Chinese AI models are now breathing down the necks of their US counterparts, but what helped set off the AI revolution in China was incidentally a US model.
In an assessment of the global AI landscape, Groq COO and President Sunny Madra has attributed China’s rapid advancement in artificial intelligence to an unexpected catalyst: the distillation of OpenAI’s GPT-4. Speaking about the factors that enabled Chinese companies to close the gap with Western AI leaders, Madra pointed to a phenomenon that has significant implications for the future of AI development and geopolitical competition in the technology sector.
“I think first and foremost there was huge costs involved in creating these models, right?” Madra explained. “And I think we can’t discount one thing that happened, which allowed the Chinese models to catch up, which is the distillation of GPT-4 in terms of the creation of the leading models in China, right?”
The process of model distillation involves training a smaller, more efficient model to mimic the behavior of a larger, more capable one. In this case, Madra suggests that Chinese researchers leveraged GPT-4’s capabilities to accelerate their own model development, bypassing some of the massive computational and financial investments that OpenAI made in creating the original model.
“And if it wasn’t for all the expense and effort that went into creating the earlier versions of what OpenAI has, I don’t think we’d have as advanced Chinese models,” Madra continued. “And so now that’s happened, the cat’s out of the bag and all the open data on the internet’s been already applied to these models.”
Looking ahead, Madra offered a provocative prediction about how the AI market will evolve. “The way I think the next two years will play out is when it comes to any model that’s built off all open data, I think that will definitely push to being driven by open source because we’ve consumed it all and those models are able to create more synthetic data for themselves,” he said.
“So we’ll really see the frontier of general purpose models become open source and then a lot of the closed stuff will happen, and like it happens in technology and other places, in specific areas where the data’s not open, it’s not available to anybody else. And so I think that’s how the market really bifurcates.”
Madra’s comments illuminate a critical inflection point in the AI industry. His thesis suggests that once publicly available internet data has been exhausted for training purposes, the competitive advantage will shift from general-purpose models to specialized ones built on proprietary datasets. This bifurcation could reshape the industry, with open-source models dominating commodity AI tasks while companies compete on domain-specific applications powered by unique data assets.
The implications extend beyond market dynamics to national security and technological sovereignty. Chinese companies like DeepSeek, Alibaba’s Qwen, and Baidu have indeed made remarkable progress, with some models now rivaling or even surpassing Western counterparts in certain benchmarks.
The distillation phenomenon Madra describes also raises questions about the return on investment for frontier model development. If competitors can rapidly catch up by distilling publicly available models, companies investing billions in compute and research face a dilemma: how to maintain their lead without the protection of proprietary training data. This dynamic may accelerate the trend toward “inference-time compute” strategies and models that improve through reasoning rather than just scale, as well as push companies to focus on verticals where they control unique data sources—healthcare records, financial transactions, enterprise workflows, or specialized scientific datasets.
As the AI arms race continues, Madra’s observations suggest that the next phase of competition won’t be won through brute-force scaling alone, but through strategic control of specialized data and the ability to efficiently leverage what’s already been learned from the first generation of large language models.