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.

The latest GPT-5.4 mini model delivers benchmark results surprisingly close to the full GPT-5.4 model while running much faster, signaling a shift toward smaller AI models powering real-world ...

In large retail operations, category management teams spend significant time deciding which product goes onto which shelf and in which order. Shelf space is very expensive real estate in retail.

Electrical distribution systems are characterized by dynamic operating conditions and complex network topologies, which pose significant challenges for the effective deployment of protection schemes.

Abstract: Modern electronic devices demand ever-smaller, higher-performance printed circuit boards (PCBs), yet miniaturization and complex service environments exacerbate failure risks. We first ...

Where do AI systems lose confidence in your content? Discovery, selection, crawling, rendering, and indexing hold the answer.

Matrix-based optimizers have attracted growing interest for improving LLM training efficiency, with significant progress centered on orthogonalization/whitening based methods. While yielding ...

Abstract: Optimization algorithms are widely employed to tackle complex problems, but designing them manually is often labor-intensive and requires significant expertise. Global placement is a ...

When we talk about the cost of AI infrastructure, the focus is usually on Nvidia and GPUs — but memory is an increasingly important part of the picture. As hyperscalers prepare to build out billions ...