Atom-thin, content-addressable memory enables edge AI applications

Recent advances in the field of artificial intelligence (AI) have opened new exciting possibilities for the rapid analysis 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 ...
SDxCentral

AI inference crisis: Google engineers on why network latency and memory trump compute

Researchers propose low-latency topologies and processing-in-network as memory and interconnect bottlenecks threaten inference economic viability ...
Medicine Buffalo

How can AI be more energy-efficient? UB researchers look to human brain for inspiration

It’s estimated it can take an AI model over 6,000 joules of energy to generate a single text response. By comparison, your brain needs just 20 joules every second to keep you alive and cognitive. That ...
Semiconductor Engineering

AI Memory: Enabling The Next Era Of High-Performance Computing

The rapid advancement of artificial intelligence (AI) is driving unprecedented demand for high-performance memory solutions. AI-driven applications are fueling significant year-over-year growth in ...
Semiconductor Engineering

Accelerator Architecture For In-Memory Computation of CNN Inferences Using Racetrack Memory

A new technical paper titled “Hardware-software co-exploration with racetrack memory based in-memory computing for CNN inference in embedded systems” was published by researchers at National ...
Medicine Buffalo

How can AI be more energy efficient? UB researchers look to human brain for inspiration

BUFFALO, N.Y. — It’s estimated it can take an AI model over 6,000 joules of energy to generate a single text response. By comparison, your brain needs just 20 joules every second to keep you alive and ...