Rambus targets AI memory bottlenecks with new HBM4E controller IP

The new HBM4E Controller builds on Rambus’s track record of more than 100 HBM design wins and the company’s long-standing ...

SOCAMM2 Is The Memory Standard AI Is Looking For

AI infrastructure can't evolve as fast as model innovation. Memory architecture is one of the few levers capable of accelerating deployment cycles. Enter SOCAMM2 ...

Scientists make a pocket-sized AI brain with help from monkey neurons

A new study suggests AI systems could be a lot more efficient. Researchers were able to shrink an AI vision model to 1/1000th ...

Google’s Titans And MIRAS: Significant Advancement In Long-Context AI

Google's new Titans architecture and MIRAS framework enable AI to handle massive amounts of data and work faster.
InfoQ

Hybrid Cloud Data at Uber: How Engineers Solved Extreme-Scale Replication Challenges

Uber’s HiveSync team optimized Hadoop Distcp to handle multi-petabyte replication across hybrid cloud and on-premise data lakes. Enhancements include task parallelization, Uber jobs for small ...
Chiang Rai Times

OpenAI’s Push to Own the Developer Ecosystem End-to-End

That's why OpenAI's push to own the developer ecosystem end-to-end matters in26. "End-to-end" here doesn't mean only better models. It means the ...
IEEE

Memory Robot Design: A New Perspective From Human Brain Model and Large Language Model

Abstract: With the spread of generative AI, the study proposed a memory-based cognitive robot architecture by using a Large Language Model (LLM), inspired by the working memory of the human brain ...
Software Engineering Institute

Temporal Memory Safety in C and C++: An AI-Enhanced Pointer Ownership Model

This podcast explores updates to the Pointer Ownership Model for C, a modeling framework designed to improve the ability of developers to statically analyze C programs for errors involving temporal ...
VentureBeat

Nvidia’s new technique cuts LLM reasoning costs by 8x without losing accuracy

Researchers at Nvidia have developed a technique that can reduce the memory costs of large language model reasoning by up to eight times. Their technique, called dynamic memory sparsification (DMS), ...
IEEE

Development of a Long Short-Term Memory (LSTM)-Based Statistical Model for Earthquake Forecasting in Central Asia

Abstract: Earthquake forecasting using traditional methods remains a complex task due to the inherent nonlinearity and stochastic nature of seismic activity. Therefore, this study examines the ...