Nvidia shrinks LLM memory 20x without changing model weights

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 Economist

Top AI models underperform in languages other than English

This illustrates a widespread problem affecting large language models (LLMs): even when an English-language version passes a safety test, it can still hallucinate dangerous misinformation in other ...

Hirundo Uses NVIDIA NeMo Evaluator, CUDA, and GB200 NVL72 to Validate Breakthrough AI Safety Results Across Open-Source LLMs

Machine Unlearning platform powered by the NVIDIA stack demonstrates up to 91% reduction in prompt injections and 95% reduction in bias across foundat ...
Harvard Business Review

LLMs Are Manipulating Users with Rhetorical Tricks

There are three common problems people face when working with AI: not understanding how AI made a decision (opacity), the ...