Why Google’s TurboQuant Algorithm is Disrupting the AI Memory Chip Market

Google's TurboQuant combines PolarQuant with Quantized Johnson-Lindenstrauss correction to shrink memory use, raising ...
Semiconductor Engineering

Recent Advances and Challenges in Processing-in-DRAM (ETH Zurich)

A new technical paper titled “Memory-Centric Computing: Recent Advances in Processing-in-DRAM” was published by researchers at ETH Zurich. “Memory-centric computing aims to enable computation ...
Design And Reuse

Advancing In-Memory Computing: A Global Effort to Build More Efficient AI Hardware

Emerging non-volatile memory ( NVM) technologies are widely viewed as key enablers of IMC architectures. Among them, Resistive RAM (ReRAM) has attracted significant interest due to its combination of ...
NextBigFuture

Analog in-memory Computing Attention Mechanism for Fast and Energy-efficient Large Language Models

A Nature paper describes an innovative analog in-memory computing (IMC) architecture tailored for the attention mechanism in large language models (LLMs). They want to drastically reduce latency and ...
Tech Xplore on MSN

Three-in-one diode integrates sensing, memory and processing for smart cameras

Think about how easily you recognize a friend in a dimly lit room. Your eyes capture light, while your brain filters out ...
techtimes

Unveiling the Fastest In-Memory Database: Revolutionizing Data Processing with Exasol

To survive in today's ultra-competitive business environment, companies have to be adaptable and be able to move quickly with the ever-changing market conditions. It's not enough to simply have a good ...