This article outlines the design strategies currently used to address these bottlenecks, ranging from data center systolic ...

Nvidia's KV Cache Transform Coding (KVTC) compresses LLM key-value cache by 20x without model changes, cutting GPU memory costs and time-to-first-token by up to 8x for multi-turn AI applications.

This paper proposes a new algorithm that allows us to compute pairwise-correlation sensitivities in a Monte Carlo framework by modifying only one trajectory at ...

The soaring cost and limited supply of computer memory is slowing some projects — and spurring creative approaches.

A new study explores how artificial intelligence models can support clinical decision-making for sepsis management. Their research, titled “Responsible AI for Sepsis Prediction: Bridging the Gap ...

The memory chip shortages probably won't last forever.

Nvidia has a structured data enablement strategy. Nvidia provides libaries, software and hardware to index and search data ...

Exponential increases in data and a mix of performance requirements are driving a top-to-bottom rethinking of what works best ...

On the post-quantum side, Cryptolib now includes hardware-accelerated implementations of three families of NIST-standardized PQC algorithms: ML-KEM, ML-DSA, and SLH-DSA. The SLH-DSA (SPHINCS+) ...

In the era of A.I. agents, many Silicon Valley programmers are now barely programming. Instead, what they’re doing is deeply, ...

Generations often struggle to understand each other, with daily habits serving as the biggest points of confusion.