机器之心报道 机器之心编辑部 在 30 日， 斯坦福大学教授，人工智能著名学者 吴恩达 就写了一封长信，从各个角度分析了中美人工智能竞争的态势，也表达了中国势必在人工智能领域超越美 国的发展预期。 。 中国在人工智能领域已经成为全球竞争的重要力量。根据斯坦福 2025 年 AI 指数报告，美国虽然仍领先于顶级模型数量，但中国正在迅速缩小差距 —— 在 MMLU、HumanEval 等基准测试中的差距已从几乎双位数下降到几乎持平。 而最近召开的 WAIC 大会，AI 应用，智能体，新模型不断更新迭代，显示了中国在人工智能方面的迅猛发展。 在目前的情势下，特朗普也意识到需要给美国人工智能的行业发展加加速了。 近期，特朗普阐述了一项新的 「人工 智能行 动计划」 （AI Action Plan），其中包含鼓励美国 AI 产业发展的政策指南。详细信息可以参考 机器之心之前的报道 「美国是人工智能竞赛的发起国，」特朗普在演讲中说道，「作为美国总统，我今天在这里宣布，美国将赢得这场竞赛。」 在这种近乎「自由放任」的产业政策下，特朗普期望能够允许人工智能 在最少的监管下发展 ，刺激美国在人工智能领域保持领先。 但事实是否真 ...

Core Viewpoint - The article highlights the rapid advancements and performance improvements of the Qwen3-30B-A3B-Instruct-2507 model, emphasizing its capabilities in reasoning, long text processing, and overall utility compared to previous models [2][4][7]. Model Performance Enhancements - The new model Qwen3-30B-A3B-Instruct-2507 shows significant improvements in reasoning ability (AIME25) by 183.8% and capability (Arena-Hard v2) by 178.2% compared to its predecessor [4]. - The long text processing capability has been enhanced from 128K to 256K, allowing for better handling of extensive documents [4][11]. - The model demonstrates superior performance in multi-language knowledge coverage, text quality for subjective and open tasks, code generation, mathematical calculations, and tool usage [5][7]. Model Characteristics - Qwen3-30B-A3B-Instruct-2507 operates entirely in a non-thinking mode, focusing on stable output and consistency, making it suitable for complex human-machine interaction applications [7]. - The model's architecture supports a context window of 256K, enabling it to retain and understand large amounts of input information while maintaining semantic coherence [11]. Model Series Overview - The Qwen series has released multiple models in a short time, showcasing a variety of configurations and capabilities tailored for different scenarios and hardware resources [12][18]. - The naming convention of the models is straightforward, reflecting their parameters and versions, which aids in understanding their specifications [14][17]. Conclusion - The Qwen3 series is positioned as a comprehensive model matrix, catering to diverse needs from research to application, and is ready to address various demands in the AI landscape [19].

Core Insights - The article highlights the rapid advancements in open-source AI models, particularly focusing on the Qwen3 series, which has achieved significant milestones in performance and capabilities [1][2][3]. Group 1: Model Performance - The newly released Qwen3-235B-A22B-Thinking-2507 model has been recognized as the "strongest open-source model globally," surpassing top closed-source models like Gemini-2.5 Pro and o4-mini [3][7]. - In the "final exam for humans," the latest model scored 18.2, an improvement from 11.8 in the previous version, outperforming competitors such as DeepSeek-R1-0528 and OpenAI o4-mini [13][14]. - The Qwen3 series has achieved state-of-the-art (SOTA) results in various benchmarks, including MMLU-Pro, GPQA, and LiveCodeBench, demonstrating superior performance in knowledge, reasoning, and programming tasks [11][16][32]. Group 2: Open-Source Impact - The rapid release of three models in a short period has positioned Qwen3 as a leader in the open-source AI landscape, with significant interest and usage reflected in API call volumes exceeding 100 billion tokens [6][31]. - The article emphasizes that the advancements in open-source AI, particularly from Chinese companies like Alibaba, are reshaping the global landscape, with Qwen models surpassing previous leaders like the Llama series [33][37]. - Alibaba plans to invest over 380 billion yuan in cloud and AI hardware infrastructure over the next three years, indicating a strong commitment to enhancing its AI capabilities [38]. Group 3: Industry Recognition - The achievements of the Qwen3 series have garnered attention from industry leaders, with discussions highlighting the success of open-source models and their potential to challenge established closed-source counterparts [29][36]. - The article notes that the speed of development in China's open-source AI sector is rapidly closing the gap with closed-source models, suggesting a shift in the competitive landscape [39][40].