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 ...

'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 ...
Semiconductor Engineering

Will In-Memory Processing Work?

The cost associated with moving data in and out of memory is becoming prohibitive, both in terms of performance and power, and it is being made worse by the data locality in algorithms, which limits ...
Nanowerk

Novel photodetector integrates event sensing and memory for optical processing

(Nanowerk Spotlight) Optical information processing is a critical technology for applications ranging from machine vision to high-speed optical communication. However, current photodetection systems ...