AI Hardware

AI hardware research focuses on developing energy-efficient and high-performance computing platforms for artificial intelligence applications, aiming to overcome limitations of traditional computing architectures. Current efforts concentrate on novel architectures like neuromorphic processors and specialized ASICs, often employing parallel processing and in-memory computing to accelerate neural network inference and training, including models such as spiking neural networks (SNNs) and convolutional neural networks (CNNs). This field is crucial for enabling the deployment of AI in resource-constrained environments (like edge devices) and for improving the scalability and reliability of AI systems, impacting various sectors from consumer electronics to industrial automation.