loughborough University

The study is being performed together with the University of Massachusetts, the Salk Institute for Biological Sciences, Texas A&M University, and ARM—a British computing and technology company.

The research group intends to create a prototype chip composed of memristors, which are electrical components that control the flow of a current in a circuit, such as a resistor, but can retain information of charges that pass through.

The design will offer the system with the potential to learn and recognize in a quicker, cheaper, and more energy efficient way when compared to conventional software-driven AI systems.

Prof Saveliev stated, “Most of the computer hardware we use is made up of a CPU (central processing unit) 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, modeling, and AI, we intend to develop a prototype of a memristive neuromorphic chipset able to analyze image-streams and to make decisions and choices in the same place – mimicking neural process in a brain cortex.”

Co-researchers of Prof Saveliev are physicists Dr Pavel Borisov and Dr Mike Cropper, Professor Upul Wijayantha from Chemistry, and Professor Eran Edirisinghe from Computer Science.

Getting this grant is a major success for the School of Science and for Loughborough University. It shows the exceptionally high standard of our research. It is particularly exciting as this is a truly interdisciplinary project at the forefront of current research in the emerging field of neuromemristive systems.

Professor Claudia Eberlein, Dean, School of Science, Loughborough University

The research group will work with world-leading experts in memristor technology, neuroscience, and neuromorphic computing: Professor Stanley Williams from Texas A&M University, Professor Joshua Yang and Professor Qiangfei Xia from the University of Massachusetts at Amherst, Dr Sergey Gepshtein and Professor Thomas Albright from Salk, and Dr Viacheslav Chesnokov from ARM.

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