IEEE

A 1–8b Reconfigurable Digital SRAM Compute-in-Memory Macro for Processing Neural Networks

This work presents a 1-8b reconfigurable digital SRAM compute-in-memory (CIM) macro, which significantly improves array utilization and energy efficiency under different input and weight ...
CryptoNewsZ

Arthur Hayes Accelerates ETH Sell-Off Amid Strong US Economic Data

Hayes made the current move right after this US economic data was released, suggesting that he is immediately reacting to ...

Micron Enters A Profit Supercycle

Booming AI-driven HBM demand boosts Micron's profits, pricing power, and growth prospects. Click here to read an analysis of ...
Scientific Research Publishing

Cumulative Link Modeling of Ordinal Outcomes in the National Health Interview Survey Data: Application to Depressive Symptom Severity ()

Williams, A. and Louis, L. (2026) Cumulative Link Modeling of Ordinal Outcomes in the National Health Interview Survey Data: Application to Depressive Symptom Severity. Journal of Data Analysis and ...
IEEE

34.2 A 16nm 96Kb Integer/Floating-Point Dual-Mode-Gain-Cell-Computing-in-Memory Macro Achieving 73.3-163.3TOPS/W and 33.2-91.2TFLOPS/W for AI-Edge Devices

Advanced AI-edge chips require computational flexibility and high-energy efficiency (EEF) with sufficient inference accuracy for a variety of applications. Floating-point (FP) numerical representation ...