In a Washington policy landscape increasingly dominated by calls for minimal AI regulation, Hugging Face is making a distinctly different case to the Trump administration: open-source and collaborative AI development may be America’s strongest competitive advantage.
The AI platform company, which hosts more than 1.5 million public models across diverse domains, has submitted its recommendations for the White House AI Action Plan, arguing that recent breakthroughs in open-source models demonstrate they can match or exceed the capabilities of closed commercial systems at a fraction of the cost.
In its official submission, Hugging Face highlights recent achievements like OlympicCoder, which outperforms Claude 3.7 on complex coding tasks while using just 7 billion parameters, and AI2’s fully open OLMo 2 models that match OpenAI’s o1-mini performance levels.
The submission comes as part of a broader effort by the Trump administration to gather input for its upcoming AI Action Plan, mandated by Executive Order 14179, officially titled “Removing Barriers to American Leadership in Artificial Intelligence,” which was issued in January. The Order, which replaced the Biden administration’s more regulation-focused approach, emphasizes U.S. competitiveness and reducing regulatory barriers to development.
Hugging Face’s submission stands in stark contrast to those from commercial AI leaders like OpenAI, which has lobbied heavily for light-touch regulation and “the freedom to innovate in the national interest,” while warning about China’s narrowing lead in AI capabilities. OpenAI’s proposal emphasizes a “voluntary partnership between the federal government and the private sector” rather than what it calls “overly burdensome state laws.”
How open source could power America’s AI advantage: Hugging Face’s triple-threat strategy
Hugging Face’s recommendations center on three interconnected pillars that emphasize democratizing AI technology. The company argues that open approaches enhance rather than hinder America’s competitive position.
“The most advanced AI systems to date all stand on a strong foundation of open research and open source software — which shows the critical value of continued support for openness in sustaining further progress,” the company wrote in its submission.
Its first pillar calls for strengthening open and open-source AI ecosystems through investments in research infrastructure like the National AI Research Resource (NAIRR) and ensuring broad access to trusted datasets. This approach contrasts with OpenAI’s emphasis on copyright exemptions that would allow proprietary models to train on copyrighted material without explicit permission.
“Investment in systems that can freely be re-used and adapted has also been shown to have a strong economic impact multiplying effect, driving a significant percentage of countries’ GDP,” Hugging Face noted, arguing that open approaches boost rather than hinder economic growth.
Smaller, faster, better: Why efficient AI models could democratize the technology revolution
The company’s second pillar focuses on addressing resource constraints faced by AI adopters, particularly smaller organizations that can’t afford the computational demands of large-scale models. By supporting more efficient, specialized models that can run on limited resources, Hugging Face argues the U.S. can enable broader participation in the AI ecosystem.
“Smaller models that may even be used on edge devices, techniques to reduce computational requirements at inference, and efforts to facilitate mid-scale training for organizations with modest to moderate computational resources all support the development of models that meet the specific needs of their use context,” the submission explains.
On security—a major focus of the administration’s policy discussions—Hugging Face makes the counterintuitive case that open and transparent AI systems may be more secure in critical applications. The company suggests that “fully transparent models providing access to their training data and procedures can support the most extensive safety certifications,” while “open-weight models that can be run in air-gapped environments can be a critical component in managing information risks.”
Big tech vs. little tech: The growing policy battle that could shape AI’s future
Hugging Face’s approach highlights growing policy divisions in the AI industry. While companies like OpenAI and Google emphasize speeding up regulatory processes and reducing government oversight, venture capital firm Andreessen Horowitz (a16z) has advocated for a middle ground, arguing for federal leadership to prevent a patchwork of state regulations while focusing regulation on specific harms rather than model development itself.
“Little Tech has an important role to play in strengthening America’s ability to compete in AI in the future, just as it has been a driving force of American technological innovation historically,” a16z wrote in its submission, using language that aligns somewhat with Hugging Face’s democratization arguments.
Google’s submission, meanwhile, focused on infrastructure investments, particularly addressing “surging energy needs” for AI deployment—a practical concern shared across industry positions.
Between innovation and access: The race to influence America’s AI future
As the administration weighs competing visions for American AI leadership, the fundamental tension between commercial advancement and democratic access remains unresolved. OpenAI’s vision of AI development prioritizes speed and competitive advantage through a centralized approach, while Hugging Face presents evidence that distributed, open development can deliver comparable results while spreading benefits more broadly.
The economic and security arguments will likely prove decisive. If administration officials accept Hugging Face’s assertion that “a robust AI strategy must leverage open and collaborative development to best drive performance, adoption, and security,” open-source could find a meaningful place in national strategy. But if concerns about China’s AI capabilities dominate, OpenAI’s calls for minimal oversight might prevail.
What’s clear is that the AI Action Plan will set the tone for years of American technological development. As Hugging Face’s submission concludes, both open and proprietary systems have complementary roles to play — suggesting that the wisest policy might be one that harnesses the unique strengths of each approach rather than choosing between them. The question isn’t whether America will lead in AI, but whether that leadership will bring prosperity to the few or innovation for the many.
The post Hugging Face submits open-source blueprint, challenging Big Tech in White House AI policy fight appeared first on Venture Beat.
