The high quality of ByteDance's C-Dance video model suggests it may be trained on copyrighted material, like David Attenborough's voice, which US labs are legally restricted from using. This freedom from IP constraints could give Chinese firms a significant competitive advantage in media generation.
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Unlike Google and Meta who own vast video libraries, OpenAI lacked training data for Sora. Their solution was a legally aggressive "opt-out" policy for copyrighted material, effectively shifting the burden to IP holders and turning IP licensing, not just data access, into the next competitive frontier.
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.
While other AI models may be more powerful, Adobe's Firefly offers a crucial advantage: legal safety. It's trained only on licensed data, protecting enterprise clients like Hollywood studios from costly copyright violations. This makes it the most commercially viable option for high-stakes professional work.
The perception of China's AI industry as a "fast follower" is outdated.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.
While US firms lead in cutting-edge AI, the impressive quality of open-source models from China is compressing the market. As these free models improve, more tasks become "good enough" for open source, creating significant pricing pressure on premium, closed-source foundation models from companies like OpenAI and Google.
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 geopolitical competition in AI will decide the economic value of intellectual property. If the U.S. approach, which respects copyright, prevails, IP retains value. If China's approach of training on all data without restriction dominates the global tech stack, the value of traditional copyright could be driven toward zero.
A common misconception is that Chinese AI is fully open-source. The reality is they are often "open-weight," meaning training parameters (weights) are shared, but the underlying code and proprietary datasets are not. This provides a competitive advantage by enabling adoption while maintaining some control.
Leading Chinese AI models like Kimi appear to be primarily trained on the outputs of US models (a process called distillation) rather than being built from scratch. This suggests China's progress is constrained by its ability to scrape and fine-tune American APIs, indicating the U.S. still holds a significant architectural and innovation advantage in foundational AI.
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.
