While artificial intelligence (AI) models are becoming increasingly advanced, training and running these models on conventional computer hardware is very energy consuming. Engineers worldwide have thus been trying to create alternative, brain-inspired hardware that could better support the high computational load of AI systems. Researchers at Technion–Israel Institute of Technology and the Peng Cheng Laboratory have recently created a new neuromorphic computing system supporting deep belief neural networks (DBNs), a generative and graphical class of deep learning models. This system, outlined in Nature Electronics, is based on silicon-based memristors, energy-efficient devices that can both store and process information. Memristors are electrical components that can switch or regulate the flow of electrical current in a circuit, while also remembering the charge that passed through it.

Researchers at Technion and TowerJazz in Israel have recently built a low-power, two-terminal floating-gate transistor that could have useful applications in neuromorphic computing. This transistor, presented in a paper in Nature Electronics, was fabricated using standard single-poly technology and a commercial 180-nm CMOS process. "Our lab usually works on circuits and architectures with emerging devices, such as memristors," Shahar Kvatinsky, one of the researchers who carried out the study, told TechXplore. "The problem with these devices is that they are not commercially available and we can only get them on a small scale and with poor reliability. So usually, we either rely on simulations or on small proofs-of-concept with available devices."

Researchers at the Technion-Israel Institute of Technology and Israeli chipmaker TowerJazz said they have developed a "revolutionary" technology that transforms a commercial flash memory chip into a device that contains both memory and computing ability. This will help provide the computing power needed for artificial intelligence-based applications, the researchers said. The new device enables the creation of a "hardware neural network" inspired by the operation of the human brain, and will "significantly" accelerate the operation of AI-based computing, the Technion said in a statement. Get The Start-Up Israel's Daily Start-Up by email and never miss our top stories Free Sign Up "We have made a big jump forward" with just a small change, Prof. Shahar Kvatinsky of the Andrew & Erna Viterbi Faculty of Electrical Engineering at the Technion, who led the project, said in a phone interview. "We have taken an existing commercial technology and made a small change, transforming it into something that is very much needed."