How China’s AI start-ups are rewiring the way models remember

As access to advanced chips narrows, Chinese AI developers are focusing on fixing an algorithmic bottleneck at the heart of large language models (LLMs) – hoping that more efficient architecture, not more powerful hardware, will help them steal a march on their Western rivals. By experimenting with hybrid forms of “attention” – the mechanism that allows LLMs to process and recall information – start-ups such as Moonshot AI and DeepSeek aim to stretch limited computing resources, while keeping...