Artificial intelligence chip developers SK hynix and TetraMem have demonstrated a new memory-centric processor ...

Scholars at the School of Engineering of the Hong Kong University of Science and Technology (HKUST) have unveiled an innovation that brings artificial intelligence (AI) closer to quantum ...

Until now, researchers have been limited in developing photonic memory for AI processing -- gaining one important attribute like speed while sacrificing another like energy usage. An international ...

In-memory computing (IMC) has had a rough go, with the most visible attempt at commercialization falling short. And while some companies have pivoted to digital and others have outright abandoned the ...

For the first time, an international cadre of electrical engineers has developed a new method for photonic in-memory computing that could make optical computing a reality in the near future. The team ...

With the explosion of AI-rich embedded applications, how do you build the performance needed into embedded microcontrollers? One approach is to offload matrix-vector model operations to an in-memory ...

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 ...

A new technical paper titled “All-in-Memory Stochastic Computing using ReRAM” was published by researchers at TU Dresden, Center for Scalable Data Analytics and Artificial Intelligence (ScaDS.AI), ...

But shuttling data between the processor and memory eats up time and energy, particularly for data-hungry artificial-intelligence (ai) models. An analysis by Amir Gholami and colleagues at the ...

TL;DR: SK hynix and TetraMem developed an analog in-memory computing chip that processes AI tasks directly in memory, reducing energy use, latency, and data transfer bottlenecks. This memristor-based ...