Interesting Engineering

New in-memory computing chip promises faster processing with lower energy use

AI chip makers SK hynix and TetraMem unveil a chip that computes inside memory to reduce power use and data movement.

TetraMem and SK hynix Showcase Successful Technology Collaboration Advancing Memory-Centric AI Computing

The collaboration brings together SK hynix’s expertise in advanced memory technologies and TetraMem's Analog In-Memory Computing platform to explore new computing architectures capable of addressing ...
IEEE

Heterogeneous Spatiotemporal Graph Convolution Network for Multi-Modal Wind-PV Power Collaborative Prediction

Abstract: Accurate and generalized collaborative prediction of multi-cluster renewable energy power generation is both an inevitable trend and urgent demand as the growth of multi-region ...
IEEE

Dual-Branch Convolution Network With Efficient Channel Attention for EEG-Based Motor Imagery Classification

Abstract: Brain-Computer Interface (BCI) is a revolutionary technique that employs wearable electroencephalography (EEG) sensors and artificial intelligence (AI) to monitor and decode brain activity.
CNBC

Upstart chipmakers keep challenging Nvidia. This time it's Microsoft-backed D-Matrix

D-Matrix says its chips can run inference workloads 10 times faster and using five times less energy than a standalone graphics processing unit from Nvidia. Like Cerebras, D-Matrix is trying to prove ...