The perception of China's AI industry as a "fast follower" is outdated. Models like ByteDance's SeedDance 2.0 are not just catching up on quality but introducing technical breakthroughs—like simultaneous sound generation—that haven't yet appeared in Western models, signaling a shift to true innovation.
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ByteDance's SeedDance 2.0 model integrates audio generation directly with video, a novel approach that suggests China may be starting to leapfrog the US in specific AI capabilities. This challenges the common narrative that China is only a fast follower in the AI race.
China is gaining an efficiency edge in AI by using "distillation"—training smaller, cheaper models from larger ones. This "train the trainer" approach is much faster and challenges the capital-intensive US strategy, highlighting how inefficient and "bloated" current Western foundational models are.
Joe Tsai reframes the US-China 'AI race' as a marathon won by adoption speed, not model size. He notes China’s focus on open source and smaller, specialized models (e.g., for mobile devices) is designed for faster proliferation and practical application. The goal is to diffuse technology throughout the economy quickly, rather than simply building the single most powerful model.
Unlike the largely closed-source US market, DeepSeek's open-source models spurred intense competition among Chinese tech giants and startups to release their own open offerings. This has made Chinese open-source models the most used globally by token count, creating a distinct competitive dynamic.
The emergence of high-quality open-source models from China drastically shortens the innovation window of closed-source leaders. This competition is healthy for startups, providing them with a broader array of cheaper, powerful models to build on and preventing a single company from becoming a chokepoint.
Counterintuitively, China leads in open-source AI models as a deliberate strategy. This approach allows them to attract global developer talent to accelerate their progress. It also serves to commoditize software, which complements their national strength in hardware manufacturing, a classic competitive tactic.
Challenging the narrative of pure technological competition, Jensen Huang points out that American AI labs and startups significantly benefited from Chinese open-source contributions like the DeepSeek model. This highlights the global, interconnected nature of AI research, where progress in one nation directly aids others.
The US-China AI race is a 'game of inches.' While America leads in conceptual breakthroughs, China excels at rapid implementation and scaling. This dynamic reduces any American advantage to a matter of months, requiring constant, fast-paced innovation to maintain leadership.
According to DeepMind CEO Demis Hassabis, while Chinese AI models are rapidly closing the capability gap with US counterparts, they have yet to demonstrate the ability to create truly novel breakthroughs, like a new transformer architecture. Their strength lies in catching up to the frontier, not pushing beyond it.
While the U.S. leads in closed, proprietary AI models like OpenAI's, Chinese companies now dominate the leaderboards for open-source models. Because they are cheaper and easier to deploy, these Chinese models are seeing rapid global uptake, challenging the U.S.'s perceived lead in AI through wider diffusion and application.
