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 ...

Machine learning (ML), a subset of artificial intelligence (AI), has become integral to our lives. It allows us to learn and reason from data using techniques such as deep neural network algorithms.

Skyrocketing AI compute workloads and fixed power budgets are forcing chip and system architects to take a much harder look at compute in memory (CIM), which until recently was considered little more ...

A new technical paper titled “IMAGIN: Library of IMPLY and MAGIC NOR Based Approximate Adders for In-Memory Computing” was published by researchers at DFKI (German Research Center for Artificial ...

Everyone is talking about the newest AI and the power of neural networks, forgetting that software is limited by the hardware on which it runs. But it is hardware become 'the bottleneck.' New ...

We all know AI has a power problem. On the whole, global AI usage already drew as much energy as the entire nation of Cyprus did in 2021. But engineering researchers at the University of Minnesota ...

The Defense Advanced Research Projects Agency awarded Professor Jie Gu and co-PIs from the University of Minnesota and Duke University up to $3.8 million through the Scalable Analog Neural-networks ...

With US curbs biting, experts say near-memory computing and chip stacking could narrow the AI hardware gap with Nvidia China ...