Transformer on MSN

Teaching AI to learn

AI"s inability to continually learn remains one of the biggest problems standing in the way to truly general purpose models. Might it soon be solved?
TMCnet

Excellence and Impact Recognized by World's Preeminent Computing Society

ACM Fellows serve as ambassadors for the organization and are often called upon to offer their expertise to the media, public ...

Is this the 'Nvidia killer'? Cerebras’ wafer-scale AI engine sparks supremacy showdown

Dubbed the "Nvidia killer," Cerebras' wafer-scale engine has reportedly crushed Nvidia's H200 in raw AI training power: 125 ...
Ulster University

Accelerating your Research using the Northern Ireland HPC cluster: Hands-on guide with GPU and CPU-based applications - Part 2

This workshop will consider several applications based on machine learning classification and the training of artificial neural networks and deep learning.
insideHPC

ISC 2026 Conference Announces Keynote from Dr. Martin Schulz on the Post-Moore Era

The ISC High Performance conference announced that Professor Dr. Martin Schulz, a leading European expert in large-scale - ...
Morning Overview on MSN

How CUDA turned NVIDIA into the unstoppable AI powerhouse

NVIDIA’s rise from graphics card specialist to the most closely watched company in artificial intelligence rests on a ...
IEEE

3-D Vertical Resistive Switching Random Access Memory (3D-VRRAM) With Multilevel Programming for High-Density, Energy-Efficient In-Memory Computing

Abstract: Resistive random access memory (RRAM) devices offer a broad range of attractive properties for in-memory computing (IMC) applications, such as nonvolatile storage, low read current, and high ...
BBC

Inside the sub-zero lair of the world's most powerful computer

It looks like a golden chandelier and contains the coldest place in the known universe. What I am looking at is not just the most powerful computer in the world, but technology pivotal to financial ...
IEEE

Simulation of Hierarchical Parallel Computing Model for Fluid Machinery Based on Support Vector Machines

Abstract: This paper presents a hierarchical parallel computational model for fluid machinery based on Support Vector Machines (SVM), and applies it to the simulation study of axial flow compressors.