The Rapid Evolution of AI: A Comparative Analysis of China and the United States
The Changing Landscape of AI
Recently, the field of artificial intelligence, especially the competition between China and the United States, has been evolving at an astonishing pace. Many are curious about the gap between the two countries, the latest breakthroughs, and the reasons behind the rapid changes. A few months ago, discussions centered around a certain model, but suddenly, the landscape shifted. To gain a deeper understanding, we will examine reports from Artificial Analysis, an independent AI standard test provider.
The Significance of Artificial Analysis Reports
Artificial Analysis reports are highly regarded in the industry due to their independence and comprehensive testing system. They offer valuable insights into various aspects of AI, including the DeepSeek RE model. On platforms like X, Wenda, Lex, and Friedman have responded to these reports. Our goal is not to merely glance at news headlines but to delve deeper into the reports, such as the AI status reports for the first and second quarters of 2025, and a special analysis of DeepSeek RE updates.
China and the United States in the AI Model Race
The first important piece of news from the Artificial Analysis report in the second quarter of 2025 is the significant reduction in the smart level gap between the top AI models in China and the United States. The gap has been shortened to less than three months, based on an assessment system that combines seven difficult evaluation standards. These include MMLU-PRO, GPQA-DIAMOND, Amy's mathematical competition topic, Humanity's Last Exam, and Leibkot Bench. The latest DeepSeek model has almost caught up with the flagship model of OpenAI, breaking the perception of a large gap between China and the United States.
Driving Forces in the AI Field
In the United States, OpenAI remains a major driving force at the front-end intelligence level, with a standard model range from O1 to O3. In China, DeepSeek and Alibaba's Damo Institute are the two major driving forces, quickly pushing up the intelligence level of China's top-tier models. This has profound implications, including intensifying global AI competition, shortening the innovation period, and increasing the uncertainty of the future pattern.
The Open Source Model Revolution
In the field of open source models, the situation has reversed, with China overtaking and gaining a leading position. The change occurred in November 2024 when Alibaba released the Queen model, which surpassed Meta's flagship open-source model Lama 3.1 405B in intelligence. The report attributes this to a strategic difference, with Chinese AI laboratories choosing to open up their most capable and flagship models. This open strategy has greatly promoted the development and prosperity of China's open AI ecosystem.
The Role of DeepSeek in the Open Source Revolution
DeepSeek R1 is a milestone in the open source revolution. The version released in January 2025 was the first to compete with OpenAI's OE open source model, and the R10528 version updated in May 2025 is currently one of the most capable open source full-scale models globally. For developers, researchers, and technology enthusiasts, China's leadership in the open source field means greater access to top-level AI capabilities.
The Leap of DeepSeek R1
The report highlights the significant leap in the capabilities of DeepSeek R1, especially in the just-released update. The update is a comprehensive and significant improvement, with increases in scores on several key standard tests. The underlying model structure of DeepSeek RE has not changed, but the huge performance improvement is mainly due to the post-training stage, specifically the application and optimization of technology for strengthening learning.
The Importance of Reinforcement Learning
Reinforcement learning allows the model to learn through trial and error and reward mechanisms, making the output more in line with human preferences or performing better on specific tasks. In recent years, RL has played an increasingly important role in improving the model, especially in improving the ability to reason. The report quotes the example of OpenAI to illustrate the importance of RL for reaching the top intelligent level, and the update of DeepSeek RE shows that they are also able to keep up with the pace of RL expansion.
Other Factors Affecting RE Performance
In addition to RL, the report also mentions other factors that help explain the improvement of RE performance, such as thinking time. The new version of RE0528 consumes more tokens, indicating deeper thinking and internal processing. This increased thinking time is believed to be an important factor in improving the model's performance in complex reasoning tasks. The report also mentions the balance and difference between the depth of reasoning and efficiency of different models.
The Specific Capabilities of the Model
The coding capabilities of the R1 update are also a highlight. The new version of R1 has reached a very top-notch level in terms of code generation and understanding, leveling off GEMLA 2.0 Pro and similar to OpenEdge O4 Mini and O3. The report also mentions a special analysis about the model general relationship number and data stream, which provides an interesting perspective on the source of model training data.
Key Trends in the AI Field
The Artificial Analysis report also highlights several key trends in the AI field, including the importance of reasoning models, the popularity of the MOE architecture, and the progress in multi-modality. Reasoning models are now the leading force in promoting smart frontiers, while the MOE architecture allows for more efficient model training and reasoning. In terms of multi-modality, China has reached a military level in text-to-photo production, and the United States is currently a little ahead in video production.
Cost and Speed in the AI Field
Cost and speed are also important considerations in the AI field. The report points out that the cost of intelligent reasoning is rapidly decreasing, but the actual total calculation needs may continue to grow due to the popularization of reasoning models and applications such as AI Agent. AI Agent is believed to be an important direction for the development of the next generation of AI, but it is still in the process of rapid development and improvement.
Core Insights for AI Enthusiasts
For those working hard to catch up with the wave of AI, there are two key points to keep in mind. The first is the speed of development, as the field is changing rapidly and advanced AI capabilities are emerging at an unprecedented rate. The second is the generalization of technology, especially the innovation of open-source models, which has opened up a huge space for innovation and application.
The Source of DeepSeek R1 Training Data
Finally, the report leaves us with an interesting question about the source of DeepSeek R1 training data. When AI models become more and more powerful and start to learn from each other, their origins, that is, training their data, especially the output of other powerful models that may be included, to what extent does it create their abilities, their potential bias, and even their worldview? This is a question that requires further exploration and consideration.
In conclusion, the field of artificial intelligence is evolving rapidly, and the competition between China and the United States is driving innovation and progress. By examining reports from independent AI standard test providers like Artificial Analysis, we can gain valuable insights into the latest trends and developments in the field. As AI continues to develop, it is important to stay informed and adapt to the changing landscape.
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