As technological advancements increasingly shape both economic power and national security, the United States faces a pressing challenge: How do we stay ahead in the race for AI supremacy? This question was at the heart of the panel “Accelerate or Fall Behind: The Urgent Push to Maintain Our U.S. Technological Edge,” moderated by Primer’s VP of Data Science, John Bohannon. Experts from academia, government, and defense tech startups—Mory Gharib from Caltech, Ellen Chang from venture capitalist firm BMNT, and Dave Gallagher from NASA’s Jet Propulsion Laboratory (JPL)—shared their insights on how collaboration, innovation, and strategic policy can help the U.S. sustain its technological edge.
The role of federal Labs: taking risks where industry won’t
Dave Gallagher, from NASA’s JPL, shed light on the pivotal role federal labs play in advancing technological innovation. He emphasized that JPL and similar institutions were designed to tackle ambitious projects that others may shy away from. “Federal labs were set up to take risks on things industry won’t touch,” Gallagher noted. These labs tackle long-term, high-risk research where immediate commercial benefits are unclear but are essential for national security and scientific progress.
Gallagher highlighted the collaboration between JPL and Qualcomm as a prime example, showcasing how Qualcomm’s Snapdragon chips—typically known for dominating the consumer mobile market—found a new purpose in space exploration. “We flew the Qualcomm Snapdragon on the helicopter on Mars, which would have been impossible with traditional space chips,” Gallagher said. This collaboration exemplifies how institutions and companies can join forces to achieve breakthroughs that neither could accomplish alone.
Gallagher also touched on the broader national security concerns that motivate these efforts, particularly the challenge posed by China’s long-term investments in AI and other advanced technologies. “China is playing the long game,” he warned, stressing that the U.S. needs to continue to invest in federal labs to stay competitive.
Academia’s role: training the next generation and driving innovation
Mory Gharib from Caltech emphasized the importance of academia in fostering the next generation of innovators. While industry attracts top talent with lucrative salaries, Gharib emphasized that universities play an irreplaceable role in education and research. “Academia’s main role is education,” Gharib said. “We have to train people to be the new innovators.”
Gharib also acknowledged the challenge of retaining talent within academic institutions, as other sectors offer increasingly competitive opportunities. This trend, he noted, could potentially weaken the innovation pipeline if not addressed. However, he pointed to the rise of joint appointments—where professors can hold positions in both academia and industry—as a possible solution to keep academia at the forefront of research. Such collaborations, Gharib argued, could help bridge the gap between the slow-moving academic world and the fast-paced demands of the private sector.
Gharib also shared a fascinating example of how academia can drive unique innovations that later find industrial applications. He referenced his own work on using kites to test how the ancient Egyptians might have built the pyramids—an example of how open-ended academic research can yield surprising, real-world results. “Sometimes the most groundbreaking innovations come from curiosity-driven research,” Gharib said.
The role of government: shaping policy and funding critical research
Ellen Chang, who brought a perspective from venture capital and defense startups, underscored the pivotal role government plays in setting policies that shape the future of AI. “Government has to step in where industry won’t,” she emphasized, especially in funding areas of research that may not yet have commercial interest but are vital to national security and public welfare.
Chang pointed to specific policy mechanisms, such as the Small Business Innovation Research (SBIR) program, which the government uses to support innovation. SBIR provides funding to startups and small businesses to develop solutions for government-identified challenges, serving as a key driver of innovation for tech startups, including Primer.
Chang also discussed the role of AI in sectors beyond traditional tech, such as healthcare and security. She highlighted the dangers of data bias in AI systems, particularly when it comes to underrepresented groups. “We need government policy to ensure that AI systems are built with diverse data sets,” Chang argued, “otherwise, we’ll see inequities in areas like healthcare that could have serious consequences for certain populations.”
The AI arms race: are we already falling behind?
A recurring theme throughout the panel was the existential question: Is the U.S. already falling behind in the AI race? With China’s aggressive investments in AI, is the race already lost? The panelists, however, were cautiously optimistic.
Bohannon noted that while China may be ahead in terms of the sheer volume of research papers published, the quality of U.S. research is still superior. “China has surpassed us in the number of academic papers published, but the quality isn’t there yet,” he said. Despite this, he emphasized that the U.S. cannot afford complacency, particularly given China’s advantage in data accumulation and usage due to fewer regulatory restrictions on data privacy.
Chang agreed that China’s AI capabilities are formidable but highlighted the U.S.’s unique strengths in innovation and entrepreneurial spirit.”The U.S. has a culture of innovation that is hard to replicate,” she said. “But we need to maintain that by ensuring our startups have the support they need to scale.”
AI: the hype, the reality, and the future
As the panel drew to a close, the discussion turned philosophical: Are we truly working with AI yet, or is much of it still hype? Bohannon pointed out that AI, especially in its current form as large language models (LLMs), is often seen as “magic pixie dust”.
Both Chang and Gallagher agreed that while AI is still in its infancy, it has already begun to transform industries in meaningful ways. Chang warned against relying too heavily on AI solutions without understanding their limitations, especially when it comes to synthetic data, which can introduce bias if not used carefully.
Gallagher expressed optimism about the future of AI, especially as it becomes more integrated with physical systems like autonomous drones and spacecraft. “We’re just scratching the surface of what AI can do,” he said. “The key is to accelerate development while ensuring we’re not sacrificing safety and ethical considerations.”
The path forward: collaboration and speed
The central takeaway from the panel was clear: collaboration between government, industry, and academia is critical to maintaining the U.S. technological edge. As Gallagher, Gharib, and Chang all stressed, no single sector can drive innovation alone. It will take partnerships, strategic funding, and a shared sense of urgency to keep the U.S. at the forefront of AI development.
Primer’s CEO, Sean Moriarty, closed the panel with a reflection on the stakes of the AI race: “AI is moving faster than any technology we’ve seen before. The countries and companies that move the fastest will shape the future. At Primer, we’re committed to building the tools that will help our most important institutions—whether in defense, healthcare, or beyond—stay ahead and keep the world a safer place.”
As the U.S. navigates this new era of AI, the message from this panel was clear: The race isn’t over, but the clock is ticking. The future of U.S. technological dominance will depend on how quickly we can accelerate research, deployment, and collaboration in the coming years.
