news-13082024-060146

Alibaba recently announced the success of its new open-source large model Qwen2-Math, which has been designed to excel in mathematical problem-solving. The tech giant claims that this advanced AI model achieves an impressive 84% accuracy rate when handling algebra and geometry problems, surpassing competitors like OpenAI’s GPT 4o and Google’s Gemini 1.5 Pro.

The Qwen2-Math model is an extension of Alibaba’s existing Qwen2 model, specifically tailored to tackle complex math challenges. It was trained using a vast and high-quality math corpus, allowing it to demonstrate superior performance in various mathematical tasks. While the current version of the model only supports English, Alibaba has revealed plans to release a bilingual version in the near future.

To test the capabilities of Qwen2-Math, the Alibaba team subjected it to rigorous benchmarks, including math problems from China’s GaoKao (college entrance exam) and questions from the US math competition AIME. The results of these tests further validated the model’s ability to handle advanced mathematical concepts with precision and accuracy.

In addition to its impressive performance in mathematical problem-solving, Alibaba is also looking to leverage the capabilities of Qwen2-Math to support small merchants during Singles Day, one of the biggest shopping events in China. The company has allocated RMB 2 billion in subsidies to empower small businesses and enhance their participation in the annual shopping extravaganza.

By investing in the development and deployment of cutting-edge AI technology like Qwen2-Math, Alibaba aims to not only strengthen its own technological capabilities but also empower small businesses and drive economic growth. The integration of advanced AI models into everyday operations has the potential to revolutionize various industries and pave the way for new opportunities and innovations. With its commitment to innovation and excellence, Alibaba continues to set new standards in the field of artificial intelligence and machine learning.