Amid chip shortages, China’s AI start-ups are re-engineering their algorithms, hoping more efficient architecture will do the heavy lifting.

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 smarter code, 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 pace with global…

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