Michigan Technological University

Researchers Apply Machine Learning and AI in Search of Less Costly Electronic Structure Method

Electron density prediction for a four-million-atom aluminum system using machine learning, deemed to be infeasible using traditional DFT method. × Researchers from Michigan Tech and the University of ...
Nature

Machine Learning Applications in High-Speed Electronic Systems

Recent advancements in machine learning have significantly impacted the domain of high-speed electronic systems. By leveraging state‐of‐the‐art algorithms and novel network architectures, researchers ...
Electronic Design

Neuromorphic NPU Sips Power to Handle Edge Machine-Learning Models

What are spiking neural networks (SNNs)? Why the Akida Pico neural processing unit (NPU) can use so little power to handle machine-learning models. Why neuromorphic computing is important to ...
Electronic Design

Dynamically Reconfigurable Processors Accelerate Machine-Learning Apps

What is a dynamically reconfigurable processor (DRP)? How DRPs accelerate machine-learning applications. Why is the RZ/V2H well-suited for robotic apps? Renesas's RZ/V2H system-on-chip (SoC) is the ...