After 30 months of fast-paced innovation in quantum algorithms, six research groups are hoping to hit paydirt. But there can be only one big winner—if there is a winner at all.

Nvidia faces competition from startups developing specialised chips for AI inference as demand shifts from training large ...

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.

Abstract: This article introduces a reactive methodology tailored for a wide range of practical graph-based path planning applications. In these scenarios, a robot with limited sensor capabilities ...

Abstract: Deep learning compilers optimize DNN program execution by capturing them as operator-based computation graphs. However, developers’ deep learning programs often contain complex Python ...