VentureBeat

Google's new neural-net LLM architecture separates memory components to control exploding costs of capacity and compute

A new neural-network architecture developed by researchers at Google might solve one of the great challenges for large language models (LLMs): extending their memory at inference time without ...

Neural holography enabled multi-beam steering for multi-task classifier

SHANNON, CLARE, IRELAND, October 13, 2026 /EINPresswire.com/ -- Announcing a new publication from Opto-Electronic ...
Semiconductor Engineering

How Neural Super Sampling Works: Architecture, Training, And Inference

This blog post is the second in our Neural Super Sampling (NSS) series. The post explores why we introduced NSS and explains its architecture, training, and inference components. In August 2025, we ...
techtarget

Machine learning vs. neural networks: What's the difference?

Machine learning and neural networks are two common terms in AI -- but what do they mean, and how do they differ? What exactly is machine learning? Machine learning is a subset of AI. ML uses an ...
Ars Technica

Researchers isolate memorization from problem-solving in AI neural networks

When engineers build AI language models like GPT-5 from training data, at least two major processing features emerge: memorization (reciting exact text they’ve seen before, like famous quotes or ...