AI Leadership Depends on What is Measured
AI Leadership Depends on What is Measured
Executive Summary:
- Chinese open-source Large Language Models (LLMs) perform better than Western ones, according to a recent report from an artificial intelligence evaluation organization SuperCLUE.
- Chinese LLMs also excel in cost-efficiency, scalability, and localized applications, with advancements in edge devices and use cases in the health and automotive sectors.
- The benchmark report shows international models still lead in reasoning, multi-modal tasks, and AI agent capabilities.
- Leadership in AI is multi-dimensional and depends on the metrics used for evaluation. Accurate assessment requires contextualizing benchmarks, understanding priorities, and recognizing that distinct national strategies and objectives shape AI development.
In November 2024, the Chinese artificial intelligence (AI) organization SuperCLUE, which describes itself as an “independent, 3rd-party AGI evaluation organization (独立第三方AGI测评机构)” released its “Chinese Large Model Benchmark 2024 October Report” (SuperCLUE, November 8; WeChat/SuperCLUE, November 18). The report offers insights into the global state of large language models (LLMs) and captures trends in the current AI landscape. It uses the SuperCLUE framework to assess the progress and challenges faced by models from the People’s Republic of China (PRC) and international leaders.
