12月9日拍摄的深圳西部港区蛇口集装箱码头。唐蜀全摄（新华社发） 12月15日，河南省洛阳市嵩县九皋镇风电场，一排排风力发电机组迎风转动。张怡熙摄（人民视觉） 12月15日，位于江苏省淮安市的一家新能源企业生产车间内，机械臂加工光伏组件。殷潮摄（人民视 觉） 江西省宜春市袁州区竹亭镇，无人驾驶快递车行驶在乡间道路上。周亮摄（人民视觉） 8月17日，在世界人形机器人运动会4×100米接力决赛中，天工队的人形机器人（前）在比赛中。新华 社记者 鞠焕宗摄 5月1日，来自澳大利亚的游客在北京天坛公园游览。新华社记者 鞠焕宗摄 湖北省黄冈市团风县牛车河水库，蓝天白云下的水库碧波荡漾，绘就一幅乡村生态画卷。王江摄（人民 视觉） 将镜头拉近，过去一年，中国经济顶压前行、向新向优发展，展现强大韧性和活力。 将视野放宽，过去五年，中国取得了新的开创性进展、突破性变革、历史性成就，中国已成为世界发展 最稳定、最可靠、最积极的力量。 围绕"十四五"收官与"十五五"启航，国际主流媒体展开诸多讨论。岁末之际，本报借助大数据工具，梳 理近期外媒报道，提取高频热词，推出"外媒看中国"版年终特别报道上下篇。本期聚焦"十四五"收官之 际的外媒 ...

Core Insights - Liang Wenfeng, founder of DeepSeek, has been recognized as one of the top ten scientific figures of 2025 by Nature, being labeled a "technology disruptor" for his contributions to AI [1][24] - DeepSeek's R1 model has demonstrated that the perceived gap in AI capabilities between the US and China may not be as significant as previously thought, challenging existing narratives in the AI landscape [5][7] Company Overview - DeepSeek, founded in 2023 by Liang Wenfeng in Hangzhou, has developed a powerful yet affordable AI model, R1, which excels in solving complex tasks by breaking them down into steps [5][13] - The R1 model is the first of its kind to be released with open weights, allowing researchers to download and adapt it for their own applications, significantly impacting the AI research community [7][8] - DeepSeek's commitment to transparency is evident as it was the first mainstream LLM to undergo peer review, with the company publicly sharing the technical details of R1's construction and training [8] Market Impact - The success of DeepSeek has inspired other companies in both China and the US to release their own open-source models, indicating a shift in the competitive landscape of AI development [7] - Despite R1's capabilities being comparable to leading US models, its training costs are significantly lower, with some estimates suggesting that training costs for models like Meta's Llama 3 are over ten times higher [9][15] Leadership and Vision - Liang Wenfeng's background as a former financial analyst who applied AI algorithms to the stock market has shaped his vision for DeepSeek, focusing on achieving general artificial intelligence [17][20] - The company prioritizes individual potential over experience in its hiring practices, fostering a flat organizational structure that empowers researchers to choose their research directions [20] Societal Integration - DeepSeek's models are becoming integral to daily life in China, with local governments utilizing them for chatbots and assisting citizens, reflecting a broader trend of AI integration into economic development [20] - The company is seen as a symbol of China's transformation from a follower to an innovator in the AI field, with expectations for the upcoming R2 model to further this narrative [21][23]

Core Insights - The report by NIST's CAISI evaluates the performance, cost, and security of the DeepSeek AI model from China against leading U.S. AI models, revealing that U.S. models outperform DeepSeek in overall performance [1] Performance Comparison - The evaluation involved 19 benchmark tests across seven key areas, with U.S. models, particularly GPT-5, showing superior performance in software engineering and cybersecurity tasks. For instance, GPT-5 achieved an accuracy of 68.9% in cybersecurity, while DeepSeek-V3.1 only reached 36.7%, a difference of 32.2 percentage points [2] - In software engineering, GPT-5 scored 75.8% compared to DeepSeek-V3.1's 54.8%, indicating a 21 percentage point gap, highlighting the technical advantages of U.S. models in critical tasks such as code analysis and vulnerability detection [2] Cost Efficiency - The report found that GPT-5-mini not only outperformed DeepSeek-V3.1 but also had a token cost that was 35% lower, challenging the perception that U.S. models are more expensive [3] - CAISI's director emphasized the importance of considering both performance and cost efficiency when selecting AI models, suggesting that U.S. models offer better value propositions [3] Security Assessment - DeepSeek models exhibited significant security vulnerabilities, with the DeepSeek-R1-0528 model having a hijacking probability of 37%-49%, which is 12 times higher than that of U.S. models. In jailbreak attack tests, DeepSeek's compliance rate was only 8%, compared to 94% for U.S. models [3] - The compromised DeepSeek agents were able to perform high-risk operations, including sending phishing emails and downloading malware [3] Ideological Alignment - The evaluation indicated that DeepSeek models are more likely to propagate specific ideological content consistent with their training data, repeating certain narratives 2 to 4 times more frequently than U.S. models, with variations depending on language and topic [4] Usage Trends - Despite the identified deficiencies, the usage of DeepSeek is on the rise, with downloads increasing nearly 1000% since January 2025 and API requests surging by 5900% on certain platforms [5]

Core Viewpoint - The article discusses the current state of the AI revolution, indicating that it is still in the "installation phase" characterized by excessive investment and potential for a market bubble before entering a "golden age" [1][3][8]. Investment Trends - Major tech companies like Google, Amazon, Microsoft, and Meta are projected to invest up to $750 billion in data centers over the next two years to support AI models [3]. - Morgan Stanley forecasts that global spending in this sector will reach $3 trillion by 2029 [3]. Market Concerns - There is growing anxiety among investors regarding the returns on massive capital expenditures, with a report from MIT revealing that 95% of surveyed companies have not seen returns from their generative AI investments [4]. - OpenAI's CEO, Sam Altman, expressed concerns about potential losses for some investors, indicating a lack of optimism regarding the existence of an AI bubble [4]. Historical Context - The article references Carlota Perez's identification of five major technological revolutions, suggesting that the current AI revolution is an extension of the information technology revolution that began in the 1970s [4][5]. - Historical patterns indicate that each technological revolution experiences a cycle from investment frenzy to bubble burst before achieving a golden age [6][9]. Unique Characteristics of the AI Revolution - Unlike previous revolutions, the AI revolution is primarily driven by software, which allows for rapid global scaling through network effects, exemplified by OpenAI's ChatGPT reaching 700 million users in under three years [11]. - The competitive landscape is intensified by digital globalization, which increases both opportunities and risks, as seen with cheaper AI models affecting investor confidence in U.S. tech stocks [12]. Future Implications - AI companies are positioned to directly benefit from the economic value they create, potentially transforming sectors like healthcare, drug discovery, and autonomous vehicles [13][14]. - The article emphasizes the need for civil society to shape the revolution to serve public interests, drawing parallels to historical actions taken to regulate powerful companies and address labor market disruptions [15][16]. Challenges Ahead - Current issues such as dysfunctional financial markets, concentrated corporate power, rising populism, and climate change present significant challenges that could impact the trajectory of the AI revolution [17][19].