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 ...
IEEE

A Novel Framework for RDF Schema Extraction in NoSQL Databases Using Sentence-BERT

Abstract: NoSQL databases, known for their flexibility and scalability, have become pivotal in handling diverse and unstructured data. However, their schema-less nature introduces significant ...
IEEE

Semiconductor Memory Technologies: State-of-the-Art and Future Trends

Abstract: This article surveys the recent development of semiconductor memory technologies spanning from the mainstream static random-access memory, dynamic random-access memory, and flash memory ...