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Recently, a project called Q * was released by the team led by Yan Shuicheng from Kunlun Wanwei in China, in collaboration with a research team from Nanyang Technological University in Singapore. The project aims to improve the inference capabilities of small models. This project differs from OpenAI, yet allows small models to achieve inference abilities comparable to models with tens or even hundreds of times more parameters.

Recently, Kunlun Wanwei, in collaboration with Nanyang Technological University in Singapore, successfully developed an algorithm called Q* that significantly enhances the inference capabilities of existing large models. Q* enables smaller models to achieve inference capabilities comparable to those of models with tens or even hundreds of times more parameters across various datasets, leading to a substantial improvement in model performance while dramatically reducing the demand for computational resources. This brings new possibilities for the widespread application of artificial intelligence and ushers in a new era of efficient intelligence.

Gemini Pro excels in common sense reasoning tasks, and research from Stanford and Meta suggests that Gemini is underrated. Researchers designed a new test set and found that Gemini's performance in complex reasoning tasks is significantly stronger than before. The evaluation includes 11 language-based datasets and one multimodal dataset, showing that Gemini Pro is on par with GPT-3.5. While GPT-4Turbo leads in overall performance, Gemini Pro slightly outperforms in specific tasks. Inference experiments demonstrate that Gem

['Kunlun Wanwei's self-developed TianGong large model achieved an 80% accuracy rate in the Benchmark GSM8K test.', 'The inference capability of the TianGong large model exceeds that of GPT-3.5 and LLaMA2.', 'The TianGong large model performs exceptionally well across multiple datasets.', 'The problem-solving approach of the TianGong large model is simpler and clearer.', 'The TianGong large model will provide strong intelligent support for users and enterprises.']