The memory supercycle is here — and the AI funding frenzy is pouring fuel on it

That’s a nine-fold expansion in four years. No segment in chip history has ever scaled that fast at that size. By 2026, memory alone is projected to reach $550 million to $570 billion — roughly 55% to ...

'Observational memory' cuts AI agent costs 10x and outscores RAG on long-context benchmarks

As AI agents move into production, teams are rethinking memory. Mastra’s open-source observational memory shows how stable ...

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

Nvidia researchers developed dynamic memory sparsification (DMS), a technique that compresses the KV cache in large language models by up to 8x while maintaining reasoning accuracy — and it can be ...
Nature

Dynamic Random Access Memory Technologies

Dynamic random access memory (DRAM) remains a cornerstone of modern electronic systems, enabling rapid data storage and retrieval. Recent developments have focused on capacitorless designs – notably ...
Nature

Dynamic Random Access Memory Security and Efficiency

Dynamic Random Access Memory (DRAM) remains a central element in computing architectures, but its intrinsic vulnerabilities and power demands have spurred a wealth of research focused on enhancing ...
Semiconductor Engineering

Dynamic KV Cache Scheduling in Heterogeneous Memory Systems for LLM Inference (Rensselaer Polytechnic Institute, IBM)

A new technical paper titled “Accelerating LLM Inference via Dynamic KV Cache Placement in Heterogeneous Memory System” was published by researchers at Rensselaer Polytechnic Institute and IBM. “Large ...
Opinion

From AI data centres to your next smartphone: The memory bottleneck is everyone’s problem

The memory shortage risks becoming a broader supply-chain problem. Unlike the pandemic-era chip crunch, which was driven largely by logistics and temporary disruptions, today’s shortage stems from a s ...