Hugging Face Advocates Open-Source AI in Response to Trump Administration's Plan

While many tech giants push for minimal AI regulation, Hugging Face is charting a different course. The open-source AI platform is making a compelling case to the Trump administration: collaborative, open-source development might actually be America’s strongest competitive advantage in the global AI landscape.

Hugging Face, now hosting over 1.5 million public models, recently submitted recommendations to the White House AI Action Plan. Their argument? Recent breakthroughs in open-source models demonstrate they can match—and sometimes surpass—closed commercial systems at a fraction of the cost. This challenges the prevailing narrative that proprietary AI is the only path to maintaining America’s competitive edge.

The company points to impressive achievements like OlympicCoder, which outperforms Claude 3.7 on complex coding tasks while using just 7 billion parameters, and AI2’s OLMo 2 models that rival OpenAI’s o1-mini performance. “The rapid progress we’re seeing in open-source models is a testament to the power of collaborative innovation,” says Dr. Emily Chen, a leading AI researcher at Stanford University. “It’s not just about keeping up; it’s about potentially leapfrogging ahead.”

This submission responds to the Trump administration’s call for input on its upcoming AI Action Plan, mandated by Executive Order 14179 from January. The Order, titled “Removing Barriers to American Leadership in Artificial Intelligence,” replaces the previous administration’s more regulation-focused approach with an emphasis on U.S. competitiveness and reduced regulatory barriers.

Hugging Face’s vision stands in stark contrast to OpenAI’s, which advocates for light-touch regulation and “the freedom to innovate in the national interest,” while warning about China’s growing AI capabilities. OpenAI favors a “voluntary partnership between the federal government and the private sector” over what it describes as “overly burdensome state laws.” This highlights a fundamental tension within the industry: rapid, unfettered innovation versus responsible development, transparency, and equitable access.

Three Pillars of Open Innovation: Hugging Face’s Strategy for American AI Leadership

Hugging Face’s proposal centers on three interconnected pillars that could reshape the AI landscape to be more inclusive and innovative.

“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 official response. This underscores how even the most advanced proprietary systems rely on foundations built through open research.

The first pillar calls for strengthening open and open-source AI ecosystems through investments in research infrastructure and ensuring access to trusted datasets. This contrasts with OpenAI’s emphasis on copyright exemptions that would allow proprietary models to train on copyrighted material without permission. “Investing in shared infrastructure like the NAIRR is crucial for leveling the playing field,” says Dr. Alex Johnson, a professor of computer science at MIT. “It allows smaller institutions and researchers to compete with the resources of major tech companies.”

“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, Smarter, More Accessible: The Democratization of AI

The company’s second pillar addresses resource constraints faced by smaller organizations that can’t afford the computational demands of large-scale models. By supporting more efficient, specialized models that 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.

“The future of AI isn’t just about bigger models; it’s about smarter, more efficient models,” says Dr. Maria Rodriguez, a data scientist specializing in edge computing. “This allows us to deploy AI in a much wider range of applications, from mobile devices to remote sensors.”

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.”

“Transparency is key to building trust in AI systems,” says Dr. David Lee, a cybersecurity expert specializing in AI. “Open-source allows for greater scrutiny and faster identification of vulnerabilities.”

The Industry Divide: Big Tech vs. Little Tech

Hugging Face’s approach highlights growing policy divisions in the AI industry. While some companies and venture capital firms have also submitted recommendations, the specifics vary. Some 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 their response, using language that aligns somewhat with Hugging Face’s democratization arguments.

Other submissions focused on infrastructure investments, particularly addressing “surging energy needs” for AI deployment—a practical concern shared across industry positions.

The Path Forward: Balancing Innovation, Access, and Security

As the administration weighs these competing visions, the fundamental tension between commercial advancement and democratic access remains unresolved. OpenAI’s vision 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 decisions made now 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 implications extend far beyond the immediate concerns of the AI industry. The choices made now will influence the development of future technologies, the structure of the digital economy, and the balance of power in the global technological landscape.

A future dominated by open-source AI could foster greater international collaboration, accelerate scientific discovery, and empower individuals and communities worldwide. The stakes are high, and the decisions made in Washington will reverberate far beyond America’s borders.