China's AI Leaders Keep Quiet: Is The US 'Slowing Down' Alarm Just Marketing?
Americans fear rising AI risks while Chinese tech giants stay silent on the issue
The latest news from Silicon Valley reads like a horror movie. OpenAI's Sam Altman and Elon Musk want to hit the brakes on artificial intelligence development. Anthropic's Dario Amodei warned of uncontrollable risks. Nvidia's Jensen Huang pushed back saying speed and safety can coexist. Yet across the ocean in China, the tech giants are strangely silent. Z.ai, Moonshot, MiniMax, Alibaba and Tencent have not echoed these warnings. They did not even respond when CNBC asked them about the concerns raised by their American counterparts. This creates a fascinating contrast in how two of the world's largest economies view the future of technology. For the average consumer, this silence might signal a shift in what you can expect from the market.
The conversation around AI safety has dominated headlines lately. US executives used the weekend to call for a slowdown in development. They cited potential risks that could spiral out of control. This rare display of industry unity was quickly followed by Dario Amodei's latest essay. He urged US companies to maintain their lead over China. His company published a similar paper in May. The Chinese foreign ministry reacted on Monday calling these US executive comments "fear-mongering." English state media used metaphors like "Cold War playbook" and "Dr. Frankenstein" to describe the warnings. In this atmosphere of geopolitical tension, Chinese companies have chosen a different path. They are simply not engaging with the hype. Ray Von, founder and CEO of Tencent-backed OpenPie, sees this as a strategic choice. His startup builds devices for companies to use AI securely on internal data. Von believes the publicity is "a little bit oversold." He explained that in China, people do not pay too much attention because this is not the first time US executives have made similar claims. "They should just do it," Von said in a phone interview on Tuesday. This suggests that for Chinese companies, the practical application matters more than the philosophical debate.
From a philosophical perspective, the silence speaks volumes. Renjie Guo, founder and CEO of JoyIn, offered an interesting take. He suggests that US companies only issue AI warnings after Chinese companies create superior models. Guo believes this is not a coincidence. He expects AI is only as dangerous as its developers. Just like humans, AI will conclude that "truth, goodness and beauty" are the best approach. This viewpoint contrasts sharply with the narrative of impending doom often found in Western media. It frames AI development as a constructive process rather than a risky experiment. However, the Chinese government is not asleep at the wheel. Beijing kicked off its own annual cybersecurity week. On Monday, they released the third edition of an "AI Safety Governance Framework." This bilingual document lays out specific guidelines for labeling AI content and developing systems for rapid AI risk detection. This regulatory framework adds another layer of complexity for international users.
The divergence between US and Chinese companies becomes clear when you look at their goals. US companies have rushed to develop AGI, or AI with super-human intelligence. They are focused on beating competitors to this theoretical finish line. In contrast, Chinese companies have focused on AI commercialization. This shift is driven by US restrictions on access to advanced semiconductors. Instead of chasing AGI for its own sake, Chinese firms are finding ways to make money now. By early 2026, Chinese AI chatbots were fighting for users with massive promotions around the Lunar New Year holiday. Several of these models vied with Anthropic's Claude and OpenAI's ChatGPT for performance. The result for the consumer is often better value. These Chinese models typically come with far lower usage costs. The cheaper, open-source Chinese models have gained many users in the US and other countries as a result.
But one thing remains constant despite the commercial competition. The AI's silence on topics Beijing deems sensitive. A practical test reveals the current limits of these systems. If you ask DeepSeek about what happened on June 4, 1989, the model says "I'm not able to help with that." It cannot provide details on the Tiananmen Square crackdown in Beijing where hundreds or possibly thousands were killed. However, the same system can explain that Sept. 11, 2001, "was the day of coordinated terrorist attacks in the United States... [that] killed nearly 3,000 people." This capability gap matters for users seeking accurate information. China's cybersecurity regulator has rolled out strict processes for approving new generative AI services. The agency publishes lists of registered models that are approved for public use. This adds a layer of vetting that users might appreciate, even if it leads to censorship.
Integrating AI across industries is also a significant part of the Chinese government's plans for economic development over the next five years. Chinese companies' development of open-source AI adds support to Beijing's international cooperation programs. These include the Global AI Governance Initiative and the World Artificial Intelligence Cooperation Organization. "We should strengthen risk-awareness and ensure that AI is secure and controllable," Chinese President Xi Jinping stated in July at the launch of the world AI organization. At the BRICS summit in India, Xi added that China would foster AI and tech cooperation among the bloc economies. These statements highlight a different operational philosophy. The focus is on control and security rather than pure speed and disruption.
For the enterprise sector, the reality of AI implementation is different from the hype. Companies frequently emphasize the importance of AI's ability to generate revenue rather than just rising in intelligence rankings. "We are not looking for the most [impressive] AI models, but trying to unlock AI potential," said Alex Lu of LSY Consulting. He pointed to China's rules on data security and labeling of AI-generated videos. The bigger challenge is addressing the AI models' penchant for making things up via hallucination. A better AI model helps but the cost might not justify the expense. Lu noted that a key approach uses less complex methods known as harness technology and reinforcement learning. This means many Chinese companies may not need to use cutting-edge AI models.
This practical approach is evident at OpenPie. Ray Von said his startup is mostly using older models, if not smaller versions, of Alibaba's Qwen and DeepSeek. He noted that "the vast majority of enterprise" sees a lot of productivity increases but they have not seen anything generate profits or reduce cost immediately. "Right now, the publicity is diverting a lot of attention," he said, emphasizing that the application side has not seen a lot of results yet. This suggests that for many businesses, the current AI hype is out of step with the actual needs of the marketplace. As the technology matures, the gap between the rhetoric and the reality will likely widen further.
The landscape for AI consumers in China and the US is evolving in opposing directions. While the US focuses on the risks of runaway intelligence and the "next big thing," China is focusing on regulation, commercial viability, and specific use cases. The silence of Chinese leaders is not a lack of innovation. It is a strategic choice to prioritize control and market readiness over public alarm. For those watching from the sidelines, the lesson is clear. Do not let the fear-mongering or the hype distract you from the actual products and services that are changing your daily life. The future of AI is not just about who builds the smartest robot. It is about who builds the safest and most useful tools for the real world.
First reported by CNBC: Finance.
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