Want smarter insights in your inbox? Sign up for our weekly newsletters to get only what matters to enterprise AI, data, and security leaders.<\/em> Subscribe Now<\/em><\/p>\n\n\n\n When President Trump released the U.S. AI Action Plan last week, many were surprised to see \u201cencourage open-source and open-weight AI,\u201d as one of the administration\u2019s top priorities. The White House has elevated what was once a highly technical topic into an urgent national concern \u2014 and a key strategy to winning the AI race against China.<\/p>\n\n\n\n China\u2019s emphasis on open source, also highlighted in its own Action Plan released shortly after the U.S., makes the open-source race imperative. And the global soft power that comes with more open models from China makes their recent leadership even more notable.\u00a0<\/p>\n\n\n\n When DeepSeek-R1, a powerful open-source large language model (LLM) out of China, was released earlier this year, it didn\u2019t come with a press tour. No flashy demos. No keynote speeches. But it was open weights and open science. Open weight means anyone with the right skills and computing resources can run, replicate, or make a model their own; open science shares some of the tricks behind the model development. <\/p>\n\n\n\n Within hours, researchers and developers seized on it. Within days, it became the most-liked model of all time<\/em> on Hugging Face \u2014 with thousands of variants created and used across major tech companies, research labs and startups. Most strikingly, this explosion of adoption happened not just abroad, but in the U.S.<\/em> For the first time, American AI was being built on Chinese foundations.<\/p>\n\n\n\n The AI Impact Series Returns to San Francisco – August 5<\/strong><\/p>\n\n\n\n The next phase of AI is here – are you ready? Join leaders from Block, GSK, and SAP for an exclusive look at how autonomous agents are reshaping enterprise workflows – from real-time decision-making to end-to-end automation.<\/p>\n\n\n\n Secure your spot now – space is limited: https:\/\/bit.ly\/3GuuPLF<\/p>\n\n\n\n Within a week, the U.S. stock market \u2014 sensing the tremor \u2014 took a tumble.<\/p>\n\n\n\n It turns out Deepseek was just the opening act. Dozens of Chinese research groups are now pushing the frontiers of open-source AI, sharing not only powerful models, but the data, code and scientific methods behind them. They\u2019re moving quickly \u2014 and they\u2019re doing it in the open.<\/p>\n\n\n\n Meanwhile, U.S.-based companies \u2014 many of which pioneered the modern AI revolution \u2014 are increasingly closing up. Flagship models like GPT-4, Claude and Gemini are no longer released in ways that allow builders more control. They\u2019re accessible only through chatbots or APIs: Gated interfaces that let you interact with a model but not see how it works, retrain it or use it freely. The model\u2019s weights, training data and behavior remain proprietary, tightly controlled by a few tech giants.<\/p>\n\n\n\n This is a dramatic reversal. Between 2016 and 2020, the U.S. was the<\/em> global leader in open-source AI. Research labs from Google, OpenAI, Stanford and elsewhere released breakthrough models and methods that laid the foundation for everything we now call \u201cAI.\u201d The transformer \u2014 the \u201cT\u201d in ChatGPT \u2014 was born out of this open culture. Hugging Face was created during this era to democratize access to these technologies.<\/p>\n\n\n\n Now, the U.S. is slipping, and the implications are profound.<\/p>\n\n\n\n American scientists, startups and institutions are increasingly driven to build on Chinese open models because the best U.S. models are locked behind APIs. As each new open model emerges from abroad, Chinese companies like DeepSeek and Alibaba strengthen their positions as foundational layers in the global AI ecosystem. The tools that power America\u2019s next generation of AI products, research and infrastructure are increasingly coming from overseas.<\/p>\n\n\n\n And at a deeper level, there\u2019s a more fundamental risk: Every advancement in AI \u2014 including the most closed systems \u2014 is built on open foundations. Proprietary models depend on open research, from transformer architecture to training libraries and evaluation frameworks. But more importantly, open-source increases a country\u2019s velocity in building AI. It fuels rapid experimentation, lowers barriers to entry and creates compounding innovation. <\/p>\n\n\n\n When openness slows down, the entire ecosystem follows. If the U.S. falls behind in open-source today, it may find itself falling behind in AI altogether.<\/p>\n\n\n\n This matters not just for innovation, but for security, science and democratic governance. Open models are transparent and auditable. They allow governments, educators, healthcare institutions and small businesses to adapt AI to their needs, without vendor lock-in or black-box dependencies.<\/p>\n\n\n\n We need more and better U.S.-developed open source models and artifacts. U.S. institutions already pushing for openness must build on their success. Meta\u2019s open-weight Llama family has led to tens of thousands of variations on Hugging Face. The Allen Institute for AI continues to publish excellent fully open models. Promising startups like Black Forest are building open multimodal systems. Even OpenAI has suggested it may release open weights soon.<\/p>\n\n\n\n With more public and policy support for open-source AI, as demonstrated by the U.S. AI Action Plan, we can restart a decentralized movement that will ensure America\u2019s leadership. It\u2019s time for the American AI community to wake up, drop the \u201copen is not safe\u201d narrative, and return to its roots: Open science and open-source AI, powered by an unmatched community of frontier labs, big tech, startups, universities and non\u2011profits.<\/p>\n\n\n\n We can restart a decentralized movement that will ensure U.S. leadership, built on openness, competition and scientific inquiry, and empower the next generation of builders. If we want AI to reflect democratic principles, we have to build it in the open. And if the U.S. wants to lead the AI race, it must lead the open-source AI race.<\/p>\n\n\n\n Cl\u00e9ment Delangue is the co-founder and CEO of Hugging Face.<\/em><\/p>\n Daily insights on business use cases with VB Daily<\/strong><\/p>\n If you want to impress your boss, VB Daily has you covered. We give you the inside scoop on what companies are doing with generative AI, from regulatory shifts to practical deployments, so you can share insights for maximum ROI.<\/p>\n \n\t\t\t\t\tThanks for subscribing. Check out more VB newsletters here.\n\t\t\t\t<\/p>\n An error occured.<\/p>\n<\/p><\/div>\n
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\n<\/div>DeepSeek wasn\u2019t the only one<\/h2>\n\n\n\n
Moving away from black box AI<\/h2>\n\n\n\n
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