Research On Edge Processing Improves Artificial Intelligence Networks

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By using multimodal transistors (MMTs), artificial intelligence (AI) hardware and associated computing will become more efficient

Using the multimodal transistor (MMT) in artificial neural networks, which mimic the human brain, is an important step towards using thin-film transistors as artificial intelligence hardware. Image credit: University of Surrey

By using multimodal transistors (MMTs), researchers at the University of Surrey have achieved success in mimicking the human brain in artificial neural networks. The feat is a step toward using MMTs for taking forward artificial intelligence (AI) hardware and improving computing, which could further reduce power needs for better efficiency.

Devised in 2020, the MMT is a switching device that can control electric current flow faster than conventional transistors. The discovery overcomes long-standing operational challenges associated with complex electronic circuits. 

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By using mathematical modelling and simulating transistor data for identifying handwritten numbers, the researchers proved the feasibility of MMTs in AI systems. The final result suggested that MMT could operate as rectified linear unit-type (ReLU) activations in artificial neural networks, thus confirming the potential of MMT devices for thin-film decision and classification circuits in complex AI systems.

“There is a great need for technological improvements to support the growth of low cost, large-area electronics, which were shown to be used in artificial intelligence applications. Thin-film transistors have a role to play in enabling high processing power with low resource use. We can now see that MMTs, a unique type of thin-film transistor, have the reliability and uniformity needed to fulfil this role,” said Isin Pesch, researcher and electronics engineering graduate from the University of Surrey.

“Many of my colleagues focus on people-centred AI and how best to maximise the benefits for humans, including how to apply these new concepts ethically. Our research takes forward the physical implementation, as a stepping stone towards powerful yet affordable next-generation hardware. It’s fantastic that collaboration is resulting in such successes with researchers involved at all levels, from undergraduates like Isin when she led this research, to seasoned experts,” said Dr Radu Sporea, Senior Lecturer at the University of Surrey’s Advanced Technology Institute.

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