DeepSeek does not appear to have fully moved beyond Nvidia. The company's technical report reveals that it is using Chinese chips to run the model for inference, but...appears to have adapted only part of V4's training process for Chinese chips.
大多数人认为中国AI公司已经完全摆脱了对Nvidia的依赖，但作者认为DeepSeek V4仍主要依赖Nvidia芯片进行训练，仅在推理阶段使用中国芯片。这一观点挑战了'中国AI已实现完全自主'的主流叙事，暗示技术脱钩比表面看起来更为复杂。
Chinese labs, for their part, are not purely idealistic: Open-source is not only free advertising but also a shrewd workaround. Without access to cutting-edge chips restricted by US export controls, releasing models openly accelerates the cycle of external feedback and contributions that compensates for constrained compute.
大多数人认为中国开源AI是出于理想主义或技术自信，但作者认为这实际上是一种战略性的 workaround（变通方法）。由于无法获得美国限制出口的高端芯片，中国通过开放源代码来加速外部反馈循环，弥补计算能力的不足，这是一种务实而非理想主义的策略。
Chinese open-weight models accounted for 17.1% of global AI model downloads over the year ending in August 2025. That narrowly surpassed the US share of 15.86%—the first time China had led in this metric.
大多数人认为美国在AI领域一直处于绝对领先地位，但作者认为中国开源模型下载量已超过美国，这是全球AI格局发生重大转变的标志。这一数据挑战了人们对AI发展路径的传统认知，表明中国通过开放源代码策略正在赢得全球开发者的青睐。
Chinese models overtook their counterparts built in the U.S. in the summer of 2025 and subsequently widened the gap over their western counterparts.
这是一个惊人的地缘政治技术转变指标，表明中国AI发展速度已超越美国，这可能重塑全球AI竞争格局和权力平衡。这种领先差距的扩大暗示着中国在开源AI模型领域的战略投入和执行力显著增强。
Qwen3.5 397B A17B: 15.3%, DeepSeek V3.2: 14.5%, GLM-5: 14.5%, Kimi K2.5: 11.5%, MiniMax-M2.7: 10.6%
中美专业服务 Agent 的差距在这里变得具体可见：顶级美国模型 33%，中国最强开源模型（Qwen3.5、DeepSeek、GLM-5）约 14-15%，差距超过 2 倍。更值得注意的是智谱 AI 的 GLM-5 与 DeepSeek V3.2 并列，说明在专业服务 Agent 这个维度，国内头部玩家的能力相当接近。对于智谱的战略意义：这个 2 倍差距是否可以通过领域专精（比如专注于中国本土金融场景）来弥补？
Tang Jie (CEO of Zhipu AI) even recently said: "The truth may be that the gap [between US and Chinese AI] is actually widening."
智谱 CEO 唐杰亲口承认差距可能正在扩大——这句话的分量极重。在中国 AI 公司普遍对外宣称「与美国差距不大」的舆论环境下，一位领军者公开说出这句话，是罕见的清醒与坦诚。这与本文的核心论点完全吻合：算力差距在出口管制和国内芯片滞后的双重压力下，短期内很难缩小。对智谱内部的战略制定而言，这句话的代价和勇气都值得深思。
Just last year, Anthropic spent over ten times more on compute than Minimax and Zhipu AI combined, and the gap is even wider for OpenAI:
这个数字对国内 AI 从业者而言极为刺耳：Anthropic 一家的算力投入就超过智谱 AI 和 MiniMax 合计的十倍以上，而与 OpenAI 相比差距更大。所谓「中美 AI 竞争激烈」的叙事背后，是一场体量悬殊的不对称战争——不是同一量级的竞争，而是大卫与歌利亚的对决。对智谱这样的公司，这既是警醒，也是生存战略的根本约束。
in the past year Huawei has overtaken Nvidia as the leading source of AI computing power in China, at least in terms of rated FLOP/s
大多数人可能认为Nvidia在中国市场仍然占据主导地位，但作者认为华为已经超过Nvidia成为中国AI计算能力的主要来源。这一发现挑战了人们对Nvidia在中国市场不可动摇地位的认知，表明本土替代技术可能比预期更快地获得市场份额。
We estimate that as of the end of 2025, Chinese companies collectively own just over 5% of the cumulative computing power of the leading AI chips sold in recent years
考虑到中国AI产业的快速发展和政府对AI的大力投资，大多数人可能认为中国拥有更大比例的全球AI计算能力，但作者认为中国公司仅拥有约5%的全球AI计算能力。这一数字远低于人们的预期，挑战了关于中国AI技术实力的普遍认知。
Low-cost Chinese AI models forge ahead, even in the US, raising the risks of a US AI bubble Nvidia’s latest earnings report reassured some. But Chinese AI models are fast gaining a following around the world, underlining concerns over an ‘AI bubble’ centered on high-investment, high-cost US models.
Rather than building superintelligence, Chinese companies have been more interested in embedding AI into robots and manufacturing lines.
a diff approach to ai-all-the-things in china compared to sv
The Communist Party lives for whole-of-society efforts.
in contrast to SV. Note that the EU is also talking (not doing yet I think) whole of society efforts.
One advantage for Beijing is that much of the global AI talent is Chinese. We can tell from the CVs of researchers as well as occasional disclosures from top labs (for example from Meta) that a large percentage of AI researchers earned their degrees from Chinese universities. American labs may be able to declare that “our Chinese are better than their Chinese.” But some of these Chinese researchers may decide to repatriate. I know that many of them prefer to stay in the US: their compensation might be higher by an order of magnitude, they have access to compute, and they can work with top peers. 5But they may also tire of the uncertainty created by Trump’s immigration policy. It’s never worth forgetting that at the dawn of the Cold War, the US deported Qian Xuesen, the CalTech professor who then built missile delivery systems for Beijing. Or these Chinese researchers expect life in Shanghai to be safer or more fun than in San Francisco. Or they miss mom. People move for all sorts of reasons, so I’m reluctant to believe that the US has a durable talent advantage.
global talent wrt AI is largely Chinese, even if many of them currently reside in the USA
it’s not obvious that the US will have a monopoly on this technology, just as it could not keep it over the bomb.
compares AI dev and attempts to keep it for oneself to the dev of atomic bombs and containment
Chinese efforts are doggedly in pursuit, sometimes a bit closer to US models, sometimes a bit further. By virtue of being open-source (or at least open-weight), the Chinese models have found receptive customers overseas, sometimes with American tech companies.
China's efforts are close to the US results, and bc of open source and/or open weight models, finding a diff path to customers.
NVIDIA lost ~$593bn in market cap as investors panicked that AI maybe wasn’t an American monopoly after all.
yup. key phrase, much of the AI bubble is the presumption of US monopoly. Watching other, sometimes less visible efforts is important wrt autonomy, sovereignty
in 2023, the Chinese leadership directly asked the Biden administration to add something else to the agenda, which was to add AI risk to the agenda. and they ultimately agreed on keeping AI out of the nuclear command and control syste
for - example - collaboration - AI - china proposed
for - report - America's Superintelligence Project - definition - ASI - Artificial Super Intelligence
summary - What is the cost of mistrust between nation states? - The mistrust between the US and China is reaching an all-tie high and it has disastrous consequences for an AI arms race - It is driving each country to move fast and break things, which will become an existential threat to all humanity - Deep Humanity, with an important dimension of progress traps can help us navigate ASI
These Measures do not apply where industry associations, enterprises, education and research institutions, public cultural bodies, and related professional bodies, etc., research, develop, and use generative AI technology, but have not provided generative AI services to the (mainland) public.
These regulations only apply to public services, not to internal uses of AI.
Title : Artificial Intelligence and Democratic Values: Next Steps for the United States Content : In Dartmouth University , appears AI as sciences however USA motionless a national AI policy comparing to Europe where The Council of Europe is developing the first international AI convention and earlier UE launched the European data privacy law, the General Data Privacy Regulation.
In addition, China's efforts to become “world leader in AI by 2030, as long as China is developing a digital structures matched with The one belt one road project . USA , did not contribute to UNESCO AI Recommendations however USA It works to promote democratic values and human rights and integrate them with the governance of artificial intelligence .
USA and UE are facing challenges with transatlantic data flows , with Ukrainian crises The situation became more difficult. In order to reinstate leadership in AI policy, the United States should advance the policy initiative launched last year by the Office of Science and Technology Policy (OSTP) and Strengthening efforts to support AI Bill of rights .
EXCERPT: USA believe that foster public trust and confidence in AI technologies and protect civil liberties, privacy, and American values in their application can establish responsible AI in USA. Link: https://www.cfr.org/blog/artificial-intelligence-and-democratic-values-next-steps-united-states Topic : AI and Democratic values Country : United States of America